CN113760992A - Method, device, equipment and storage medium for predicting running state of electrical equipment - Google Patents
Method, device, equipment and storage medium for predicting running state of electrical equipment Download PDFInfo
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Abstract
The invention discloses a method, a device, equipment and a storage medium for predicting the running state of electrical equipment, and relates to the technical field of computers, in particular to the technical fields of artificial intelligence such as deep learning and big data. The specific implementation scheme is as follows: acquiring historical operating state parameters of target electrical equipment; acquiring a reference data set according to the type of the target electrical equipment, wherein the reference data set comprises operating state parameters of a plurality of reference electrical equipment at each period; and determining the operation state of the target electrical equipment according to the historical operation state parameters of the target electrical equipment and the operation state parameters of the plurality of reference electrical equipment in each period. Therefore, the electrical data of the target electrical equipment can be predicted according to the running state parameters of the target electrical equipment and the reference electrical equipment in each period by comprehensively considering the historical data of the equipment and the development rules of the same family equipment of the same type, so that the equipment fault can be pre-warned individually.
Description
Technical Field
The disclosure relates to the technical field of computers, in particular to the technical field of artificial intelligence such as deep learning and big data, and specifically relates to a method, a device, equipment and a storage medium for predicting an operating state of electrical equipment.
Background
With the rapid development of the power industry and the expansion of the power grid scale, higher requirements are made on the safe operation and the power supply reliability of the power system. Therefore, reliable operation of equipment in the power system is determined, and the safety and the stability of the power system are directly related.
The operation state of the current equipment is mainly determined according to the importance degree of the equipment in the system, the failure rate of the equipment and the like. On the other hand, in order to ensure reliable operation of the power system, it is often desirable to know the insulation aging process of the equipment in the power system so as to reasonably overhaul the equipment, and avoid long-time power failure caused by sudden failure. How to determine the running state of the equipment is a problem which needs to be solved urgently at present.
Disclosure of Invention
The present disclosure provides a method, apparatus, device, and storage medium for prediction of an operating state of an electrical device.
According to a first aspect of the present disclosure, there is provided a method for predicting an operating state of an electrical device, including:
acquiring historical operating state parameters of target electrical equipment;
acquiring a reference data set according to the type of the target electrical equipment, wherein the reference data set comprises operating state parameters of a plurality of reference electrical equipment at each period;
and determining the operation state of the target electrical equipment according to the historical operation state parameters of the target electrical equipment and the operation state parameters of the plurality of reference electrical equipment in each period.
According to a second aspect of the present disclosure, there is provided an apparatus for predicting an operating state of an electrical device, including:
the first acquisition module is used for acquiring the historical operating state parameters of the target electrical equipment;
the second acquisition module is used for acquiring a reference data set according to the type of the target electrical equipment, wherein the reference data set comprises the operation state parameters of a plurality of reference electrical equipment at each period;
and the determining module is used for determining the operating state of the target electrical equipment according to the historical operating state parameters of the target electrical equipment and the operating state parameters of the plurality of reference electrical equipment in each period.
According to a third aspect of the present disclosure, there is provided a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the method of the first aspect when executing the program.
A fourth aspect of the present disclosure is directed to a non-transitory computer-readable storage medium storing a computer program, which when executed by a processor implements the method as set forth in the first aspect of the present disclosure.
A fifth aspect of the present disclosure provides a computer program product, which when executed by an instruction processor performs the method provided in the first aspect of the present disclosure.
The device in the embodiment of the disclosure firstly obtains the historical operating state parameters of the target electrical equipment, then obtains a reference data set according to the type of the target electrical equipment, wherein the reference data set comprises the operating state parameters of a plurality of reference electrical equipment in each period, and then determines the operating state of the target electrical equipment according to the historical operating state parameters of the target electrical equipment and the operating state parameters of the plurality of reference electrical equipment in each period. Therefore, the electrical data of the target electrical equipment can be predicted according to the running state parameters of the target electrical equipment and the reference electrical equipment in each period by comprehensively considering the historical data of the equipment and the development rules of the same family equipment of the same type, so that the equipment fault can be pre-warned individually.
It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.
Drawings
The drawings are included to provide a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:
fig. 1 is a schematic flowchart illustrating a method for predicting an operating state of an electrical device according to an embodiment of the present disclosure;
fig. 2 is a schematic flowchart of a method for predicting an operating state of an electrical device according to another embodiment of the present disclosure;
fig. 3 is a flowchart illustrating a method for predicting an operating state of an electrical device according to another embodiment of the present disclosure;
fig. 4 is a block diagram illustrating a configuration of a device for predicting an operating state of an electrical device according to an embodiment of the present disclosure;
fig. 5 is a block diagram of an electronic device for implementing a prediction method of an operating state of an electrical device according to an embodiment of the present disclosure.
Detailed Description
Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, in which various details of the embodiments of the disclosure are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
The method for predicting the operating state of the electrical device provided by the present disclosure may be executed by the apparatus for predicting the operating state of the electrical device provided by the present disclosure, and may also be executed by the electronic device provided by the present disclosure, where the electronic device may include, but is not limited to, a terminal device such as a desktop computer, a tablet computer, and the like, and may also be a server, and the method for predicting the operating state of the electrical device provided by the present disclosure is executed by the apparatus for predicting the operating state of the electrical device provided by the present disclosure, and is not limited by the present disclosure, and is hereinafter simply referred to as "apparatus".
The following describes in detail a method, an apparatus, a computer device, and a storage medium for predicting an operating state of an electrical device according to the present disclosure with reference to the accompanying drawings.
Fig. 1 is a flowchart illustrating a method for predicting an operating state of an electrical device according to an embodiment of the present disclosure.
As shown in fig. 1, the method for predicting the operating state of the electrical device may include the steps of:
The target electrical device may be an electrical device to be predicted, which may be a generator, a transformer, a circuit breaker, and the like, and is not limited herein.
For example, if the target electrical device is a generator, the operating state parameter may be insulation resistance data, leakage current data, partial discharge data, direct current resistance data, dielectric loss data, capacitance data, and the like of the generator, and is not limited herein.
It should be noted that a test database for each electrical device may be established in advance, where the test database may be a data set containing electrical test data of each type of each electrical device and other analysis and calculation data.
The type of the target electrical device may be a voltage level, a cooling method, a use, a winding, and the like, and is not limited herein.
The operating state parameter of each time period may refer to an operating state parameter of the target electrical device in each previous year or an operating state parameter of each previous month, and is not limited herein.
Wherein the reference electrical device may be the same type of electrical device as the target electrical device, and the reference data set may be a set of data sets for respective periods established for the same type of electrical device.
Specifically, according to the type of the current target electrical device, the operating state parameters of each reference electrical device of the same type as the target electrical device may be obtained from the test database.
And 103, determining the operation state of the target electrical equipment according to the historical operation state parameters of the target electrical equipment and the operation state parameters of the plurality of reference electrical equipment at each period.
Optionally, if the current operating state parameter of the target electrical device is the same as or close to the operating state parameter of any reference electrical device in each period, for example, the difference is smaller than a preset threshold, the electrical test data of the reference electrical device in the same operating time may be used as a reference, or the operating state parameter of the reference electrical device may be used as the operating state parameter of the target electrical device in the current period.
For example, if the operating state parameters of the current target electrical device a in the past four years are 12%, 22%, 32%, and 40%, respectively, and the operating state parameters of the reference electrical device B in the past six years are 11%, 22%, 33%, 39%, 15%, and 26%, respectively, it is considered that the current target electrical device and the reference electrical device may have the same aging process because the operating state parameters of the target electrical device and the reference electrical device in the previous four years are different by less than 1%, and therefore, the operating state parameter 15% of the reference electrical device in the 5 th year may be used as the predicted value of the target electrical device in the 5 th year, which is not limited herein.
It should be noted that, according to the current operating state parameter of the target electrical device, the apparatus may determine whether the current target electrical device is in a normal operating state. For example, a threshold value of the operation state parameter may be set, and if the current operation state parameter exceeds the threshold value, it indicates that the current operation state of the target electrical device is not good, and a fault or a damage may occur, so that an early warning may be timely performed on a worker, and therefore, the maintenance and technical improvement work of the unit can be reasonably arranged.
The device in the embodiment of the disclosure firstly obtains the historical operating state parameters of the target electrical equipment, then obtains a reference data set according to the type of the target electrical equipment, wherein the reference data set comprises the operating state parameters of a plurality of reference electrical equipment in each period, and then determines the operating state of the target electrical equipment according to the historical operating state parameters of the target electrical equipment and the operating state parameters of the plurality of reference electrical equipment in each period. Therefore, the electrical data of the target electrical equipment can be predicted according to the running state parameters of the target electrical equipment and the reference electrical equipment in each period by comprehensively considering the historical data of the equipment and the development rules of the same family equipment of the same type, so that the equipment fault can be pre-warned individually.
Fig. 2 is a flowchart illustrating a method for predicting an operating state of an electrical device according to another embodiment of the present disclosure.
As shown in fig. 2, the method for predicting the operating state of the electrical device may include the steps of:
The initial operating state parameter value may be an initial value of the operating state parameter of the current target electrical device, or may be understood as a basic value. It will be appreciated that if the current target electrical device is at the initial state parameter value, no loss occurs for a while.
It should be noted that, because the design, installation, and other factors of some electrical devices of the unit are worse than the electrical devices of the same type, the initial operating state parameter values of the electrical devices are calibrated.
The safety threshold may be a minimum value required by the current standard of the target electrical device, that is, if the current status parameter value of the target electrical device is lower than the safety threshold, the target electrical device is in a fault or damaged state.
The historical operating state data may be measured values of electrical data of the target electrical device at previous periods. For example, if the target electrical device is a generator, the insulation resistance value of the generator at each time may be obtained. Further, an operating rate of change of the insulation resistance value, such as an insulation resistance decrease rate, may then be calculated, without limitation.
Alternatively, the operational rate of change may be calculated by the following formula:
wherein Az is a safety threshold, A0For initial operating state parameter values, Ai% is the operating rate of change in the i-th year, Ai% is the operating state data of the i-th year.
For example, taking the insulation resistance of the generator as an example, if Az is 10000M Ω, A0Is 20000M omega, AiAt 12000 M.OMEGA, the insulation resistance degradation rate in year i can be calculated to be 20% according to the above formula.
It should be noted that, in the embodiment of the present disclosure, the operation change rate is also an operation state parameter. Through the above formula, the operation change rate of each electrical device in each period can be determined, and thus a data set about the operation state parameters of each electrical device can be established, so as to provide data support for predicting the change trend of the electrical device later.
The initial data set may be a data set including operating state parameters of each type of electrical equipment at each time period, that is, raw data, which may be directly measured and recorded data, and is not limited herein.
The reference electrical equipment can be the same type of electrical equipment as the current target electrical equipment, and data support can be provided for later comparison of the operation rule between the current target electrical equipment and the reference electrical equipment by obtaining the operation state parameters of the reference electrical equipment at each period.
In step 205, the operation change rates of the target electrical device and the plurality of reference electrical devices at each period are obtained.
The operation state parameters corresponding to the target electrical device and the reference electrical device may be extracted to obtain the operation change rate of each corresponding period, so as to provide data support for predicting the operation change rate corresponding to the target electrical device at the current period.
For example, if the current target device is a, the operating state parameter corresponding to the target electrical device may be a1％，A2％，A3％，A4％.....Ai% of the total weight of the composition. If the current reference electrical device is B, the operating state parameter corresponding to the current reference electrical device may be B1％，B2％，B3％，B4％.....Bi%, is not limited herein.
And step 206, determining a first weight according to the operation change rate of the target electrical equipment in the first period and the operation change rates of the plurality of reference electrical equipment in the first period, wherein the first period is the initial operation period in each period.
The first time period may be an initial operation time period of each time period, such as the first year, the first month, and the first quarter of the time when the target electrical device is put into use, which is not limited herein.
Wherein the first weight may be determined according to the target electrical device and an operation change rate of the reference electrical device during the first period.
Alternatively, the first weight λ may be calculated by the following formula:
wherein, V1% is the operation change rate of the plurality of reference electrical devices in the first period, and A1% is the operation change rate of the current target electrical device in the first period.
And step 207, determining the current operation change rate of the target electrical equipment according to the first weight, the operation change rate of the target electrical equipment in each period and the operation change rates of the multiple reference electrical equipments in a second period, wherein the second period is the first k periods in each period, and k is a designated positive integer.
The second period may be the first k periods extracted from each period, for example, if the current target electrical device operates for 8 years, the second period may be 3 years, that is, the first 3 years from the 1 st year.
Alternatively, the operation change rate of the target electrical device at the current time may be calculated by the following formula:
η＝1-λ
where Vn is the operation change rate of the nth reference electrical equipment in the second period, Ai is the operation change rate of the current target electrical equipment in the ith year, Ai + 1% is the operation change rate of the current period, and η is the second weight.
And step 208, determining the operation state of the target electrical equipment according to the current operation change rate of the target electrical equipment.
It should be noted that, according to the current operation change rate of the target electrical device, the apparatus may determine whether the current target electrical device is in a normal operation state. For example, a threshold value of the operation change rate may be set, and if the current operation change rate exceeds the threshold value, it indicates that the current operation state of the target electrical device is not good, and a fault or a damage may occur, so that an early warning may be timely performed on a worker, and therefore, the maintenance and technical improvement work of the unit can be reasonably arranged.
In the disclosed embodiment, the apparatus first obtains an initial operating state parameter value and a safety threshold value of a target electrical device, determines an operating change rate of the target electrical device at each period according to the initial operating state parameter value, the safety threshold value and historical operating state data, then obtains an initial data set, wherein the initial data set comprises the operating state parameters of each type of electrical device at each period, extracts a reference electrical device belonging to the same type as the target electrical device and the operating state parameters of the reference electrical device at each period from the initial data set, obtains the operating change rates of the target electrical device and a plurality of reference electrical devices at each period, determines a first weight according to the operating change rate of the target electrical device at a first period and the operating change rates of the plurality of reference electrical devices at the first period, the first period is an initial operation period in each period, and finally, the operation state of the target electrical equipment is determined according to the current operation change rate of the target electrical equipment. Therefore, by fusing the data of multiple reference electrical equipment and performing index calculation, the development rules of historical equipment data and the same-type family equipment can be comprehensively considered, and the electrical data of the target electrical equipment can be predicted, so that the equipment fault can be pre-warned individually.
Fig. 3 is a flowchart illustrating a method for predicting an operating state of an electrical device according to another embodiment of the present disclosure.
As shown in fig. 3, the method for predicting the operating state of the electrical device may include the steps of:
It should be noted that, for the specific implementation of steps 301, 302, and 303, reference may be made to any of the above embodiments, and this disclosure is not repeated herein.
And step 304, acquiring the operation change rate of the target electrical equipment in each period.
After the operating state of the target electrical device is acquired, the remaining life of the target electrical device may also be calculated from the rate of change of the target electrical device at each period.
Alternatively, the remaining life μ of the target electrical device may be calculated by the following formula:
it should be noted that, by calculating the maximum value of the operation change rate of the target electrical device at each period, the minimum remaining life of the target electrical device, that is, the remaining safe operation time, may be predicted, and it is understood that, if the current operation time of the target electrical device exceeds the remaining life, it indicates that the current target electrical device may be in an aged state, and is prone to malfunction or damage, and needs to be repaired and modified to ensure electrical safety.
The device in the embodiment of the disclosure firstly obtains a historical operating state parameter of a target electrical device, then obtains a reference data set according to a type to which the target electrical device belongs, wherein the reference data set comprises operating state parameters of a plurality of reference electrical devices in each period, then determines an operating state of the target electrical device according to the historical operating state parameter of the target electrical device and the operating state parameters of the plurality of reference electrical devices in each period, then obtains an operating change rate of the target electrical device in each period, and finally determines a remaining life of the target electrical device according to a maximum value of the operating change rate of the target electrical device in each period. Therefore, the equipment operation safety interval can be predicted by predicting the residual service life of the target electrical equipment, so that the unit overhaul and technical improvement work can be reasonably arranged, and the safety is improved.
In order to implement the above embodiments, the present disclosure further provides a device for predicting an operating state of an electrical device.
Fig. 4 is a schematic structural diagram of a device for predicting an operating state of an electrical device according to an embodiment of the present disclosure.
As shown in fig. 4, the apparatus 400 for predicting the operating state of the electrical device may include: a first obtaining module 410, a second obtaining module 420, and a determining module 430.
The first obtaining module 410 is configured to obtain a historical operating state parameter of the target electrical device.
The second obtaining module 420 is configured to obtain a reference data set according to a type to which the target electrical device belongs, where the reference data set includes operating state parameters of a plurality of reference electrical devices at each time period.
The determining module 430 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 each period.
Optionally, the second obtaining module is specifically configured to:
acquiring an initial data set, wherein the initial data set comprises operating state parameters of various types of electrical equipment in various periods;
and extracting the reference electrical equipment with the same type as the target electrical equipment from the initial data set and the operating state parameters of the reference electrical equipment at each period.
Optionally, the first obtaining module is specifically configured to:
acquiring an initial operation state parameter value and a safety threshold value of the target electrical equipment;
and 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 parameter.
Optionally, the determining module is specifically configured to:
acquiring operation change rates of the target electrical equipment and the plurality of reference electrical equipment in each period;
determining a first weight according to the operation change rate of the target electrical equipment in a first period and the operation change rates of the plurality of reference electrical equipment in the first period, wherein the first period is an initial operation period in each period;
determining the current operation change rate of the target electrical equipment according to the first weight, the operation change rate of the target electrical equipment in each period and the operation change rate of the plurality of reference electrical equipment in a second period, wherein the second period is the first i periods in each period, and i is a designated positive integer;
and determining the operation state of the target electrical equipment according to the current operation change rate of the target electrical equipment.
Optionally, the second obtaining module is further configured to:
acquiring the operation change rate of the target electrical equipment in each period;
and determining the residual life of the target electrical equipment according to the maximum value of the operation change rate of the target electrical equipment in each period.
The device in the embodiment of the disclosure firstly obtains the historical operating state parameters of the target electrical equipment, then obtains a reference data set according to the type of the target electrical equipment, wherein the reference data set comprises the operating state parameters of a plurality of reference electrical equipment in each period, and then determines the operating state of the target electrical equipment according to the historical operating state parameters of the target electrical equipment and the operating state parameters of the plurality of reference electrical equipment in each period. Therefore, the electrical data of the target electrical equipment can be predicted according to the running state parameters of the target electrical equipment and the reference electrical equipment in each period by comprehensively considering the historical data of the equipment and the development rules of the same family equipment of the same type, so that the equipment fault can be pre-warned individually.
The present disclosure also provides an electronic device, a readable storage medium, and a computer program product according to embodiments of the present disclosure.
FIG. 5 illustrates a schematic block diagram of an example electronic device 500 that can be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the disclosure described and/or claimed herein.
As shown in fig. 5, the apparatus 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. In the RAM 503, various programs and data required for the operation of the device 500 can also be stored. The calculation unit 501, the ROM 502, and the RAM 503 are connected to each other by a bus 504. An input/output (I/O) interface 505 is also connected to bus 504.
A number of components in the device 500 are connected to the I/O interface 505, including: an input unit 506 such as a keyboard, a mouse, or the like; an output unit 507 such as various types of displays, speakers, and the like; a storage unit 508, such as a magnetic disk, optical disk, or the like; and a communication unit 509 such as a network card, modem, wireless communication transceiver, etc. The communication unit 509 allows the device 500 to exchange information/data with other devices through a computer network such as the internet and/or various telecommunication networks.
The computing unit 501 may be a variety of general-purpose and/or special-purpose processing components having 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 running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, and so forth. The calculation unit 501 executes the respective methods and processes described above, such as the prediction method of the operating state of the electrical device. For example, in some embodiments, the method of predicting an operating state of an electrical device may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as storage unit 508. In some embodiments, part or all of the computer program may be loaded and/or installed onto 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 an operating state of an electrical device described above may be performed. Alternatively, in other embodiments, the calculation unit 501 may be configured by any other suitable means (e.g. by means of firmware) to perform the prediction method of the electrical device operating state.
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), system on a chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
Program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, 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 disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here 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 a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, 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 may be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, 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: local Area Networks (LANs), Wide Area Networks (WANs), the internet, and blockchain networks.
The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The Server can be a cloud Server, also called a cloud computing Server or a cloud host, and is a host product in a cloud computing service system, so as to solve the defects of high management difficulty and weak service expansibility in the traditional physical host and VPS service ("Virtual Private Server", or simply "VPS"). The server may also be a server of a distributed system, or a server incorporating a blockchain.
The device in the embodiment of the disclosure firstly obtains the historical operating state parameters of the target electrical equipment, then obtains a reference data set according to the type of the target electrical equipment, wherein the reference data set comprises the operating state parameters of a plurality of reference electrical equipment in each period, and then determines the operating state of the target electrical equipment according to the historical operating state parameters of the target electrical equipment and the operating state parameters of the plurality of reference electrical equipment in each period. Therefore, the electrical data of the target electrical equipment can be predicted according to the running state parameters of the target electrical equipment and the reference electrical equipment in each period by comprehensively considering the historical data of the equipment and the development rules of the same family equipment of the same type, so that the equipment fault can be pre-warned individually.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present disclosure may be executed in parallel, sequentially, or in different orders, as long as the desired results of the technical solutions disclosed in the present disclosure can be achieved, and the present disclosure is not limited herein.
The above detailed description should not be construed as limiting the scope of the disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present disclosure should be included in the scope of protection of the present disclosure.
Claims (13)
1. A method for predicting an operating state of an electrical device, comprising:
acquiring historical operating state parameters of target electrical equipment;
acquiring a reference data set according to the type of the target electrical equipment, wherein the reference data set comprises operating state parameters of a plurality of reference electrical equipment at each period;
and determining the operation state of the target electrical equipment according to the historical operation state parameters of the target electrical equipment and the operation state parameters of the plurality of reference electrical equipment in each period.
2. The method of claim 1, wherein said obtaining a reference data set according to a type to which the target electrical device belongs comprises:
acquiring an initial data set, wherein the initial data set comprises operating state parameters of various types of electrical equipment in various periods;
and extracting the reference electrical equipment with the same type as the target electrical equipment from the initial data set and the operating state parameters of the reference electrical equipment at each period.
3. The method of claim 1, wherein the obtaining of the historical operating state parameters of the target electrical device comprises:
acquiring an initial operation state parameter value and a safety threshold value of the target electrical equipment;
and 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 parameter.
4. The method of claim 1, wherein determining the operating state of the target electrical device based on historical operating state parameters of the target electrical device and operating state parameters of the plurality of reference electrical devices at various times comprises:
acquiring operation change rates of the target electrical equipment and the plurality of reference electrical equipment in each period;
determining a first weight according to the operation change rate of the target electrical equipment in a first period and the operation change rates of the plurality of reference electrical equipment in the first period, wherein the first period is an initial operation period in each period;
determining the current operation change rate of the target electrical equipment according to the first weight, the operation change rate of the target electrical equipment in each period and the operation change rate of the plurality of reference electrical equipment in a second period, wherein the second period is the first k periods in each period, and k is a designated positive integer;
and determining the operation state of the target electrical equipment according to the current operation change rate of the target electrical equipment.
5. The method according to any one of claims 1-4, further comprising, after obtaining a reference data set according to a type to which the target electrical device belongs:
acquiring the operation change rate of the target electrical equipment in each period;
and determining the residual life of the target electrical equipment according to the maximum value of the operation change rate of the target electrical equipment in each period.
6. An apparatus for predicting an operating state of an electrical device, comprising:
the first acquisition module is used for acquiring the historical operating state parameters of the target electrical equipment;
the second acquisition module is used for acquiring a reference data set according to the type of the target electrical equipment, wherein the reference data set comprises the operation state parameters of a plurality of reference electrical equipment at each period;
and the determining module is used for determining the operating state of the target electrical equipment according to the historical operating state parameters of the target electrical equipment and the operating state parameters of the plurality of reference electrical equipment in each period.
7. The apparatus of claim 6, wherein the second obtaining module is specifically configured to:
acquiring an initial data set, wherein the initial data set comprises operating state parameters of various types of electrical equipment in various periods;
and extracting the reference electrical equipment with the same type as the target electrical equipment from the initial data set and the operating state parameters of the reference electrical equipment at each period.
8. The apparatus of claim 6, wherein the first obtaining module is specifically configured to:
acquiring an initial operation state parameter value and a safety threshold value of the target electrical equipment;
and 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 parameter.
9. The apparatus of claim 6, wherein the determination module is specifically configured to:
acquiring operation change rates of the target electrical equipment and the plurality of reference electrical equipment in each period;
determining a first weight according to the operation change rate of the target electrical equipment in a first period and the operation change rates of the plurality of reference electrical equipment in the first period, wherein the first period is an initial operation period in each period;
determining the current operation change rate of the target electrical equipment according to the first weight, the operation change rate of the target electrical equipment in each period and the operation change rate of the plurality of reference electrical equipment in a second period, wherein the second period is the first i periods in each period, and i is a designated positive integer;
and determining the operation state of the target electrical equipment according to the current operation change rate of the target electrical equipment.
10. The apparatus of any of claims 6-9, wherein the second obtaining module is further configured to:
acquiring the operation change rate of the target electrical equipment in each period;
and determining the residual life of the target electrical equipment according to the maximum value of the operation change rate of the target electrical equipment in each period.
11. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-5.
12. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of any one of claims 1-5.
13. A computer program product, characterized in that it comprises a computer program which, when being executed by a processor, carries out the method of any one of claims 1-5.
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|---|---|---|---|
| CN202110866997.9A CN113760992A (en) | 2021-07-29 | 2021-07-29 | Method, device, equipment and storage medium for predicting running state of electrical equipment |
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| CN202110866997.9A CN113760992A (en) | 2021-07-29 | 2021-07-29 | Method, device, equipment and storage medium for predicting running state of electrical equipment |
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| CN202110866997.9A Pending CN113760992A (en) | 2021-07-29 | 2021-07-29 | Method, device, equipment and storage medium for predicting running state of electrical equipment |
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| CN (1) | CN113760992A (en) |
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