CN111811820B - Steam turbine main unit vibration state evaluation method based on multi-parameter comparison - Google Patents

Steam turbine main unit vibration state evaluation method based on multi-parameter comparison Download PDF

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CN111811820B
CN111811820B CN202010697682.1A CN202010697682A CN111811820B CN 111811820 B CN111811820 B CN 111811820B CN 202010697682 A CN202010697682 A CN 202010697682A CN 111811820 B CN111811820 B CN 111811820B
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侯栋楠
夏亚磊
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Huazhong Electric Power Test Research Institute China of Datang Corp Science and Technology Research Institute Co Ltd
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Abstract

The invention relates to a turbine main machine vibration state evaluation method based on multi-parameter comparison, which adopts the technical scheme that 19 parameters closely related to the vibration amplitude of a turbine main machine are extracted from a power plant DCS (distributed control System), a time sequence in 24h of the 19 parameters is extracted, a vibration amplitude time sequence in 24h of 5 bearing vibration measuring points of the turbine main machine is extracted, and 19 parameter sequences closely related to the vibration amplitude of the turbine main machine are respectively calculated
Figure DDA0002591915120000011
And vibration amplitude sequence of main engine of steam turbine

Description

Steam turbine main unit vibration state evaluation method based on multi-parameter comparison
Technical Field
The invention relates to a steam turbine main unit vibration state evaluation method based on multi-parameter comparison.
Background
The turbine is one of the most important devices of a power plant, and the vibration monitoring and evaluation of the turbine are always the key points for ensuring the safe operation of the power plant. If can discover as early as possible to lead to the reason of unit abnormal vibration through the analysis steam turbine vibration condition, instruct the operating personnel to take measures, will effectual assurance equipment safety and stability operation.
Most of the existing steam turbine fault diagnosis technologies are used for judging the fault state of a steam turbine by analyzing vibration signals of the steam turbine. At present, the diagnosis technology for researching the abnormal vibration of the steam turbine caused by the state change of other equipment in a power plant is less, and in practice, if the running equipment with the larger vibration correlation with a main machine of the steam turbine can be found, engineering personnel can be effectively helped to find the source causing the abnormal vibration of the steam turbine, and the problem of the abnormal vibration of the equipment is solved.
Disclosure of Invention
In view of the above situation, in order to overcome the defects of the prior art, the present invention aims to provide a method for evaluating the vibration state of a steam turbine main unit based on multi-parameter comparison, which can effectively solve the problem of finding the cause of abnormal vibration of the steam turbine main unit.
The technical scheme of the invention is as follows:
a steam turbine main unit vibration state evaluation method based on multi-parameter comparison comprises the following steps:
step 1: when the power generation load is maintained to be more than 50% of the total load of the unit, no fluctuation exceeding 10% occurs within 24h, and the vibration amplitudes of the 1-5 # bearings are smaller than 40 mu m, 19 parameters closely related to the vibration amplitude of the main engine of the steam turbine are extracted from a power plant DCS, and the parameters specifically comprise the following parameters:
the method comprises the steps of unit load, main steam flow, main steam valve front pressure, main steam valve front temperature, regulation stage pressure, high-pressure cylinder exhaust pressure, environment temperature, back pressure, 1# bearing temperature, 1# shaft seal steam supply temperature, 2# bearing temperature, 2# shaft seal steam supply temperature, 3# bearing temperature, 3# shaft seal steam supply temperature, 4# bearing temperature, 4# shaft seal steam supply temperature, 5# bearing temperature, 5# shaft seal steam supply temperature and condenser end difference, extracting a time sequence A in 19 parameters 24hi 1、Ai 2、Ai 3······Ai 19；
Step 2: extracting vibration amplitude time sequences in 24h of 1# bearing bush vibration, 2# bearing bush vibration, 3# bearing bush vibration, 4# bearing bush vibration and 5# bearing bush vibration of a main machine of the steam turbine in a DCS system of a power plant, ensuring that the data extraction time and the sampling interval are consistent with the data extraction time and the sampling interval in the step 1 during extraction, and extracting the vibration amplitude time sequences V in 24h of the 5 bearing vibration measuring points of the main machine of the steam turbinei 1、Vi 2、Vi 3、Vi 4、Vi 5；
And step 3: and (3) normalizing the time series of the parameters extracted in the steps 1 and 2, wherein the normalization formula is as follows:
f(x)＝(x-Min)/(Max-Min)
in the formula: x is a term in the normalized sequence, Min is the minimum value of the time sequence, and Max is the maximum value of the time sequence;
the time sequence within 19 parameters 24h closely related to the vibration amplitude of the main engine of the steam turbine is normalized to obtain a new time sequence f (A)i 1)、f(Ai 2)、f(Ai 3)……f(Ai 19) Is marked as ai 1、ai 2、ai 3······ai 19；
The vibration amplitude time sequence in the vibration measuring point 24h of the 1-5 # bearing of the steam turbine main unit is subjected to normalization processing to obtain a new vibration amplitude time sequence f (V)i 1)、f(Vi 2)、f(Vi 3)、f(Vi 4)、f(Vi 5) Is denoted by vi 1、vi 2、vi 3、vi 4、vi 5；
And 4, step 4:
calculating the normalized 1# bearing bush vibration amplitude time sequence v obtained in the stepsi 1And a normalized time sequence a of 19 parameters closely related to the vibration amplitude of the main machine of the steam turbinei 1、ai 2、ai 3······ai 19The linear correlation coefficient between the two is calculated according to the following formula:
Figure GDA0002973336980000021
in the formula: rvaIs a linear correlation coefficient, viThe bearing bush vibration amplitude is the bearing bush vibration amplitude of the normalized bearing bush vibration amplitude time sequence,
Figure GDA0002973336980000022
for normalized bearing bush vibrationBearing bush vibration amplitude average value of vibration amplitude time sequence, aiIs 19 parameters a closely related to the vibration amplitude of the main machine of the steam turbinei 1、ai 2、ai 3······ai 19In the above-mentioned manner, the first and second,
Figure GDA0002973336980000023
is a time series of 19 parametersi 1、ai 2、ai 3······ai 19Average value of (d);
respectively calculating linear correlation coefficients between the 1# bearing bush vibration amplitude time sequence and the 19 parameter time sequence to form a 1# bearing bush vibration linear correlation coefficient vector:
Figure GDA0002973336980000024
according to the method in the step 4, calculating a 2-5 # bearing bush vibration amplitude time sequence vi 2、vi 3、vi 4、vi 5Respectively adding the linear correlation coefficients of the time series of 19 parameters to form respective linear correlation coefficient vectors of the bearing bush vibration of 2-5 #;
and 5: when the steam turbine set vibration influence factors are diagnosed, 19 parameters and bearing bush vibration data of the bearing to be detected, which are closely related to the vibration amplitude of the main machine of the steam turbine, are extracted by the power plant DCS system, and a diagnosis parameter sequence a is obtained according to the steps 1-3i 1’、ai 2’、ai 3’······ai 19’And diagnosing the vibration amplitude sequence vi 1’(ii) a Calculating a correlation coefficient according to the linear correlation coefficient vectors of the bearing bush vibration 1-5 # obtained in the step 4, and comprising the following steps:
1) processing the diagnostic parameter sequence and the diagnostic vibration amplitude sequence using the following formulas:
f(x)＝xi/x1
in the formula:x1to extract the first term of the sequence, xiFor each item in the sequence;
obtaining a new parameter sequence
Figure GDA0002973336980000025
And vibration amplitude sequence
Figure GDA0002973336980000026
2) Calculated according to the following formula
Figure GDA0002973336980000027
And
Figure GDA0002973336980000028
direct relevance index LN(i)：
Figure GDA0002973336980000031
Figure GDA0002973336980000032
In the formula (I), the compound is shown in the specification,
Figure GDA0002973336980000033
for the corresponding values of the corresponding linear correlation coefficient vector,
Figure GDA0002973336980000034
g is
Figure GDA0002973336980000035
And
Figure GDA0002973336980000036
n is an integer from 1 to 19, namely, the serial number of the corresponding parameter in the 19 parameters, and i is the ith item of data in the corresponding sequence;
calculated according to the following formula
Figure GDA0002973336980000037
And
Figure GDA0002973336980000038
coefficient of correlation C betweenN：
Figure GDA0002973336980000039
In the formula, k is the number of sampling points of a sampling sequence, and 19 parameters closely related to the vibration amplitude of the steam turbine main engine are the same as the length, the sampling start time and the sampling interval of the sampling points of the bearing bush vibration data to be detected;
3) respectively calculating 19 parameter sequences closely related to vibration amplitude of main engine of steam turbine
Figure GDA00029733369800000310
And vibration amplitude sequence of main engine of steam turbine
Figure GDA00029733369800000311
To obtain C1,C2,......C19；
Step 6: at C1,C2,......C19In (1), when any item C<0.7 this factor is not related to abnormal vibration, when any item C>0.7, the factor is closely related to the abnormal vibration, and whether the equipment monitored by the factor is in failure or not is mainly checked, so that the bearing bush of the steam turbine is caused to vibrate to a large extent.
Preferably, the main machine of the steam turbine is a condensing 150MW unit produced by a Shanghai steam turbine plant.
Preferably, the DCS system extracts a time sequence A within 19 parameters 24h closely related to the vibration amplitude of the main machine of the steam turbinei 1、Ai 2、Ai 3······Ai 19The sampling interval of (3) s; the DCS system extracts a vibration amplitude time sequence V in 24h of vibration measurement points of 1-5 # bearing bush of the steam turbine main uniti 1、Vi 2、Vi 3、Vi 4、Vi 5The sampling interval of (3) s; the DCS extracts 19 parameters of the bearing to be detected, which are more than 4h and closely related to the vibration amplitude of the main machine of the steam turbine, and the sampling interval of the bearing bush vibration data to be detected is 3 s.
The method is novel and unique, and the relevance index L is establishedN(i) Obtaining the correlation indexes between the bearing bush vibration and 19 closely related variables with the vibration of the main machine of the steam turbine in a fault state, introducing linear correlation coefficients of the bearing bush vibration and 19 closely related variables with the vibration of the main machine of the steam turbine when the running state of the unit is good into the indexes, weakening the indexes with large influence on the unit vibration when the state is good, enhancing the indexes with small influence on the unit vibration when the state is good, and further obtaining the correlation coefficient CNThe system can reflect that the coefficient which has small influence on the unit when the unit is in a good state can not closely influence the vibration state of the unit when the unit is in a fault, so that factors behind the indexes are the reasons for reducing the probability of the fault, a numerical parameter for evaluating the correlation between different operation parameters and the vibration amplitude of the main machine of the steam turbine is provided, the reason for causing the abnormal vibration of the main machine of the steam turbine can be obtained according to the calculated correlation parameters, compared with the traditional manual identification and diagnosis method, the system can provide quantitative indexes to assist in fault reason analysis, the calculation speed is high through computer programming, the influence of human subjective factors in fault diagnosis can be effectively reduced, the use is convenient, the effect is good, the accuracy is high, and the system is an innovation in the method for evaluating the vibration state of the main machine of the steam turbine.
Detailed Description
The following examples further illustrate the embodiments of the present invention in detail.
A steam turbine main unit vibration state evaluation method based on multi-parameter comparison comprises the following steps:
step 1: when the power generation load is maintained to be more than 50% of the total load of the unit, no fluctuation exceeding 10% occurs in 24h, and the vibration amplitudes of 1-5 # bearings are smaller than 40 mu m, 19 parameters closely related to the vibration amplitude of a main machine of a steam turbine are extracted from a power plant DCS (distributed control systems), and the parameters specifically comprise the following parameters:
the method comprises the steps of unit load, main steam flow, main steam valve front pressure, main steam valve front temperature, regulation stage pressure, high-pressure cylinder exhaust pressure, environment temperature, back pressure, 1# bearing temperature, 1# shaft seal steam supply temperature, 2# bearing temperature, 2# shaft seal steam supply temperature, 3# bearing temperature, 3# shaft seal steam supply temperature, 4# bearing temperature, 4# shaft seal steam supply temperature, 5# bearing temperature, 5# shaft seal steam supply temperature and condenser end difference, extracting a time sequence A in 19 parameters 24hi 1、Ai 2、Ai 3······Ai 19(sampling interval 3 s);
step 2: extracting vibration amplitude time sequences in 24h of vibration of 1# bearing bush, 2# bearing bush, 3# bearing bush, 4# bearing bush and 5# bearing bush of a main machine of the steam turbine in a DCS (distributed control systems) of a power plant, ensuring that the data extraction time and the sampling interval are consistent with the data extraction time and the sampling interval in the step 1 during extraction, and extracting the vibration amplitude time sequences V in 24h of the 5 bearing vibration measuring points of the main machine of the steam turbinei 1、Vi 2、Vi 3、Vi 4、Vi 5(sampling interval 3 s);
the main machine of the steam turbine is a condensing 150MW unit produced by a Shanghai steam turbine plant;
and step 3: and (3) normalizing the time series of the parameters extracted in the steps 1 and 2, wherein the normalization formula is as follows:
f(x)＝(x-Min)/(Max-Min)
in the formula: x is a term in the normalized sequence, Min is the minimum value of the time sequence, and Max is the maximum value of the time sequence;
the time sequence within 19 parameters 24h closely related to the vibration amplitude of the main engine of the steam turbine is normalized to obtain a new time sequence f (A)i 1)、f(Ai 2)、f(Ai 3)……f(Ai 19) Is marked as ai 1、ai 2、ai 3······ai 19；
The vibration amplitude time sequence in the vibration measuring point 24h of the 1-5 # bearing of the steam turbine main unit is subjected to normalization processing to obtain a new vibration amplitude time sequence f (V)i 1)、f(Vi 2)、f(Vi 3)、f(Vi 4)、f(Vi 5) Is denoted by vi 1、vi 2、vi 3、vi 4、vi 5；
And 4, step 4:
calculating the normalized 1# bearing bush vibration amplitude time sequence v obtained in the stepsi 1And a normalized time sequence a of 19 parameters closely related to the vibration amplitude of the main machine of the steam turbinei 1、ai 2、ai 3······ai 19The linear correlation coefficient between the two is calculated according to the following formula:
Figure GDA0002973336980000051
in the formula: rvaIs a linear correlation coefficient, viThe bearing bush vibration amplitude is the bearing bush vibration amplitude of the normalized bearing bush vibration amplitude time sequence,
Figure GDA0002973336980000052
bearing bush vibration amplitude average value a of normalized bearing bush vibration amplitude time sequenceiIs 19 parameters a closely related to the vibration amplitude of the main machine of the steam turbinei 1、ai 2、ai 3······ai 19In the above-mentioned manner, the first and second,
Figure GDA0002973336980000053
is a time series of 19 parametersi 1、ai 2、ai 3······ai 19Average value of (d);
respectively calculating linear correlation coefficients between the 1# bearing bush vibration amplitude time sequence and the 19 parameter time sequence to form a 1# bearing bush vibration linear correlation coefficient vector:
Figure GDA0002973336980000054
according to the method in the step 4, calculating a 2-5 # bearing bush vibration amplitude time sequence vi 2、vi 3、vi 4、vi 5Respectively adding the linear correlation coefficients of the time series of 19 parameters to form respective linear correlation coefficient vectors of the bearing bush vibration of 2-5 #;
and 5: when the vibration influence factors of the steam turbine set are diagnosed, 19 parameters closely related to the vibration amplitude of the main machine of the steam turbine and the vibration data of the bearing bush to be detected are extracted by the power plant DCS system for more than 4h of the bearing to be detected (if the bearing to be detected is the 1# bearing vibration, the 1# bearing bush vibration data is extracted, if the bearing to be detected is the 2# bearing vibration, the 2# bearing bush vibration data is extracted, and the like), and the diagnosis parameter sequence a is obtained according to the steps 1-3i 1’、ai 2’、ai 3’······ai 19’And diagnosing the vibration amplitude sequence vi 1’(sampling interval 3 s); calculating a correlation coefficient according to the linear correlation coefficient vectors of the bearing bush vibration 1-5 # obtained in the step 4, and comprising the following steps:
1) processing the diagnostic parameter sequence and the diagnostic vibration amplitude sequence using the following formulas:
f(x)＝xi/x1
in the formula: x is the number of1To extract the first term of the sequence, xiFor each item in the sequence;
obtaining a new parameter sequence
Figure GDA0002973336980000055
And vibration amplitude sequence
Figure GDA0002973336980000056
N is an integer from 1 to 19, namely the serial number of the corresponding parameter in the 19 parameters;
2) calculated according to the following formula
Figure GDA0002973336980000057
And
Figure GDA0002973336980000058
direct relevance index LN(i)：
Figure GDA0002973336980000061
Figure GDA0002973336980000062
In the formula (I), the compound is shown in the specification,
Figure GDA0002973336980000063
for the corresponding values of the corresponding linear correlation coefficient vector,
Figure GDA0002973336980000064
g is
Figure GDA0002973336980000065
And
Figure GDA0002973336980000066
n is an integer from 1 to 19, namely, the serial number of the corresponding parameter in the 19 parameters, and i is the ith item of data in the corresponding sequence;
calculated according to the following formula
Figure GDA0002973336980000067
And
Figure GDA0002973336980000068
coefficient of correlation C betweenN：
Figure GDA0002973336980000069
In the formula, k is the number of sampling points of a sampling sequence, and 19 parameters closely related to the vibration amplitude of the steam turbine main engine are the same as the length, the sampling start time and the sampling interval of the sampling points of the bearing bush vibration data to be detected;
3) respectively calculating 19 parameter sequences closely related to vibration amplitude of main engine of steam turbine
Figure GDA00029733369800000610
And vibration amplitude sequence of main engine of steam turbine
Figure GDA00029733369800000611
To obtain C1,C2,......C19；
Step 6: at C1,C2,......C19In (1), when any item C<0.7 this factor is not related to abnormal vibration, when any item C>0.7, the factor is closely related to the abnormal vibration, and whether the equipment monitored by the factor is in failure or not is mainly checked, so that the bearing bush of the steam turbine is caused to vibrate to a large extent.
The invention obtains better results through practical application, and the cases are as follows:
case 1:
taking the condensing type 150MW unit of the marine steam turbine plant as an example, 1# bearing bush vibration data abnormity occurs in 2016, 9, 12 and the maximum amplitude is 83 mu m, and the 1# bearing and 19 related parameters are calculated according to the method to obtain the related parameter C. The calculation results are as follows:
Figure GDA00029733369800000612
Figure GDA0002973336980000071
the related parameter C of the pressure of the adjusting stage and the bearing bush vibration of the 1# bearing is 0.890 to 0.7, and the related parameter C of the other parameters is less than 0.7, and the condition that the stress of a steam turbine rotor at the bearing of the 1# bearing is uneven due to adjustment of an adjusting stage air supply valve sequence is found through inquiry, so that the practicability and feasibility of the method are verified.
Case 2:
taking the condensing type 150MW unit of the marine steam turbine plant as an example, abnormal vibration data of a bearing bush of the 4# bearing occurs in 2018, 2 month and 5 days, the maximum amplitude is 69 micrometers, the 4# bearing and 19 relevant parameters are calculated according to the method, and the relevant parameter C is obtained through calculation. The calculation results are as follows:
Figure GDA0002973336980000072
Figure GDA0002973336980000081
the adjusting-stage pressure 4# shaft seal steam supply temperature parameter C is more than 0.797 and less than 0.7, correlation parameters C of other parameters are less than 0.7, and the condition that the shaft seal steam supply amount fluctuates and the 4# shaft seal steam supply is insufficient is found through inquiry, so that the vibration of a unit is abnormal.
Compared with the traditional manual identification and diagnosis method, the method can provide quantitative indexes to assist in fault cause analysis, has high calculation speed through computer programming, can effectively reduce the influence of human subjective factors during fault diagnosis, is convenient to use, has good effect and high accuracy, and is an innovation in the method for evaluating the vibration state of the main machine of the steam turbine.

Claims (5)

1. A steam turbine main unit vibration state evaluation method based on multi-parameter comparison is characterized by comprising the following steps:
step 1: when the power generation load is maintained to be more than 50% of the total load of the unit, no fluctuation exceeding 10% occurs within 24h, and the vibration amplitudes of the 1-5 # bearings are smaller than 40 mu m, 19 parameters closely related to the vibration amplitude of the main engine of the steam turbine are extracted from a power plant DCS, and the parameters specifically comprise the following parameters:
the method comprises the steps of unit load, main steam flow, main steam valve front pressure, main steam valve front temperature, regulation stage pressure, high-pressure cylinder exhaust pressure, environment temperature, back pressure, 1# bearing temperature, 1# shaft seal steam supply temperature, 2# bearing temperature, 2# shaft seal steam supply temperature, 3# bearing temperature, 3# shaft seal steam supply temperature, 4# bearing temperature, 4# shaft seal steam supply temperature, 5# bearing temperature, 5# shaft seal steam supply temperature and condenser end difference, extracting a time sequence A in 19 parameters 24hi 1、Ai 2、Ai 3······Ai 19；
Step 2: extracting vibration amplitude time sequences in 24h of 1# bearing bush vibration, 2# bearing bush vibration, 3# bearing bush vibration, 4# bearing bush vibration and 5# bearing bush vibration of a main machine of the steam turbine in a DCS system of a power plant, ensuring that the data extraction time and the sampling interval are consistent with the data extraction time and the sampling interval in the step 1 during extraction, and extracting the vibration amplitude time sequences V in 24h of the 5 bearing vibration measuring points of the main machine of the steam turbinei 1、Vi 2、Vi 3、Vi 4、Vi 5；
And step 3: and (3) normalizing the time series of the parameters extracted in the steps 1 and 2, wherein the normalization formula is as follows:
f(x)＝(x-Min)/(Max-Min)
in the formula: x is a term in the normalized sequence, Min is the minimum value of the time sequence, and Max is the maximum value of the time sequence;
the time sequence within 19 parameters 24h closely related to the vibration amplitude of the main engine of the steam turbine is normalized to obtain a new time sequence f (A)i 1)、f(Ai 2)、f(Ai 3)……f(Ai 19) Is marked as ai 1、ai 2、ai 3······ai 19；
The vibration amplitude time sequence in the vibration measuring point 24h of the 1-5 # bearing of the steam turbine main unit is subjected to normalization processing to obtain a new vibration amplitude time sequence f (V)i 1)、f(Vi 2)、f(Vi 3)、f(Vi 4)、f(Vi 5) Is denoted by vi 1、vi 2、vi 3、vi 4、vi 5；
And 4, step 4:
calculating the normalized 1# bearing bush vibration amplitude time sequence v obtained in the stepsi 1And a normalized time sequence a of 19 parameters closely related to the vibration amplitude of the main machine of the steam turbinei 1、ai 2、ai 3······ai 19The linear correlation coefficient between the two is calculated according to the following formula:
Figure FDA0002973336970000011
in the formula: rvaIs a linear correlation coefficient, viThe bearing bush vibration amplitude is the bearing bush vibration amplitude of the normalized bearing bush vibration amplitude time sequence,
Figure FDA0002973336970000012
bearing bush vibration amplitude average value a of normalized bearing bush vibration amplitude time sequenceiIs 19 parameters a closely related to the vibration amplitude of the main machine of the steam turbinei 1、ai 2、ai 3······ai 19In the above-mentioned manner, the first and second,
Figure FDA0002973336970000013
is a time series of 19 parametersi 1、ai 2、ai 3······ai 19Average value of (d);
respectively calculating linear correlation coefficients between the 1# bearing bush vibration amplitude time sequence and the 19 parameter time sequence to form a 1# bearing bush vibration linear correlation coefficient vector:
Figure FDA0002973336970000021
according to the method in the step 4, calculating a 2-5 # bearing bush vibration amplitude time sequence vi 2、vi 3、vi 4、vi 5Respectively adding the linear correlation coefficients of the time series of 19 parameters to form respective linear correlation coefficient vectors of the bearing bush vibration of 2-5 #;
and 5: when the steam turbine set vibration influence factors are diagnosed, 19 parameters and bearing bush vibration data of the bearing to be detected, which are closely related to the vibration amplitude of the main machine of the steam turbine, are extracted by the power plant DCS system, and a diagnosis parameter sequence a is obtained according to the steps 1-3i 1’、ai 2’、ai 3’······ai 19’And diagnosing the vibration amplitude sequence vi 1’(ii) a Calculating a correlation coefficient according to the linear correlation coefficient vectors of the bearing bush vibration 1-5 # obtained in the step 4, and comprising the following steps:
1) processing the diagnostic parameter sequence and the diagnostic vibration amplitude sequence using the following formulas:
f(x)＝xi/x1
in the formula: x is the number of1To extract the first term of the sequence, xiFor each item in the sequence;
obtaining a new parameter sequence
Figure FDA0002973336970000022
And vibration amplitude sequence
Figure FDA0002973336970000023
2) Calculated according to the following formula
Figure FDA0002973336970000024
And
Figure FDA0002973336970000025
direct relevance index LN(i)：
Figure FDA0002973336970000026
Figure FDA0002973336970000027
In the formula (I), the compound is shown in the specification,
Figure FDA0002973336970000028
for the corresponding values of the corresponding linear correlation coefficient vector,
Figure FDA0002973336970000029
g is
Figure FDA00029733369700000210
And
Figure FDA00029733369700000211
n is an integer from 1 to 19, namely, the serial number of the corresponding parameter in the 19 parameters, and i is the ith item of data in the corresponding sequence;
calculated according to the following formula
Figure FDA00029733369700000212
And
Figure FDA00029733369700000213
coefficient of correlation C betweenN：
Figure FDA00029733369700000214
In the formula, k is the number of sampling points of a sampling sequence, and 19 parameters closely related to the vibration amplitude of the steam turbine main engine are the same as the length, the sampling start time and the sampling interval of the sampling points of the bearing bush vibration data to be detected;
3) respectively calculating 19 parameter sequences closely related to vibration amplitude of main engine of steam turbine
Figure FDA0002973336970000031
And vibration amplitude sequence of main engine of steam turbine
Figure FDA0002973336970000032
To obtain C1,C2,......C19；
Step 6: at C1,C2,......C19In (1), when any item C<0.7 this factor is not related to abnormal vibration, when any item C>0.7, the factor is closely related to the abnormal vibration, and whether the equipment monitored by the factor is in failure or not is mainly checked, so that the bearing bush of the steam turbine is caused to vibrate to a large extent.
2. The multi-parameter comparison-based vibration state evaluation method for the main machine of the steam turbine according to claim 1, wherein the main machine of the steam turbine is a condensing 150MW unit produced by a Shanghai steam turbine plant.
3. The method for evaluating the vibration state of the main machine of the steam turbine based on the multi-parameter comparison as claimed in claim 1, wherein the DCS system extracts the time sequence A within 19 parameters 24h closely related to the vibration amplitude of the main machine of the steam turbinei 1、Ai 2、Ai 3······Ai 19The sampling interval of (3) s.
4. The multi-parameter comparison-based steam turbine main unit vibration state evaluation method according to claim 1, wherein the DCS system extracts a vibration amplitude time sequence V within 24h of vibration measuring points of bearing bush vibration of 1-5 # of the steam turbine main uniti 1、Vi 2、Vi 3、Vi 4、Vi 5The sampling interval of (3) s.
5. The multi-parameter comparison-based steam turbine main unit vibration state evaluation method according to claim 1, wherein the DCS system extracts more than 4h of 19 parameters of the bearing to be tested, which are closely related to the vibration amplitude of the steam turbine main unit, and the sampling interval of the bearing bush vibration data of the bearing to be tested is 3 s.
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