CN112561736A - Fault diagnosis system and method for relay protection device of intelligent substation - Google Patents
Fault diagnosis system and method for relay protection device of intelligent substation Download PDFInfo
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Abstract
The invention provides a fault diagnosis system and a fault diagnosis method for a relay protection device of an intelligent substation, which relate to the field of electrical equipment and electrical engineering and comprise the following steps: the data acquisition module acquires state quantity data of the relay protection device; database state quantity data; the data processing module filters and deletes redundant data and invalid data in the acquired data; analyzing and evaluating the state quantity data of the state evaluation module, and finally obtaining the health state grade of the device; the fault prediction module judges the state trend and the residual service life of the device and carries out fault prediction; and the starting element hidden fault analysis module is used for performing wavelet transformation analysis on the acquired fault recording data to acquire a real fault node so as to judge the execution performance of the starting element and judge whether a hidden fault exists and whether a starting threshold needs to be modified. The invention can effectively avoid the problems of improper maintenance, excessive maintenance and the like of the relay protection device, improve the safety condition of the device and prolong the service life of the device.
Description
Technical Field
The invention relates to the field of electrical equipment and electrical engineering, in particular to a fault diagnosis system and method for an intelligent substation relay protection device.
Background
The research of China on the relay protection equipment state overhaul is still in the exploration and test stage, and several different theories based on life cycle cost, reliability, risk assessment and the like are provided for the state overhaul. Although the relay protection realizes microcomputer protection, the following 2 problems are difficult to solve:
1) the traditional relay protection device adopts a regular inspection mode, and has great compulsory property and blindness, thereby causing 'excessive inspection' and 'insufficient inspection'. Excessive maintenance can increase the workload of maintenance management personnel, cause the waste of equipment resources, reduce economic benefits and the like; the insufficient maintenance can affect the maintenance quality and the safety of the power grid and equipment. The relay protection health management system aims to improve pertinence and effectiveness of maintenance work of relay protection equipment, reasonably reduce maintenance cost and particularly need research and construction of the relay protection health management system.
2) At present, whether a relay protection system in operation has faults or not is mostly guaranteed only by some simple self-checking functions in microcomputer protection. Whether the protection system is regularly scheduled for maintenance or the protection device is self-checking, it is difficult to accurately predict the failure of the relay protection.
Therefore, the fault diagnosis system and method for the relay protection device of the intelligent substation are provided.
Disclosure of Invention
In order to overcome the defects in the prior art, the invention provides a fault diagnosis system for an intelligent substation relay protection device. The invention introduces the thought of fault Prediction and Health Management (PHM), can effectively process a large amount of data information of the relay protection device, comprehensively expresses the Health state of the device, and gives an early warning in time before the fault occurs. The realization of the PHM technology can timely make stress response when the relay protection device is in an unhealthy operation state, and the healthy operation of the relay protection device is recovered through a series of sensing, evaluating, predicting, diagnosing and deciding processes. The performance of a starting element of the protective device is analyzed and judged by analyzing fault recording data of the relay protective device, and hidden faults of the starting element of the protective device are expected to be monitored.
In order to achieve the above purpose, the invention provides the following technical scheme:
intelligent substation relay protection device fault diagnosis system includes:
the data acquisition module is used for acquiring state quantity data of the relay protection device reflecting the health state index of the device and a fault recording data table from an external system or device;
the database is used for storing the acquired state quantity data of the relay protection device; the database comprises a state evaluation data table of the relay protection device and a fault recording data table of each device;
the data processing module is used for filtering and deleting redundant data and invalid data in the acquired state quantity data of the relay protection device;
the state evaluation module is used for analyzing and evaluating the processed state quantity data of the relay protection device according to the state characteristic quantity of the relay protection device and the state evaluation related guide rule standard, and finally obtaining the health state grade of the device;
the fault prediction module is used for analyzing the historical index data of the device and the processed state quantity data of the relay protection device, judging the state trend and the residual life of the device, and performing fault prediction on the device;
and the starting element hidden fault analysis module is used for performing wavelet transformation analysis on the acquired fault recording data to acquire a real fault node so as to judge the execution performance of the starting element and judge whether a hidden fault exists and whether a starting threshold needs to be modified.
Preferably, the state quantity data of the relay protection device refers to parameters directly or indirectly representing technical indexes, performances and operation conditions of the state of the relay protection device, and includes various types of equipment basic data, real-time data, test data and other data, which are classified into the following four types: operating environment state quantity, detection type state quantity, improved type state quantity and alarm state quantity;
and the operating environment state quantity, the detection type state quantity, the improved type state quantity and the alarm state quantity are all stored in the state evaluation data table of the relay protection device.
Preferably, the operating environment state quantity is: the method comprises the following steps of (1) monitoring the ambient temperature, the humidity and the infrared monitoring temperature of each original part;
the detection type state quantity: the method comprises the steps that whether the relay protection device has abnormal correct action rate, insulation condition, analog quantity error condition and switching value or not is judged;
the improved state quantity is as follows: the method comprises the following steps of (1) including familial defect conditions, self defect conditions, counter measure execution conditions and the operation age of the device;
the alarm state quantity is as follows: the alarm frequency is more, the more the alarm frequency is, the more unstable the operation is, and the worse the health state of the device is.
The invention also provides a diagnosis method of the fault diagnosis system of the intelligent substation relay protection device, which comprises the following steps:
step 1, acquiring state quantity data and a fault recording data table of a relay protection device through a data acquisition module, and storing the acquired state quantity data in a database;
step 2, filtering and deleting redundant data and invalid data in the acquired state quantity data of the relay protection device through a data processing module;
step 3, analyzing and evaluating the processed state quantity data of the relay protection device through a state evaluation module according to the state characteristic quantity of the relay protection device and a state evaluation related guide rule standard, and finally obtaining a health state grade of the device;
step 4, analyzing the historical index data of the device and the processed state quantity data of the relay protection device through a fault prediction module, and judging the state trend and the residual life of the device, namely performing fault prediction on the relay protection device;
and 5, performing wavelet transformation analysis on the acquired fault recording data through the starting element hidden fault analysis module to acquire a real fault node, so as to judge the execution performance of the starting element, and judge whether a hidden fault exists and whether a starting threshold needs to be modified.
Preferably, the establishment of the evaluation rule is the basis of state evaluation, and the step 3 of analyzing and evaluating the state quantity data of the relay protection device by using an information classification scoring system comprises the following steps:
step 3.1, classifying all the information participating in evaluation, and determining the weight of each type of information and the score of each piece of information (supporting flexible configuration);
and 3.2, summarizing the received various information and calculating scores to obtain a protection total score, wherein different score ranges correspondingly protect different running states.
Preferably, the step 3.2 is to calculate the state evaluation by combining a fuzzy comprehensive membership function comprehensive evaluation method and a BP neural network, and specifically includes the following steps:
step 3.2.1, an evaluation standard matrix consisting of a fuzzy evaluation matrix and standard values of the state quantities in the states is constructed on the data, and then a proper fuzzy evaluation membership function is selected for calculation to obtain a fuzzy membership function;
taking the fuzzy membership function after dimensionality reduction as the input of the BP neural network, and outputting the fuzzy membership function as the maximum membership 1 corresponding to each state, for example, the output of a normal state is [1, 0, 0, 0], and the output of a notice state is [0, 1, 0, 0 ]; and the maximum value in the array obtained after training is the corresponding state, namely the state evaluation result.
The evaluation results are divided into five states of a normal state, an attention state, an abnormal state and a serious abnormal state according to the quantitative score:
since the evaluation result obtained by the neural network is a probability value, it is necessary to convert the evaluation result, and a conversion method between the result vector of the fuzzy state evaluation and the state score D is established according to a state score division method:
1) when the fuzzy evaluation result is in a normal state:
D＝90+b1×10 (1)
2) when the fuzzy evaluation result is the attention state or the abnormal state:
3) when the fuzzy comprehensive evaluation result is in a serious abnormal state:
D＝50-b4×10 (3)
in the formula, i represents a state grade, 1 is a normal state, 2 is an attention state, 3 is an abnormal state, and 4 is a serious abnormal state; dmiIs the median score of state i, Dmax_iAnd Dmin_iRespectively representing the upper and lower limits of the status score, biThe results are fuzzy comprehensive evaluation results.
Preferably, in the step 4, the failure distribution of the relay protection device is obtained by using an inhomogeneous poisson distribution model and weibull distribution, and the fault of the relay protection device is predicted:
the failure rate function λ (t) is:
λ(t)＝γβtβ-1 (4)
λ and β are Weibull distribution parameters; m (t) is an unreliable degree function and represents the fault frequency of the relay protection device in the operation time period, t is the relay protection operation time, and tau is an integral variable;
the failure rate function lambda (t) is a relay protection device fault intensity function which represents the number of times of faults occurring in the relay protection unit time; gamma and beta can be obtained through Weibull distribution and parameter solution, the fault process of the relay protection device can be determined according to the value of the parameter beta, and the failure rate lambda (t) is calculated.
Preferably, the step 5 is to monitor the performance of the starting element of the relay protection device by using the fault recording data and the relay protection information, and specifically includes the following steps:
step 5.1, extracting fault time in the fault waveform by adopting a wavelet method;
definition protection device PiStart time difference Δ T:
ΔT＝Ti-Tf (6)
in the formula: t isiFor protecting the device PiThe starting time of (c); t isfIs the time of actual occurrence of the fault; delta TεFor protecting the device PiWhen the starting time difference is allowed to reach the threshold value, when the starting performance of the relay protection is normal, the following should be provided:
ΔT≤ΔTε (7)
extraction of fault time T using wavelet techniquefCriterion Δ TεA value taking method;
step 5.2, comparing the actual starting time of the relay protection device with TfAnd comparing, evaluating the starting performance of the starting element of the relay protection device according to the difference, adjusting the threshold value of the starting element according to the difference, and ensuring that the delta T meets the formula (7) after adjustment so as to achieve the balance between sensitivity and reliability.
Preferably, the step 1 of obtaining the number of states of the relay protection device includes the following three ways:
1) manually acquiring the state quantity of the relay protection device; collecting regular operation conditions, including historical records of device operation and maintenance and inspection of professional operators; the method is an important means and way for acquiring the state quantity of the device by periodically carrying out various tests under the protection shutdown state;
2) automatically acquiring the state quantity of the relay protection device;
basic principles of state information acquisition: the device operation data can be collected through an RS485 interface reserved by equipment, or through an interface of IEC61850 standard;
the establishment of a power grid relay protection fault information system and a scheduling production management system realizes computer management and information sharing on the running condition, the defect fault condition, the previous maintenance test record and the like of the device. In the systems, partial state quantities of the relay protection device and the secondary circuit are respectively recorded, and the information is an important basis for making a state maintenance decision;
3) judging whether the starting element has a hidden fault or not according to the fault recording data;
the system information is characterized in that the information has quasi-real-time performance, only little information exists when the power system normally operates, a large amount of information can be generated when the power system fails, and the size of the information quantity is positively correlated with the fault range and the severity;
the real time of the fault can be extracted by analyzing the fault recording, and the health state of the equipment starting device can be known by comparing the real time with the action time of the device, so that whether the hidden fault exists or not is judged.
The fault diagnosis system and method for the intelligent substation relay protection device provided by the invention have the following beneficial effects:
(1) according to the invention, fault data can be obtained in time, and the data is analyzed and processed in time, and the fault is judged in time according to the analysis result, so that the problems of improper maintenance, excessive maintenance and the like of the relay protection device can be effectively avoided, the safety condition of the device is improved, and the service life of the device is prolonged; meanwhile, auxiliary decision information is provided for managers, the state maintenance informatization of the secondary protection device is realized, the stable operation capacity of the power grid can be improved, the method has effectiveness, the problems of the protection device can be found and solved in time, the economic efficiency is improved, the workload of personnel maintenance is reduced, and the maintenance cost is greatly reduced, so that the product has great social and economic benefits.
(2) The introduction of the PHM idea can effectively process a large amount of data information of the relay protection device, comprehensively represent the health state of the device and give an early warning in time before a fault occurs;
(3) the safety management level of the transformer substation is improved, and safety accidents are reduced;
(4) the fault diagnosis system and method for the relay protection device of the intelligent substation convert the traditional 'after maintenance' into 'according to the situation maintenance' and 'predictive maintenance', and create a new idea for better solving the defects in the traditional maintenance and realizing the state maintenance informatization of the relay protection device.
Drawings
In order to more clearly illustrate the embodiments of the present invention and the design thereof, the drawings required for the embodiments will be briefly described below. The drawings in the following description are only some embodiments of the invention and it will be clear to a person skilled in the art that other drawings can be derived from them without inventive effort.
Fig. 1 is a block diagram of a fault diagnosis system of an intelligent substation relay protection device according to embodiment 1 of the present invention;
FIG. 2 is a schematic diagram of startup element performance monitoring;
fig. 3 is a graph of a bathtub.
Detailed Description
In order that those skilled in the art will better understand the technical solutions of the present invention and can practice the same, the present invention will be described in detail with reference to the accompanying drawings and specific examples. The following examples are only for illustrating the technical solutions of the present invention more clearly, and the protection scope of the present invention is not limited thereby.
Example 1
The invention provides a fault diagnosis system for a relay protection device of an intelligent substation, which is specifically shown in figure 1 and comprises the following components:
the data acquisition module is used for acquiring state quantity data of the relay protection device reflecting the health state index of the device and a fault recording data table from an external system or device;
the database is used for storing the acquired state quantity data of the relay protection device; the database comprises a state evaluation data table of the relay protection device and a fault recording data table of each device; with the common use of digital equipment such as microcomputer-type relay protection devices and microcomputer-type fault oscillographs in power grids, when a power system fails, both the protection and fault oscillographs have the possibility of uploading fault information in a data mode. In order to improve the informatization and intellectualization level of a dispatching system for safe operation of a power grid, real-time fault information is provided for dispatching when the power grid fails, and the system is effectively and quickly restored. The invention is to select and establish a state evaluation data table of the relay protection device and a fault recording data table of each device, and the state evaluation data table and the fault recording data table are used for storing state quantity data acquired by relay protection. The establishment of the relay protection device database provides a necessary basis for the evaluation of the relay protection state, so that data can be derived from the database to accurately evaluate the state of the relay protection device. The data in the state evaluation data table of the relay protection device mainly comprise the state quantity of the operating environment of the protection device, the detection state quantity, the improved state quantity and the alarm state quantity. The data mainly stored in the fault recording data table of each device is the data of each channel in each fault recording.
The data processing module is used for filtering and deleting redundant data and invalid data in the acquired state quantity data of the relay protection device;
the state evaluation module is used for analyzing and evaluating the processed state quantity data of the relay protection device according to the state characteristic quantity of the relay protection device and the state evaluation related guide rule standard, and finally obtaining the health state grade of the device;
the fault prediction module is used for analyzing the historical index data of the device and the processed state quantity data of the relay protection device, judging the state trend and the residual life of the device, and performing fault prediction on the device;
and the starting element hidden fault analysis module is used for performing wavelet transformation analysis on the acquired fault recording data to acquire a real fault node so as to judge the execution performance of the starting element and judge whether a hidden fault exists and whether a starting threshold needs to be modified.
In this embodiment, the state quantity data of the relay protection device refers to parameters that directly or indirectly represent technical indexes, performance and operation conditions of the state of the relay protection device, and includes various types of device basic data, real-time data, test data and other data, and is classified into the following four types: operating environment state quantity, detection type state quantity, improved type state quantity and alarm state quantity;
and the operating environment state quantity, the detection state quantity, the improved state quantity and the alarm state quantity are stored in a state evaluation data table of the relay protection device. To some extent, the effectiveness and rapidity of information acquisition during a fault are one of the important signs of the practical effect of fault diagnosis.
Specifically, the operating environment state quantity: the method comprises the following steps of (1) monitoring the ambient temperature, the humidity and the infrared monitoring temperature of each original part;
detection type state quantity: the method comprises the steps of judging whether the relay protection device has abnormal correct action rate, insulation condition, analog quantity error condition, switching value and the like;
improved state quantity: the method comprises the following steps of (1) including familial defect conditions, self defect conditions, counter measure execution conditions and the operation age of the device;
alarm state quantity: the alarm frequency is more, the more the alarm frequency is, the more unstable the operation is, and the worse the health state of the device is.
The invention also provides a diagnosis method of the fault diagnosis system of the intelligent substation relay protection device, which comprises the following steps:
step 1, acquiring state quantity data and a fault recording data table of a relay protection device through a data acquisition module, and storing the acquired state quantity data in a database;
step 2, filtering and deleting redundant data and invalid data in the acquired state quantity data of the relay protection device through a data processing module;
step 3, analyzing and evaluating the processed state quantity data of the relay protection device through a state evaluation module according to the state characteristic quantity of the relay protection device and a state evaluation related guide rule standard, and finally obtaining a health state grade of the device;
the establishment of the evaluation rule is the basis of state evaluation, the step 3 adopts an information classification grading system, and the analysis and evaluation of the state quantity data of the relay protection device comprises the following steps:
step 3.1, classifying all the information participating in evaluation, and determining the weight of each type of information and the score of each piece of information (supporting flexible configuration);
and 3.2, summarizing the received various information and calculating scores to obtain a protection total score, wherein different score ranges correspondingly protect different running states.
Specifically, step 3.2 is to calculate the state evaluation by combining a fuzzy comprehensive membership function comprehensive evaluation method and a BP neural network, and specifically includes the following steps:
step 3.2.1, an evaluation standard matrix consisting of a fuzzy evaluation matrix and standard values of the state quantities in the states is constructed on the data, and then a proper fuzzy evaluation membership function is selected for calculation to obtain a fuzzy membership function;
and (4) selecting the state quantity which can most embody the health state of the device as a data basis by referring to Q/GDW 11285-2014 relay protection state evaluation guide rule.
TABLE 1 State variables
And establishing an evaluation standard matrix consisting of a fuzzy evaluation matrix and standard values of the state quantities in the states for the data, and then selecting a proper fuzzy evaluation membership function to calculate to obtain the fuzzy membership function.
Taking the fuzzy membership function after dimensionality reduction as the input of the BP neural network, and outputting the fuzzy membership function as the maximum membership 1 corresponding to each state, for example, the output of a normal state is [1, 0, 0, 0], and the output of a notice state is [0, 1, 0, 0 ]; and the maximum value in the array obtained after training is the corresponding state, namely the state evaluation result.
The evaluation results are divided into five states of a normal state, an attention state, an abnormal state and a serious abnormal state according to the quantitative score:
TABLE 2 State score and Categories
The determination of the information category and the determination of the weight, the score and the evaluation result can all refer to the national grid company enterprise standard Q/GDW 11285-2014 Relay protection state evaluation guide rule.
Since the evaluation result obtained by the neural network is a probability value, it is necessary to convert the evaluation result, and a conversion method between the result vector of the fuzzy state evaluation and the state score D is established according to a state score division method:
1) when the fuzzy evaluation result is in a normal state:
D＝90+b1×10 (3)
2) when the fuzzy evaluation result is the attention state or the abnormal state:
3) when the fuzzy comprehensive evaluation result is in a serious abnormal state:
D＝50-b4×10 (5)
in the formula, i represents a state grade, 1 is a normal state, 2 is an attention state, 3 is an abnormal state, and 4 is a serious abnormal state; dmiIs the median score of state i, Dmax_iAnd Dmin_iRespectively representing the upper and lower limits of the status score, biThe results are fuzzy comprehensive evaluation results.
The bathtub curve shown in fig. 3 reflects different stages and working time of the failure rate of the relay protection device. As can be seen from fig. 3, three specific periods of the protection fault, namely, an initial operation period (early fault period), a steady operation period (accidental fault period), and a loss period (loss fault period), are provided, and the bathtub curve reflects the fault trend change of the whole working process of the relay protection device, so that the fault can be more accurately checked according to the trend graph.
Step 4, analyzing the historical index data of the device and the processed state quantity data of the relay protection device through a fault prediction module, and judging the state trend and the residual life of the device, namely performing fault prediction on the relay protection device;
through a fault prediction module, a prediction evaluation module is an important module in a relay protection device fault prediction and management system, and the prediction evaluation means that historical index data and current state data of a device are analyzed, and a proper prediction evaluation algorithm is adopted to judge the state trend and the residual life of the device, namely the fault prediction is carried out on the device;
firstly, establishing a prediction algorithm, adopting a proper prediction algorithm through the configuration of the state quantity and the prediction algorithm of the relay protection device, and predicting the possible value of the state related parameters of the device in a period of time in the future by analyzing the index data of the current and historical states of the device. Then, predicting the service life, and predicting the residual service life of the device according to factors influencing the service life of the device;
specifically, step 4, obtaining failure distribution of the relay protection device by adopting an inhomogeneous poisson distribution model and Weibull distribution, and predicting the fault of the relay protection device:
the failure rate function λ (t) is:
λ(t)＝γβtβ-1 (6)
λ and β are Weibull distribution parameters; m (t) is an unreliable degree function and represents the fault frequency of the relay protection device in the operation time period, t is the relay protection operation time, and tau is an integral variable;
the failure rate function lambda (t) is a relay protection device fault intensity function which represents the number of times of faults occurring in the relay protection unit time; gamma and beta can be obtained through Weibull distribution and parameter solution, the fault process of the relay protection device can be determined according to the value of the parameter beta, and the failure rate lambda (t) is calculated.
And 5, performing wavelet transformation analysis on the acquired fault recording data through the starting element hidden fault analysis module to acquire a real fault node, so as to judge the execution performance of the starting element, and judge whether a hidden fault exists and whether a starting threshold needs to be modified.
Specifically, step 5 is to monitor the performance of the starting element of the relay protection device by using the fault recording data and the relay protection information, and specifically includes the following steps:
step 5.1, extracting fault time in the fault waveform by adopting a wavelet method;
definition protection device PiStart time difference Δ T:
ΔT＝Ti-Tf (1)
in the formula: t isiFor protecting the device PiThe starting time of (c); t isfIs the time of actual occurrence of the fault; delta TεFor protecting the device PiWhen the starting time difference is allowed to reach the threshold value, when the starting performance of the relay protection is normal, the following should be provided:
ΔT≤ΔTε (2)
extraction of fault time T using wavelet techniquefCriterion Δ TεA value taking method;
step 5.2, comparing the actual starting time of the relay protection device with TfAnd comparing, evaluating the starting performance of the starting element of the relay protection device according to the difference, adjusting the threshold value of the starting element according to the difference, and ensuring that the delta T meets the formula (2) after adjustment so as to achieve the balance between sensitivity and reliability.
Under normal conditions, when a power system fault occurs, the starting element can be automatically started according to the abnormal change of the monitored electrical quantity, and the more timely the starting element of the protection device is started, the closer the starting time is to the fault occurrence time, and the better the performance of the starting element is; otherwise, if the starting element cannot be started or the starting time is different from the fault time, the starting principle of the protection device is incorrect or the starting threshold value is incorrect, and the performance monitoring principle diagram of the starting element is shown in fig. 2.
Further, in this embodiment, the obtaining of the number of states of the relay protection device in step 1 includes the following three ways:
1) manually acquiring the state quantity of the relay protection device; collecting regular operation conditions, including historical records of device operation and maintenance and inspection of professional operators; the method is an important means and way for acquiring the state quantity of the device by periodically carrying out various tests under the protection shutdown state;
2) automatically acquiring the state quantity of the relay protection device;
basic principles of state information acquisition: the device operation data can be collected through an RS485 interface reserved by equipment, or through an interface of IEC61850 standard;
the establishment of a power grid relay protection fault information system and a scheduling production management system realizes computer management and information sharing on the running condition, the defect fault condition, the previous maintenance test record and the like of the device. In the systems, partial state quantities of the relay protection device and the secondary circuit are respectively recorded, and the information is an important basis for making a state maintenance decision;
3) judging whether the starting element has a hidden fault or not according to the fault recording data;
the system information is characterized in that the information has quasi-real-time performance, only little information exists when the power system normally operates, a large amount of information can be generated when the power system fails, and the size of the information quantity is positively correlated with the fault range and the severity;
the real time of the fault can be extracted by analyzing the fault recording, and the health state of the equipment starting device can be known by comparing the real time with the action time of the device, so that whether the hidden fault exists or not is judged.
The above-mentioned embodiments are only preferred embodiments of the present invention, and the scope of the present invention is not limited thereto, and any simple modifications or equivalent substitutions of the technical solutions that can be obviously obtained by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention.
Claims (8)
1. The utility model provides an intelligent substation relay protection device fault diagnosis system which characterized in that includes:
the data acquisition module is used for acquiring state quantity data of the relay protection device reflecting the health state index of the device and a fault recording data table from an external system or device;
the database is used for storing the acquired state quantity data of the relay protection device; the database comprises a state evaluation data table of the relay protection device and a fault recording data table of each device;
the data processing module is used for filtering and deleting redundant data and invalid data in the acquired state quantity data of the relay protection device;
the state evaluation module is used for analyzing and evaluating the processed state quantity data of the relay protection device according to the state characteristic quantity of the relay protection device and the state evaluation related guide rule standard, and finally obtaining the health state grade of the device;
the fault prediction module is used for analyzing the historical index data of the device and the processed state quantity data of the relay protection device, judging the state trend and the residual life of the device, and performing fault prediction on the device;
and the starting element hidden fault analysis module is used for performing wavelet transformation analysis on the acquired fault recording data to acquire a real fault node so as to judge the execution performance of the starting element and judge whether a hidden fault exists and whether a starting threshold needs to be modified.
2. The fault diagnosis system for the intelligent substation relay protection device according to claim 1, wherein the relay protection device state quantity data refers to parameters directly or indirectly representing technical indexes, performances and operating conditions of the relay protection device state, and includes various types of equipment basic data, real-time data, test data and other data, and is classified into the following four types: operating environment state quantity, detection type state quantity, improved type state quantity and alarm state quantity;
and the operating environment state quantity, the detection type state quantity, the improved type state quantity and the alarm state quantity are all stored in the state evaluation data table of the relay protection device.
3. The diagnostic method of the intelligent substation relay protection device fault diagnostic system of any one of claims 1 and 2, comprising the steps of:
step 1, acquiring state quantity data and a fault recording data table of a relay protection device through a data acquisition module, and storing the acquired state quantity data in a database;
step 2, filtering and deleting redundant data and invalid data in the acquired state quantity data of the relay protection device through a data processing module;
step 3, analyzing and evaluating the processed state quantity data of the relay protection device through a state evaluation module according to the state characteristic quantity of the relay protection device and a state evaluation related guide rule standard, and finally obtaining a health state grade of the device;
step 4, analyzing the historical index data of the device and the processed state quantity data of the relay protection device through a fault prediction module, and judging the state trend and the residual life of the device, namely performing fault prediction on the relay protection device;
and 5, performing wavelet transformation analysis on the acquired fault recording data through the starting element hidden fault analysis module to acquire a real fault node, so as to judge the execution performance of the starting element, and judge whether a hidden fault exists and whether a starting threshold needs to be modified.
4. The diagnosis method of the fault diagnosis system of the intelligent substation relay protection device according to claim 3, wherein the establishment of the evaluation rule is the basis of state evaluation, and the step 3 of analyzing and evaluating the state quantity data of the relay protection device by using an information classification scoring system comprises the following steps:
step 3.1, classifying all the information participating in evaluation, and determining the weight of each type of information and the score of each piece of information;
and 3.2, summarizing the received various information and calculating scores to obtain a protection total score, wherein different score ranges correspondingly protect different running states.
5. The diagnosis method of the fault diagnosis system of the intelligent substation relay protection device according to claim 4, wherein the step 3.2 is to calculate the state evaluation by adopting a method of combining a fuzzy comprehensive membership function comprehensive evaluation method and a BP neural network, and specifically comprises the following steps:
step 3.2.1, an evaluation standard matrix consisting of a fuzzy evaluation matrix and standard values of the state quantities in the states is constructed on the data, and then a proper fuzzy evaluation membership function is selected for calculation to obtain a fuzzy membership function;
step 3.2.2, the fuzzy membership function after dimensionality reduction is used as the input of the BP neural network, the output is the maximum membership 1 corresponding to each state, and the maximum value in the array obtained after training is the corresponding state, namely the state evaluation result;
step 3.2.3, establishing a conversion method between the result vector of the fuzzy state evaluation and the state score D according to the state score dividing mode:
1) when the fuzzy evaluation result is in a normal state:
D＝90+b1×10 (1)
2) when the fuzzy evaluation result is the attention state or the abnormal state:
3) when the fuzzy comprehensive evaluation result is in a serious abnormal state:
D＝50-b4×10 (3)
in the formula, i represents the status level, 1 is the normal status, and 2 is the attention statusState 3 is abnormal state and 4 is severe abnormal state; dmiIs the median score of state i, Dmax_iAnd Dmin_iRespectively representing the upper and lower limits of the status score, biThe results are fuzzy comprehensive evaluation results.
6. The diagnosis method of the fault diagnosis system of the intelligent substation relay protection device according to claim 3, wherein the step 4 adopts an inhomogeneous poisson distribution model to obtain the failure distribution of the relay protection device by adopting Weibull distribution, so as to predict the fault of the relay protection device:
the failure rate function λ (t) is:
λ(t)＝γβtβ-1 (4)
λ and β are Weibull distribution parameters; m (t) is an unreliable degree function and represents the fault frequency of the relay protection device in the operation time period, t is the relay protection operation time, and tau is an integral variable;
the failure rate function lambda (t) is a relay protection device fault intensity function which represents the number of times of faults occurring in the relay protection unit time; gamma and beta can be obtained through Weibull distribution and parameter solution, the fault process of the relay protection device can be determined according to the value of the parameter beta, and the failure rate lambda (t) is calculated.
7. The diagnosis method of the fault diagnosis system of the intelligent substation relay protection device according to claim 3, wherein the step 5 is to monitor the performance of the starting element of the relay protection device by using fault recording data and relay protection information, and specifically comprises the following steps:
step 5.1, extracting fault time in the fault waveform by adopting a wavelet method;
definition protection device PiStart time difference Δ T:
ΔT＝Ti-Tf (6)
in the formula: t isiFor protecting the device PiThe starting time of (c); t isfIs the time of actual occurrence of the fault; delta TεFor protecting the device PiWhen the starting time difference is allowed to reach the threshold value, when the starting performance of the relay protection is normal, the following should be provided:
ΔT≤ΔTε (7)
extraction of fault time T using wavelet techniquefCriterion Δ TεA value taking method;
step 5.2, comparing the actual starting time of the relay protection device with TfAnd comparing, evaluating the starting performance of the starting element of the relay protection device according to the difference, adjusting the threshold value of the starting element according to the difference, and ensuring that the delta T meets the formula (7) after adjustment.
8. The diagnosis method of the fault diagnosis system of the intelligent substation relay protection device according to claim 3, wherein the step 1 of obtaining the number of states of the relay protection device comprises the following three ways:
1) manually acquiring the state quantity of the relay protection device; collecting regular operation conditions, including historical records of device operation and maintenance and inspection of professional operators;
2) automatically acquiring the state quantity of the relay protection device;
3) and judging whether the starting element has a hidden fault or not according to the fault recording data.
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