Multi-dimensional diagnostic evaluation method and device for auxiliary equipment of pumped storage power station

Abstract

The present invention discloses a multidimensional diagnostic evaluation method and device for auxiliary equipment of a pumped-storage power station. The method and device establish evaluation indicators and grades for each key component of each auxiliary equipment in the pumped-storage power station, collect operating data of each key component of each auxiliary equipment, evaluate each evaluation indicator of each key component according to the operating data, evaluation indicators and grades, and obtain a fuzzy relationship matrix; determine the weight of each evaluation indicator, obtain a fuzzy comprehensive evaluation result vector of each key component according to the fuzzy relationship matrix and the weight, further determine the health status of each key component, and determine the first health status of each auxiliary equipment through priority; obtain fault diagnosis data of each auxiliary equipment in the equipment system of the pumped-storage power station, determine the second health status of each auxiliary equipment according to the fault diagnosis data, and obtain the health status of each auxiliary equipment through priority determination based on the first health status and the second health status.

Description

Technical Field

[0001] The present invention relates to the field of equipment fault diagnosis, and in particular to a multi-dimensional diagnosis and evaluation method and device for auxiliary equipment of a pumped storage power station. Background Art

[0002] As my country's water conservancy and hydropower construction continues, the intelligent development of auxiliary equipment, such as those in pumped-storage power plants, is constrained by safety requirements. Edge computing, diagnostics, and early warning systems need improvement, and the intelligence level of individual equipment remains relatively low. The health of auxiliary equipment significantly impacts the operation of pumped-storage power plants. Currently, the health of auxiliary equipment is assessed using individual device monitoring, with personnel assessing the equipment status based on monitoring data, resulting in high costs. Alternatively, the equipment status is determined directly based on systemic fault diagnosis results. However, since systemic faults can be caused by a single or multiple causes, the assessment accuracy is low. Summary of the Invention

[0003] In response to the above-mentioned problems of high cost and low efficiency of manual monitoring and low accuracy of systemic fault diagnosis, the embodiment of this application aims to propose a multi-dimensional diagnosis and evaluation method and device for auxiliary equipment of pumped storage power station to solve the technical problems mentioned in the above background technology section.

[0004] In a first aspect, the present invention provides a multi-dimensional diagnostic and evaluation method for auxiliary equipment of a pumped storage power station, comprising the following steps:

[0005] S1, establishing an evaluation index and a grade of each evaluation index for each key component of each auxiliary equipment in the pumped storage power station, collecting operating data of each key component of each auxiliary equipment, evaluating each evaluation index of each key component during operation based on the operating data, evaluation index, and grade, determining the degree of membership of each key component to the grade of each evaluation index, and obtaining a fuzzy relationship matrix;

[0006] S2, determine the weight of each evaluation index, and obtain the fuzzy comprehensive evaluation result vector of each key component according to the fuzzy relationship matrix and the weight;

[0007] S3, determining the health status of each key component according to the fuzzy comprehensive evaluation result vector, and determining the first health status of each auxiliary device according to the priority based on the health status of all key components of each auxiliary device;

[0008] S4, obtaining fault diagnosis data of each auxiliary device in the equipment system of the pumped storage power station, determining the second health state of each auxiliary device according to the fault diagnosis data, and obtaining the health state of each auxiliary device by priority determination based on the first health state and the second health state.

[0009] Preferably, step S1 specifically includes:

[0010] Determine the evaluation indicators of each key component of each auxiliary equipment:

[0011] u={u1,u2,……,u p};

[0012] Among them, u p is the pth evaluation index;

[0013] Determine the level set for each evaluation indicator:

[0014] v={v1,v2,……,v q};

[0015] Among them, v q is the qth level fuzzy subset;

[0016] According to the operation data of each key indicator, each evaluation indicator u of each key component is evaluated one by one. i (i=1,2,……,p) is quantified to determine the membership degree of key components to the fuzzy subset of the level from a single evaluation index (R|u i ), and get the fuzzy relationship matrix:

[0017]

[0018] The element r in row i and column j of the fuzzy relationship matrix R ij Indicates the key components of auxiliary equipment from the evaluation index u i Let's look at the rank fuzzy subset v j The membership degree of each key component is the evaluation index u i The performance is achieved through the fuzzy vector (R|u i )=(r i1 ,r i2 ,……,r im )express.

[0019] Preferably, step S2 specifically includes:

[0020] Determine the weight of the evaluation indicators:

[0021] A=(a1,a2,……,a p );

[0022] Among them, the element a in weight A i Essentially, it is the evaluation index u i For the membership of fuzzy sub-{evaluation index important to key components}, the hierarchical analysis method is used to determine the relative importance order between the evaluation indexes and determine the value of each factor of the weight, where:

[0023] The fuzzy comprehensive evaluation result vector B of the key components of each auxiliary equipment is calculated according to the following formula:

[0024]

[0025] Among them, b j It is obtained by calculating the jth column of A and R, which indicates the key components of the auxiliary equipment as a whole. j The degree of membership of a hierarchical fuzzy subset.

[0026] Preferably, step S3 specifically includes:

[0027] S31, determine b respectively according to the state threshold j The corresponding health status, statistics of the health status of all evaluation indicators of each key component;

[0028] S32, determining the health status of each key component based on the status of all evaluation indicators of each key component;

[0029] S33 , sorting the health statuses of all key components of each auxiliary device according to priority, and selecting the health status with the highest priority as the first health status of the auxiliary device.

[0030] Preferably, step S32 specifically includes:

[0031] Determine whether all evaluation indicators of the key component are in normal state. If so, determine that the state of the key component is normal.

[0032] Otherwise, determine whether three or more of the states of all evaluation indicators of the key component are in a dangerous state. If so, determine that the health state of the key component is dangerous;

[0033] Otherwise, determine whether any of the states of all evaluation indicators of the key component is in a dangerous state. If so, determine that the health state of the key component is abnormal;

[0034] Otherwise, it is determined whether any of the states of all evaluation indicators of the key component is in a caution or abnormal state. If so, the health state of the key component is determined to be caution.

[0035] Preferably, step S4 specifically includes:

[0036] Determining whether the fault diagnosis data contains a primary fault, and if so, determining that the secondary health state of the auxiliary equipment is dangerous;

[0037] Otherwise, determining whether the fault diagnosis data has a secondary fault, and if so, determining that the second health state of the auxiliary device is abnormal;

[0038] Otherwise, it is determined whether the fault diagnosis data contains a level 3 fault. If so, it is determined whether the auxiliary device has had a level 3 fault three times or more. If so, the second health state of the auxiliary device is determined to be abnormal. Otherwise, the second health state of the auxiliary device is determined to be caution.

[0039] If the fault diagnosis data does not indicate a level 3 fault, determining that the second health state of the auxiliary device is normal;

[0040] A health state with the highest priority between the first health state and the second health state of each auxiliary device is selected as the health state of the auxiliary device.

[0041] Preferably, the priorities are sorted as follows: dangerous over abnormal, abnormal over caution, caution over normal.

[0042] In a second aspect, the present invention provides a multi-dimensional diagnostic and evaluation device for auxiliary equipment of a pumped storage power station, comprising:

[0043] a hierarchical analysis module configured to establish an evaluation index and a grade of each evaluation index for each key component of each auxiliary equipment in the pumped storage power station, collect operating data of each key component of each auxiliary equipment, evaluate each evaluation index of each key component during operation based on the operating data, the evaluation index and the grade, determine the degree of membership of each key component to the grade of each evaluation index, and obtain a fuzzy relationship matrix;

[0044] A fuzzy evaluation module is configured to determine the weight of each evaluation index and obtain a fuzzy comprehensive evaluation result vector of each key component according to the fuzzy relationship matrix and the weight;

[0045] a single device evaluation module configured to determine a health state of each key component according to a fuzzy comprehensive evaluation result vector, and determine a first health state of each auxiliary device according to a priority based on the health states of all key components of each auxiliary device;

[0046] The comprehensive evaluation module is configured to obtain fault diagnosis data of each auxiliary equipment in the equipment system of the pumped-storage power station, determine the second health state of each auxiliary equipment based on the fault diagnosis data, and obtain the health state of each auxiliary equipment through priority determination based on the first health state and the second health state.

[0047] In a third aspect, the present invention provides an electronic device comprising one or more processors; a storage device for storing one or more programs, wherein when the one or more programs are executed by one or more processors, the one or more processors implement the method described in any implementation manner in the first aspect.

[0048] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in any implementation manner in the first aspect.

[0049] Compared with the prior art, the present invention has the following beneficial effects:

[0050] (1) The multi-dimensional diagnostic evaluation method for auxiliary equipment of a pumped storage power station proposed in the present invention uses multiple dimensions to evaluate the health status of the auxiliary equipment. On the one hand, the health status of the key components of the auxiliary equipment is analyzed to comprehensively obtain the first health status of the auxiliary equipment. On the other hand, the fault diagnosis data of the equipment system is analyzed to obtain the second health status of the auxiliary equipment. By combining the first health status and the second health status, the most accurate health status of the auxiliary equipment is obtained, which can accurately manage the auxiliary equipment.

[0051] (2) The multi-dimensional diagnostic evaluation method for auxiliary equipment of a pumped-storage power station proposed in the present invention manages the auxiliary equipment throughout its life cycle by analyzing the health status of key components of various auxiliary equipment and the types of fault diagnosis. This is conducive to achieving less-manned duty in the pumped-storage power station, reducing the loss of auxiliary equipment in the pumped-storage power station, and improving the comprehensive benefits of the pumped-storage power station.

[0052] (3) The multi-dimensional diagnosis and evaluation method for auxiliary equipment of a pumped-storage power station proposed in the present invention can manage the basic information and fault information of the equipment of the pumped-storage power station, understand the health status of the equipment at the current stage, make a scientific estimate of the health status of the equipment, and guide the rational development of the work of the pumped-storage power station, such as equipment operation, maintenance, and replacement. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0054] Figure 1 is a diagram of an exemplary device architecture to which an embodiment of the present application may be applied;

[0055] Figure 2 A flowchart of a multi-dimensional diagnostic and evaluation method for auxiliary equipment of a pumped storage power station according to an embodiment of the present application;

[0056] Figure 3 Schematic diagram of the overall evaluation process of the multi-dimensional diagnostic evaluation method for auxiliary equipment of a pumped storage power station according to an embodiment of the present application;

[0057] Figure 4Schematic diagram of a multi-dimensional diagnostic and evaluation device for auxiliary equipment of a pumped-storage power station according to an embodiment of the present application;

[0058] Figure 5 It is a structural diagram of a computer device suitable for implementing the electronic device of the embodiment of the present application. DETAILED DESCRIPTION

[0059] To make the objectives, technical solutions, and advantages of the present invention more apparent, the present invention will be further described in detail below with reference to the accompanying drawings. It is apparent that the embodiments described are only some, not all, of the present invention. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without creative effort are intended to fall within the scope of protection of the present invention.

[0060] Figure 1 An exemplary device architecture 100 is shown in which a multi-dimensional diagnosis and evaluation method for auxiliary equipment of a pumped-storage power station or a multi-dimensional diagnosis and evaluation device for auxiliary equipment of a pumped-storage power station according to an embodiment of the present application can be applied.

[0061] like Figure 1 As shown, the device architecture 100 may include terminal devices 101, 102, 103, a network 104, and a server 105. The network 104 is used to provide a medium for communication links between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired or wireless communication links or fiber optic cables.

[0062] Users can use terminal devices 101, 102, 103 to interact with server 105 via network 104 to receive or send messages, etc. Various applications, such as data processing applications and file processing applications, can be installed on terminal devices 101, 102, 103.

[0063] Terminal devices 101, 102, and 103 can be hardware or software. When terminal devices 101, 102, and 103 are hardware, they can be various electronic devices, including but not limited to smartphones, tablet computers, laptop computers, and desktop computers. When terminal devices 101, 102, and 103 are software, they can be installed in the electronic devices listed above. They can be implemented as multiple software or software modules (for example, software or software modules used to provide distributed services), or they can be implemented as a single software or software module. No specific limitations are given here.

[0064] The server 105 may be a server that provides various services, such as a background data processing server that processes files or data uploaded by the terminal devices 101, 102, and 103. The background data processing server may process the acquired files or data and generate processing results.

[0065] It should be noted that the multi-dimensional diagnostic and evaluation method for auxiliary equipment of a pumped-storage power station provided in the embodiment of the present application can be executed by the server 105 or by the terminal devices 101, 102, and 103. Accordingly, the multi-dimensional diagnostic and evaluation device for auxiliary equipment of a pumped-storage power station can be set in the server 105 or in the terminal devices 101, 102, and 103.

[0066] It should be understood that Figure 1 The number of terminal devices, networks, and servers in the above description is merely illustrative. Any number of terminal devices, networks, and servers may be provided as needed. If the processed data does not need to be acquired remotely, the above-described apparatus architecture may not include a network, but only require servers or terminal devices.

[0067] Figure 2 A multi-dimensional diagnostic and evaluation method for auxiliary equipment of a pumped storage power station provided by an embodiment of the present application is shown, comprising the following steps:

[0068] S1, establish the evaluation index of each key component of each auxiliary equipment in the pumped storage power station and the grade of each evaluation index, collect the operating data of each key component of each auxiliary equipment, evaluate each evaluation index of each key component during the operation process according to the operating data, evaluation index and grade, determine the membership degree of each key component to the grade of each evaluation index, and obtain the fuzzy relationship matrix.

[0069] In a specific embodiment, step S1 specifically includes:

[0070] Determine the evaluation indicators of each key component of each auxiliary equipment:

[0071] u={u1,u2,……,u p};

[0072] Among them, u p is the pth evaluation index;

[0073] Determine the level set for each evaluation indicator:

[0074] v={v1,v2,……,v q};

[0075] Among them, v q is the qth level fuzzy subset;

[0076] According to the operation data of each key indicator, each evaluation indicator u of each key component is evaluated one by one. i (i=1,2,……,p) is quantified to determine the membership degree of key components to the fuzzy subset of the level from a single evaluation index (R|ui ), and get the fuzzy relationship matrix:

[0077]

[0078] The element r in row i and column j of the fuzzy relationship matrix R ij Indicates the key components of auxiliary equipment from the evaluation index u i Let's look at the rank fuzzy subset v j The membership degree of each key component is the evaluation index u i The performance is achieved through the fuzzy vector (R|u i )=(r i1 ,r i2 ,……,r im )express.

[0079] Specifically, the key components of the auxiliary equipment include the stator, rotor, water guide bearing, upper guide bearing, lower guide bearing, top cover, and the evaluation indicators are temperature, swing, vibration amplitude, water level, and pressure.

[0080] The equipment system of a pumped-storage power station is composed of a single auxiliary device, so the health status of each auxiliary device needs to be evaluated. The embodiment of the present application collects the operating data of the key components of a single auxiliary device, and constructs a multi-level fuzzy comprehensive evaluation model for the health status of the key components of the auxiliary equipment of the pumped-storage power station based on the hierarchical analysis method and the basic principles of fuzzy evaluation. By calculating the fuzzy evaluation matrix and indicator status of the key components, the evaluation results of the key components are obtained. The auxiliary equipment of the pumped-storage power station is evaluated separately according to the key components to obtain the fuzzy relationship matrix, thereby realizing online quantitative evaluation of the health status.

[0081] S2, determine the weight of each evaluation index, and obtain the fuzzy comprehensive evaluation result vector of each key component according to the fuzzy relationship matrix and weight.

[0082] In a specific embodiment, step S2 specifically includes:

[0083] Determine the weight of the evaluation indicators:

[0084] A=(a1,a2,……,a p );

[0085] Among them, the element a in weight A i Essentially, it is the evaluation index u i For the membership of fuzzy sub-{evaluation index important to key components}, the hierarchical analysis method is used to determine the relative importance order between the evaluation indexes and determine the value of each factor of the weight, where:

[0086] The fuzzy comprehensive evaluation result vector B of the key components of each auxiliary equipment is calculated according to the following formula:

[0087]

[0088] Among them, b j It is obtained by calculating the jth column of A and R, which indicates the key components of the auxiliary equipment as a whole. j The degree of membership of a hierarchical fuzzy subset.

[0089] Specifically, the embodiments of the present application, based on expert knowledge and subjective experience, use rigorous logical mathematical methods to eliminate subjective components, and test the rationality of the weight values ​​by judging whether the fuzzy relationship matrix has satisfactory consistency, so that the weight values ​​are more in line with objective reality than the weight values ​​determined by the expert evaluation method, and are easy to express quantitatively, thereby improving the reliability, accuracy and objectivity of the evaluation results.

[0090] S3, determining the health status of each key component according to the fuzzy comprehensive evaluation result vector, and determining the first health status of each auxiliary device according to the priority based on the health status of all key components of each auxiliary device.

[0091] In a specific embodiment, step S3 specifically includes:

[0092] S31, determine b respectively according to the state threshold j The corresponding health status, statistics of the health status of all evaluation indicators of each key component;

[0093] S32, determining the health status of each key component based on the status of all evaluation indicators of each key component;

[0094] S33 , sorting the health statuses of all key components of each auxiliary device according to priority, and selecting the health status with the highest priority as the first health status of the auxiliary device.

[0095] Preferably, step S32 specifically includes:

[0096] Determine whether all evaluation indicators of the key component are in normal state. If so, determine that the state of the key component is normal.

[0097] Otherwise, determine whether three or more of the states of all evaluation indicators of the key component are in a dangerous state. If so, determine that the health state of the key component is dangerous;

[0098] Otherwise, determine whether any of the states of all evaluation indicators of the key component is in a dangerous state. If so, determine that the health state of the key component is abnormal;

[0099] Otherwise, it is determined whether any of the states of all evaluation indicators of the key component is in a caution or abnormal state. If so, the health state of the key component is determined to be caution.

[0100] Specifically, refer to Figure 3 , the characteristic data b of the fuzzy comprehensive evaluation result vector B of each key component j For specific evaluation indicators, a corresponding threshold can be set for each evaluation indicator to calculate the health status of each evaluation indicator. The health status of each key component is determined based on the calculated health status of each evaluation indicator and pre-set rules. The health status of all key components of each auxiliary device is statistically analyzed, and the primary health status of each auxiliary device is determined based on priority. Specifically, the priority is ranked as follows: dangerous is higher than abnormal, abnormal is higher than caution, and caution is higher than normal. For example, if a device has three key components with health statuses of "dangerous," "abnormal," and "caution," the highest priority is "dangerous," and the device's health status is "dangerous." For example, if a device has three key components with health statuses of "abnormal," "abnormal," or "normal," the highest priority is "abnormal," and the device's health status is "abnormal." And so on. Therefore, the primary health status calculated based on all evaluation indicators of each key component of a single auxiliary device is more accurate, eliminates the need for manual judgment, and reduces operating costs.

[0101] S4, obtaining fault diagnosis data of each auxiliary device in the equipment system of the pumped storage power station, determining the second health state of each auxiliary device according to the fault diagnosis data, and obtaining the health state of each auxiliary device by priority determination based on the first health state and the second health state.

[0102] In a specific embodiment, step S4 specifically includes:

[0103] Determining whether the fault diagnosis data contains a primary fault, and if so, determining that the secondary health state of the auxiliary equipment is dangerous;

[0104] Otherwise, determining whether the fault diagnosis data has a secondary fault, and if so, determining that the second health state of the auxiliary device is abnormal;

[0105] Otherwise, it is determined whether the fault diagnosis data contains a level 3 fault. If so, it is determined whether the auxiliary device has had a level 3 fault three times or more. If so, the second health state of the auxiliary device is determined to be abnormal. Otherwise, the second health state of the auxiliary device is determined to be caution.

[0106] If the fault diagnosis data does not indicate a level 3 fault, determining that the second health state of the auxiliary device is normal;

[0107] A health state with the highest priority between the first health state and the second health state of each auxiliary device is selected as the health state of the auxiliary device.

[0108] Specifically, the first health status is compared with the second health status diagnosed by the device system's diagnostic platform. Priority is determined based on the likelihood and impact of the fault, as well as the difficulty of fault management. The higher-priority health status is selected between the first and second health statuses to determine the health status of the auxiliary device. After all evaluation indicators have been determined, the highest-priority evaluation indicator is used as the health status of the auxiliary device. This method allows for the assessment of the health status of auxiliary devices, enabling on-site maintenance personnel to promptly understand the health status of the auxiliary devices and provide more accurate diagnosis.

[0109] Further references Figure 4 As an implementation of the methods shown in the above figures, the present application provides an embodiment of a multi-dimensional diagnostic and evaluation device for auxiliary equipment of a pumped storage power station. Figure 2 Corresponding to the method embodiment shown, the device can be specifically applied to various electronic devices.

[0110] The present application provides a multi-dimensional diagnostic and evaluation device for auxiliary equipment of a pumped storage power station, comprising:

[0111] A hierarchy analysis module 1 is configured to establish an evaluation index and a grade of each evaluation index for each key component of each auxiliary equipment in the pumped storage power station, collect operating data of each key component of each auxiliary equipment, evaluate each evaluation index of each key component during operation based on the operating data, the evaluation index, and the grade, determine the degree of membership of each key component to the grade of each evaluation index, and obtain a fuzzy relationship matrix;

[0112] The fuzzy evaluation module 2 is configured to determine the weight of each evaluation index and obtain the fuzzy comprehensive evaluation result vector of each key component according to the fuzzy relationship matrix and the weight;

[0113] a single device evaluation module 3, configured to determine the health status of each key component according to the fuzzy comprehensive evaluation result vector, and determine the first health status of each auxiliary device according to the health status of all key components of each auxiliary device by priority;

[0114] The comprehensive evaluation module 4 is configured to obtain fault diagnosis data of each auxiliary equipment in the equipment system of the pumped-storage power station, determine the second health state of each auxiliary equipment based on the fault diagnosis data, and obtain the health state of each auxiliary equipment through priority determination based on the first health state and the second health state.

[0115] Reference below Figure 5, which shows an electronic device (eg Figure 1 A structural diagram of a computer device 500 (a server or terminal device as shown). Figure 5 The electronic device shown is merely an example and should not limit the functions and scope of use of the embodiments of the present application.

[0116] like Figure 5 As shown, the computer device 500 includes a central processing unit (CPU) 501 and a graphics processing unit (GPU) 502, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 503 or the program loaded from the storage part 509 to the random access memory (RAM) 504. Various programs and data required for the operation of the device 500 are also stored in the RAM 504. The CPU 501, GPU 502, ROM 503 and RAM 504 are connected to each other via a bus 505. An input / output (I / O) interface 506 is also connected to the bus 505.

[0117] The following components are connected to the I / O interface 506: an input section 507 including a keyboard, a mouse, etc.; an output section 508 including a display such as a liquid crystal display (LCD), a speaker, etc.; a storage section 509 including a hard disk, etc.; and a communication section 510 including a network interface card such as a LAN card, a modem, etc. The communication section 510 performs communication processing via a network such as the Internet. A drive 511 may also be connected to the I / O interface 506 as needed. A removable medium 512, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed in the drive 511 as needed, so that a computer program read therefrom can be installed into the storage section 509 as needed.

[0118] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through the communication part 510, and / or installed from a removable medium 512. When the computer program is executed by the central processing unit (CPU) 501 and the graphics processing unit (GPU) 502, the above-mentioned functions defined in the method of the present application are performed.

[0119] It should be noted that the computer-readable medium described in this application may be a computer-readable signal medium or a computer-readable medium, or any combination thereof. Computer-readable media may be, for example, but not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor devices, apparatuses, or components, or any combination thereof. More specific examples of computer-readable media may include, but are not limited to, an electrical connection having one or more conductors, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this application, a computer-readable medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution device, apparatus, or component. In this application, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable medium that can transmit, propagate, or transport a program for use by or in conjunction with an instruction execution apparatus, device, or device. Program code embodied on a computer-readable medium may be transmitted using any suitable medium, including but not limited to wireless, wireline, optical cable, RF, or any suitable combination thereof.

[0120] Computer program code for performing the operations of the present application can be written in one or more programming languages, or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on the remote computer or server. In cases involving a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0121] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions and operations of the devices, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, program segment or part of code, and the module, program segment or part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart and the combination of boxes in the block diagram and / or flowchart can be implemented with a dedicated hardware-based device that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0122] The modules involved in the embodiments described in this application may be implemented in software or hardware, and may also be set in a processor.

[0123] As another aspect, the present application also provides a computer-readable medium, which may be included in the electronic device described in the above embodiment; or may exist independently and not be assembled into the electronic device. The computer-readable medium carries one or more programs, and when the one or more programs are executed by the electronic device, the electronic device causes the electronic device to: establish evaluation indicators and grades of each key component of each auxiliary equipment in the pumped-storage power station; collect operating data of each key component of each auxiliary equipment; evaluate each evaluation indicator of each key component during operation according to the operating data, the evaluation indicators, and the grades; determine the membership of each key component to the grades of each evaluation indicator, and obtain a fuzzy relationship matrix; determine the weight of each evaluation indicator; obtain a fuzzy comprehensive evaluation result vector for each key component according to the fuzzy relationship matrix and the weight; determine the health state of each key component according to the fuzzy comprehensive evaluation result vector, and determine the first health state of each auxiliary device according to the health states of all key components of each auxiliary device by priority; obtain fault diagnosis data of each auxiliary device in the equipment system of the pumped-storage power station, determine the second health state of each auxiliary device according to the fault diagnosis data, and obtain the health state of each auxiliary device according to the first health state and the second health state by priority.

[0124] The above description is merely a preferred embodiment of the present application and an illustration of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in this application is not limited to the technical solutions formed by the specific combination of the above-mentioned technical features, but also encompasses other technical solutions formed by any combination of the above-mentioned technical features or their equivalents without departing from the above-mentioned inventive concept. For example, a technical solution formed by replacing the above-mentioned features with (but not limited to) technical features with similar functions disclosed in this application.

Claims

1. A multi-dimensional diagnostic and evaluation method for auxiliary equipment of a pumped storage power station, characterized in that: The following steps are involved: S1, establishing an evaluation index and a grade of each evaluation index for each key component of each auxiliary equipment in the pumped storage power station, collecting operating data of each key component of each auxiliary equipment, the key components of the auxiliary equipment including the stator, rotor, water guide bearing, upper guide bearing, lower guide bearing, and top cover, the evaluation indexes including temperature, swing, vibration amplitude, water level, and pressure, evaluating each evaluation index of each key component during operation based on the operating data, the evaluation index, and the grade, determining the membership of each key component to the grade of each evaluation index, and obtaining a fuzzy relationship matrix; specifically including: Determine the evaluation indicators of each key component of each auxiliary equipment: u={u1,u2,……,u p }; Among them, u p is the pth evaluation index; Determine the level set for each evaluation indicator: v={v1,v2,……,v q }; Among them, v q is the qth level fuzzy subset; According to the operation data of each key indicator, each evaluation indicator u of each key component is evaluated one by one. i (i=1,2,……,p) is quantified to determine the membership degree (R|u i ), and obtain the fuzzy relationship matrix: The element r in the i-th row and j-th column of the fuzzy relationship matrix R ij Indicates the key components of auxiliary equipment from the evaluation index u i Let's look at the rank fuzzy subset v j The membership degree of each key component is the evaluation index u i The performance is achieved through the fuzzy vector (R|u i )=(r i1 ,r i2 ,……,r im )express; S2, determining the weight of each evaluation index, and obtaining the fuzzy comprehensive evaluation result vector of each key component according to the fuzzy relationship matrix and the weight; specifically including: Determine the weight of the evaluation indicators: Among them, the element a in weight A i Essentially, it is the evaluation index u i For the membership of fuzzy sub-{evaluation index important to key components}, the hierarchical analysis method is used to determine the relative importance order between the evaluation indexes and determine the value of each factor of the weight, where: a i ≥0, i=1,2,……,p; The fuzzy comprehensive evaluation result vector B of the key components of each auxiliary equipment is calculated according to the following formula: Among them, b j It is obtained by calculating the jth column of A and R, which indicates the key components of the auxiliary equipment as a whole. j The degree of membership of hierarchical fuzzy subsets; S3, determining the health status of each key component according to the fuzzy comprehensive evaluation result vector, and determining the first health status of each auxiliary device according to the health status of all key components of each auxiliary device by priority; S4, obtaining fault diagnosis data of each auxiliary equipment in the equipment system of the pumped-storage power station, determining the second health state of each auxiliary equipment according to the fault diagnosis data, and obtaining the health state of each auxiliary equipment by priority determination based on the first health state and the second health state.

2. The multi-dimensional diagnostic and evaluation method for auxiliary equipment of a pumped storage power station according to claim 1, characterized in that: The step S3 specifically includes: S31, determine b respectively according to the state threshold j The corresponding health status, statistics of the health status of all evaluation indicators of each key component; S32, determining the health status of each key component based on the status of all evaluation indicators of each key component; S33 , sorting the health statuses of all key components of each auxiliary device according to priority, and selecting the health status with the highest priority as the first health status of the auxiliary device.

3. The multi-dimensional diagnostic and evaluation method for auxiliary equipment of a pumped storage power station according to claim 2, characterized in that: The step S32 specifically includes: Determining whether the states of all evaluation indicators of the key component are all normal; if so, determining that the state of the key component is normal; Otherwise, determining whether three or more of the states of all evaluation indicators of the key component are in a dangerous state, and if so, determining that the health state of the key component is dangerous; Otherwise, determining whether any of the states of all evaluation indicators of the key component is in a dangerous state, and if so, determining that the health state of the key component is abnormal; Otherwise, it is determined whether any of the states of all evaluation indicators of the key component is in a caution or abnormal state. If so, the health state of the key component is determined to be caution.

4. The multi-dimensional diagnostic and evaluation method for auxiliary equipment of a pumped storage power station according to claim 1, characterized in that: The step S4 specifically includes: determining whether the fault diagnosis data contains a first-level fault, and if so, determining that the second health state of the auxiliary device is dangerous; otherwise, determining whether the fault diagnosis data has a secondary fault, and if so, determining that the second health state of the auxiliary device is abnormal; otherwise, determining whether the fault diagnosis data contains a level 3 fault; if so, determining whether the auxiliary device has had a level 3 fault three times or more; if so, determining that the second health state of the auxiliary device is abnormal; otherwise, determining that the second health state of the auxiliary device is caution; If the fault diagnosis data does not contain a level 3 fault, determining that the second health state of the auxiliary device is normal; A health state with the highest priority between the first health state and the second health state of each auxiliary device is selected as the health state of the auxiliary device.

5. The multi-dimensional diagnostic and evaluation method for auxiliary equipment of a pumped storage power station according to claim 2 or 4, characterized in that: The priorities are ranked as follows: Dangerous over Abnormal, Abnormal over Caution, Caution over Normal.

6. A multi-dimensional diagnostic and evaluation device for auxiliary equipment of a pumped storage power station, adopting the multi-dimensional diagnostic and evaluation method for auxiliary equipment of a pumped storage power station according to any one of claims 1 to 5, characterized in that: include: a hierarchical analysis module configured to establish an evaluation index and a grade of each evaluation index for each key component of each auxiliary equipment in the pumped storage power station, collect operating data of each key component of each auxiliary equipment, evaluate each evaluation index of each key component during operation based on the operating data, the evaluation index and the grade, determine the degree of membership of each key component to the grade of each evaluation index, and obtain a fuzzy relationship matrix; a fuzzy evaluation module configured to determine the weight of each evaluation indicator and obtain a fuzzy comprehensive evaluation result vector of each key component according to the fuzzy relationship matrix and the weight; a single device evaluation module configured to determine the health status of each key component according to the fuzzy comprehensive evaluation result vector, and determine a first health status of each auxiliary device according to the health status of all key components of each auxiliary device by priority; The comprehensive evaluation module is configured to obtain fault diagnosis data of each auxiliary equipment in the equipment system of the pumped-storage power station, determine the second health state of each auxiliary equipment based on the fault diagnosis data, and obtain the health state of each auxiliary equipment through priority determination based on the first health state and the second health state.

7. An electronic device comprising: one or more processors; a storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 5 is implemented.

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