CN103364200A - State evaluation method of starting procedure of gas turbine - Google Patents
State evaluation method of starting procedure of gas turbine Download PDFInfo
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- CN103364200A CN103364200A CN2013102773724A CN201310277372A CN103364200A CN 103364200 A CN103364200 A CN 103364200A CN 2013102773724 A CN2013102773724 A CN 2013102773724A CN 201310277372 A CN201310277372 A CN 201310277372A CN 103364200 A CN103364200 A CN 103364200A
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Abstract
The invention relates to the field of state monitoring of a rotary machine, in particular to a state evaluation method of a starting procedure of a gas turbine. The state evaluation method comprises the following steps of (1) collecting state information; (2) constructing a normal curve band for rotating speed of an output shaft of the gas turbine; (3) evaluating the state; and (4) updating the normal curve band. The invention provides an evaluation method of the starting procedure of the normal curve band for the rotating speed of the output shaft of the gas turbine, and has the advantages of small calculated amount, fast computation speed and easiness in comprehending and the like, and the evaluation problem of a quantitative state of the starting procedure of the gas turbine is solved.
Description
Technical field
The present invention relates to the condition monitoring for rotating machinery field, particularly a kind of gas turbine start-up course state evaluating method.
Background technology
Gas turbine maneuverability is good, has good peaking performance.So gas turbine starts success or not and directly affects the needs that can gas turbine respond and satisfy the user rapidly.If the startup fault will cause heavy economic losses, even have influence on the complete of whole electrical network.
The start-up course of gas turbine is a multisystem cross-couplings process.Chinese invention patent 94193471.3 provides a kind of method of the operation conditions for showing the start-up course turbine, its technical characterictic is: other at a datum curve (RV) that draws specific parameter (m.w.b) and operation correlation parameter (kz, kT, kp) from turbine, also show the time dependent curve of turbine speed (n) (AV).But the purpose of this patent is that the operating turbine state in the start-up course is carried out suitable demonstration, and is not used in the state estimation of start-up course.
Compare with Chinese invention patent 94193471.3, the invention provides a kind of gas turbine start-up course state evaluating method, according to the normalized curve band that repeatedly normally starts sample structure gas turbine output shaft rotating speed, contrast actual speed line and normalized curve band, realize the state estimation of start-up course, find that in time gas turbine starts abnormal conditions, reduce maintenance cost.
Summary of the invention
The object of the present invention is to provide a kind of gas turbine start-up course state evaluating method, realize the state estimation of gas turbine start-up course.
The object of the present invention is achieved like this, the present invention includes following steps:
(1) acquisition state information: gather gas turbine start-up course status information, comprise starting trigger pip and gas turbine output shaft rotating speed;
(2) make up gas turbine output shaft rotating speed normalized curve band: the normal start-up course sample of accumulation gas turbine, carry out the statistical study of gas turbine output shaft rotating speed and feature modeling, set up gas turbine output shaft rotating speed normalized curve band;
(3) state estimation: when gas turbine starts triggering, the gas turbine start-up course is carried out state estimation, if the gas turbine output shaft rotating speed is in gas turbine output shaft rotating speed normalized curve band the time, then the start-up course assessment result is normal, and the start-up course state estimation finishes; When if the gas turbine output shaft rotating speed exceeds the normalized curve band, the start-up course assessment result is undesired;
(4) assessment result is confirmed: be abnormal start-up course by finally confirming to assessment result in the step (3), if confirm that assessment result is correct, then select maintenance measure, the start-up course state estimation finishes; If confirm that assessment result is incorrect, be that abnormal start-up course assessment result changes to normally with assessment result in the step (3) then, simultaneously these start-up course data are added into the normal start-up course sample in the step (2);
(5) upgrade the normalized curve band: according to step (2), recomputate coboundary and the lower boundary of gas turbine output shaft rotating speed sample, obtain new gas turbine output shaft rotating speed normalized curve band.
The step of setting up gas turbine output shaft rotating speed normalized curve band of step (2) comprising:
(1) the normal start-up course sample of accumulation: when the sample of normal start-up course referred to that gas turbine normally starts, the gas turbine output shaft rotating speed was triggered to idling rating sampled value during this period of time in startup:
Wherein, small tenon i=1,2,3,, m represents sample, j=1, and 2,3,, n represents sampling instant;
(2) gas turbine output shaft rotating speed statistical study: seek in all samples, maximal value, the minimum value of each sampling instant gas turbine output shaft rotating speed define i gas turbine output shaft rotating speed sample and are respectively in j maximal value, minimum value constantly:
max(X
j)＝1.1*max{x
1,j,x
2,j,…,x
i,j}
,
min(X
j)＝0.9*min{x
1,j,x
2,j,…,x
i,j}
(3) calculate gas turbine output shaft rotating speed border: the coboundary and the lower boundary that calculate gas turbine output shaft rotating speed normalized curve band based on maximal value, the minimum value of gas turbine output shaft rotating speed:
X
The coboundary=max (X
j), j=1,2 ..., n
。
X
Lower boundary=min (X
j), j=1,2 ..., n
Beneficial effect of the present invention is:
The start-up course appraisal procedure based on gas turbine output shaft rotating speed normalized curve band that the present invention proposes has the advantages such as calculated amount is little, computing velocity fast, easy to understand, has solved the quantitative state estimation problem of gas turbine start-up course.
Description of drawings
Fig. 1 is the state estimation process flow diagram of gas turbine start-up course;
Fig. 2 is gas turbine output shaft rotating speed normalized curve band schematic diagram;
Fig. 3 is gas turbine start-up course assessment result example schematic diagram;
Fig. 4 is the gas turbine output shaft rotating speed normalized curve band schematic diagram before and after upgrading.
Embodiment
Below in conjunction with accompanying drawing the present invention is described further.
Basic step of the present invention may further comprise the steps:
At first, collection of the present invention can reflect the status information of gas turbine start-up course.
Then, according to the normal start-up course sample that history data obtains, adopt statistical law to make up gas turbine output shaft rotating speed normalized curve band.
Afterwards, assess the state of this start-up course according to gas turbine output shaft rotating speed normalized curve band, if assessment result is " normally ", then this start-up course assessment finishes.
If assessment result is " undesired ", but through confirming as " normally " start-up course, the start-up course data that then this group are determined " undesired " are added into normal start-up course sample, rebuild gas turbine output shaft rotating speed normalized curve band.
Gas turbine start-up course state estimation process flow diagram referring to shown in Figure 1 is elaborated for gas turbine start-up course state evaluating method of the present invention, may further comprise the steps:
Step 101: gather the information of reflection gas turbine start-up course, start trigger pip and gas turbine output shaft rotating speed.Gas turbine output shaft rotating speed when only collection startup trigger pip is "True".For the relevant information of start-up course, can adopt corresponding sensor directly to gather, also can obtain from the database of gas turbine supervisory system.For the collection of parameter, between the sample frequency 1Hz to 5Hz.
Step 102: according to the historical normal start-up course sample of accumulation, adopt statistical law to make up gas turbine output shaft rotating speed normalized curve band.
The below has listed the method for statistical law structure gas turbine output shaft rotating speed normalized curve band:
(1) collect normal start-up course sample, this is the process of an initial accumulated.For the ease of setting forth specific implementation process of the present invention, suppose and collected at present two subnormal startup gas turbine output shaft rotary speed datas, sample frequency 2Hz, 120 seconds sampling times, 60 of sampled points, namely
j=[0?1?2?3?4?5?6?7?8?9?10?11?12?13?14?15?16?17?18?19?20?21?22?23?24?25?26?27?28?29?30?31?32?33?3435?36?37?38?39?40?41?42?43?44?45?46?47?48?49?50?51?52?53?54?55?56?57?58?59?60]
X
1=[0?0?0?0?0?0?0?0?0?2.6479?11.7124?19.3371?22.0332?22.0332?22.033222.0429?22.0332?22.0332?22.0332?22.0332?22.0236?22.0332?22.0236?22.0268?22.0268?22.026822.0268?22.0268?22.0268?22.0268?22.0268?22.0268?22.0332?22.0332?22.0429?22.0236?26.459232.4314?36.7897?39.7951?42.414?44.6753?46.753?48.6664?50.7248?52.8508?54.9092?57.112559.4704?62.9204?66.2737?71.1249?73.7341?75.8118?78.6625?80.9722?83.4461?86.1519?88.693590.9644?93.564]
X
2=[0?0?0?0?0?0?0?0?0?2.2516?10.5721?18.0035?22.0236?22.0236?22.023622.0429?22.0429?22.0236?22.0332?22.0429?22.0332?22.0236?22.0429?22.0332?22.0332?22.042922.0236?22.0332?22.0236?22.0332?22.0332?22.0332?22.0429?22.0332?22.0429?22.0429?26.720132.4121?37.2149?41.4283?44.9749?47.6034?50.0097?52.1453?54.1844?56.2138?58.7167?62.243966.8342?71.5501?74.1399?76.4689?79.0588?81.6293?84.2965?86.7897?89.109?91.38?93.989296.637?99.2656];
(2) the gas turbine output shaft rotating speed obtains max(X in maximal value, the minimum value of each sampling instant gas turbine output shaft rotating speed in the above-mentioned sample of searching
j) and min (X
j), sampling instant j=1,2 ..., n.
For example, the computation process of the maximal value of sampling instant j=10, minimum value
max(X
10)=1.1*max(x
1,10，x
2,10)=1.1*max(2.2516，2.6479)=1.1*2.6479=2.91269
min(X
10)=0.9*min(x
1,10，x
2,10)=0.9*max(2.2516，2.6479)=0.9*2.2516=2.02644
(3) feature modeling: each maximal value, the minimum value constantly of gas turbine output shaft rotating speed based on step (2) obtains according to sample sequence, obtains coboundary and the lower boundary of gas turbine output shaft rotating speed normalized curve band.
X
The coboundary=[0 0 0 0 0 0 0 0 0 2.91269 12.88364 21.27081 24.2365224.23652 24.23652 24.24719 24.24719 24.23652 24.23652 24.2471924.23652 24.23652 24.24719 24.23652 24.23652 24.24719 24.2294824.23652 24.22948 24.23652 24.23652 24.23652 24.24719 24.2365224.24719 24.24719 29.39211 35.67454 40.93639 45.57113 49.4723952.36374 55.01067 57.35983 59.60284 61.83518 64.58837 68.4682973.51762 78.70511 81.55389 84.11579 86.96468 89.79223 92.7261595.46867 98.0199 100.518 103.38812 106.3007 109.19216]
X
Lower boundary=[0 0 0 0 0 0 0 0 0 2.02644 9.51489 16.20315 19.8212419.82124 19.82124 19.83861 19.82988 19.82124 19.82988 19.8298819.82124 19.82124 19.82124 19.82412 19.82412 19.82412 19.8212419.82412 19.82124 19.82412 19.82412 19.82412 19.82988 19.8298819.83861 19.82124 23.81328 29.17089 33.11073 35.81559 38.172640.20777 42.0777 43.79976 45.65232 47.56572 49.41828 51.4012553.52336 56.62836 59.64633 64.01241 66.36069 68.23062 70.7962572.87498 75.10149 77.53671 79.82415 81.86796 84.2076]
According to coboundary and the lower boundary of gas turbine output shaft rotating speed, be depicted as gas turbine output shaft rotating speed normalized curve band shown in Figure 2.
Step 103: the startup trigger pip of Real-Time Monitoring gas turbine, when monitoring when starting trigger pip and being "True", begin to contrast gas turbine output shaft rotating speed and normalized curve band, judge whether to exceed the scope of normalized curve band, if the gas turbine output shaft rotating speed is in the normalized curve band, then the start-up course assessment result is " normally "; If the gas turbine output shaft rotating speed exceeds the normalized curve band, then the start-up course assessment result is " undesired ".
For example, the start-up course data that gas turbine is new
X
3=[0?0?0?0?0?0?0?0?0?0?7.2961?15.4909?20.1971?20.1778?20.177820.1875?20.1875?20.1875?20.1875?20.1778?20.1971?20.1875?20.1971?20.1875?20.1875?20.187520.1875?20.1875?20.1875?20.1778?20.1875?20.1875?20.1875?20.1778?20.1778?20.1875?22.100928.6529?33.4847?37.5338?41.3993?44.6077?47.3425?49.4009?51.5365?53.2953?55.344?58.349461.9927?68.9215?72.3038?74.3815?77.126?79.9768?81.9675?84.6927?86.9347?89.4279?92.44394.453?96.9463];
This start-up course curve is carried out comparative analysis with the normal start up curve band of gas turbine that step 102 calculates.Fig. 3 is assessment result, X
3At j=10,11,12,37,38 five sampling instants exceed the normal start up curve band of gas turbine lower boundary X
Following The boundary, so the start-up course assessment result is " undesired ".
Step 104: the start-up course assessment result that step 103 obtains is " undesired ", need to confirm the correctness of assessment result.Confirm assessment " incorrect ", assessment result in the step 103 is changed to " normally " for the start-up course assessment result of " undesired ", simultaneously with these start-up course data X
3Be added into the normal start-up course sample in the step 102.
Step 105: step 103 is judged the start-up course of " undesired ", but the start-up course data of confirming as " normally " through step 104 are stored, be added into normal start-up course sample, recomputate according to the normal start up curve band of step 102 pair gas turbine.Concrete step of updating is as follows:
At first, according to step 102, calculate new normal start-up course sample X
1, X
2And X
3Middle gas turbine output shaft rotating speed obtains max(X in maximal value, the minimum value of each sampling instant gas turbine output shaft rotating speed
j) and min (X
j), sampling instant j=1,2 ..., n.For example, maximal value, the minimum value of the gas turbine output shaft rotating speed during sampling instant j=10
max(X
10)=1.1*max(x
1,10，x
2,10，x
3,10)=1.1*max(2.2516，2.6479，0)=1.1*2.6479=2.91269
min(X
10)=0.9*min(x
1,10，x
2,10，x
3,10)=0.9*max(2.2516，2.6479，0)=0.9*0=0
Secondly, based on each constantly new maximal value, minimum value of gas turbine output shaft rotating speed, calculate new coboundary and the lower boundary of the normal start up curve band of gas turbine output shaft rotating speed.
X
The coboundary=[0 0 0 0 0 0 0 0 0 2.91269 12.88364 21.27081 24.2365224.23652 24.23652 24.24719 24.24719 24.23652 24.23652 24.2471924.23652 24.23652 24.24719 24.23652 24.23652 24.24719 24.2294824.23652 24.22948 24.23652 24.23652 24.23652 24.24719 24.2365224.24719 24.24719 29.39211 35.67454 40.93639 45.57113 49.4723952.36374 55.01067 57.35983 59.60284 61.83518 64.58837 68.4682973.51762 78.70511 81.55389 84.11579 86.96468 89.79223 92.7261595.46867 98.0199 100.518 103.38812 106.3007 109.19216]
X
Lower boundary=[0 0 0 0 0 0 0 0 0 0 6.56649 13.94181 18.17739 18.1600218.16002 18.16875 18.16875 18.16875 18.16875 18.16002 18.1773918.16875 18.17739 18.16875 18.16875 18.16875 18.16875 18.1687518.16875 18.16002 18.16875 18.16875 18.16875 18.16002 18.1600218.16875 19.89081 25.78761 30.13623 33.78042 37.25937 40.1469342.0777 43.79976 45.65232 47.56572 49.41828 51.40125 53.5233656.62836 59.64633 64.01241 66.36069 68.23062 70.79625 72.8749875.10149 77.53671 79.82415 81.86796 84.2076]
At last, according to coboundary and the lower boundary of the new gas turbine output shaft rotating speed that calculates, obtain new gas turbine output shaft rotating speed normalized curve band shown in Figure 4.
The start-up course state estimation finishes.
The present invention has analyzed the gas turbine start-up course, has proposed the concept of gas turbine start-up course normalized curve band.Can realize the qualitative assessment of gas turbine start-up course based on start-up course normalized curve band.
It is optionally that gas turbine output shaft rotating speed normalized curve band upgrades.Only (3) judge the start-up course of " undesired " in steps, but when confirming as the start-up course of " normally " through step (4), just should organize the start-up course data stores, be added into normal start-up course sample, according to obtaining new gas turbine output shaft rotating speed normalized curve band in the step (2).
Claims (2)
1. a gas turbine start-up course state evaluating method is characterized in that, comprises the steps:
(1) acquisition state information: gather gas turbine start-up course status information, comprise starting trigger pip and gas turbine output shaft rotating speed;
(2) make up gas turbine output shaft rotating speed normalized curve band: the normal start-up course sample of accumulation gas turbine, carry out the statistical study of gas turbine output shaft rotating speed and feature modeling, set up gas turbine output shaft rotating speed normalized curve band;
(3) state estimation: when gas turbine starts triggering, the gas turbine start-up course is carried out state estimation, if the gas turbine output shaft rotating speed is in gas turbine output shaft rotating speed normalized curve band the time, then the start-up course assessment result is normal, and the start-up course state estimation finishes; When if the gas turbine output shaft rotating speed exceeds the normalized curve band, the start-up course assessment result is undesired;
(4) assessment result is confirmed: be abnormal start-up course by finally confirming to assessment result in the step (3), if confirm that assessment result is correct, then select maintenance measure, the start-up course state estimation finishes; If confirm that assessment result is incorrect, be that abnormal start-up course assessment result changes to normally with assessment result in the step (3) then, simultaneously these start-up course data are added into the normal start-up course sample in the step (2);
(5) upgrade the normalized curve band: according to step (2), recomputate coboundary and the lower boundary of gas turbine output shaft rotating speed sample, obtain new gas turbine output shaft rotating speed normalized curve band.
2. a kind of gas turbine start-up course state evaluating method according to claim 1 is characterized in that, the described step of setting up gas turbine output shaft rotating speed normalized curve band of step (2) comprises:
(1) the normal start-up course sample of accumulation: when the sample of normal start-up course referred to that gas turbine normally starts, the gas turbine output shaft rotating speed was triggered to idling rating sampled value during this period of time in startup:
Wherein, small tenon i=1,2,3,, m represents sample, j=1, and 2,3,, n represents sampling instant;
(2) gas turbine output shaft rotating speed statistical study: seek in all samples, maximal value, the minimum value of each sampling instant gas turbine output shaft rotating speed define i gas turbine output shaft rotating speed sample and are respectively in j maximal value, minimum value constantly:
max(X
j)＝1.1*max{x
1,j,x
2,j,…,x
i,j}
,
min(X
j)＝0.9*min{x
1,j,x
2,j,…,x
i,j}
(3) calculate gas turbine output shaft rotating speed border: the coboundary and the lower boundary that calculate gas turbine output shaft rotating speed normalized curve band based on maximal value, the minimum value of gas turbine output shaft rotating speed:
X
The coboundary=max (X
j), j=1,2 ..., n
。
X
Lower boundary=min (X
j), j=1,2 ..., n.
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|---|---|---|---|
| CN201310277372.4A CN103364200B (en) | 2013-07-03 | 2013-07-03 | A kind of gas turbine start-up course state evaluating method |
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| CN103364200B CN103364200B (en) | 2015-12-02 |
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ID=49366053
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104460602A (en) * | 2014-11-07 | 2015-03-25 | 浙江大学 | Method and system for detecting safety of industrial process control technological process |
| CN113374582A (en) * | 2021-07-28 | 2021-09-10 | 哈电发电设备国家工程研究中心有限公司 | Device and method for evaluating running state of gas turbine |
| CN114235423A (en) * | 2021-12-13 | 2022-03-25 | 中国船舶重工集团公司第七0三研究所 | Method for detecting faults of gas turbine lubricating oil supply system |
| CN114235422A (en) * | 2021-12-13 | 2022-03-25 | 中国船舶重工集团公司第七0三研究所 | Method for detecting abnormal starting of gas turbine |
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| CN1131450A (en) * | 1993-09-21 | 1996-09-18 | 西门子公司 | Process and device for imaging operational condition of turbine during starting process |
| US20020173897A1 (en) * | 2001-05-18 | 2002-11-21 | Leamy Kevin Richard | System and method for monitoring thermal state to normalize engine trending data |
| CN101078373A (en) * | 2007-07-05 | 2007-11-28 | 东北大学 | Combustion controlling device and controlling method for mini combustion turbine |
| CN101487756A (en) * | 2009-01-13 | 2009-07-22 | 东南大学 | Harmonic component rotational speed balancing method in rotating machinery vibration analysis |
-
2013
- 2013-07-03 CN CN201310277372.4A patent/CN103364200B/en not_active Expired - Fee Related
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1131450A (en) * | 1993-09-21 | 1996-09-18 | 西门子公司 | Process and device for imaging operational condition of turbine during starting process |
| US20020173897A1 (en) * | 2001-05-18 | 2002-11-21 | Leamy Kevin Richard | System and method for monitoring thermal state to normalize engine trending data |
| CN101078373A (en) * | 2007-07-05 | 2007-11-28 | 东北大学 | Combustion controlling device and controlling method for mini combustion turbine |
| CN101487756A (en) * | 2009-01-13 | 2009-07-22 | 东南大学 | Harmonic component rotational speed balancing method in rotating machinery vibration analysis |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104460602A (en) * | 2014-11-07 | 2015-03-25 | 浙江大学 | Method and system for detecting safety of industrial process control technological process |
| CN113374582A (en) * | 2021-07-28 | 2021-09-10 | 哈电发电设备国家工程研究中心有限公司 | Device and method for evaluating running state of gas turbine |
| CN114235423A (en) * | 2021-12-13 | 2022-03-25 | 中国船舶重工集团公司第七0三研究所 | Method for detecting faults of gas turbine lubricating oil supply system |
| CN114235422A (en) * | 2021-12-13 | 2022-03-25 | 中国船舶重工集团公司第七0三研究所 | Method for detecting abnormal starting of gas turbine |
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|---|---|
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