Method, device, equipment and storage medium for predicting operating status of electrical equipment

Abstract

The present disclosure discloses a method, apparatus, device and storage medium for predicting the operating status of electrical equipment, which relates to the field of computer technology, and in particular to the field of artificial intelligence technology such as deep learning and big data. The specific implementation scheme is: obtaining the historical operating status parameters of the target electrical equipment; obtaining a reference data set according to the type of the target electrical equipment, wherein the reference data set includes the operating status parameters of multiple reference electrical equipment in various periods; determining the operating status of the target electrical equipment according to the historical operating status parameters of the target electrical equipment and the operating status parameters of the multiple reference electrical equipment in various periods. Therefore, the electrical data of the target electrical equipment can be predicted based on the operating status parameters of the target electrical equipment and the reference electrical equipment in various periods, taking into account the historical data of the equipment and the development laws of the same type and family of equipment, so that personalized early warning of equipment failures can be given.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technology, in particular to the field of artificial intelligence technologies such as deep learning and big data, and specifically to a method, apparatus, device and storage medium for predicting the operating status of electrical equipment. Background Art

[0002] With the rapid development of the power industry and the expansion of the power grid, higher requirements are placed on the safe operation and power supply reliability of the power system. Therefore, ensuring the reliable operation of equipment in the power system is directly related to the safety and stability of the power system.

[0003] Currently, the operating status of equipment is primarily determined by its importance in the system and its inherent failure rate. Furthermore, to ensure reliable power system operation, it is often desirable to understand the progress of insulation aging in equipment to facilitate appropriate equipment maintenance and avoid prolonged power outages caused by sudden failures. Determining the operating status of equipment is a pressing issue. Summary of the Invention

[0004] The present disclosure provides a method, apparatus, device, and storage medium for predicting the operating status of electrical equipment.

[0005] According to a first aspect of the present disclosure, a method for predicting an operating state of an electrical device is provided, comprising:

[0006] Obtain historical operating status parameters of target electrical equipment;

[0007] Acquire a reference data set according to the type of the target electrical device, wherein the reference data set includes operating status parameters of a plurality of reference electrical devices at various periods;

[0008] The operating state of the target electrical device is determined according to the historical operating state parameters of the target electrical device and the operating state parameters of the plurality of reference electrical devices at various periods.

[0009] According to a second aspect of the present disclosure, there is provided a device for predicting the operating status of an electrical device, comprising:

[0010] A first acquisition module is used to obtain historical operating status parameters of the target electrical equipment;

[0011] A second acquisition module is configured to acquire a reference data set according to the type of the target electrical device, wherein the reference data set includes operating status parameters of a plurality of reference electrical devices at various periods;

[0012] The determination module is configured to determine the operating state of the target electrical device according to the historical operating state parameters of the target electrical device and the operating state parameters of the plurality of reference electrical devices at various periods.

[0013] According to a third aspect of the present disclosure, a computer device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method described in the first aspect is implemented.

[0014] The fourth embodiment of the present disclosure proposes a non-temporary computer-readable storage medium storing a computer program, which, when executed by a processor, implements the method proposed in the first embodiment of the present disclosure.

[0015] The fifth embodiment of the present disclosure provides a computer program product. When an instruction processor in the computer program product executes the method provided in the first embodiment of the present disclosure, the method provided in the first embodiment of the present disclosure is executed.

[0016] In the disclosed embodiment, the device first obtains historical operating status parameters of a target electrical device. Then, based on the type of the target electrical device, it obtains a reference data set, where the reference data set includes operating status parameters of multiple reference electrical devices at various time periods. The device then determines the operating status of the target electrical device based on the historical operating status parameters of the target electrical device and the operating status parameters of the multiple reference electrical devices at various time periods. Thus, based on the operating status parameters of the target electrical device and the reference electrical devices at various time periods, and taking into account the historical data of the device and the development trends of similar-type and family devices, the device's electrical data can be predicted, thereby providing personalized early warning of equipment failures.

[0017] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present disclosure, nor are they intended to limit the scope of the present disclosure. Other features of the present disclosure will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings are provided to facilitate a better understanding of the present invention and do not constitute a limitation of the present disclosure.

[0019] Figure 1 A flow chart of a method for predicting the operating status of electrical equipment provided in one embodiment of the present disclosure;

[0020] Figure 2 A flowchart of a method for predicting the operating status of electrical equipment provided by another embodiment of the present disclosure;

[0021] Figure 3 A schematic flow chart of a method for predicting the operating status of an electrical device provided by another embodiment of the present disclosure;

[0022] Figure 4 This is a structural block diagram of a device for predicting the operating status of electrical equipment provided by an embodiment of the present disclosure;

[0023] Figure 5 The block diagram is a block diagram of an electronic device used to implement the method for predicting the operating status of an electrical device according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0024] The following description of exemplary embodiments of the present disclosure is made in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding. These details should be considered as merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0025] The present disclosure provides a method for predicting the operating status of an electrical device. This method can be executed by a device for predicting the operating status of an electrical device provided by the present disclosure, or by an electronic device provided by the present disclosure, wherein the electronic device may include but is not limited to terminal devices such as desktop computers and tablet computers, or may be a server. The following uses a device for predicting the operating status of an electrical device provided by the present disclosure to execute a method for predicting the operating status of an electrical device provided by the present disclosure, and this is not intended to limit the present disclosure, and is hereinafter referred to as a "device."

[0026] The following describes in detail the method, device, computer device and storage medium for predicting the operating status of electrical equipment provided by the present disclosure with reference to the accompanying drawings.

[0027] Figure 1 It is a flowchart of a method for predicting the operating status of electrical equipment according to an embodiment of the present disclosure.

[0028] like Figure 1 As shown, the method for predicting the operating status of electrical equipment may include the following steps:

[0029] Step 101: Acquire historical operating status parameters of a target electrical device.

[0030] The target electrical equipment may be an electrical equipment to be predicted, which may be a generator, a transformer, a circuit breaker, etc., which is not limited here.

[0031] Among them, the historical operating status parameters can be the operating status parameters of previous periods corresponding to the target electrical equipment. For example, if the target electrical equipment is a generator, the operating status parameters can be the insulation resistance data, leakage current data, partial discharge data, DC resistance data, dielectric loss data, capacitance data, etc. of the generator, which are not limited here.

[0032] It should be noted that a test database for each electrical device may be pre-established, wherein the test database may be a data set containing various types of electrical test data for each electrical device and other data obtained through analysis and calculation.

[0033] Step 102 : Acquire a reference data set according to the type of the target electrical device, wherein the reference data set includes operating status parameters of a plurality of reference electrical devices at various periods.

[0034] The type of the target electrical equipment may be voltage level, cooling method, purpose, winding, etc., which are not limited here.

[0035] The operating status parameters of each period may refer to the operating status parameters of the target electrical equipment in previous years or previous months, which are not limited here.

[0036] The reference electrical device may be an electrical device of the same type as the target electrical device, and the reference data set may be a collection of data sets of different periods established for the same type of electrical device.

[0037] Specifically, according to the type of the current target electrical device, the operating status parameters of various reference electrical devices of the same type as the target electrical device may be obtained from the test database.

[0038] Step 103 : determining the operating state of the target electrical device according to the historical operating state parameters of the target electrical device and the operating state parameters of a plurality of reference electrical devices at various periods.

[0039] Optionally, if the operating status parameters of the current target electrical equipment are the same as or close to the operating status parameters of any reference electrical equipment in each period, for example, the difference is less than a preset threshold, then the electrical test data of the reference electrical equipment at the same operating time can be used as a reference, or the operating status parameters of the reference electrical equipment can be used as the operating status parameters of the target electrical equipment in the current period.

[0040] For example, if the operating status parameters of the current target electrical equipment A in the past four years were 12%, 22%, 32%, and 40%, respectively, and the operating status parameters of the reference electrical equipment B in the past six years were 11%, 22%, 33%, 39%, 15%, and 26%, respectively, since the operating status parameters of the target electrical equipment and the reference electrical equipment in the first four years are slightly different, less than 1%, it can be considered that the current target electrical equipment and the reference electrical equipment may have the same aging process, and therefore the operating status parameter of 15% of the reference electrical equipment in the 5th year can be used as the predicted value of the target electrical equipment in the 5th year, without limitation here.

[0041] It should be noted that, based on the current operating status parameters of the target electrical equipment, the device can determine whether the target electrical equipment is currently operating normally. For example, a threshold value for the operating status parameter can be set. If the current operating status parameter exceeds the threshold value, it indicates that the target electrical equipment is currently operating poorly and may be faulty or damaged. This can provide a timely warning to personnel, thereby facilitating the rational arrangement of unit maintenance and technical improvements.

[0042] In the disclosed embodiment, the device first obtains historical operating status parameters of a target electrical device. Then, based on the type of the target electrical device, it obtains a reference data set, where the reference data set includes operating status parameters of multiple reference electrical devices at various time periods. The device then determines the operating status of the target electrical device based on the historical operating status parameters of the target electrical device and the operating status parameters of the multiple reference electrical devices at various time periods. Thus, based on the operating status parameters of the target electrical device and the reference electrical devices at various time periods, and taking into account the historical data of the device and the development trends of similar-type and family devices, the device's electrical data can be predicted, thereby providing personalized early warning of equipment failures.

[0043] Figure 2 It is a flowchart of a method for predicting the operating status of electrical equipment according to another embodiment of the present disclosure.

[0044] like Figure 2 As shown, the method for predicting the operating status of electrical equipment may include the following steps:

[0045] Step 201: Acquire initial operating state parameter values ​​and safety thresholds of target electrical equipment.

[0046] The initial operating state parameter value may be the initial value of the operating state parameter of the current target electrical device, and may also be understood as a basic value. It is understood that if the current target electrical device is at the initial state parameter value, no loss occurs temporarily.

[0047] It should be noted that due to factors such as design and installation, the electrical equipment of some units has a worse foundation than the same type of electrical equipment, so the initial operating status parameter values ​​of the electrical equipment are calibrated.

[0048] The safety threshold may be the minimum value required by the standard of the current target electrical device. That is, if the state parameter value of the current target electrical device is lower than the safety threshold, it is in a fault or damage state.

[0049] Step 202 : determining the operation change rate of the target electrical equipment in each period according to the initial operation state parameter value, the safety threshold value and the historical operation state data.

[0050] The historical operating status data may be measured values ​​of electrical data of the target electrical equipment at various time periods. For example, if the target electrical equipment is a generator, the insulation resistance values ​​of the generator at various time periods may be obtained. The operating rate of change of the insulation resistance value, such as the insulation resistance drop rate, may then be calculated, although this is not limited here.

[0051] Optionally, the running rate of change can be calculated using the following formula:

[0052]

[0053] Among them, Az is the safety threshold, A0 is the initial operating state parameter value, A i % is the operating change rate in the i-th year, A i % is the operating status data of the i-th year.

[0054] For example, taking the insulation resistance of a generator as an example, if Az is 10000MΩ, A0 is 20000MΩ, A i If the insulation resistance is 12000MΩ, the insulation resistance decrease rate in year i can be calculated as 20% according to the above formula.

[0055] It should be noted that in the disclosed embodiments, the aforementioned operating change rate is also referred to as the operating status parameter. Using the above formula, the operating change rate of each electrical device at various time periods can be determined, thereby establishing a dataset of the operating status parameters of each electrical device, thereby providing data support for subsequent predictions of the changing trends of the electrical devices.

[0056] Step 203: Acquire an initial data set, wherein the initial data set includes operating status parameters of various types of electrical equipment at various periods.

[0057] The initial data set may be a data set containing operating status parameters of various types of electrical equipment at various periods, that is, raw data, which may be directly measured and recorded data and is not limited here.

[0058] Step 204 : extracting reference electrical equipment of the same type as the target electrical equipment from the initial data set, and operating status parameters of the reference electrical equipment at various time periods.

[0059] Among them, the reference electrical equipment can be an electrical equipment of the same type as the current target electrical equipment. By obtaining the operating status parameters of the reference electrical equipment in various periods, data support can be provided for subsequent comparison of the operating rules between the current target electrical equipment and the reference electrical equipment.

[0060] Step 205 : Obtain the operation change rates of the target electrical device and multiple reference electrical devices in various periods.

[0061] It should be noted that the operating change rates of the target electrical equipment and the reference electrical equipment in each period can be extracted from their corresponding operating status parameters, thereby providing data support for the subsequent prediction of the operating change rate of the target electrical equipment in the current period.

[0062] For example, if the current target device is A, the operating status parameters corresponding to the target electrical device can be A1%, A2%, A3%, A4%.....A i %. If the current reference electrical equipment is B, the operating status parameters corresponding to the current reference electrical equipment can be B1%, B2%, B3%, B4%.....B i %, no restriction is imposed here.

[0063] Step 206 : determining a first weight according to the operation change rate of the target electrical device in the first period and the operation change rates of multiple reference electrical devices in the first period, wherein the first period is an initial operation period in each period.

[0064] The first period may be the initial operation period in each period, such as the first year, first month, or first quarter after the target electrical equipment is put into use, and is not limited here.

[0065] The first weight may be determined according to the operating change rates of the target electrical device and the reference electrical device in the first period.

[0066] Optionally, the first weight λ may be calculated using the following formula:

[0067]

[0068] Among them, V1% is the operation change rate of multiple reference electrical equipment in the first period, and A1% is the operation change rate of the current target electrical equipment in the first period.

[0069] Step 207, determining the current operation change rate of the target electrical device based on the first weight, the operation change rate of the target electrical device in each period, and the operation change rate of multiple reference electrical devices in the second period, wherein the second period is the first k cycles in each period, and k is a specified positive integer.

[0070] The second period may be the first k periods extracted from each period. For example, if the current target electrical equipment has been in operation for 8 years, the second period may be 3 years, that is, the first 3 years starting from the first year.

[0071] Optionally, the operating change rate of the target electrical equipment in the current period can be calculated using the following formula:

[0072] η=1-λ

[0073]

[0074] Among them, Vn is the operating change rate of the nth reference electrical equipment in the second period, Ai is the operating change rate of the current target electrical equipment in the i-th year, Ai+1% is the operating change rate in the current period, and η is the second weight.

[0075] Step 208 : determining the operating state of the target electrical device according to the current operating change rate of the target electrical device.

[0076] It should be noted that based on the current operating rate of change of the target electrical equipment, the device can determine whether the target electrical equipment is currently operating normally. For example, a threshold for the operating rate of change can be set. If the current operating rate of change exceeds the threshold, it indicates that the target electrical equipment is currently operating poorly and may be experiencing a failure or damage. This can provide a timely warning to personnel, thereby facilitating the rational arrangement of unit maintenance and technical improvements.

[0077] In an embodiment of the present disclosure, the apparatus first obtains an initial operating state parameter value and a safety threshold of a target electrical device, determines an operating change rate of the target electrical device in each period based on the initial operating state parameter value, the safety threshold, and historical operating state data, then obtains an initial data set, wherein the initial data set includes operating state parameters of various types of electrical devices in each period, extracts reference electrical devices of the same type as the target electrical device from the initial data set, and the operating state parameters of the reference electrical devices in each period, then obtains the operating change rates of the target electrical device and multiple reference electrical devices in each period, determines a first weight based on the operating change rate of the target electrical device in a first period and the operating change rates of multiple reference electrical devices in the first period, wherein the first period is the initial operating period of each period, and finally determines the operating state of the target electrical device based on the current operating change rate of the target electrical device. Thus, by integrating the data of multiple reference electrical devices and performing index calculations, the electrical data of the target electrical device can be predicted by comprehensively considering the historical data of the device and the development patterns of devices of the same type and family, thereby providing personalized early warning of equipment failures.

[0078] Figure 3 It is a flowchart of a method for predicting the operating status of electrical equipment according to another embodiment of the present disclosure.

[0079] like Figure 3 As shown, the method for predicting the operating status of electrical equipment may include the following steps:

[0080] Step 301: Acquire historical operating status parameters of a target electrical device.

[0081] Step 302 : Acquire a reference data set according to the type of the target electrical device, wherein the reference data set includes operating status parameters of a plurality of reference electrical devices at various periods.

[0082] Step 303 : determining the operating state of the target electrical device according to the historical operating state parameters of the target electrical device and the operating state parameters of a plurality of reference electrical devices at various periods.

[0083] It should be noted that the specific implementation of steps 301 , 302 , and 303 may refer to any of the above embodiments, and this disclosure will not elaborate on them here.

[0084] Step 304: Obtain the operation change rate of the target electrical equipment in each period.

[0085] Step 305 : determining the remaining life of the target electrical equipment according to the maximum value of the operation change rate of the target electrical equipment in each period.

[0086] After the operating status of the target electrical equipment is obtained, the remaining life of the target electrical equipment may be calculated based on the change rate of the target electrical equipment in each period.

[0087] Alternatively, the remaining life μ of the target electrical equipment can be calculated using the following formula:

[0088]

[0089] It should be noted that by calculating the maximum value of the operating change rate of the target electrical equipment in each period, the minimum remaining life of the target electrical equipment, that is, the remaining safe operating time, can be predicted. It can be understood that if the current operating time of the target electrical equipment exceeds the remaining life, it means that the current target electrical equipment may be in an aging state and is prone to failure or damage, and needs to be inspected and rectified to ensure electrical safety.

[0090] In the disclosed embodiment, the device first obtains the historical operating status parameters of the target electrical equipment, and then obtains a reference data set based on the type of the target electrical equipment, wherein the reference data set includes the operating status parameters of multiple reference electrical equipment in various periods. Then, based on the historical operating status parameters of the target electrical equipment and the operating status parameters of multiple reference electrical equipment in various periods, the operating status of the target electrical equipment is determined, and the operating change rate of the target electrical equipment in various periods is obtained. Finally, based on the maximum value of the operating change rate of the target electrical equipment in various periods, the remaining life of the target electrical equipment is determined. Thus, by predicting the remaining life of the target electrical equipment, the safe operating range of the equipment can be predicted, so as to reasonably arrange the unit maintenance and technical transformation work and improve safety.

[0091] In order to implement the above embodiments, the present disclosure also proposes a device for predicting the operating status of electrical equipment.

[0092] Figure 4 A schematic diagram of the structure of a device for predicting the operating status of electrical equipment provided by an embodiment of the present disclosure.

[0093] like Figure 4 As shown, the device 400 for predicting the operating status of an electrical device may include: a first acquisition module 410 , a second acquisition module 420 , and a determination module 430 .

[0094] The first acquisition module 410 is configured to acquire historical operating status parameters of a target electrical device.

[0095] The second acquisition module 420 is configured to acquire a reference data set according to the type of the target electrical device, wherein the reference data set includes operating status parameters of a plurality of reference electrical devices at various periods.

[0096] The determination module 430 is configured to determine the operating status of the target electrical device according to the historical operating status parameters of the target electrical device and the operating status parameters of the plurality of reference electrical devices at various periods.

[0097] Optionally, the second acquisition module is specifically configured to:

[0098] Acquiring an initial data set, wherein the initial data set includes operating status parameters of various types of electrical equipment at various periods;

[0099] Reference electrical equipment of the same type as the target electrical equipment and operating status parameters of the reference electrical equipment at various periods are extracted from the initial data set.

[0100] Optionally, the first acquisition module is specifically configured to:

[0101] Obtaining initial operating state parameter values ​​and safety thresholds of the target electrical equipment;

[0102] The operation change rate of the target electrical equipment in each period is determined according to the initial operation state parameter value, the safety threshold value and the historical operation state parameter.

[0103] Optionally, the determining module is specifically configured to:

[0104] Obtaining the operation change rates of the target electrical device and the plurality of reference electrical devices in various periods;

[0105] determining a first weight according to an operation change rate of the target electrical device in a first period and an operation change rate of the plurality of reference electrical devices in the first period, wherein the first period is an initial operation period among the periods;

[0106] determining a current operation change rate of the target electrical device according to the first weight, the operation change rate of the target electrical device in each of the periods, and the operation change rates of the multiple reference electrical devices in a second period, wherein the second period is the first i periods of each of the periods, and i is a specified positive integer;

[0107] The operating state of the target electrical device is determined according to a current operating change rate of the target electrical device.

[0108] Optionally, the second acquisition module is further configured to:

[0109] Obtaining the operating change rate of the target electrical equipment in each of the periods;

[0110] The remaining life of the target electrical equipment is determined according to the maximum value of the operation change rate of the target electrical equipment in each period.

[0111] In the disclosed embodiment, the device first obtains historical operating status parameters of a target electrical device. Then, based on the type of the target electrical device, it obtains a reference data set, where the reference data set includes operating status parameters of multiple reference electrical devices at various time periods. The device then determines the operating status of the target electrical device based on the historical operating status parameters of the target electrical device and the operating status parameters of the multiple reference electrical devices at various time periods. Thus, based on the operating status parameters of the target electrical device and the reference electrical devices at various time periods, and taking into account the historical data of the device and the development trends of similar-type and family devices, the device's electrical data can be predicted, thereby providing personalized early warning of equipment failures.

[0112] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0113] Figure 5 A schematic block diagram of an example electronic device 500 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are provided as examples only and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0114] like Figure 5 As shown, the device 500 includes a computing unit 501, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 502 or a computer program loaded from a storage unit 505 into a random access memory (RAM) 503. Various programs and data required for the operation of the device 500 can also be stored in the RAM 503. The computing unit 501, the ROM 502, and the RAM 503 are connected to each other via a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.

[0115] Various components in device 500 are connected to I / O interface 505, including: an input unit 506, such as a keyboard, mouse, etc.; an output unit 507, such as various types of displays, speakers, etc.; a storage unit 508, such as a magnetic disk, optical disk, etc.; and a communication unit 509, such as a network card, modem, wireless communication transceiver, etc. The communication unit 509 allows device 500 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0116] The computing unit 501 can be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 501 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units that run machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 501 performs the various methods and processes described above, such as the method for predicting the operating state of an electrical device. For example, in some embodiments, the method for predicting the operating state of an electrical device can be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 508. In some embodiments, part or all of the computer program can be loaded and / or installed on the device 500 via the ROM 502 and / or the communication unit 509. When the computer program is loaded into the RAM 503 and executed by the computing unit 501, one or more steps of the method for predicting the operating state of the electrical device described above can be performed. Alternatively, in other embodiments, the computing unit 501 may be configured to execute the method for predicting the operating status of the electrical device in any other appropriate manner (for example, by means of firmware).

[0117] Various embodiments of the systems and techniques described herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system-on-chip systems (SOCs), programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0118] The program code for implementing the method of the present disclosure can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device so that when the program code is executed by the processor or controller, the functions / operations specified in the flow chart and / or block diagram are implemented. The program code can be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0119] In the context of the present disclosure, a machine-readable medium can be a tangible medium that can contain or store a program for use by or in conjunction with an instruction execution system, device or equipment. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium can include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0120] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0121] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), the Internet, and a blockchain network.

[0122] A computer system may include a client and a server. The client and server are generally remote from each other and typically interact via a communication network. This client-server relationship is established by computer programs running on the respective computers, establishing a client-server relationship. The server may be a cloud server, also known as a cloud computing server or cloud host, a host product within the cloud computing service ecosystem that addresses the management difficulties and limited scalability of traditional physical hosts and VPS services ("Virtual Private Servers" or simply "VPS"). The server may also be a server in a distributed system or a server integrated with blockchain.

[0123] In the disclosed embodiment, the device first obtains historical operating status parameters of a target electrical device. Then, based on the type of the target electrical device, it obtains a reference data set, where the reference data set includes operating status parameters of multiple reference electrical devices at various time periods. The device then determines the operating status of the target electrical device based on the historical operating status parameters of the target electrical device and the operating status parameters of the multiple reference electrical devices at various time periods. Thus, based on the operating status parameters of the target electrical device and the reference electrical devices at various time periods, and taking into account the historical data of the device and the development trends of similar-type and family devices, the device's electrical data can be predicted, thereby providing personalized early warning of equipment failures.

[0124] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in this disclosure can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved. This is not a limitation herein.

[0125] The above specific embodiments do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure shall be included within the scope of protection of this disclosure.

Claims

1. A method for predicting the operating status of electrical equipment, characterized in that: include: Obtain historical operating status parameters of target electrical equipment; Acquire a reference data set according to the type of the target electrical device, wherein the reference data set includes operating status parameters of a plurality of reference electrical devices at various periods; determining the operating state of the target electrical device according to the historical operating state parameters of the target electrical device and the operating state parameters of the plurality of reference electrical devices at various periods; The determining the operating state of the target electrical device according to the historical operating state parameters of the target electrical device and the operating state parameters of the plurality of reference electrical devices at various periods includes: Obtaining the operation change rates of the target electrical device and the plurality of reference electrical devices in various periods; determining a first weight according to an operation change rate of the target electrical device in a first period and an operation change rate of the plurality of reference electrical devices in the first period, wherein the first period is an initial operation period among the periods; determining a current operation change rate of the target electrical device according to the first weight, the operation change rate of the target electrical device in each of the periods, and the operation change rates of the multiple reference electrical devices in a second period, wherein the second period is the first k cycles of each of the periods, and k is a specified positive integer; The operating state of the target electrical device is determined according to a current operating change rate of the target electrical device.

2. The method according to claim 1, wherein The acquiring of a reference data set according to the type of the target electrical equipment includes: Acquiring an initial data set, wherein the initial data set includes operating status parameters of various types of electrical equipment at various periods; Reference electrical equipment of the same type as the target electrical equipment and operating status parameters of the reference electrical equipment at various periods are extracted from the initial data set.

3. The method according to claim 1, wherein The step of obtaining historical operating status parameters of the target electrical equipment includes: Obtaining initial operating state parameter values ​​and safety thresholds of the target electrical equipment; The operation change rate of the target electrical equipment in each period is determined according to the initial operation state parameter value, the safety threshold value and the historical operation state parameter.

4. The method according to any one of claims 1 to 3, wherein After obtaining a reference data set according to the type of the target electrical device, the method further includes: Obtaining the operating change rate of the target electrical equipment in each of the periods; The remaining life of the target electrical equipment is determined according to the maximum value of the operation change rate of the target electrical equipment in each period.

5. A device for predicting the operating status of electrical equipment, characterized in that: include: A first acquisition module is used to obtain historical operating status parameters of the target electrical equipment; A second acquisition module is configured to acquire a reference data set according to the type of the target electrical device, wherein the reference data set includes operating status parameters of a plurality of reference electrical devices at various periods; a determination module, configured to determine the operating state of the target electrical device based on the historical operating state parameters of the target electrical device and the operating state parameters of the plurality of reference electrical devices at various periods; The determining module is specifically configured to: Obtaining the operation change rates of the target electrical device and the plurality of reference electrical devices in various periods; determining a first weight according to an operation change rate of the target electrical device in a first period and an operation change rate of the plurality of reference electrical devices in the first period, wherein the first period is an initial operation period among the periods; determining a current operation change rate of the target electrical device according to the first weight, the operation change rate of the target electrical device in each of the periods, and the operation change rates of the multiple reference electrical devices in a second period, wherein the second period is the first i cycles of each of the periods, and i is a specified positive integer; The operating state of the target electrical device is determined according to a current operating change rate of the target electrical device.

6. The device according to claim 5, characterized in that The second acquisition module is specifically configured to: Acquiring an initial data set, wherein the initial data set includes operating status parameters of various types of electrical equipment at various periods; Reference electrical equipment of the same type as the target electrical equipment and operating status parameters of the reference electrical equipment at various periods are extracted from the initial data set.

7. The device according to claim 5, characterized in that The first acquisition module is specifically configured to: Obtaining initial operating state parameter values ​​and safety thresholds of the target electrical equipment; The operation change rate of the target electrical equipment in each period is determined according to the initial operation state parameter value, the safety threshold value and the historical operation state parameter.

8. The device according to any one of claims 5 to 7, characterized in that The second acquisition module is further configured to: Obtaining the operating change rate of the target electrical equipment in each of the periods; The remaining life of the target electrical equipment is determined according to the maximum value of the operation change rate of the target electrical equipment in each period.

9. An electronic device comprising: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 4.

10. A non-transitory computer-readable storage medium storing computer instructions, wherein: The computer instructions are used to cause the computer to execute the method according to any one of claims 1 to 4.

11. A computer program product, characterized in that The invention comprises a computer program which, when executed by a processor, implements the method according to any one of claims 1 to 4.

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