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CN113010843A - Method and device for determining measurement parameter set, verification method and fault diagnosis method - Google Patents

Method and device for determining measurement parameter set, verification method and fault diagnosis method Download PDF

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CN113010843A
CN113010843A CN202110244931.6A CN202110244931A CN113010843A CN 113010843 A CN113010843 A CN 113010843A CN 202110244931 A CN202110244931 A CN 202110244931A CN 113010843 A CN113010843 A CN 113010843A
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measurement parameter
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邢继
苗壮
徐钊
孙涛
于方小稚
张敏
楚济如
堵树宏
洪郡滢
马心童
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China Nuclear Power Engineering Co Ltd
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Abstract

The invention discloses a method for determining a measurement parameter set for fault diagnosis of a nuclear power plant, which comprises the following steps: respectively acquire each MiCorrelation matrix D of fault and measurement parameter in operation modeiThe correlation matrix DiIs a matrix with m rows and n columns; judging the incidence matrix DiWhether the row vectors corresponding to the faults in the group are different or not; after the judgment result is yes, determining a correlation matrix DiN columns in (1) are MiTarget measurement parameter subset F in operation modei(ii) a For each MiTarget measurement parameter subset F in operation modeiAnd solving a union set to obtain a target measurement parameter set for fault diagnosis of the nuclear power plant. Further, a corresponding device, a verification method and a nuclear power plant fault diagnosis method are also provided. The measurement parameter set determined by the method can provide quantification, integrity and feasibility for establishing a predictive maintenance system for the nuclear power plantThe method has the advantages of improving the safety and the economical efficiency of the nuclear power plant by adopting a high-quality data base in the aspects of traceability, reliability and the like.

Description

Method and device for determining measurement parameter set, verification method and fault diagnosis method
Technical Field
The invention belongs to the technical field of nuclear power equipment detection, and particularly relates to a method and a device for determining a measurement parameter set for nuclear power plant fault diagnosis, a verification method and a method for nuclear power plant fault diagnosis.
Background
The predictive maintenance is to monitor the state of the equipment based on the sensor set (i.e. the measurement parameter set), predict the remaining service life of the equipment, and then decide the time and object of maintenance. The predictive maintenance can realize accurate maintenance before the equipment has obvious function degradation, thereby saving the maintenance cost and improving the equipment safety.
In a nuclear power plant, the current maintenance strategy mainly comprises regular maintenance and corrective maintenance, the intellectualization level of maintenance decision is low, the waste of maintenance resources is serious, and a predictive maintenance system needs to be established urgently to improve the safety and the economy of the operation of the nuclear power plant. Whereas predictive maintenance requires complete, accurate and reliable sensor data, existing sensor settings in nuclear power plants are based primarily on operational control requirements, without consideration of fault monitoring and diagnostic requirements. Applying the traditional analysis method of the measurement parameter set (i.e. the sensor set) to the nuclear power plant has the following technical problems:
firstly, the nuclear power plant system composition is complicated, the operation condition is various, most of the traditional measurement parameter analysis methods are experience-based qualitative analysis methods, errors or omissions are easy to occur, and the requirements of measurement parameter set design on quantification, integrity and traceability are difficult to meet.
Secondly, the traditional analysis method for measuring parameters cannot meet the special requirements of nuclear safety requirements of a nuclear power plant, such as: for a core security related failure, the reliability of the data source used for the measurement parameter set needs to be guaranteed.
In addition, because the design cost of the nuclear power plant is high, in order to reduce the risk and the cost of design and implementation, the measurement parameter set of the nuclear power plant should ensure that the existing parameter basis of the nuclear power plant can be fully utilized so as to reduce the influence on the existing design of the power plant.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a method and a device for determining a measurement parameter set for nuclear power plant fault diagnosis, a verification method and a method for nuclear power plant fault diagnosis, aiming at the defects in the prior art, the measurement parameter set determined by the method can provide a high-quality data basis in the aspects of quantification, integrity, traceability, reliability and the like for establishing an advanced predictive maintenance system for a nuclear power plant, so that the safety and the economy of the nuclear power plant are improved.
In a first aspect, an embodiment of the present invention provides a method for determining a measurement parameter set for nuclear power plant fault diagnosis, including: respectively acquire each MiCorrelation matrix D of fault and measurement parameter in operation modeiWhere i 1, 2iThe method comprises the following steps of (1) forming a matrix with m rows and n columns, wherein m and n are positive integers, the m rows correspond to m faults, and the n columns correspond to n measurement parameters; judging the incidence matrix DiWhether the row vectors corresponding to the faults in the group are different or not; after the judgment result is yes, determining a correlation matrix DiN columns in (1) are MiTarget measurement parameter subset F in operation modei(ii) a For each MiTarget measurement parameter subset F in operation modeiObtaining a union setAnd measuring parameter sets of the nuclear power plant fault diagnosis targets.
Preferably, said separately acquiring each MiCorrelation matrix D of fault and measurement parameter in operation modeiThe method specifically comprises the following steps: acquiring an incidence matrix A of faults and subsystem states, wherein the incidence matrix A is a matrix with m rows and p columns, and the p columns correspond to the p subsystem states; acquiring an incidence matrix B of the subsystem state and the measurement parameters, wherein the incidence matrix B is a matrix with p rows and n columns; obtaining an incidence matrix E of the faults and the measurement parameters under the condition of no influence of the operation mode according to the product of the incidence matrix A and the incidence matrix B, wherein the incidence matrix E is a matrix with m rows and n columns; obtain each MiObtaining a correlation matrix C of the faults and the operation modes by using the influence coefficient of the operation modes on the faults, wherein the correlation matrix C is a matrix of m rows and t columns, p and t are positive integers, and the t columns correspond to t operation modes; respectively obtaining M according to the incidence matrix E and the incidence matrix CiCorrelation matrix D of fault and measurement parameter in operation modeiWherein D isiThe elements in each row are the products of the elements in each row of the incidence matrix E and the influence coefficients of the corresponding faults in the ith column element of the incidence matrix C.
Preferably, said separately acquiring each MiCorrelation matrix D of fault and measurement parameter in operation modeiThe method also comprises the following steps: respectively obtaining subsystem state vectors
Figure BDA0002963749100000031
Fault vector
Figure BDA0002963749100000032
And measuring the parameter vector
Figure BDA0002963749100000033
Wherein,
Figure BDA0002963749100000034
is a vector of the p-dimension,
Figure BDA0002963749100000035
is a vector with the dimension of m,
Figure BDA0002963749100000036
is an n-dimensional vector. The obtaining of the incidence matrix a of the fault and the subsystem state specifically includes: identification of subsystem state vectors using a full-range nuclear power plant simulator
Figure BDA0002963749100000038
Respectively in the fault vector
Figure BDA0002963749100000037
And determining the correlation coefficient of each fault and the subsystem state according to the influence degree to obtain a correlation matrix A. The acquiring of the incidence matrix B of the subsystem state and the measurement parameter specifically includes: if the measurement parameter is inevitably existed in the subsystem state, determining that the correlation coefficient of the subsystem state and the measurement parameter is 1, and if not, determining that the correlation coefficient of the subsystem state and the measurement parameter is 0; and taking the determined correlation coefficient of each subsystem state and the measured parameter as the corresponding element of the correlation matrix B to obtain the correlation matrix B of the subsystem state and the measured parameter. Said obtaining each MiObtaining a correlation matrix C of the faults and the operation mode by using the influence coefficient of the operation mode on the faults, and specifically comprising the following steps: according to the unit at each MiDetermining the defense quit time length after each fault in the operation modeiThe level of impact of the operating mode on the fault; according to each MiDetermining each M by the influence level of the operation mode on the faultiThe influence coefficient of the operation mode on the fault; each M to be determinediAnd taking the influence coefficient of the operation mode on the fault as a corresponding element of the incidence matrix C to obtain the incidence matrix C of the fault and the operation mode.
Preferably, the determining the correlation coefficient between each fault and the subsystem state according to the degree of influence to obtain the correlation matrix a includes: after the simulated fault occurs, respectively calculating the change interval of key parameters of each subsystem, wherein the key parameters comprise temperature, and/or pressure, and/or liquid level, and/or flow; if the variation interval of the key parameters is smaller than or equal to the first threshold, determining that the correlation coefficient of the fault and the subsystem state is S1; if the change interval of the key parameter is between the first threshold and the second threshold, determining that the correlation coefficient of the fault and the subsystem state is S2; if the variation interval of the key parameter is greater than or equal to the second threshold value, determining that the correlation coefficient of the fault and the subsystem state is S3; and taking the determined correlation coefficient of each fault and the subsystem state as a corresponding element of the correlation matrix A to obtain the correlation matrix A.
Preferably, after the judgment result is yes, determining a correlation matrix DiN columns in (1) are MiTarget measurement parameter subset F in operation modeiThe method comprises the following steps: after the judgment result is yes, determining a correlation matrix DiN measurement parameters corresponding to n columns in the first target measurement parameter subset; performing data set optimization on the first target measurement parameter subset to obtain M from the first target measurement parameter subsetiTarget measurement parameter subset F in operation modei. The optimizing the data set of the first target measurement parameter subset specifically includes: any measurement parameter in the first target measurement parameter subset is deleted; further judging the corresponding incidence matrix D after the measurement parameters are deletediWhether the row vectors corresponding to the faults are different or not is judged; deleting the measurement parameters in the first target measurement parameter subset after the judgment result is negative; and if so, keeping the measurement parameters in the first target measurement parameter subset, and traversing all the measurement parameters in the first target measurement parameter subset to complete the data set optimization of the first target measurement parameter subset.
Preferably, the incidence matrix D is judgediAfter the row vectors corresponding to all faults in the target measurement parameter subset F are different, and in all the operation modesiBefore the union set is worked out, the method for determining the measurement parameter set for the fault diagnosis of the nuclear power plant further comprises the following steps: after the judgment result is negative, the incidence matrix D is matchediAnd optimizing the data set by using the n measurement parameters corresponding to the n columns. The pair correlation matrix DiThe data set optimization is performed on n measurement parameters corresponding to the n columns, and the method specifically comprises the following steps: increased by 1 new measurement parameter at a timej new measurement parameters, j 1, 2iCorrelation matrix D of fault and measurement parameter in operation modeijThe correlation matrix DijA matrix of m rows and n + j columns; up to the correlation matrix DijIf the row vectors corresponding to all faults in the measurement parameter list are different, stopping adding new measurement parameters to obtain n + j measurement parameters; any one new measurement parameter in j new measurement parameters is deleted; further judging the corresponding incidence matrix D after the new measurement parameters are deletediiWhether the row vectors corresponding to the faults are different or not is judged; if not, deleting the new measurement parameters from the n + j measurement parameters; if yes, retaining the new measurement parameters in the n + j measurement parameters, traversing the j new measurement parameters to obtain an incidence matrix DijThe n + j measurement parameters corresponding to the n + j columns in the (M) are MiTarget measurement parameter subset F in operation modei。
Preferably, for each MiTarget measurement parameter subset F in operation modeiObtaining a target measurement parameter set for fault diagnosis of the nuclear power plant by solving a union set, which specifically comprises the following steps: for each MiTarget measurement parameter subset F in operation modeiSolving a union set to obtain a second target measurement parameter set; analyzing the risk of each measurement parameter in the second target measurement parameter set after failure, and screening out key measurement parameters; carrying out redundancy setting on the key measurement parameters; and determining each measurement parameter of the second target measurement parameter set and the key measurement parameter of the redundancy setting as the target measurement parameter set for the fault diagnosis of the nuclear power plant.
In a second aspect, an embodiment of the present invention further provides a verification method for a measurement parameter set for nuclear power plant fault diagnosis, including: the target measurement parameter set obtained by the method for determining the measurement parameter set for the nuclear power plant fault diagnosis according to the first aspect is set at each MiSimulation results after various faults in the operation mode occur; judging whether all simulation results present different change curves; when the judgment result shows different change curves for the simulation result, determining the available target measurement parameter setAnd diagnosing faults of the nuclear power plant.
Preferably, the target measurement parameter set obtained by the method for determining the measurement parameter set for the nuclear power plant fault diagnosis according to the first aspect is set at each MiSimulation results after various faults in the operation mode occur, including: simulating the measurement parameter set for fault diagnosis of the nuclear power plant according to the first aspect by using a full-range nuclear power plant simulator to obtain a target measurement parameter set in each MiSimulation results after non-nuclear safety faults occur in the operation mode, or after shielding redundant settings in the target measurement parameter set obtained by the method for determining the measurement parameter set for nuclear power plant fault diagnosis in the first aspect, simulating the shielded target measurement parameter set at each M by using a nuclear power plant full-range simulatoriAnd (5) a simulation result after the occurrence of the nuclear safety fault in the operation mode.
In a third aspect, an embodiment of the present invention further provides a method for diagnosing a fault of a nuclear power plant, including: measuring target measurement parameters obtained by the method for determining the measurement parameter set for the fault diagnosis of the nuclear power plant according to the first aspect by using a sensor; monitoring the sensor on line; and carrying out fault diagnosis and residual life prediction of the nuclear power plant unit according to the signal fed back by the sensor.
In a fourth aspect, an embodiment of the present invention further provides a device for determining a measurement parameter set for fault diagnosis of a nuclear power plant, including an obtaining module, a determining module, and a calculating module. An obtaining module for respectively obtaining each MiCorrelation matrix D of fault and measurement parameter in operation modeiWhere i 1, 2iThe method is a matrix with m rows and n columns, wherein m and n are positive integers, m rows correspond to m faults, and n columns correspond to n measurement parameters. A judging module connected with the acquiring module and used for judging the incidence matrix DiWhether the row vectors corresponding to the respective faults in (a) are different. A determining module connected with the judging module and used for determining the incidence matrix D after the judging result is yesiN columns in (1) are MiTarget measurement parameter subset F in operation modei. Calculating modelA block connected with the determination module for each MiTarget measurement parameter subset F in operation modeiAnd solving a union set to obtain a target measurement parameter set for fault diagnosis of the nuclear power plant.
The method and the device for determining the measurement data set for the fault diagnosis of the nuclear power plant, the verification method and the method for the fault diagnosis of the nuclear power plant respectively acquire the M measured data setsiCorrelation matrix D of fault and measurement parameter in operation modeiThe correlation matrix DiThe method comprises the following steps of (1) forming a matrix with m rows and n columns, wherein the m rows correspond to m faults, and the n columns correspond to n measurement parameters; judging the incidence matrix DiWhether the row vectors corresponding to the faults in the group are different or not; after the judgment result is yes, determining a correlation matrix DiN columns in (1) are MiTarget measurement parameter subset F in operation modei(ii) a For each MiTarget measurement parameter subset F in operation modeiAnd solving a union set to obtain a target measurement parameter set for fault diagnosis of the nuclear power plant. Due to the incidence matrix DiIf the row vectors corresponding to the faults in (1) are different, the correlation matrix D is usediM of n measurement parameter monitoringiThe operation data of the equipment in the operation mode can be matched with MiAnd identifying and diagnosing each fault in the operation mode. The equipment operating data monitored by the target measurement parameter set can then be used to identify and diagnose faults in all operating modes. In other words, by monitoring signals of the sensor set to which the target measurement parameter set belongs, different faults in all operation modes can be identified, so that the method is used for fault diagnosis of the nuclear power plant, and requirements on quantification, integrity and traceability and reliability of a data source are met.
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FIG. 1: the method is a flow chart of a method for determining a measurement parameter set for fault diagnosis of a nuclear power plant in embodiment 1 of the invention;
FIG. 2: a configuration diagram of a device for determining a measurement parameter set for nuclear power plant fault diagnosis according to embodiment 4 of the present invention is shown.
Detailed Description
In order to make the technical solutions of the present invention better understood, the present invention is further described in detail below with reference to the accompanying drawings and examples.
Example 1:
as shown in fig. 1, the present embodiment provides a method for determining a measurement parameter set for nuclear power plant fault diagnosis, where the measurement parameter set refers to a set of sensors to which measurement parameters belong, and the method for determining the measurement parameter set for nuclear power plant fault diagnosis includes:
step 101, obtaining each M respectivelyiCorrelation matrix D of fault and measurement parameter in operation modeiWhere i 1, 2iThe method is a matrix with m rows and n columns, wherein m and n are positive integers, m rows correspond to m faults, and n columns correspond to n measurement parameters.
In this embodiment, the operation modes include power operation, hot shutdown, cold shutdown, refueling shutdown, and maintenance shutdown. For example, with M1Indicating a power mode of operation, M2Indicating a hot shutdown mode, and the like, wherein only one operation mode is currently operated in a certain time period.
Specifically, each M is acquired separatelyiCorrelation matrix D of fault and measurement parameter in operation modeiIncludes steps S11-S15:
step S11, obtaining a correlation matrix A of the faults and the subsystem states, wherein the correlation matrix A is a matrix of m rows and p columns, the m rows correspond to the m faults, the p columns correspond to the p subsystem states, and p is a positive integer.
In the embodiment, a subsystem state list, a common fault list and an existing measuring point list of a given nuclear power process system are obtained through analysis and numbering by combing a nuclear power plant system design manual, an alarm rule and a fault operation rule, and a subsystem state vector is further obtained through numbering
Figure BDA0002963749100000071
Fault vector
Figure BDA0002963749100000072
And measuring the parameter vector
Figure BDA0002963749100000073
For example, the results of the analysis obtained for a typical nuclear power plant process system are shown in tables 1-3:
TABLE 1 list of common failures
Fault coding Name of failure
f1 Low liquid level in the control box
f2 High temperature of the lower discharge pipeline
f3 High pressure of the control box
TABLE 2 subsystem status List
State coding Subsystem state names
s1 Pressure mode
s2 Temperature mode
s3 Boric acid injection mode
s4 Water replenishment mode
s5 Shaft seal injection mode
TABLE 3 measurement parameter List
Parameter coding Point names
y1 Liquid level of control tank
y2 Temperature of let-down pipe
y3 Pressure of the control box
y4 Temperature at the lower discharge outlet of the heat exchanger
y5 Pressure in let down line
Identification of subsystem state vectors using a full-range nuclear power plant simulator
Figure BDA0002963749100000081
Respectively in the fault vector
Figure BDA0002963749100000082
And determining the correlation coefficient of each fault and the subsystem state according to the influence degree to obtain a correlation matrix A.
Determining the correlation coefficient of each fault and the subsystem state according to the influence degree to obtain a correlation matrix A, wherein the correlation matrix A comprises the following steps: after the simulated fault occurs, respectively calculating the change interval of key parameters of each subsystem, wherein the key parameters comprise temperature, and/or pressure, and/or liquid level, and/or flow; if the variation interval of the key parameters is smaller than or equal to the first threshold, determining that the correlation coefficient of the fault and the system state is S1; if the change interval of the key parameter is between the first threshold and the second threshold, determining that the correlation coefficient of the fault and the system state is S2; if the variation interval of the key parameter is greater than or equal to the second threshold, determining that the correlation coefficient of the fault and the system state is S3; and taking the determined correlation coefficient of each fault and the subsystem state as a corresponding element of the correlation matrix A to obtain the correlation matrix A.
For example, the value of a critical parameter P of a subsystem is max [ delta temperature, delta pressure, delta liquid level, delta flow ]. When P is less than or equal to x, the correlation coefficient is 0; when P belongs to (x, y), the correlation coefficient is 0.5; when P is more than or equal to y, the correlation coefficient is 1. The resulting correlation matrix a is shown in table 4,
table 4 correlation matrix a
s1 s2 s3 s4 s5
f1 1 0.5 0 0.5 0
f2 0 1 0.5 1 0.5
f3 0.5 0.5 0 0 1
Step S12, obtaining a correlation matrix B of the subsystem state and the measurement parameters, wherein the correlation matrix B is a matrix with p rows and n columns, the p rows correspond to p subsystem states, and the n columns correspond to n measurement parameters.
In this embodiment, if the measurement parameter inevitably exists in the subsystem state, it is determined that the correlation coefficient between the subsystem state and the measurement parameter is 1, and if not, it is determined that the correlation coefficient between the subsystem state and a certain measurement parameter is 0; and taking the determined correlation coefficient of each subsystem state and the measured parameter as the corresponding element of the correlation matrix B to obtain the correlation matrix B of the subsystem state and the measured parameter.
For example, according to the system design of the nuclear power plant, if there is a sensor to which a measurement parameter belongs to perform a measurement function in a certain subsystem state, the correlation coefficient between the subsystem state and the measurement parameter is 1, otherwise, the correlation coefficient between the subsystem state and the measurement parameter is 0. The resulting correlation matrix B is shown in table 5,
TABLE 5 Association matrix B
y1 y2 y3 y4 y5
s1 1 0 1 0 0
s2 1 0 1 1 0
s3 0 1 1 0 1
s4 1 1 0 1 1
s5 0 1 0 1 1
And step S13, obtaining a correlation matrix E of the faults and the measurement parameters under the condition of no influence of the operation mode according to the product of the correlation matrix A and the correlation matrix B, wherein the correlation matrix E is a matrix with m rows and n columns, the m rows correspond to the m faults, and the n columns correspond to the n measurement parameters.
In this embodiment, a correlation matrix E of faults and measurement parameters without considering the influence of the unit operation mode is obtained by multiplying the matrix a and the matrix B, as shown in table 6. The operating mode is as described in step 101.
TABLE 6 Association matrix E
y1 y2 y3 y4 y5
f1 2 0.5 1.5 1 0.5
f2 2 2 1.5 2.5 2
f3 1 1 1 1.5 1
Step S14, obtaining each MiAnd obtaining a correlation matrix C of the faults and the operation modes by using the influence coefficient of the operation modes on the faults, wherein the correlation matrix C is a matrix of m rows and t columns, t is a positive integer, and the t columns correspond to t operation modes.
In this embodiment, each M is set according to the unitiDetermining the defense quit time length after each fault in the operation modeiThe level of impact of the operating mode on the fault; according to each MiDetermining each M by the influence level of the operation mode on the faultiThe influence coefficient of the operation mode on the fault; each M to be determinediAnd taking the influence coefficient of the operation mode on the fault as a corresponding element of the incidence matrix C to obtain the incidence matrix C of the fault and the operation mode.
For example, in the operating specifications of nuclear power plants, it is specified how long the unit is to be disarmed after each fault has occurred in a given operating mode. Based on the length of the defense withdrawing time of the operation technical specification, the influence degree of each fault in a given operation mode is divided into 4 grades, and the influence coefficients corresponding to the 4 grades are m1, m2, m3 and m4 respectively. Taking the values of m1, m2, m3 and m4 as 0, 0.3, 0.7 and 1 respectively to obtain the incidence matrix C shown in Table 7,
TABLE 7 Association matrix C
M1 M2 M3 M4 M5
f1 1 1 0.7 0.3 0
f2 0.7 0.7 0.3 0 0
f3 0.3 0.7 0.7 0.7 1
Step S15, obtaining M according to the incidence matrix E and the incidence matrix C respectivelyiCorrelation matrix D of fault and measurement parameter in operation modeiWherein D isiThe elements in each row are the products of the elements in each row of the incidence matrix E and the influence coefficients of the corresponding faults in the ith column element of the incidence matrix C.
In this embodiment, the column vector of the correlation matrix C is given at MiAnd under the operation mode, influence coefficients of all faults. Thus, the unit is at M1Correlation matrix D of fault and measurement parameter in operation mode1As shown in table 8, the product of each row element of the correlation matrix E and the influence coefficient of the corresponding fault in the 1 st column element of the correlation matrix C is obtained. Accordingly, M can be obtained separately2Correlation matrix D in run mode2，M3Correlation matrix D in run mode3And the like.
TABLE 8 Association matrix D1
y1 y2 y3 y4 y5
f1 2 0.5 1.5 1 0.5
f2 1.4 1.4 1.05 1.75 1.4
f3 0.3 0.3 0.3 0.45 0.3
Step 102, judging the incidence matrix DiWhether the row vectors corresponding to the respective faults in (a) are different.
In this example, D1Fault in (f)1The corresponding row vector is [2, 0.5, 1.5, 1, 0.5 ]]Fault f2The corresponding row vectors are [1.4, 1.4, 1.05, 1.75, 1.4 ]]Fault f3The corresponding row vector is [0.3, 0.3, 0.3, 0.45, 0.3 ]]Judgment of D1Whether the row vectors corresponding to the 3 faults are different or not. If the judgment result shows that the row vectors corresponding to the 3 faults are different, the current measurement parameter set { y is indicated1，y2，y3，y4，y5For failure f1、f2、f3Identifiable, diagnosable. The basis for judging the diagnosability of the fault in this embodiment is as follows: all the faulty eigenvectors are different. If all faults can be diagnosed, the current measurement parameter set meets the requirement of fault monitoring, and a data set (namely the measurement parameter set) can be further optimized; otherwise, the data set needs to be further optimized.
Step 103, after the judgment result is yes, determining the incidence matrix DiN columns in (1) are MiTarget measurement parameter subset F in operation modei。
Specifically, step 103 includes: after the judgment result is yes, determining a correlation matrix DiN measurement parameters corresponding to n columns in the first target measurement parameter subset; performing data set optimization on the first target measurement parameter subset to obtain M from the first target measurement parameter subsetiTarget in run modeSubset of measurement parameters Fi。
The data set optimization of the first target measurement parameter subset specifically includes: any measurement parameter in the first target measurement parameter subset is deleted; further judging the corresponding incidence matrix D after the measurement parameters are deletediWhether the row vectors corresponding to the faults are different or not is judged; deleting the measurement parameters in the first target measurement parameter subset after the judgment result is negative; and if so, keeping the measurement parameters in the first target measurement parameter subset, and traversing all the measurement parameters in the first target measurement parameter subset to complete the data set optimization of the first target measurement parameter subset.
For example, the incidence matrix D is determined in the present embodiment15 columns of the first set of target measurement parameters { y }1，y2，y3，y4，y5At { y }1，y2，y3，y4，y5And traversing the measuring points in the measuring parameter set on the basis, and judging whether the row vectors of the corresponding incidence matrixes after the measuring points are deleted are different. Discovery deletion y4、y5Then, the corresponding incidence matrix D1Fault f of1The corresponding row vector is [2, 0.5, 1.5 ]]Fault f2The corresponding row vector is [1.4, 1.4, 1.05 ]]Fault f3The corresponding row vector is [0.3, 0.3 ]]The 3 column vectors are different, so the measurement parameter set { y1，y2，y3Still effectively identify and diagnose all faults, but further delete y3Then, all faults can not be effectively identified and diagnosed, so M is obtained1Target measurement parameter subset F in operation mode1Is { y1，y2，y3}. And obtaining corresponding target measurement parameter subsets in other operation modes by adopting the same method.
Step 104, for each MiTarget measurement parameter subset F in operation modeiAnd solving a union set to obtain a target measurement parameter set for fault diagnosis of the nuclear power plant.
In this embodiment, for example, M1Target measurement parameter subset F in operation mode1Is { y1，y2，y3}，M2Target measurement parameter subset F in operation mode2Is { y3，y4}，M3、M4、M5The target measurement parameter subsets in the running mode are all { y1，y2，y5Solving a union set of the target measurement parameter subsets in all the operation modes to obtain a target measurement parameter set for fault diagnosis of the nuclear power plant, wherein the target measurement parameter set is { y }1，y2，y3，y4，y5}。
Optionally, in step 102 (i.e., determining the correlation matrix D)iWhether the row vectors corresponding to each fault in (a) are different), and for each M in step 104iTarget measurement parameter subset F in operation modeiBefore the union set is worked out, the method for determining the measurement parameter set for the fault diagnosis of the nuclear power plant further comprises the following steps: if the judgment result is negative (namely, the row vectors corresponding to the faults are the same), the correlation matrix D is subjected toiAnd optimizing the data set by using the n measurement parameters corresponding to the n columns.
Wherein, for the incidence matrix DiThe data set optimization is performed on n measurement parameters corresponding to the n columns, and the method specifically comprises the following steps: j new measurement parameters are added in a manner of adding 1 new measurement parameter each time, j is 1, 2iCorrelation matrix D of fault and measurement parameter in operation modeijThe correlation matrix DijA matrix of m rows and n + j columns; up to the correlation matrix DijIf the row vectors corresponding to all faults in the measurement parameter list are different, stopping adding new measurement parameters to obtain n + j measurement parameters; any one new measurement parameter in j new measurement parameters is deleted; further judging the corresponding incidence matrix D after the new measurement parameters are deletedijWhether the row vectors corresponding to the faults are different or not is judged; deleting new measurement parameters from the n + j measurement parameters after the judgment result is negative; if yes, retaining new measurement parameters in the n + j measurement parameters, and traversing the j new measurement parameters to obtainTo the incidence matrix DijThe n + j measurement parameters corresponding to the n + j columns in the (M) are MiTarget measurement parameter subset F in operation modei。
In this embodiment, a tentative new measurement parameter is explored for a measurement parameter set scheme that temporarily does not satisfy diagnosability, so as to achieve the purpose that the measurement parameter set satisfies diagnosable all faults, but points added in the process are invalid, so that new measurement points need to be deleted one by one, and it is ensured that no diagnosable subset exists in the obtained target measurement parameter set, thereby reducing project implementation cost and achieving the purpose of optimization.
Optionally, step 104 specifically includes: for each MiTarget measurement parameter subset F in operation modeiSolving a union set to obtain a second target measurement parameter set; analyzing the risk of each measurement parameter in the second target measurement parameter set after failure, and screening out key measurement parameters; carrying out redundancy setting on key measurement parameters; and determining each measurement parameter of the second target measurement parameter set and the key measurement parameter of the redundancy setting as the target measurement parameter set for the fault diagnosis of the nuclear power plant.
In this embodiment, the key measurement parameters are redundantly set, and redundant sensors are set for important parameter measurement points according to the result of the hazard analysis, so as to ensure the reliability of data acquisition. A redundant arrangement typically adds one redundant sensor. For a nuclear power plant, the hazard analysis needs to pay attention to three key factors which affect the nuclear safety, namely 'whether emergency shutdown is caused', 'whether core cooling is affected' and 'whether radioactive overrun is caused', and the specific analysis process is shown in table 9:
TABLE 9
Figure BDA0002963749100000131
Figure BDA0002963749100000141
For example, parameters are measured for a second targetNumber set { y1，y2，y3，y4，y5Performing hazard analysis and finding y2The 'core cooling' function is influenced after the failure, so that the key measurement parameter y is responded2Redundancy setting is carried out to obtain a target measurement parameter set for fault diagnosis of the nuclear power plant
Figure BDA0002963749100000142
In the method for determining the measurement parameter set for the nuclear power plant fault diagnosis of the embodiment, the correlation matrix D is usediIf the row vectors (i.e., the measurement parameter set data) corresponding to the faults in (a) are different, it means that the correlation matrix D is usediM monitored by corresponding n sensorsiThe operation data of the equipment in the operation mode can be matched with MiAnd identifying and diagnosing each fault in the operation mode. The individual faults in all operating modes can then be identified and diagnosed using the plant operating data monitored using the determined set of target measurement parameters (set of sensors) in all operating modes. Therefore, a high-quality data basis in the aspects of quantification, completeness, traceability, reliability and the like is provided for the establishment of a predictive maintenance system of the nuclear power plant, and the safety of the nuclear power plant is improved. Furthermore, the redundancy setting is carried out on the key measurement parameters, so that the data source reliability requirement of the nuclear power plant nuclear safety requirement can be met; in addition, under the condition that the current measurement parameter set does not meet the condition that the fault can be diagnosed, new measurement parameters are added tentatively to meet the condition that the fault can be diagnosed, and then the added new measurement parameters are deleted tentatively one by one, so that the target measurement parameter set is optimal, a subset which can be diagnosed by the fault does not exist, the existing parameter basis of the nuclear power plant can be fully utilized, and the influence on the existing design of the power plant is reduced.
Example 2:
the embodiment provides a verification method of a measurement parameter set for fault diagnosis of a nuclear power plant, which comprises the following steps:
step 201, obtaining a target measurement parameter set at each M according to the method for determining a measurement parameter set for nuclear power plant fault diagnosis described in embodiment 1iIn the operating modeThe simulation results after various failures occur.
Step 202, determine whether all simulation results present different variation curves.
And step 203, when the judgment result shows that the simulation result shows different change curves, determining that the target measurement parameter set can be used for fault diagnosis of the nuclear power plant.
Optionally, step 201 specifically includes: the method for determining the measurement parameter set for the nuclear power plant fault diagnosis described in embodiment 1 is adopted to simulate the target measurement parameter set at each MiSimulation results after the non-nuclear safety fault occurs in the operation mode, or after shielding the redundant setting in the target measurement parameter set obtained by the method for determining the measurement parameter set for the fault diagnosis of the nuclear power plant described in embodiment 1, simulating the shielded target measurement parameter set at each M by using the full-range simulator of the nuclear power plantiAnd (5) a simulation result after the occurrence of the nuclear safety fault in the operation mode.
In this embodiment, a scheme of a target measurement parameter set to be verified and confirmed is configured on a full-range simulation machine of a nuclear power plant, different operation modes of the nuclear power plant are selected, all fault modes are inserted, and the change condition of each parameter in the target measurement parameter set is recorded. In the verification process, according to the core safety requirement, the faults related to the core safety and the non-core safety are verified in a distinguishing way: (1) for non-nuclear safety related faults, the target measurement parameter set scheme can ensure that all faults can be effectively diagnosed, namely, the faults pass verification; (2) for nuclear safety related faults, diagnostic tests are carried out after all the redundantly arranged measuring points are shielded in a row, and the fault monitoring function of the scheme can meet a single fault criterion. In the embodiment, after different faults are inserted, the target measurement parameter set
Figure BDA0002963749100000151
Different response curves are shown, therefore, the target measurement parameter set scheme verifies that the result is feasible. The verification method of the measurement parameter set for the nuclear power plant fault diagnosis of the embodiment can meet the special requirements of nuclear safety of the nuclear power plant, namely, the designThe measured target measurement parameter set can be effectively simulated, verified and confirmed, and the risk and the cost of the nuclear power plant in the improvement implementation process are further reduced.
Example 3:
the embodiment provides a method for diagnosing faults of a nuclear power plant, which comprises the following steps:
in step 301, the target measurement parameter obtained by the method for determining the measurement parameter set for the nuclear power plant fault diagnosis according to embodiment 1 is measured by a sensor.
Step 302, the sensor is monitored online.
And 303, performing fault diagnosis and residual life prediction of the nuclear power plant unit according to the signal fed back by the sensor.
Example 4:
as shown in fig. 2, the embodiment provides a device for determining a measurement parameter set for nuclear power plant fault diagnosis, which includes an obtaining module 41, a judging module 42, a determining module 43, and a calculating module 44.
An obtaining module 41, configured to obtain each M respectivelyiCorrelation matrix D of fault and measurement parameter in operation modeiWhere i 1, 2iThe method is a matrix with m rows and n columns, wherein m and n are positive integers, m rows correspond to m faults, and n columns correspond to n measurement parameters.
A judging module 42 connected to the obtaining module 41 for judging the incidence matrix DiWhether the row vectors corresponding to the respective faults in (a) are different.
A determining module 43 connected to the judging module 42 for determining the correlation matrix D after the judgment result is yesiN columns in (1) are MiTarget measurement parameter subset F in operation modei。
A calculation module 44 connected to the determination module 43 for each MiTarget measurement parameter subset F in operation modeiAnd solving a union set to obtain a target measurement parameter set for fault diagnosis of the nuclear power plant.
Optionally, the obtaining module includes a first obtaining unit, a second obtaining unit, and a third obtaining unit.
The first obtaining unit is used for obtaining a correlation matrix A of faults and subsystem states, wherein the correlation matrix A is a matrix with m rows and P columns, and the P columns correspond to the P subsystem states.
And the second acquisition unit is used for acquiring a correlation matrix B of the subsystem state and the measurement parameters, wherein the correlation matrix B is a matrix with p rows and n columns.
And the third acquisition unit is connected with the first acquisition unit and the second acquisition unit and used for obtaining an incidence matrix E of the faults and the measurement parameters under the influence of no operation mode according to the product of the incidence matrix A and the incidence matrix B, wherein the incidence matrix E is a matrix with m rows and n columns. A third obtaining unit for obtaining each MiAnd obtaining a correlation matrix C of the faults and the operation modes by using the influence coefficient of the operation modes on the faults, wherein the correlation matrix C is a matrix of m rows and t columns, p and t are positive integers, and the t columns correspond to the t operation modes. And is used for respectively obtaining each M according to the incidence matrix E and the incidence matrix CiCorrelation matrix D of fault and measurement parameter in operation modeiWherein D isiThe elements in each row are the products of the elements in each row of the incidence matrix E and the influence coefficients of the corresponding faults in the ith column element of the incidence matrix C.
Optionally, the first obtaining unit is further configured to identify a subsystem state vector using a full-range nuclear power plant simulator
Figure BDA0002963749100000172
Respectively in the fault vector
Figure BDA0002963749100000171
And determining the correlation coefficient of each fault and the subsystem state according to the influence degree to obtain a correlation matrix A.
The second obtaining unit is further configured to determine that the correlation coefficient between the subsystem state and the measurement parameter is 1 if the measurement parameter inevitably exists in the subsystem state, and determine that the correlation coefficient between the subsystem state and the measurement parameter is 0 if the measurement parameter does not necessarily exist in the subsystem state; and taking the determined correlation coefficient of each subsystem state and the measured parameter as the corresponding element of the correlation matrix B to obtain the correlation matrix B of the subsystem state and the measured parameter.
A third obtaining unit, further used for obtaining M units according to the unitiDetermining the defense quit time length after each fault in the operation modeiThe level of impact of the operating mode on the fault; according to each MiDetermining each M by the influence level of the operation mode on the faultiThe influence coefficient of the operation mode on the fault; each M to be determinediAnd taking the influence coefficient of the operation mode on the fault as a corresponding element of the incidence matrix C to obtain the incidence matrix C of the fault and the operation mode.
Optionally, the determining module comprises a determining unit and a first optimizing unit.
A determining unit for determining the incidence matrix D after the judgment result is yesiThe n measurement parameters corresponding to the n columns in the first target measurement parameter subset are obtained.
A first optimization unit connected to the determination unit for performing data set optimization on the first target measurement parameter subset to obtain M from the first target measurement parameter subsetiTarget measurement parameter subset F in operation modei。
Optionally, the first optimization unit is configured to delete any one of the measurement parameters in the first target measurement parameter subset; further judging the corresponding incidence matrix D after the measurement parameters are deletediWhether the row vectors corresponding to the faults are different or not is judged; deleting the measurement parameters in the first target measurement parameter subset after the judgment result is negative; and if so, keeping the measurement parameters in the first target measurement parameter subset, and traversing all the measurement parameters in the first target measurement parameter subset to complete the data set optimization of the first target measurement parameter subset.
Optionally, the device for determining the measurement parameter set for the nuclear power plant fault diagnosis further comprises an optimization module. The optimization module is connected with the judgment module and used for correlating the incidence matrix D after the judgment result is negativeiAnd optimizing the data set by using the n measurement parameters corresponding to the n columns.
The optimization module comprises a second optimization unit for optimizing the second optimization unitJ new measurement parameters are added in a manner of adding 1 new measurement parameter each time, j is 1, 2iCorrelation matrix D of fault and measurement parameter in operation modeijThe correlation matrix DijA matrix of m rows and n + j columns; up to the correlation matrix DijIf the row vectors corresponding to all faults in the measurement parameter list are different, stopping adding new measurement parameters to obtain n + j measurement parameters; any one new measurement parameter in j new measurement parameters is deleted; further judging the corresponding incidence matrix D after the new measurement parameters are deletedijWhether the row vectors corresponding to the faults are different or not is judged; if not, deleting the new measurement parameters from the n + j measurement parameters; if yes, retaining the new measurement parameters in the n + j measurement parameters, traversing the j new measurement parameters to obtain an incidence matrix DijThe n + j measurement parameters corresponding to the n + j columns in the (M) are MiTarget measurement parameter subset F in operation modei。
Optionally, the calculation module includes a redundancy setting unit, and the redundancy setting unit is connected to the determination module and the optimization module, and is configured to perform redundancy setting on the key measurement parameters in the target measurement parameter set.
It will be understood that the above embodiments are merely exemplary embodiments taken to illustrate the principles of the present invention, which is not limited thereto. It will be apparent to those skilled in the art that various modifications and improvements can be made without departing from the spirit and substance of the invention, and these modifications and improvements are also considered to be within the scope of the invention.

Claims (11)

1. A method for determining a measurement parameter set for nuclear power plant fault diagnosis is characterized by comprising the following steps:
respectively acquire each MiCorrelation matrix D of fault and measurement parameter in operation modeiWhere i 1, 2iThe method comprises the following steps of (1) forming a matrix with m rows and n columns, wherein m and n are positive integers, the m rows correspond to m faults, and the n columns correspond to n measurement parameters;
judging the incidence matrix DiWhether the row vectors corresponding to the faults in the group are different or not;
after the judgment result is yes, determining a correlation matrix DiN columns in (1) are MiTarget measurement parameter subset F in operation modei；
For each MiTarget measurement parameter subset F in operation modeiAnd solving a union set to obtain a target measurement parameter set for fault diagnosis of the nuclear power plant.
2. The method of determining a measurement data set for nuclear power plant fault diagnosis according to claim 1, wherein the obtaining each M is performed separatelyiCorrelation matrix D of fault and measurement parameter in operation modeiThe method specifically comprises the following steps:
acquiring an incidence matrix A of faults and subsystem states, wherein the incidence matrix A is a matrix with m rows and p columns, and the p columns correspond to the p subsystem states;
acquiring an incidence matrix B of the subsystem state and the measurement parameters, wherein the incidence matrix B is a matrix with p rows and n columns;
obtaining an incidence matrix E of the faults and the measurement parameters under the condition of no influence of the operation mode according to the product of the incidence matrix A and the incidence matrix B, wherein the incidence matrix E is a matrix with m rows and n columns;
obtain each MiObtaining a correlation matrix C of the faults and the operation modes by using the influence coefficient of the operation modes on the faults, wherein the correlation matrix C is a matrix of m rows and t columns, p and t are positive integers, and the t columns correspond to t operation modes;
respectively obtaining M according to the incidence matrix E and the incidence matrix CiCorrelation matrix D of fault and measurement parameter in operation modeiWherein D isiThe elements in each row are the products of the elements in each row of the incidence matrix E and the influence coefficients of the corresponding faults in the ith column element of the incidence matrix C.
3. The method of determining the measurement data set for nuclear power plant fault diagnosis according to claim 2, wherein the obtaining each M is performed separatelyiCorrelation matrix D of fault and measurement parameter in operation modeiThe method also comprises the following steps:
respectively obtaining subsystem state vectors
Figure FDA0002963749090000021
Fault vector
Figure FDA0002963749090000022
And measuring the parameter vector
Figure FDA0002963749090000023
Wherein,
Figure FDA0002963749090000024
is a vector of the p-dimension,
Figure FDA0002963749090000025
is a vector with the dimension of m,
Figure FDA0002963749090000026
is an n-dimensional vector;
the obtaining of the incidence matrix a of the fault and the subsystem state specifically includes:
identification of subsystem state vectors using a full-range nuclear power plant simulator
Figure FDA0002963749090000027
Respectively in the fault vector
Figure FDA0002963749090000028
Determining the correlation coefficient of each fault and the subsystem state according to the influence degree to obtain a correlation matrix A,
the acquiring of the incidence matrix B of the subsystem state and the measurement parameter specifically includes:
if the measurement parameter is inevitably existed in the subsystem state, determining that the correlation coefficient of the subsystem state and the measurement parameter is 1, and if not, determining that the correlation coefficient of the subsystem state and the measurement parameter is 0;
taking the determined correlation coefficient of each subsystem state and the measurement parameter as the corresponding element of the correlation matrix B to obtain the correlation matrix B of the subsystem state and the measurement parameter;
said obtaining each MiObtaining a correlation matrix C of the faults and the operation mode by using the influence coefficient of the operation mode on the faults, and specifically comprising the following steps:
according to the unit at each MiDetermining the defense quit time length after each fault in the operation modeiThe level of impact of the operating mode on the fault;
according to each MiDetermining each M by the influence level of the operation mode on the faultiThe influence coefficient of the operation mode on the fault;
each M to be determinediAnd taking the influence coefficient of the operation mode on the fault as a corresponding element of the incidence matrix C to obtain the incidence matrix C of the fault and the operation mode.
4. The method for determining the measurement data set for the fault diagnosis of the nuclear power plant according to claim 3, wherein the determining the correlation coefficient between each fault and the subsystem state according to the influence degree to obtain the correlation matrix A comprises:
after the simulated fault occurs, respectively calculating the change interval of key parameters of each subsystem, wherein the key parameters comprise temperature, and/or pressure, and/or liquid level, and/or flow;
if the variation interval of the key parameters is smaller than or equal to the first threshold, determining that the correlation coefficient of the fault and the subsystem state is S1;
if the change interval of the key parameter is between the first threshold and the second threshold, determining that the correlation coefficient of the fault and the subsystem state is S2;
if the variation interval of the key parameter is greater than or equal to the second threshold value, determining that the correlation coefficient of the fault and the subsystem state is S3;
and taking the determined correlation coefficient of each fault and the subsystem state as a corresponding element of the correlation matrix A to obtain the correlation matrix A.
5. The method for determining the measurement data set for nuclear power plant fault diagnosis according to claim 4, wherein the incidence matrix D is determined after the determination result is yesiN columns in (1) are MiTarget measurement parameter subset F in operation modeiThe method comprises the following steps:
after the judgment result is yes, determining a correlation matrix DiN measurement parameters corresponding to n columns in the first target measurement parameter subset;
performing data set optimization on the first target measurement parameter subset to obtain M from the first target measurement parameter subsetiTarget measurement parameter subset F in operation modei，
The optimizing the data set of the first target measurement parameter subset specifically includes:
any measurement parameter in the first target measurement parameter subset is deleted;
further judging the corresponding incidence matrix D after the measurement parameters are deletediWhether the row vectors corresponding to the faults are different or not is judged;
deleting the measurement parameters in the first target measurement parameter subset after the judgment result is negative; after the judgment result is yes, keeping the measurement parameters in the first target measurement parameter subset,
all measurement parameters in the first subset of target measurement parameters are traversed to complete the dataset optimization for the first subset of target measurement parameters.
6. The method for determining the measurement data set for nuclear power plant fault diagnosis according to claim 5, wherein the incidence matrix D is determined at the time of the judgmentiAfter the row vectors corresponding to all faults in the target measurement parameter subset F are different, and in all the operation modesiBefore the union set, the method further comprises the following steps: after the judgment result is negative, the incidence matrix D is matchediN columns of the data set optimization is performed on the n measured parameters corresponding to the n columns of the data set,
the pair correlation matrix DiThe data set optimization is performed on n measurement parameters corresponding to the n columns, and the method specifically comprises the following steps:
j new measurement parameters are added in a manner of adding 1 new measurement parameter each time, j is 1, 2iCorrelation matrix D of fault and measurement parameter in operation modeijThe correlation matrix DijA matrix of m rows and n + j columns;
up to the correlation matrix DijIf the row vectors corresponding to all faults in the measurement parameter list are different, stopping adding new measurement parameters to obtain n + j measurement parameters;
any one new measurement parameter in j new measurement parameters is deleted;
further judging the corresponding incidence matrix D after the new measurement parameters are deletedijWhether the row vectors corresponding to the faults are different or not is judged;
if not, deleting the new measurement parameters from the n + j measurement parameters; after the judgment result is yes, the new measurement parameter is reserved in the n + j measurement parameters,
traversing j new measurement parameters to obtain an incidence matrix DijThe n + j measurement parameters corresponding to the n + j columns in the (M) are MiTarget measurement parameter subset F in operation modei。
7. The method of determining a measurement data set for nuclear power plant fault diagnosis according to claim 6, wherein the determination is for each MiTarget measurement parameter subset F in operation modeiObtaining a target measurement parameter set for fault diagnosis of the nuclear power plant by solving a union set, which specifically comprises the following steps:
for each MiTarget measurement parameter subset F in operation modeiSolving a union set to obtain a second target measurement parameter set;
analyzing the risk of each measurement parameter in the second target measurement parameter set after failure, and screening out key measurement parameters;
carrying out redundancy setting on the key measurement parameters;
and determining each measurement parameter of the second target measurement parameter set and the key measurement parameter of the redundancy setting as the target measurement parameter set for the fault diagnosis of the nuclear power plant.
8. A verification method for a measurement parameter set for nuclear power plant fault diagnosis is characterized by comprising the following steps:
the method for determining the measurement parameter set for nuclear power plant fault diagnosis according to any one of claims 1 to 7, wherein the target measurement parameter set is obtained at each MiSimulation results after various faults in the operation mode occur;
judging whether all simulation results present different change curves;
and when the judgment result shows different change curves for the simulation result, determining that the target measurement parameter set can be used for fault diagnosis of the nuclear power plant.
9. The verification method for the measurement parameter set for nuclear power plant fault diagnosis according to claim 8, wherein the target measurement parameter set obtained by the determination method for the measurement parameter set for nuclear power plant fault diagnosis according to any one of claims 1 to 7 is set at each MiSimulation results after various faults in the operation mode occur, including:
simulation of the target measurement parameter set obtained by the method for determining the measurement parameter set for fault diagnosis of the nuclear power plant according to any one of claims 1 to 7 by using a full-scope simulation of the nuclear power plant on each MiSimulation results after the occurrence of the non-nuclear safety failure in the operation mode, or,
after shielding the redundant setting in the target measurement parameter set obtained by the method for determining the measurement parameter set for nuclear power plant fault diagnosis according to any one of claims 1 to 7, simulating the shielded target measurement parameter set at each M by using a full-range nuclear power plant simulatoriAnd (5) a simulation result after the occurrence of the nuclear safety fault in the operation mode.
10. A method of nuclear power plant fault diagnosis, comprising:
measuring a target measurement parameter obtained by the method for determining the measurement parameter set for the fault diagnosis of the nuclear power plant according to any one of claims 1 to 7 by a sensor;
monitoring the sensor on line;
and carrying out fault diagnosis and residual life prediction of the nuclear power plant unit according to the signal fed back by the sensor.
11. A device for determining a measurement parameter set for nuclear power plant fault diagnosis is characterized by comprising an acquisition module, a judgment module, a determination module and a calculation module,
an obtaining module for respectively obtaining each MiCorrelation matrix D of fault and measurement parameter in operation modeiWhere i 1, 2iIs a matrix with m rows and n columns, wherein m and n are positive integers, m rows correspond to m faults, n columns correspond to n measurement parameters,
a judging module connected with the acquiring module and used for judging the incidence matrix DiWhether the row vectors corresponding to each fault in (a) are different,
a determining module connected with the judging module and used for determining the incidence matrix D after the judging result is yesiN columns in (1) are MiTarget measurement parameter subset F in operation modei，
A calculation module connected with the determination module and used for calculating MiTarget measurement parameter subset F in operation modeiAnd solving a union set to obtain a target measurement parameter set for fault diagnosis of the nuclear power plant.
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