CN112507286A - State-based equipment fault probability analysis method and device and electronic equipment - Google Patents
State-based equipment fault probability analysis method and device and electronic equipment Download PDFInfo
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Abstract
The invention relates to a method and a device for analyzing equipment fault probability based on state and electronic equipment, wherein the method comprises the following steps: evaluating the equipment state to obtain an equipment state evaluation result; constructing an equipment state and fault probability model based on the equipment state evaluation result and the equipment fault rate; solving the equipment state and fault probability model; and analyzing the fault probability of the equipment according to the state of the equipment and the solving result of the fault probability model. According to the method, the matching of the running state of the nuclear power plant equipment and the fault probability relation is realized through model establishment and solution, the precision of fault rate analysis and calculation is improved, the reliability is high, and the defect of application lag is avoided.
Description
Technical Field
The invention relates to the technical field of equipment fault analysis of nuclear power plants, in particular to a state-based equipment fault probability analysis method and device and electronic equipment.
Background
The failure probability of the electrical equipment is generally obtained by recording the actual operation condition of the equipment for a long time and performing statistical analysis on the obtained data. Under the condition of small data quantity or completely lacking of statistical data, the fault rate obtained by the method is extremely low in reliability, and the fault rate of the equipment obtained by the method is obtained based on posterior statistical analysis, so that the fault rate cannot be obtained by the method of data statistical analysis for the equipment to be overhauled and the equipment which is overhauled according to the state detection information in the optimization process of the equipment state overhaul decision.
Disclosure of Invention
The present invention provides a method and an apparatus for analyzing a failure probability of a device based on a state, and an electronic device, aiming at the above-mentioned defects in the prior art.
The technical scheme adopted by the invention for solving the technical problems is as follows: a method for analyzing the fault probability of equipment based on the state is constructed, and comprises the following steps:
evaluating the equipment state to obtain an equipment state evaluation result;
constructing an equipment state and fault probability model based on the equipment state evaluation result and the equipment fault rate;
solving the equipment state and fault probability model;
and analyzing the equipment fault probability according to the equipment state and the solving result of the fault probability model.
Preferably, the evaluating the device status, and the obtaining the device status evaluation result includes:
acquiring state quantities of all parts of equipment;
and evaluating the equipment state by adopting a preset state evaluation method according to the state quantity of each part of the equipment to obtain an equipment state evaluation result.
Preferably, the constructing a device state and fault probability model based on the device state evaluation result and the device fault rate includes:
establishing a first model based on the equipment state evaluation result and the equipment fault rate;
correcting the first model by adopting a preset correction method to obtain a corrected model of the first model; and the modified model of the first model is the equipment state and fault probability model.
Preferably, the modifying the first model by using a preset modifying method to obtain a modified model of the first model includes:
and correcting the first model by adopting a regression analysis method to obtain a corrected model of the first model.
Preferably, the solving the equipment state and fault probability model includes:
establishing a nonlinear regression model based on the equipment state and fault probability model;
solving the parameters of the nonlinear regression model to obtain the residual square sum of the nonlinear regression model;
taking the minimum value of the sum of squared residuals to obtain the parameter value of the nonlinear regression model;
and determining a solving result of the equipment state and fault model based on the parameter values of the nonlinear regression model.
Preferably, solving the parameters of the non-linear regression model comprises:
and solving the parameters of the nonlinear regression model by adopting a least square method.
Preferably, the method further comprises:
and testing the equipment state and the fault probability model by adopting a preset testing method.
Preferably, the checking the equipment state and fault probability model by using a preset checking method comprises: and comparing the equipment state with the fault probability model by adopting nonlinear regression correlation to carry out inspection.
Preferably, the comparing the equipment state with the fault probability model by using the nonlinear regression correlation comprises:
determining a sum of squares of residuals of the device failure rate based on the device failure rate;
determining a regression sum of squares of the equipment failure rate based on the equipment failure rate;
obtaining a value of a nonlinear regression correlation ratio according to the residual sum of squares and the regression sum of squares;
and according to the value of the nonlinear regression correlation ratio, checking the equipment state and fault probability model.
Preferably, the determining a sum of squared residuals of the device failure rate based on the device failure rate comprises:
acquiring an estimated value of the equipment failure rate based on the equipment failure rate;
and performing residual square sum operation according to the equipment failure rate and the estimated value of the equipment failure rate to obtain the residual square sum of the equipment failure rate.
Preferably, said determining a regression sum of squares of equipment failure rate based on said equipment failure rate comprises:
acquiring an average value of the equipment failure rates based on the equipment failure rates;
and performing regression sum of squares operation according to the equipment failure rate and the average value of the equipment failure rate to obtain the regression sum of squares of the equipment failure rate.
The invention also provides a device for analyzing the failure probability of equipment based on the state, which comprises:
the state evaluation unit is used for evaluating the state of the equipment and acquiring an equipment state evaluation result;
the model building unit is used for building an equipment state and fault probability model based on the equipment state evaluation result and the equipment fault rate;
the solving unit is used for solving the equipment state and fault probability model;
and the analysis unit is used for analyzing the equipment fault probability according to the equipment state and the solving result of the fault probability model.
The present invention also provides an electronic device comprising: a memory and a processor; the memory is for storing program instructions and the processor is for performing the steps of the method as described above in accordance with the program instructions stored by the memory.
The invention also provides a storage medium having stored thereon a computer program which, when executed by a processor, carries out the steps of the method as described above.
The implementation of the state-based equipment fault probability analysis method and device and the electronic equipment has the following beneficial effects: the method comprises the following steps: evaluating the equipment state to obtain an equipment state evaluation result; constructing an equipment state and fault probability model based on the equipment state evaluation result and the equipment fault rate; solving the equipment state and fault probability model; and analyzing the fault probability of the equipment according to the state of the equipment and the solving result of the fault probability model. According to the method, the matching of the running state of the nuclear power plant equipment and the fault probability relation is realized through model establishment and solution, the precision of fault rate analysis and calculation is improved, the reliability is high, and the defect of application lag is avoided.
Drawings
The invention will be further described with reference to the accompanying drawings and examples, in which:
FIG. 1 is a schematic flow chart diagram illustrating a method for analyzing a failure probability of a state-based device according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a device failure probability analysis apparatus based on states according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
For a more clear understanding of the technical features, objects and effects of the present invention, embodiments of the present invention will now be described in detail with reference to the accompanying drawings.
The invention provides a state-based equipment fault probability analysis method, which aims to solve the problems of low reliability and application lag of the traditional equipment fault analysis method and the problem that the fault rate cannot be obtained completely by a data statistical analysis method. The invention can provide rational theoretical basis for equipment state evaluation, trend analysis, risk evaluation and maintenance strategy decision.
Specifically, referring to fig. 1, fig. 1 is a schematic flow chart of an alternative embodiment of each embodiment of the method for analyzing a fault probability of a state-based device according to the present invention. Alternatively, the device of the present invention may be a power transformer, for example, a large power transformer. Of course, it is understood that the devices herein may also include other electrical devices. Further, the present invention may be applied to nuclear power plant equipment.
As shown in fig. 1, the method for analyzing the failure probability of the state-based device includes:
and S101, evaluating the equipment state to obtain an equipment state evaluation result.
In some embodiments, evaluating the device status, and obtaining the device status evaluation result includes:
step S1011 acquires the state quantities of the respective components of the apparatus.
Step S1012, evaluating the device status by using a preset status evaluation method according to the status quantities of the components of the device, so as to obtain a device status evaluation result.
In some embodiments, assuming that the device is a power transformer, the power transformer may be divided into: the device comprises a body, a sleeve, an on-load tap-changer, a cooling system, a non-electric quantity protection system and an on-line monitoring device. After the components of the power transformer are divided, state quantities of the components are respectively obtained, then the states of the components are evaluated according to the state quantities of the components, and a state evaluation result of the power transformer is obtained according to the state evaluation result of the components.
Wherein the state quantities of the respective components each include:
(1) original data: the method comprises the steps of ordering technical specification, nameplate value, test report, equipment monitoring and manufacturing report, delivery test report, transportation and installation record, handover test report, installation and use instruction and the like.
(2) And (3) running data: the method comprises the following steps of short circuit impact condition, overload condition, equipment inspection record, year-round defect and abnormality record, infrared temperature measurement record and the like.
(3) And (3) maintenance test data: the method comprises a maintenance report, a pre-test report, an oil chromatography inspection analysis report, online monitoring information, a special test report, relevant counter measure execution conditions, equipment technical improvement, main component replacement conditions and the like.
(4) Other data: including the conditions of operation, repair, testing, defects and faults of the same type (same type) of equipment; the change of the equipment operation environment and the change of the system operation mode; other factors influencing the safe and stable operation of the transformer, and the like.
Further, in the embodiment of the present invention, for the specific state evaluation method of the power transformer, the state evaluation guide rule of the DL/T1685 oil-immersed transformer (reactor) in the power industry standard may be adopted to perform the state evaluation of the transformer.
And S102, constructing an equipment state and fault probability model based on the equipment state evaluation result and the equipment fault rate.
The method for constructing the equipment state and fault probability model based on the equipment state evaluation result and the equipment fault rate comprises the following steps:
and S1021, establishing a first model based on the equipment state evaluation result and the equipment failure rate.
Step S1022, correcting the first model by adopting a preset correction method to obtain a corrected model of the first model; the modified model of the first model is a device state and fault probability model.
In the embodiment of the present invention, the preset correction method is a regression analysis method, that is, the regression analysis method may be used to correct the first model, so as to obtain a corrected model of the first model. The modified model of the first model is the equipment state and fault probability model required to be constructed in the embodiment of the invention.
Specifically, if the mathematical expression is used for representation, the first model can be represented as:
P＝K·e-CHI (1)；
(1) in the formula, P is the equipment fault probability and takes the value of 0-1; k is a proportionality coefficient; c is a curvature coefficient; and the HI is an equipment state evaluation result and takes a value of 0-100.
As can be seen from equation (1), the failure probability of a device is an exponential function varying with the state of health of the device, and when the result of the state of health of the device is 0, i.e., the state of the device is the worst, the failure probability of the device approaches to 1 indefinitely; when the device status result is 100, i.e., the device status is optimal, the device failure probability approaches 0 indefinitely. According to the formula (1), the exponential function is obtained, and can be converted into a linear model by taking the logarithm of a natural number on both sides, and the linear model belongs to an intrinsic linear model in a regression analysis model. However, due to the characteristics of the geographical positions of the nuclear power plants and the operating environments of the large power transformers of the nuclear power plants with different geographical positions, and due to the differences of factors such as manufacturing processes of manufacturers, technical levels of maintainers, equipment maintenance standards and the like, the characteristics of fuzzy matching and nonlinearity exist between the equipment state and the fault probability, and therefore, a mathematical model between the health state and the fault probability of the large power transformers of the nuclear power plants is essentially a nonlinear model. Based on the principle, the method adopts a regression analysis method, introduces random error terms to correct the first model, and enables the equipment state and fault probability model to be a nonlinear model. Wherein, its mathematical expression can be expressed as:
(2) in the formula, beta0、β1Is a proportionality coefficient; ε is the random error.
And step S103, solving the equipment state and fault probability model.
Solving the equipment state and fault probability model comprises the following steps:
and step S1031, establishing a nonlinear regression model based on the equipment state and fault probability model.
Step S1032, solving is carried out on the parameters of the nonlinear regression model, and the sum of squares of the residuals of the nonlinear regression model is obtained. Wherein solving for the parameters of the non-linear regression model comprises: and solving the parameters of the nonlinear regression model by adopting a least square method.
And step S1033, taking the minimum value of the sum of squared residuals to obtain the parameter value of the nonlinear regression model.
And S1034, determining a solving result of the equipment state and the fault model based on the parameter value of the nonlinear regression model.
Specifically, the nonlinear regression model can be generally expressed as:
Y＝f(X，θ)+ε (3)；
(3) wherein Y is a dependent variable; f () is a functional form; x is a self-variation vector; theta is an unknown parameter vector; ε is a random error term. Wherein Y represents the equipment failure probability, namely, the probability corresponds to P in the formula (2); x represents the evaluation result of the state of the device (i.e., the state of health of the device), i.e., corresponds to HI in the formula (2); theta is an unknown parameter vector corresponding to the unknown quantity beta of the formula (2)0And beta1。
Therefore, based on equation (3), the parameters of the nonlinear regression model are solved by applying the least square method to find the minimum sum of squared residuals, that is:
(4) wherein, Q () is a residual sum-of-squares function; y isiIs the ith dependent variable; x is the number ofiIs the ith argument. When Q (theta) → min
I.e. a least squares estimate of theta. Here, yiI.e., equivalent to the ith equipment failure rate (i.e., pi); x is the number ofiI.e., the status evaluation result (i.e., HIi) corresponding to the ith device. Therefore, when Q (θ) takes the minimum value, the value of θ, i.e., β, can be obtained0And beta1The value of (c). Since HI and P are known, β is obtained0And beta1The random error ε can be calculated according to equation (2). And then solving results of the equipment state and fault probability model can be obtained. Namely, β in the formula (2) is calculated0、β1And the value of epsilon.
And step S104, analyzing the equipment fault probability according to the equipment state and the solving result of the fault probability model.
Specifically, in step S103, β is calculated0、β1And e, analyzing the equipment failure probability according to the equipment state and the failure probability model (namely, the formula (2)), and based on the formula (2), the equipment failure probability can be calculated in a ready manner based on the equipment state.
Further, in some other embodiments, the method for analyzing the probability of failure of the state-based device further includes:
and (4) inspecting the equipment state and the fault probability model by adopting a preset inspection method. Wherein, adopting and predetermineeing the inspection method and carrying out the inspection to equipment state and fault probability model and including: and comparing the equipment state with the fault probability model by adopting nonlinear regression correlation to carry out inspection.
Specifically, the step of comparing the equipment state with the fault probability model by adopting nonlinear regression correlation comprises the following steps: determining a residual sum of squares of the device failure rates based on the device failure rates; determining a regression sum of squares of the equipment failure rate based on the equipment failure rate; obtaining a value of a nonlinear regression correlation ratio according to the residual sum of squares and the regression sum of squares; and (4) according to the value of the nonlinear regression correlation ratio, checking the equipment state and fault probability model. Wherein determining a sum of squared residuals of the device failure rate based on the device failure rate comprises: acquiring an estimated value of the equipment failure rate based on the equipment failure rate; and performing residual square sum operation according to the equipment failure rate and the estimated value of the equipment failure rate to obtain the residual square sum of the equipment failure rate. Determining a regression sum of squares of the equipment failure rate based on the equipment failure rate comprises: acquiring an average value of the equipment failure rate based on the equipment failure rate; and performing regression sum of squares operation according to the average value of the equipment failure rate and the equipment failure rate to obtain the regression sum of squares of the equipment failure rate.
Wherein, the data expression can be expressed as:
(5) wherein SSE is the sum of the squares of the residuals;
is a parameter estimated value (namely an equipment fault probability estimated value); (6) in the formula
Is a parameter average value (namely an equipment failure probability average value); SSR is regression sum of squares. The nonlinear regression correlation ratio calculation based on the formulas (5) and (6) can be obtained:
as can be seen from equation (7), the closer the correlation ratio is to 1, the better the regression fit.
The following description takes the fault data of a certain transformer as an example:
as shown in table 1, there are 12 groups of devices, the number of devices and the number of failures are shown in table 1, wherein the probability of device failure is equal to the quotient of the number of failures and the number of devices.
Table 1:
according to the data in the table 1, the first model variance analysis result is 0.868 through analysis and solution, the variance analysis result obtained through the adoption of the equipment state and fault probability model for solution is 0.930, and the analysis result shows that the correlation ratio of the equipment state and the fault probability model is closer to 1, the precision is better, the reliability is higher, and the problem of application lag does not exist.
The invention aims at the problems of large deviation, low reliability and poor applicability of the fault probability calculation method of the large-scale power transformer of the nuclear power plant, fully analyzes the defects of the traditional method, corrects a first model formula based on the nonlinear regression principle by taking the operation characteristics of the large-scale power transformer of the nuclear power plant as a base point, realizes the fitting of the operation state and the fault probability relation of the large-scale power transformer of the nuclear power plant by establishing and solving the equipment state and fault probability model of the invention, checks the calculation model by applying the nonlinear regression correlation, improves the calculation precision of the fault probability of the large-scale power transformer of the nuclear power plant based on the state by solving, provides a theoretical basis for the state maintenance of the large-scale power transformer of the nuclear power plant, and can accurately analyze the fault probability of the equipment based on the equipment state and the fault probability model provided by the invention, the applicability is improved.
Referring to fig. 2, fig. 2 is a schematic structural diagram of an alternative embodiment of each embodiment of the state-based device failure probability analysis apparatus according to the present invention. The analysis device can be used for realizing the equipment fault probability analysis method based on the state disclosed by the embodiment of the invention.
Specifically, as shown in fig. 2, the apparatus for analyzing the probability of failure of a device in a state includes:
and the state evaluation unit is used for evaluating the state of the equipment and acquiring the evaluation result of the state of the equipment.
And the model building unit is used for building an equipment state and fault probability model based on the equipment state evaluation result and the equipment fault rate.
And the solving unit is used for solving the equipment state and fault probability model.
And the analysis unit is used for analyzing the equipment fault probability according to the equipment state and the solving result of the fault probability model.
Further, as shown in fig. 3, the present invention also provides an electronic device, including: a memory and a processor; the memory is used for storing program instructions, and the processor is used for executing the steps of the method for analyzing the probability of equipment failure based on the state provided by the embodiment of the invention according to the program instructions stored in the memory.
Further, the present invention also provides a storage medium on which a computer program is stored, wherein the stored computer program, when executed by a processor, implements the steps of the state-based device failure probability analysis method provided by the embodiment of the present invention.
The above embodiments are merely illustrative of the technical ideas and features of the present invention, and are intended to enable those skilled in the art to understand the contents of the present invention and implement the present invention, and not to limit the scope of the present invention. All equivalent changes and modifications made within the scope of the claims of the present invention should be covered by the claims of the present invention.
Claims (14)
1. A method for analyzing the failure probability of equipment based on the state is characterized by comprising the following steps:
evaluating the equipment state to obtain an equipment state evaluation result;
constructing an equipment state and fault probability model based on the equipment state evaluation result and the equipment fault rate;
solving the equipment state and fault probability model;
and analyzing the equipment fault probability according to the equipment state and the solving result of the fault probability model.
2. The method according to claim 1, wherein the evaluating the device status and obtaining the device status evaluation result comprises:
acquiring state quantities of all parts of equipment;
and evaluating the equipment state by adopting a preset state evaluation method according to the state quantity of each part of the equipment to obtain an equipment state evaluation result.
3. The method of claim 1, wherein constructing a device state and fault probability model based on the device state assessment results and device fault rates comprises:
establishing a first model based on the equipment state evaluation result and the equipment fault rate;
correcting the first model by adopting a preset correction method to obtain a corrected model of the first model; and the modified model of the first model is the equipment state and fault probability model.
4. The method according to claim 3, wherein the modifying the first model by a preset modification method to obtain a modified model of the first model comprises:
and correcting the first model by adopting a regression analysis method to obtain a corrected model of the first model.
5. The method of claim 1, wherein solving the device state and fault probability model comprises:
establishing a nonlinear regression model based on the equipment state and fault probability model;
solving the parameters of the nonlinear regression model to obtain the residual square sum of the nonlinear regression model;
taking the minimum value of the sum of squared residuals to obtain the parameter value of the nonlinear regression model;
and determining a solving result of the equipment state and fault model based on the parameter values of the nonlinear regression model.
6. The method of state-based equipment fault probability analysis of claim 5, wherein said solving the parameters of the non-linear regression model comprises:
and solving the parameters of the nonlinear regression model by adopting a least square method.
7. The method of state-based device failure probability analysis of claim 1, further comprising:
and testing the equipment state and the fault probability model by adopting a preset testing method.
8. The method of claim 7, wherein the verifying the device state and fault probability model using a predetermined verification method comprises: and comparing the equipment state with the fault probability model by adopting nonlinear regression correlation to carry out inspection.
9. The method of claim 8, wherein the verifying the equipment state versus fault probability model using nonlinear regression correlation comprises:
determining a sum of squares of residuals of the device failure rate based on the device failure rate;
determining a regression sum of squares of the equipment failure rate based on the equipment failure rate;
obtaining a value of a nonlinear regression correlation ratio according to the residual sum of squares and the regression sum of squares;
and according to the value of the nonlinear regression correlation ratio, checking the equipment state and fault probability model.
10. The method of state-based device failure probability analysis of claim 9, wherein the determining a sum of squared residuals of a device failure rate based on the device failure rate comprises:
acquiring an estimated value of the equipment failure rate based on the equipment failure rate;
and performing residual square sum operation according to the equipment failure rate and the estimated value of the equipment failure rate to obtain the residual square sum of the equipment failure rate.
11. The method of state-based equipment failure probability analysis of claim 9, wherein the determining a regression sum of squares of equipment failure rates based on the equipment failure rates comprises:
acquiring an average value of the equipment failure rates based on the equipment failure rates;
and performing regression sum of squares operation according to the equipment failure rate and the average value of the equipment failure rate to obtain the regression sum of squares of the equipment failure rate.
12. A state-based device failure probability analysis apparatus, comprising:
the state evaluation unit is used for evaluating the state of the equipment and acquiring an equipment state evaluation result;
the model building unit is used for building an equipment state and fault probability model based on the equipment state evaluation result and the equipment fault rate;
the solving unit is used for solving the equipment state and fault probability model;
and the analysis unit is used for analyzing the equipment fault probability according to the equipment state and the solving result of the fault probability model.
13. An electronic device, comprising: a memory and a processor; the memory is adapted to store program instructions and the processor is adapted to perform the steps of the method of any of claims 1-11 in accordance with the program instructions stored in the memory.
14. A storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, performs the steps of the method according to any one of claims 1-11.
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| CN115580635A (en) * | 2022-09-26 | 2023-01-06 | 广州健新科技有限责任公司 | Intelligent fault diagnosis method and system for terminal of Internet of things |
| CN115580635B (en) * | 2022-09-26 | 2023-06-13 | 广州健新科技有限责任公司 | Intelligent fault diagnosis method and system for Internet of things terminal |
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