WO1999049369A1 - Signal processing technique which separates signal components in a sensor signal for sensor diagnostics - Google Patents
Signal processing technique which separates signal components in a sensor signal for sensor diagnostics Download PDFInfo
- Publication number
- WO1999049369A1 WO1999049369A1 PCT/US1999/006123 US9906123W WO9949369A1 WO 1999049369 A1 WO1999049369 A1 WO 1999049369A1 US 9906123 W US9906123 W US 9906123W WO 9949369 A1 WO9949369 A1 WO 9949369A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- sensor
- signal
- sensor signal
- wavelet
- circuitry
- Prior art date
Links
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01K—MEASURING TEMPERATURE; MEASURING QUANTITY OF HEAT; THERMALLY-SENSITIVE ELEMENTS NOT OTHERWISE PROVIDED FOR
- G01K15/00—Testing or calibrating of thermometers
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B9/00—Safety arrangements
- G05B9/02—Safety arrangements electric
- G05B9/03—Safety arrangements electric with multiple-channel loop, i.e. redundant control systems
-
- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C3/00—Registering or indicating the condition or the working of machines or other apparatus, other than vehicles
-
- G—PHYSICS
- G08—SIGNALLING
- G08C—TRANSMISSION SYSTEMS FOR MEASURED VALUES, CONTROL OR SIMILAR SIGNALS
- G08C19/00—Electric signal transmission systems
- G08C19/02—Electric signal transmission systems in which the signal transmitted is magnitude of current or voltage
Definitions
- SIGNAL PROCESSING TECHNIQUE WHICH SEPARATES SIGNAL COMPONENTS IN A SENSOR SIGNAL FOR SENSOR DIAGNOSTICS
- the present invention relates to process variable sensors of the type used in the process control industry. More specifically, the invention relates to life expectancy estimation and diagnostics for such a process variable sensor.
- Process control transmitters are used to monitor process variables in industrial processes. For example, a transmitter might monitor pressure, temperature or flow (e.g., process variables) and transmit such process variables back to a control room, where a controller sends a control signal back to an actuator (e.g., valve, motor) to control the process.
- an actuator e.g., valve, motor
- the transmitter In order to monitor a process variable, the transmitter must include some type of a sensor.
- transmitters include sensors with resistances or capacitances which vary in response to temperature, deformations or strain which allow the transmitter to measure, for example, temperature, pressure, flow, level, pH or turbidity.
- Diagnostics can be performed on a sensor by monitoring the sensor output signal. For example, a simple diagnostic technique is to compare the sensor output to a maximum or minimum value and provide an alarm indication if the threshold is exceeded. However, one difficulty in prior art diagnostic techniques is that - 2 - the variations in the process variable being sensed should not be incorrectly interpreted as a sensor fault .
- a device in a process control system includes a sensor input which receives a composite sensor signal from a process variable sensor.
- the composite sensor signal includes a process variable signal related to the process variable being sensed and a residual sensor signal related to sensor operation.
- Wavelet preprocessing circuitry coupled to the sensor input separates components of the composite sensor signal and responsively provides the components of the sensor signal to diagnostic circuitry. Diagnostic circuitry receives and responsively provides an output related to sensor health.
- Figure 1 shows a process control system including a transmitter in accordance with the present invention.
- Figure 2 is a simplified block diagram of diagnostic circuitry in accordance with the present invention.
- Figure 3 is a simplified block diagram of a process device in accordance with the present invention.
- Figure 4 is a graph showing a nominal base signature for a sensor signal.
- Figure 5 is a diagram illustrating an individual wavelet transformation.
- Figure 6 is a graph illustrating various components of a process variable sensor output from a wavelet decomposition of a composite sensor signal . -3 -
- FIG. 1 is a diagram of process control system 2 including field mounted transmitter 40 coupled to control room 4 over a two wire process control loop 6.
- Transmitter 40 monitors a process variable (e.g., flow, pressure temperature) of process fluid in process piping 8.
- Transmitter 40 transmits information related to the sensed process variable to control room 4 over loop 6 by controlling the current flowing through loop 6. For example, the current flowing through loop 6 may be controlled between 4 and 20 mA and properly calibrated to indicate the process variable. Additionally or in the alternative, transmitter 40 may transmit digital information related to the sensed process variable over loop 6 to control room 4 such as in a HART ® or Fieldbus protocol.
- Transmitter 40 includes circuitry described herein in more detail which provides advanced diagnostics including life expectancy information (e.g. health) related to sensor operation.
- the present invention may be implemented in, for example, a pressure transmitter, a magnetic flowmeter, a coriolis flowmeter, a level transmitter with a low power radar measuring means, a resistance based temperature transmitter, or any
- FIG. 2 is a simplified block diagram of one example of circuitry for performing sensor diagnostics in accordance with the invention.
- process variable sensor 20 and sensor compensation circuit 22 provide a composite sensor signal to measurement circuitry 11 and preprocessing function 14.
- Measurement circuitry 11 provides an output to output circuitry 13 representative of the process variable being measured.
- the composite sensor signal provided by sensor 20 includes a component related to the sensed process variable and a residual sensor signal due to mechanical or electrical characteristics (e.g., the transfer function, process noise, etc.) of sensor 20. Further, the signal related to the process variable may be separated into two components, one component due to repeatable sensor variations and another due to repeatable process variations.
- Wavelet preprocessing function 14 receives the composite sensor signal and separates the individual signal components, including seasonal variations. These separate signals are provided to diagnostic circuitry 12 on data bus 15. As explained below, this allows diagnostic circuitry 12 to function on the separate, individual signals which make up the composite sensor signal, and, for example, provide a diagnostic output indicative of a failure of sensor 20.
- Output circuitry 13 receives the process variable from measurement circuitry 11 and formats the output as desired. For example, the output may be coupled to loop 6 shown in Figure 1. Further, output circuitry 13 receives the diagnostic signal from circuitry 12 which, for example, may be output on loop 6, used to inhibit the output of process variable or to alarm.
- FIG. 3 is a simplified block diagram of transmitter 40 in accordance with the present invention including wavelet preprocessing circuitry 32.
- Transmitter 40 includes sensor 20 which provides a sensor signal to sensor circuitry 22.
- Sensor 20 can be a resistance based sensor for sensing pressure or temperature (e.g., an RTD or a strain gauge), a capacitive pressure sensor, etc.
- the sensor signal is a composite signal which includes a process variable signal and a residual sensor signal.
- Sensor circuitry 22 performs initial compensation including optional scaling, on the analog sensor signal and the output of sensor circuitry 22 is converted into a digital format by analog to digital converter 24.
- a microprocessor 26 receives the digitized process signal and is also coupled to memory 28 and a system clock 30.
- Microprocessor 26 operates in accordance with instructions stored in a memory 28 to perform various functions. Two such functions in accordance with the present invention are shown as blocks within microprocessor block 26. Specifically, microprocessor 26 includes substantially all of wavelet preprocessing circuitry 32 and sensor life expectancy and diagnostic circuitry 34. Outputs from microprocessor 26 are connected to input/output circuitry 36 and coupled to process control loop 6. I/O circuitry 36 also provides a regulated voltage output which, in some preferred embodiments, powers all of the circuitry of transmitter 40 received through process control loop 6.
- Prior art diagnostic circuitry is often unable to separate the signal due to the process from the signal arising from the sensor and its transfer function. Thus, the prior art frequently cannot distinguish whether a recognized problem is caused, by the sensor or the process.
- the wavelet processing circuitry 32 of the present invention separates the composite sensor signal into its separate components. The separated sensor signals are provided to life expectancy and diagnostic circuitry 34 which is thereby able to more accurately determine life expectancy and diagnose sensor operation. Circuitry 34 receives a signal in which the "noise" from the process has been substantially eliminated. Circuits 32 and 34 may be realized in analog circuits, separate digital circuits, or through a microprocessor 26 as illustrated in Figure 3.
- Microprocessor 26 provides a signal related to the process variable and a life expectancy and diagnostics signal to I/O circuitry 36.
- I/O circuitry 36 transmits information over two wire loop 6 in accordance with known techniques as in a fully digital protocol such as Fieldbus or WorldFIP, a hybrid analog/digital protocol such as a 4-20 mA signal with a digital signal superimposed (e.g., HART ® ), or even according to the DE protocol. Further, microprocessor 26 may receive instructions sent from a hand-held communicator or control room 4 over loop 6.
- the present invention can also be practiced in software resident in any of a number of places in a process control system such as in a field mounted controller, a remote PC or controller or even a final control element such as a valve, motor or switch.
- modern digital protocols such as Fieldbus, Profibus and others allow for the software which practices the present invention to be communicated between elements in a process control system, and also provide for process variables to be sensed in one transmitter and then sent to the software in a different piece of equipment .
- Wavelet analysis is a technique for transforming a time domain signal into the frequency domain which, like a Fourier transformation, allows the frequency components to be identified.
- the output includes information related to time. This may be expressed in the form of a three dimensional graph with time shown on one axis, frequency on a second -7- axis and signal amplitude on a third axis.
- a discussion of wavelet analysis is given in On-Line Tool Condition Monitoring System With Wavelet Fuzzy Neural Network, by . Xiaoli et al . , 8 JOURNAL OF INTELLIGENT MANUFACTURING pgs. 271-276 (1997) .
- a portion of the sensor signal is windowed and convolved with a wavelet function. This convolution is performed by superimposing the wavelet function at the beginning of a sample, multiplying the wavelet function with the signal and then integrating the result over the sample period.
- the result of the integration is scaled and provides the first value for continuous wavelet transform at time equals zero. This point may be then mapped onto a three dimensional plane.
- the wavelet function is then shifted right and the multiplication and integration steps are repeated to obtain another set of data points which are mapped onto the 3-D space. This process is repeated and the wavelet is moved (convolved) through the entire composite signal.
- the wavelet is then scaled, which changes the frequency resolution of the transformation, and the above steps are repeated.
- Data from a wavelet transformation of a composite sensor signal from sensor 20 is shown in Figure 4.
- the data is graphed in three dimensions and forms a surface 41.
- the composite sensor signal includes a small signal peak at about 1 kHz at time t_ and another peak at about 100 Hz at time t 2 .
- wavelet transformation data such as that represented in Figure 4 is calculated and stored in memory 28 shown in Figure 3 during normal operation of the sensor. This data represents a base "plane" of normal operation.
- the data - 8 - may be collected at various times during the day, during a process cycle and during the year.
- life expectancy and diagnostic circuitry 34 retrieves the stored wavelet transformation from memory 28 and compares the base plane data with information gathered through wavelet analysis during operation. For example, if circuitry 34 subtracts the base plane data from a current wavelet transformation, the resultant data represents only the anomalies occurring in the process. Such a subtraction process separates the process variations from the sensor signal along with daily and seasonal variations in the signal. For example, the sensor signal may change during the day or over the course of a year due to environmental temperature changes. Thus, this allows separation of the process signal from the signal due to the sensor.
- wavelet processing circuit 32 performs a discrete wavelet transform (DWT) which is well suited for implementation in a microprocessor.
- DWT discrete wavelet transform
- One efficient discrete wavelet transform uses the Mallat algorithm which is a two channel sub-band coder.
- the Mallet algorithm provides a series of separated or decomposed signals which are representative of individual frequency components of the original signal .
- Figure 5 shows an example of such a system in which an original sensor signal S is decomposed using a sub-band coder of a Mallet algorithm.
- the signal S has a frequency range from 0 to a maximum of f ⁇ .
- the signal is passed simultaneously through a first high pass filter having a frequency range from 1/2 ⁇ MAX to £ MA ' an ⁇ a l° w pass filter having a frequency range from 0 to 1/2 f ⁇ . This process is called - 9 - decomposition.
- the output from the high pass filter provides "level 1" discrete wavelet transform coefficients.
- the level 1 coefficients represent the amplitude as a function of time of that portion of the input signal which is between 1/2 f max and f ⁇ .
- the output from the 0 - 1/2 f ⁇ low pass filter is passed through subsequent high pass (1/4 f max - 1/2 f ⁇ A and low pass (0 - 1/4 f roa filters, as desired, to provide additional levels (beyond "level 1") of discrete wavelet transform coefficients.
- level 1 the outputs from each low pass filter may be subjected to further decompositions offering additional levels of discrete wavelet transformation coefficients as desired. This process continues until the desired resolution is achieved or until the number of remaining data samples after a decomposition is too small to yield any further information.
- the resolution of the wavelet transform may be chosen to be approximately the same as the sensor or the same as the minimum signal resolution required to monitor the process.
- each level of DWT coefficients is representative of signal amplitude as a function of time for a given frequency range. Coefficients for each frequency range may be concatenated to form a graph such as that shown in Figure 4.
- Figure 6 is an example showing a signal S generated by an RTD temperature sensor and the resultant approximation signals yielded in seven levels labelled level 1 through level 7.
- signal level 7 is representative of the signal due to the sensor itself and any further decomposition will yield noise.
- signal due to the sensor is identified as the last signal in the decomposition prior to generating such a noise signal.
- this - 10 - can be determined by comparing the differences between successive decompositions and identifying the signal which has the smallest change relative to the next decomposed signal. However, this may vary for different types of sensors or processes.
- padding is defined as appending extra data on either side of the current active data window, for example, extra data points are added which extend 25% of the current window beyond either window edge.
- extra data is generated by repeating a portion of the data in the current window so that the added data "pads" the existing signal on either side. The entire data set is then fit to a quadratic equation which is used to extrapolate the signal 25% beyond the active data window.
- the variation can be modeled and thereby removed from the sensor signal to obtain the residual sensor signal.
- modeling may be performed by observing the process or otherwise predicting how the process will change over time.
- the model may be a function of other process variables or control signals which are used in predicting the process variable signal.
- a number of predetermined models are stored in memory 28.
- a - 11 - neural network operating in microprocessor 26 monitors operation of the process and selects the optimum model stored in memory. Coefficients related to operation of the model may be generated using a neural network or may be received over loop 6 during installation of transmitter 40 as provided for in various communication protocols such as Fieldbus.
- models include a first order model including dead time which is typically good for non-oscillatory systems, or second order models plus dead time which typically suffice for oscillatory processes.
- Another modeling technique is to use an adaptive neural network-fuzzy logic model.
- Such a hybrid system includes a neural network and fuzzy logic.
- the fuzzy logic allows adaption of the model to variability of the process while the neural network models allows flexibility of the modeling to thereby adjust to changing processes. This provides a relatively robust model.
- the use of adaptive membership functions in the fuzzy logic model further allows the determination whether the particular model should be updated.
- wavelet analysis is well suited for analyzing signals which have transients or other non-stationary characteristics in the time domain.
- wavelet analysis retains information in the time domain, i.e., when the signal occurred.
- the present invention may operate with any appropriate type of life expectancy or diagnostic circuitry. Examples of such techniques are shown in the co-pending application Serial No. 08/744,980, filed November 7, 1996, entitled “DIAGNOSTICS FOR RESISTANCE BASED TRANSMITTER,” which is incorporated by reference. Further, the invention may be used with any type of - 12 - process sensor including sensors which measure temperature, pressure, level, flow, pH, turbity, etc.
- the senor may be any type of process variable sensor including temperature, pressure, flow, level, etc.
Abstract
Description
Claims
Priority Applications (4)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
JP2000538277A JP4847642B2 (en) | 1998-03-26 | 1999-03-26 | Signal processing technology for sensor diagnosis that separates signal components in sensor signals |
AU31059/99A AU3105999A (en) | 1998-03-26 | 1999-03-26 | Signal processing technique which separates signal components in a sensor signalfor sensor diagnostics |
GB0023453A GB2353364B (en) | 1998-03-26 | 1999-03-26 | Signal processing technique which separates signal components in a sensor signal for sensor diagnostics |
DE19983112.2T DE19983112B3 (en) | 1998-03-26 | 1999-03-26 | Signal processing technique that separates signal components in a sensor signal for signal diagnosis |
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US09/048,452 | 1998-03-26 | ||
US09/048,452 US5956663A (en) | 1996-11-07 | 1998-03-26 | Signal processing technique which separates signal components in a sensor for sensor diagnostics |
Publications (1)
Publication Number | Publication Date |
---|---|
WO1999049369A1 true WO1999049369A1 (en) | 1999-09-30 |
Family
ID=21954663
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/US1999/006123 WO1999049369A1 (en) | 1998-03-26 | 1999-03-26 | Signal processing technique which separates signal components in a sensor signal for sensor diagnostics |
Country Status (6)
Country | Link |
---|---|
US (1) | US5956663A (en) |
JP (1) | JP4847642B2 (en) |
AU (1) | AU3105999A (en) |
DE (1) | DE19983112B3 (en) |
GB (1) | GB2353364B (en) |
WO (1) | WO1999049369A1 (en) |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
DE10258921A1 (en) * | 2002-12-17 | 2004-07-01 | Abb Research Ltd. | Feedback control method, e.g. for regulation of the contact force between a current collector and a power wire in electrically driven vehicles, wherein a narrow band filter range is matched to measurement signal properties |
Families Citing this family (92)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US8290721B2 (en) | 1996-03-28 | 2012-10-16 | Rosemount Inc. | Flow measurement diagnostics |
US6654697B1 (en) | 1996-03-28 | 2003-11-25 | Rosemount Inc. | Flow measurement with diagnostics |
US6017143A (en) | 1996-03-28 | 2000-01-25 | Rosemount Inc. | Device in a process system for detecting events |
US6539267B1 (en) * | 1996-03-28 | 2003-03-25 | Rosemount Inc. | Device in a process system for determining statistical parameter |
US7949495B2 (en) | 1996-03-28 | 2011-05-24 | Rosemount, Inc. | Process variable transmitter with diagnostics |
US6754601B1 (en) | 1996-11-07 | 2004-06-22 | Rosemount Inc. | Diagnostics for resistive elements of process devices |
US6449574B1 (en) * | 1996-11-07 | 2002-09-10 | Micro Motion, Inc. | Resistance based process control device diagnostics |
US6601005B1 (en) | 1996-11-07 | 2003-07-29 | Rosemount Inc. | Process device diagnostics using process variable sensor signal |
US6434504B1 (en) | 1996-11-07 | 2002-08-13 | Rosemount Inc. | Resistance based process control device diagnostics |
US6519546B1 (en) | 1996-11-07 | 2003-02-11 | Rosemount Inc. | Auto correcting temperature transmitter with resistance based sensor |
WO1999019782A1 (en) | 1997-10-13 | 1999-04-22 | Rosemount Inc. | Communication technique for field devices in industrial processes |
US6615149B1 (en) | 1998-12-10 | 2003-09-02 | Rosemount Inc. | Spectral diagnostics in a magnetic flow meter |
US6611775B1 (en) | 1998-12-10 | 2003-08-26 | Rosemount Inc. | Electrode leakage diagnostics in a magnetic flow meter |
JP2000221053A (en) * | 1999-02-02 | 2000-08-11 | Oki Micro Design Co Ltd | Sensor circuit |
US6356191B1 (en) | 1999-06-17 | 2002-03-12 | Rosemount Inc. | Error compensation for a process fluid temperature transmitter |
EP1247268B2 (en) | 1999-07-01 | 2009-08-05 | Rosemount Inc. | Low power two-wire self validating temperature transmitter |
US6505517B1 (en) | 1999-07-23 | 2003-01-14 | Rosemount Inc. | High accuracy signal processing for magnetic flowmeter |
US6701274B1 (en) | 1999-08-27 | 2004-03-02 | Rosemount Inc. | Prediction of error magnitude in a pressure transmitter |
US6556145B1 (en) | 1999-09-24 | 2003-04-29 | Rosemount Inc. | Two-wire fluid temperature transmitter with thermocouple diagnostics |
US6735484B1 (en) | 2000-09-20 | 2004-05-11 | Fargo Electronics, Inc. | Printer with a process diagnostics system for detecting events |
CA2429480A1 (en) * | 2000-11-22 | 2002-05-30 | Tomiya Mano | Ophthalmological preparations |
DE10102791B4 (en) * | 2001-01-22 | 2004-04-15 | Ifm Electronic Gmbh | Electrical transmitter |
US6629059B2 (en) | 2001-05-14 | 2003-09-30 | Fisher-Rosemount Systems, Inc. | Hand held diagnostic and communication device with automatic bus detection |
US6431953B1 (en) * | 2001-08-21 | 2002-08-13 | Cabot Microelectronics Corporation | CMP process involving frequency analysis-based monitoring |
US6772036B2 (en) | 2001-08-30 | 2004-08-03 | Fisher-Rosemount Systems, Inc. | Control system using process model |
US20030204373A1 (en) * | 2001-12-06 | 2003-10-30 | Fisher-Rosemount Systems, Inc. | Wireless communication method between handheld field maintenance tools |
RU2299458C2 (en) | 2001-12-06 | 2007-05-20 | Фишер-Роузмаунт Системз, Инк. | Spark-safe instrument for technical service under field conditions |
US20030229472A1 (en) * | 2001-12-06 | 2003-12-11 | Kantzes Christopher P. | Field maintenance tool with improved device description communication and storage |
US7426452B2 (en) * | 2001-12-06 | 2008-09-16 | Fisher-Rosemount Systems. Inc. | Dual protocol handheld field maintenance tool with radio-frequency communication |
DE10202028A1 (en) * | 2002-01-18 | 2003-07-24 | Endress & Hauser Gmbh & Co Kg | Transmitter for detecting a physical measured variable and for converting it into an electrical variable uses signal processors to reshape the electrical variable into a test signal |
US7039744B2 (en) * | 2002-03-12 | 2006-05-02 | Fisher-Rosemount Systems, Inc. | Movable lead access member for handheld field maintenance tool |
US7027952B2 (en) * | 2002-03-12 | 2006-04-11 | Fisher-Rosemount Systems, Inc. | Data transmission method for a multi-protocol handheld field maintenance tool |
DE10255288A1 (en) * | 2002-11-26 | 2004-07-08 | Endress + Hauser Gmbh + Co. Kg | Method for determining the state of a field measuring device for process automation and process measurement technology and field measuring device for carrying out the method |
US10261506B2 (en) * | 2002-12-05 | 2019-04-16 | Fisher-Rosemount Systems, Inc. | Method of adding software to a field maintenance tool |
US6834258B2 (en) * | 2002-12-31 | 2004-12-21 | Rosemount, Inc. | Field transmitter with diagnostic self-test mode |
WO2004081686A2 (en) * | 2003-03-06 | 2004-09-23 | Fisher-Rosemount Systems, Inc. | Heat flow regulating cover for an electrical storage cell |
US7512521B2 (en) * | 2003-04-30 | 2009-03-31 | Fisher-Rosemount Systems, Inc. | Intrinsically safe field maintenance tool with power islands |
US7054695B2 (en) | 2003-05-15 | 2006-05-30 | Fisher-Rosemount Systems, Inc. | Field maintenance tool with enhanced scripts |
US7526802B2 (en) * | 2003-05-16 | 2009-04-28 | Fisher-Rosemount Systems, Inc. | Memory authentication for intrinsically safe field maintenance tools |
US6925419B2 (en) * | 2003-05-16 | 2005-08-02 | Fisher-Rosemount Systems, Inc. | Intrinsically safe field maintenance tool with removable battery pack |
US7036386B2 (en) * | 2003-05-16 | 2006-05-02 | Fisher-Rosemount Systems, Inc. | Multipurpose utility mounting assembly for handheld field maintenance tool |
US8874402B2 (en) * | 2003-05-16 | 2014-10-28 | Fisher-Rosemount Systems, Inc. | Physical memory handling for handheld field maintenance tools |
US7199784B2 (en) * | 2003-05-16 | 2007-04-03 | Fisher Rosemount Systems, Inc. | One-handed operation of a handheld field maintenance tool |
US7280048B2 (en) * | 2003-08-07 | 2007-10-09 | Rosemount Inc. | Process control loop current verification |
US7018800B2 (en) * | 2003-08-07 | 2006-03-28 | Rosemount Inc. | Process device with quiescent current diagnostics |
WO2005017851A1 (en) * | 2003-08-07 | 2005-02-24 | Rosemount Inc. | Process device with loop override |
US6959607B2 (en) * | 2003-11-10 | 2005-11-01 | Honeywell International Inc. | Differential pressure sensor impulse line monitor |
US8180466B2 (en) * | 2003-11-21 | 2012-05-15 | Rosemount Inc. | Process device with supervisory overlayer |
US7464721B2 (en) * | 2004-06-14 | 2008-12-16 | Rosemount Inc. | Process equipment validation |
RU2389057C2 (en) * | 2005-02-28 | 2010-05-10 | Роузмаунт Инк. | Temporary joint to diagnose production process |
CN101156119B (en) * | 2005-04-04 | 2011-04-13 | 费希尔-罗斯蒙德系统公司 | Diagnostics in industrial process control system |
US8112565B2 (en) | 2005-06-08 | 2012-02-07 | Fisher-Rosemount Systems, Inc. | Multi-protocol field device interface with automatic bus detection |
US20070068225A1 (en) | 2005-09-29 | 2007-03-29 | Brown Gregory C | Leak detector for process valve |
DE102006004582B4 (en) * | 2006-02-01 | 2010-08-19 | Siemens Ag | Procedure for diagnosing clogging of a pulse line in a pressure transmitter and pressure transmitter |
DE102006018174B4 (en) * | 2006-04-18 | 2016-06-23 | Abb Ag | Data acquisition device |
US8032234B2 (en) * | 2006-05-16 | 2011-10-04 | Rosemount Inc. | Diagnostics in process control and monitoring systems |
US7913566B2 (en) | 2006-05-23 | 2011-03-29 | Rosemount Inc. | Industrial process device utilizing magnetic induction |
WO2008009303A1 (en) * | 2006-07-20 | 2008-01-24 | Siemens Aktiengesellschaft | Method for the diagnosis of a blockage of an impulse line in a pressure measurement transducer, and pressure measurement transducer |
US7509220B2 (en) * | 2006-08-16 | 2009-03-24 | Rosemount Inc. | Inclination measurement in process transmitters |
JP4529964B2 (en) * | 2006-09-21 | 2010-08-25 | トヨタ自動車株式会社 | Simulation device, simulation method, and simulation program |
US7953501B2 (en) | 2006-09-25 | 2011-05-31 | Fisher-Rosemount Systems, Inc. | Industrial process control loop monitor |
US8788070B2 (en) | 2006-09-26 | 2014-07-22 | Rosemount Inc. | Automatic field device service adviser |
US7750642B2 (en) | 2006-09-29 | 2010-07-06 | Rosemount Inc. | Magnetic flowmeter with verification |
US7901131B2 (en) * | 2006-12-22 | 2011-03-08 | Hewlett-Packard Development Company, L.P. | Apparatus state determination method and system |
DE102007030713A1 (en) * | 2007-07-02 | 2009-01-08 | Robert Bosch Gmbh | Method for plausibilizing the output signal of a rail pressure sensor |
CN101802928B (en) * | 2007-07-20 | 2014-02-26 | 罗斯蒙德公司 | Pressure diagnostic for rotary equipment |
US7770459B2 (en) * | 2007-07-20 | 2010-08-10 | Rosemount Inc. | Differential pressure diagnostic for process fluid pulsations |
US8898036B2 (en) | 2007-08-06 | 2014-11-25 | Rosemount Inc. | Process variable transmitter with acceleration sensor |
RU2476901C2 (en) * | 2007-09-20 | 2013-02-27 | Фега Грисхабер Кг | Refinement function-based measurement |
US8320751B2 (en) | 2007-12-20 | 2012-11-27 | S.C. Johnson & Son, Inc. | Volatile material diffuser and method of preventing undesirable mixing of volatile materials |
US8250924B2 (en) | 2008-04-22 | 2012-08-28 | Rosemount Inc. | Industrial process device utilizing piezoelectric transducer |
US8165849B2 (en) * | 2008-07-14 | 2012-04-24 | General Electric Company | Medical equipment monitoring method and system |
US7977924B2 (en) | 2008-11-03 | 2011-07-12 | Rosemount Inc. | Industrial process power scavenging device and method of deriving process device power from an industrial process |
US7779702B2 (en) * | 2008-11-03 | 2010-08-24 | Rosemount Inc. | Flow disturbance compensation for magnetic flowmeter |
US7921734B2 (en) | 2009-05-12 | 2011-04-12 | Rosemount Inc. | System to detect poor process ground connections |
US8682630B2 (en) * | 2009-06-15 | 2014-03-25 | International Business Machines Corporation | Managing component coupling in an object-centric process implementation |
DE102011009894A1 (en) | 2011-01-31 | 2012-08-02 | Krohne Messtechnik Gmbh | Vortex flowmeter |
WO2012118775A2 (en) * | 2011-03-02 | 2012-09-07 | Robert Batey | Apparatus for sensing media density in a pipeline |
US9207670B2 (en) | 2011-03-21 | 2015-12-08 | Rosemount Inc. | Degrading sensor detection implemented within a transmitter |
US9020768B2 (en) | 2011-08-16 | 2015-04-28 | Rosemount Inc. | Two-wire process control loop current diagnostics |
US9052240B2 (en) | 2012-06-29 | 2015-06-09 | Rosemount Inc. | Industrial process temperature transmitter with sensor stress diagnostics |
US9207129B2 (en) | 2012-09-27 | 2015-12-08 | Rosemount Inc. | Process variable transmitter with EMF detection and correction |
US9602122B2 (en) | 2012-09-28 | 2017-03-21 | Rosemount Inc. | Process variable measurement noise diagnostic |
EP2778619B1 (en) * | 2013-03-15 | 2015-12-02 | Invensys Systems, Inc. | Process variable transmitter |
US9939820B2 (en) | 2013-03-15 | 2018-04-10 | RPM Industries, LLC | Electronic control of fluid operations for machines |
MX350081B (en) | 2013-08-19 | 2017-08-25 | Touchsensor Tech Llc | Capacitive sensor filtering method. |
US9569054B2 (en) | 2013-08-19 | 2017-02-14 | Touchsensor Technologies, Llc | Capacitive sensor filtering apparatus, method, and system |
US10013113B2 (en) | 2013-08-19 | 2018-07-03 | Touchsensor Technologies, Llc | Capacitive sensor filtering apparatus, method, and system |
US10663331B2 (en) | 2013-09-26 | 2020-05-26 | Rosemount Inc. | Magnetic flowmeter with power limit and over-current detection |
CN105874308B (en) | 2014-01-06 | 2018-09-25 | 株式会社神户制钢所 | Deterioration detecting apparatus and thermocouple check device |
US10367612B2 (en) | 2015-09-30 | 2019-07-30 | Rosemount Inc. | Process variable transmitter with self-learning loop diagnostics |
KR102550799B1 (en) * | 2020-10-26 | 2023-07-03 | 주식회사 웰릭스 | System of separating composite signals of multiple composite sensors |
Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPH0728502A (en) * | 1993-07-08 | 1995-01-31 | Toshiba Corp | Plant controller |
JPH08114638A (en) * | 1994-10-14 | 1996-05-07 | Meidensha Corp | Machinery abnormality diagnosing apparatus |
US5587931A (en) * | 1995-10-20 | 1996-12-24 | Tri-Way Machine Ltd. | Tool condition monitoring system |
WO1997008627A1 (en) * | 1995-08-31 | 1997-03-06 | Arch Development Corporation | A neural network based system for equipment surveillance |
US5646600A (en) * | 1995-01-12 | 1997-07-08 | General Electric Company | Instrument for detecting potential future failures of valves in critical control systems |
JPH10263989A (en) * | 1997-03-24 | 1998-10-06 | Mitsubishi Materials Corp | Defect detecting device and detecting method for rotary cutting tool |
Family Cites Families (103)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US29383A (en) * | 1860-07-31 | Improvement in preserving food | ||
NL135953C (en) | 1960-12-02 | |||
US3096434A (en) * | 1961-11-28 | 1963-07-02 | Daniel Orifice Fitting Company | Multiple integration flow computer |
US3404264A (en) * | 1965-07-19 | 1968-10-01 | American Meter Co | Telemetering system for determining rate of flow |
US3701280A (en) * | 1970-03-18 | 1972-10-31 | Daniel Ind Inc | Method and apparatus for determining the supercompressibility factor of natural gas |
USRE29383E (en) | 1974-01-10 | 1977-09-06 | Process Systems, Inc. | Digital fluid flow rate measurement or control system |
US4058975A (en) * | 1975-12-08 | 1977-11-22 | General Electric Company | Gas turbine temperature sensor validation apparatus and method |
US4099413A (en) * | 1976-06-25 | 1978-07-11 | Yokogawa Electric Works, Ltd. | Thermal noise thermometer |
US4337516A (en) * | 1980-06-26 | 1982-06-29 | United Technologies Corporation | Sensor fault detection by activity monitoring |
US4530234A (en) * | 1983-06-30 | 1985-07-23 | Mobil Oil Corporation | Method and system for measuring properties of fluids |
JPH0619666B2 (en) * | 1983-06-30 | 1994-03-16 | 富士通株式会社 | Failure diagnosis processing method |
US4707796A (en) * | 1983-10-19 | 1987-11-17 | Calabro Salvatore R | Reliability and maintainability indicator |
US4649515A (en) * | 1984-04-30 | 1987-03-10 | Westinghouse Electric Corp. | Methods and apparatus for system fault diagnosis and control |
US4517468A (en) * | 1984-04-30 | 1985-05-14 | Westinghouse Electric Corp. | Diagnostic system and method |
US4642782A (en) * | 1984-07-31 | 1987-02-10 | Westinghouse Electric Corp. | Rule based diagnostic system with dynamic alteration capability |
US4644479A (en) * | 1984-07-31 | 1987-02-17 | Westinghouse Electric Corp. | Diagnostic apparatus |
JPH0734162B2 (en) * | 1985-02-06 | 1995-04-12 | 株式会社日立製作所 | Analogical control method |
US5179540A (en) * | 1985-11-08 | 1993-01-12 | Harris Corporation | Programmable chip enable logic function |
US5005142A (en) * | 1987-01-30 | 1991-04-02 | Westinghouse Electric Corp. | Smart sensor system for diagnostic monitoring |
EP0308455B1 (en) * | 1987-04-02 | 1993-01-27 | Eftag Entstaubungs- Und Fördertechnik Ag | Circuit arrangement for evaluating a signal produced by a semiconductor sensor |
US4873655A (en) * | 1987-08-21 | 1989-10-10 | Board Of Regents, The University Of Texas System | Sensor conditioning method and apparatus |
US4907167A (en) * | 1987-09-30 | 1990-03-06 | E. I. Du Pont De Nemours And Company | Process control system with action logging |
US4831564A (en) * | 1987-10-22 | 1989-05-16 | Suga Test Instruments Co., Ltd. | Apparatus for estimating and displaying remainder of lifetime of xenon lamps |
US5274572A (en) * | 1987-12-02 | 1993-12-28 | Schlumberger Technology Corporation | Method and apparatus for knowledge-based signal monitoring and analysis |
US5488697A (en) * | 1988-01-12 | 1996-01-30 | Honeywell Inc. | Problem state monitoring system |
US5193143A (en) * | 1988-01-12 | 1993-03-09 | Honeywell Inc. | Problem state monitoring |
US4924418A (en) * | 1988-02-10 | 1990-05-08 | Dickey-John Corporation | Universal monitor |
JPH0774961B2 (en) * | 1988-04-07 | 1995-08-09 | 株式会社日立製作所 | Auto tuning PID controller |
US4964125A (en) * | 1988-08-19 | 1990-10-16 | Hughes Aircraft Company | Method and apparatus for diagnosing faults |
US5197328A (en) * | 1988-08-25 | 1993-03-30 | Fisher Controls International, Inc. | Diagnostic apparatus and method for fluid control valves |
US5099436A (en) * | 1988-11-03 | 1992-03-24 | Allied-Signal Inc. | Methods and apparatus for performing system fault diagnosis |
EP0369489A3 (en) * | 1988-11-18 | 1991-11-27 | Omron Corporation | Sensor controller system |
JP2714091B2 (en) * | 1989-01-09 | 1998-02-16 | 株式会社日立製作所 | Field instrument |
US5098197A (en) * | 1989-01-30 | 1992-03-24 | The United States Of America As Represented By The United States Department Of Energy | Optical Johnson noise thermometry |
US5081598A (en) * | 1989-02-21 | 1992-01-14 | Westinghouse Electric Corp. | Method for associating text in automatic diagnostic system to produce recommended actions automatically |
JPH0692914B2 (en) * | 1989-04-14 | 1994-11-16 | 株式会社日立製作所 | Equipment / facility condition diagnosis system |
US5089984A (en) * | 1989-05-15 | 1992-02-18 | Allen-Bradley Company, Inc. | Adaptive alarm controller changes multiple inputs to industrial controller in order for state word to conform with stored state word |
US4934196A (en) * | 1989-06-02 | 1990-06-19 | Micro Motion, Inc. | Coriolis mass flow rate meter having a substantially increased noise immunity |
US5293585A (en) * | 1989-08-31 | 1994-03-08 | Kabushiki Kaisha Toshiba | Industrial expert system |
JP2656637B2 (en) * | 1989-11-22 | 1997-09-24 | 株式会社日立製作所 | Process control system and power plant process control system |
JPH03166601A (en) * | 1989-11-27 | 1991-07-18 | Hitachi Ltd | Symbolizing device and process controller and control supporting device using the symbolizing device |
CA2031765C (en) * | 1989-12-08 | 1996-02-20 | Masahide Nomura | Method and system for performing control conforming with characteristics of controlled system |
US5111531A (en) * | 1990-01-08 | 1992-05-05 | Automation Technology, Inc. | Process control using neural network |
US5235527A (en) * | 1990-02-09 | 1993-08-10 | Toyota Jidosha Kabushiki Kaisha | Method for diagnosing abnormality of sensor |
US5134574A (en) * | 1990-02-27 | 1992-07-28 | The Foxboro Company | Performance control apparatus and method in a processing plant |
US5122976A (en) * | 1990-03-12 | 1992-06-16 | Westinghouse Electric Corp. | Method and apparatus for remotely controlling sensor processing algorithms to expert sensor diagnoses |
US5053815A (en) * | 1990-04-09 | 1991-10-01 | Eastman Kodak Company | Reproduction apparatus having real time statistical process control |
EP0460892B1 (en) * | 1990-06-04 | 1996-09-04 | Hitachi, Ltd. | A control device for controlling a controlled apparatus, and a control method therefor |
US5282261A (en) * | 1990-08-03 | 1994-01-25 | E. I. Du Pont De Nemours And Co., Inc. | Neural network process measurement and control |
US5142612A (en) * | 1990-08-03 | 1992-08-25 | E. I. Du Pont De Nemours & Co. (Inc.) | Computer neural network supervisory process control system and method |
US5167009A (en) * | 1990-08-03 | 1992-11-24 | E. I. Du Pont De Nemours & Co. (Inc.) | On-line process control neural network using data pointers |
US5197114A (en) * | 1990-08-03 | 1993-03-23 | E. I. Du Pont De Nemours & Co., Inc. | Computer neural network regulatory process control system and method |
US5121467A (en) * | 1990-08-03 | 1992-06-09 | E.I. Du Pont De Nemours & Co., Inc. | Neural network/expert system process control system and method |
US5224203A (en) * | 1990-08-03 | 1993-06-29 | E. I. Du Pont De Nemours & Co., Inc. | On-line process control neural network using data pointers |
US5212765A (en) * | 1990-08-03 | 1993-05-18 | E. I. Du Pont De Nemours & Co., Inc. | On-line training neural network system for process control |
US5175678A (en) * | 1990-08-15 | 1992-12-29 | Elsag International B.V. | Method and procedure for neural control of dynamic processes |
US5130936A (en) * | 1990-09-14 | 1992-07-14 | Arinc Research Corporation | Method and apparatus for diagnostic testing including a neural network for determining testing sufficiency |
US5367612A (en) * | 1990-10-30 | 1994-11-22 | Science Applications International Corporation | Neurocontrolled adaptive process control system |
US5265031A (en) * | 1990-11-26 | 1993-11-23 | Praxair Technology, Inc. | Diagnostic gas monitoring process utilizing an expert system |
US5214582C1 (en) * | 1991-01-30 | 2001-06-26 | Edge Diagnostic Systems | Interactive diagnostic system for an automobile vehicle and method |
EP0570505B1 (en) * | 1991-02-05 | 1999-03-31 | Storage Technology Corporation | Knowledge based machine initiated maintenance system and method |
US5357449A (en) * | 1991-04-26 | 1994-10-18 | Texas Instruments Incorporated | Combining estimates using fuzzy sets |
US5671335A (en) * | 1991-05-23 | 1997-09-23 | Allen-Bradley Company, Inc. | Process optimization using a neural network |
US5317520A (en) * | 1991-07-01 | 1994-05-31 | Moore Industries International Inc. | Computerized remote resistance measurement system with fault detection |
US5414645A (en) * | 1991-10-25 | 1995-05-09 | Mazda Motor Corporation | Method of fault diagnosis in an apparatus having sensors |
US5327357A (en) * | 1991-12-03 | 1994-07-05 | Praxair Technology, Inc. | Method of decarburizing molten metal in the refining of steel using neural networks |
DE69210041T2 (en) * | 1991-12-13 | 1996-10-31 | Honeywell Inc | DESIGN OF PIEZORESISTIVE PRESSURE SENSOR MADE FROM SILICON |
US5365423A (en) * | 1992-01-08 | 1994-11-15 | Rockwell International Corporation | Control system for distributed sensors and actuators |
US5282131A (en) * | 1992-01-21 | 1994-01-25 | Brown And Root Industrial Services, Inc. | Control system for controlling a pulp washing system using a neural network controller |
US5349541A (en) * | 1992-01-23 | 1994-09-20 | Electric Power Research Institute, Inc. | Method and apparatus utilizing neural networks to predict a specified signal value within a multi-element system |
EP0565761B1 (en) * | 1992-04-15 | 1997-07-09 | Mita Industrial Co. Ltd. | An image forming apparatus provided with self-diagnosis system |
GB9208704D0 (en) * | 1992-04-22 | 1992-06-10 | Foxboro Ltd | Improvements in and relating to sensor units |
JP3100757B2 (en) * | 1992-06-02 | 2000-10-23 | 三菱電機株式会社 | Monitoring and diagnostic equipment |
FR2692037B1 (en) * | 1992-06-03 | 1997-08-08 | Thomson Csf | DIAGNOSTIC PROCESS OF AN EVOLVING PROCESS. |
CA2097558C (en) * | 1992-06-16 | 2001-08-21 | William B. Kilgore | Directly connected display of process control system in an open systems windows environment |
US5384699A (en) * | 1992-08-24 | 1995-01-24 | Associated Universities, Inc. | Preventive maintenance system for the photomultiplier detector blocks of pet scanners |
US5477444A (en) * | 1992-09-14 | 1995-12-19 | Bhat; Naveen V. | Control system using an adaptive neural network for target and path optimization for a multivariable, nonlinear process |
US5228780A (en) * | 1992-10-30 | 1993-07-20 | Martin Marietta Energy Systems, Inc. | Dual-mode self-validating resistance/Johnson noise thermometer system |
US5486996A (en) * | 1993-01-22 | 1996-01-23 | Honeywell Inc. | Parameterized neurocontrollers |
US5394341A (en) * | 1993-03-25 | 1995-02-28 | Ford Motor Company | Apparatus for detecting the failure of a sensor |
US5361628A (en) * | 1993-08-02 | 1994-11-08 | Ford Motor Company | System and method for processing test measurements collected from an internal combustion engine for diagnostic purposes |
US5386373A (en) * | 1993-08-05 | 1995-01-31 | Pavilion Technologies, Inc. | Virtual continuous emission monitoring system with sensor validation |
US5404064A (en) * | 1993-09-02 | 1995-04-04 | The United States Of America As Represented By The Secretary Of The Navy | Low-frequency electrostrictive ceramic plate voltage sensor |
US5489831A (en) * | 1993-09-16 | 1996-02-06 | Honeywell Inc. | Pulse width modulating motor controller |
US5408406A (en) * | 1993-10-07 | 1995-04-18 | Honeywell Inc. | Neural net based disturbance predictor for model predictive control |
JP2893233B2 (en) * | 1993-12-09 | 1999-05-17 | 株式会社ユニシアジェックス | Diagnostic device for in-cylinder pressure sensor |
US5440478A (en) * | 1994-02-22 | 1995-08-08 | Mercer Forge Company | Process control method for improving manufacturing operations |
JP3040651B2 (en) * | 1994-02-23 | 2000-05-15 | 三菱重工業株式会社 | Signal processing device |
MX9602687A (en) * | 1994-02-23 | 1997-05-31 | Rosemount Inc | Field transmitter for storing information. |
US5483387A (en) * | 1994-07-22 | 1996-01-09 | Honeywell, Inc. | High pass optical filter |
JP3307095B2 (en) * | 1994-08-23 | 2002-07-24 | 株式会社日立製作所 | Control system diagnosis / analysis apparatus and method |
US5704011A (en) * | 1994-11-01 | 1997-12-30 | The Foxboro Company | Method and apparatus for providing multivariable nonlinear control |
US5600148A (en) * | 1994-12-30 | 1997-02-04 | Honeywell Inc. | Low power infrared scene projector array and method of manufacture |
US5572420A (en) * | 1995-04-03 | 1996-11-05 | Honeywell Inc. | Method of optimal controller design for multivariable predictive control utilizing range control |
US5781878A (en) | 1995-06-05 | 1998-07-14 | Nippondenso Co., Ltd. | Apparatus and method for diagnosing degradation or malfunction of oxygen sensor |
CN1047442C (en) * | 1995-06-06 | 1999-12-15 | 罗斯蒙德公司 | Open sensor diagnostic system for temperature transmitter in a process control system |
US5561599A (en) * | 1995-06-14 | 1996-10-01 | Honeywell Inc. | Method of incorporating independent feedforward control in a multivariable predictive controller |
US5610552A (en) * | 1995-07-28 | 1997-03-11 | Rosemount, Inc. | Isolation circuitry for transmitter electronics in process control system |
US5705978A (en) * | 1995-09-29 | 1998-01-06 | Rosemount Inc. | Process control transmitter |
CA2165400C (en) * | 1995-12-15 | 1999-04-20 | Jean Serodes | Method of predicting residual chlorine in water supply systems |
US5746511A (en) * | 1996-01-03 | 1998-05-05 | Rosemount Inc. | Temperature transmitter with on-line calibration using johnson noise |
US5700090A (en) * | 1996-01-03 | 1997-12-23 | Rosemount Inc. | Temperature sensor transmitter with sensor sheath lead |
US5757852A (en) * | 1997-01-24 | 1998-05-26 | Western Atlas International, Inc. | Method for compression of high resolution seismic data |
-
1998
- 1998-03-26 US US09/048,452 patent/US5956663A/en not_active Expired - Lifetime
-
1999
- 1999-03-26 DE DE19983112.2T patent/DE19983112B3/en not_active Expired - Fee Related
- 1999-03-26 AU AU31059/99A patent/AU3105999A/en not_active Abandoned
- 1999-03-26 WO PCT/US1999/006123 patent/WO1999049369A1/en active Application Filing
- 1999-03-26 GB GB0023453A patent/GB2353364B/en not_active Expired - Fee Related
- 1999-03-26 JP JP2000538277A patent/JP4847642B2/en not_active Expired - Lifetime
Patent Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPH0728502A (en) * | 1993-07-08 | 1995-01-31 | Toshiba Corp | Plant controller |
JPH08114638A (en) * | 1994-10-14 | 1996-05-07 | Meidensha Corp | Machinery abnormality diagnosing apparatus |
US5646600A (en) * | 1995-01-12 | 1997-07-08 | General Electric Company | Instrument for detecting potential future failures of valves in critical control systems |
WO1997008627A1 (en) * | 1995-08-31 | 1997-03-06 | Arch Development Corporation | A neural network based system for equipment surveillance |
US5587931A (en) * | 1995-10-20 | 1996-12-24 | Tri-Way Machine Ltd. | Tool condition monitoring system |
JPH10263989A (en) * | 1997-03-24 | 1998-10-06 | Mitsubishi Materials Corp | Defect detecting device and detecting method for rotary cutting tool |
Non-Patent Citations (5)
Title |
---|
CACCAVALE F ET AL: "OBSERVER-BASED FAULT DETECTION FOR ROBOT MANIPULATORS", PROCEEDINGS OF THE 1997 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS A AUTOMATION, ALBUQUERQUE, APR. 20 - 25, 1997, vol. 4, no. CONF. 14, 20 April 1997 (1997-04-20), INSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS, pages 2881 - 2887, XP000776267 * |
PATENT ABSTRACTS OF JAPAN vol. 095, no. 004 31 May 1995 (1995-05-31) * |
PATENT ABSTRACTS OF JAPAN vol. 096, no. 009 30 September 1996 (1996-09-30) * |
PATENT ABSTRACTS OF JAPAN vol. 099, no. 001 29 January 1999 (1999-01-29) * |
SCHNEIDER C ET AL: "VERGLEICHENDE UNTERSUCHUNG VON METHODEN ANALYTISCHER REDUNDANZ", AUTOMATISIERUNGSTECHNIK - AT, vol. 43, no. 10, 1 October 1995 (1995-10-01), pages 484 - 489, XP000534071 * |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
DE10258921A1 (en) * | 2002-12-17 | 2004-07-01 | Abb Research Ltd. | Feedback control method, e.g. for regulation of the contact force between a current collector and a power wire in electrically driven vehicles, wherein a narrow band filter range is matched to measurement signal properties |
Also Published As
Publication number | Publication date |
---|---|
GB2353364A (en) | 2001-02-21 |
DE19983112B3 (en) | 2016-04-07 |
JP2002508540A (en) | 2002-03-19 |
US5956663A (en) | 1999-09-21 |
JP4847642B2 (en) | 2011-12-28 |
GB2353364B (en) | 2002-08-07 |
GB0023453D0 (en) | 2000-11-08 |
DE19983112T1 (en) | 2001-07-12 |
AU3105999A (en) | 1999-10-18 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US5956663A (en) | Signal processing technique which separates signal components in a sensor for sensor diagnostics | |
EP1190282B1 (en) | Process device diagnostics using process variable sensor signal | |
US7010459B2 (en) | Process device diagnostics using process variable sensor signal | |
US6505517B1 (en) | High accuracy signal processing for magnetic flowmeter | |
EP1915660B1 (en) | Process variable transmitter with diagnostics | |
JP4422412B2 (en) | Flow diagnostic system | |
EP1866716B1 (en) | Diagnostics in industrial process control system | |
US6701274B1 (en) | Prediction of error magnitude in a pressure transmitter | |
WO2002071362A2 (en) | Remaining life prediction for field device electronics board | |
EP0829038A1 (en) | Device in a process system for detecting events | |
EP2856269B1 (en) | Process control loop current verification |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
AK | Designated states |
Kind code of ref document: A1 Designated state(s): AE AL AM AT AU AZ BA BB BG BR BY CA CH CN CU CZ DE DK EE ES FI GB GE GH GM HU ID IL IN IS JP KE KG KP KR KZ LC LK LR LS LT LU LV MD MG MK MN MW MX NO NZ PL PT RO RU SD SE SG SI SK SL TJ TM TR TT UA UG UZ VN YU ZA ZW |
|
AL | Designated countries for regional patents |
Kind code of ref document: A1 Designated state(s): GH GM KE LS MW SD SL SZ UG ZW AM AZ BY KG KZ MD RU TJ TM AT BE CH CY DE DK ES FI FR GB GR IE IT LU MC NL PT SE BF BJ CF CG CI CM GA GN GW ML MR NE SN TD TG |
|
DFPE | Request for preliminary examination filed prior to expiration of 19th month from priority date (pct application filed before 20040101) | ||
121 | Ep: the epo has been informed by wipo that ep was designated in this application | ||
ENP | Entry into the national phase |
Ref document number: 200023453 Country of ref document: GB Kind code of ref document: A |
|
ENP | Entry into the national phase |
Ref document number: 2000 538277 Country of ref document: JP Kind code of ref document: A |
|
NENP | Non-entry into the national phase |
Ref country code: KR |
|
RET | De translation (de og part 6b) |
Ref document number: 19983112 Country of ref document: DE Date of ref document: 20010712 |
|
WWE | Wipo information: entry into national phase |
Ref document number: 19983112 Country of ref document: DE |
|
122 | Ep: pct application non-entry in european phase |