Diagnostic system and method for electric equipment generating reverse electric quantity at night

Abstract

The invention provides a diagnosis system and method for electric equipment generating reverse electric quantity at night. The method comprises the following steps: acquiring an electric energy meter operation log and an electric equipment operation log; extracting feature information of reverse electric quantity based on the running log of the electric energy meter; determining abnormal associated feature information of the electric equipment based on the feature information of the reverse electric quantity and the operation log of the electric equipment; and inputting the abnormal associated feature information of the electric equipment into a pre-selected constructed reverse electric quantity equipment identification model for identification, and if the diagnosis result of the electric equipment shows that reverse electric quantity is generated, outputting prompt information, so that real-time and accurate monitoring and early warning of the electric equipment are realized, and the power utilization safety management level is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of electricity consumption monitoring, and in particular to a diagnosis system and method for electrical equipment that generates reverse power at night. Background Art

[0002] In power systems, energy meters are used to measure the amount of electricity consumed by electrical equipment. Under normal circumstances, energy meters record the positive active energy consumed by the equipment. However, in unusual situations such as leakage, equipment failure, or illegal electricity use, energy meters may instead record the reverse flow of electricity generated by the equipment. This reverse flow is particularly noticeable at night, when electricity consumption is low, yet it can pose a serious safety hazard.

[0003] At present, the existing electricity meter abnormality monitoring technology has shortcomings in monitoring the reverse power generated by electrical equipment at night, making it difficult to achieve real-time and accurate monitoring and early warning.

[0004] Therefore, it is necessary to develop a special diagnostic system and method for electrical equipment that generates reverse power at night to improve the level of electricity safety management. Summary of the Invention

[0005] The present invention provides a diagnostic system and method for electrical equipment that generates reverse power at night, so as to address the shortcomings of the existing technology in monitoring the reverse power generated by electrical equipment at night, making it difficult to achieve real-time and accurate monitoring and early warning, resulting in a low level of electricity safety management.

[0006] In one aspect, the present invention provides a method for diagnosing an electrical device that generates reverse power at night, comprising: Obtain the operation logs of electricity meters and electrical equipment; Extracting characteristic information of reverse power based on the electric energy meter operation log; Determining abnormality-related characteristic information of the electric device based on the characteristic information of the reverse power and the operation log of the electric device; Inputting the abnormal correlation feature information of the electric device into a pre-selected reverse electric quantity device identification model for identification, thereby obtaining a diagnosis result of the electric device; If the diagnosis result of the electrical device indicates that reverse power is generated, a prompt message is output.

[0007] According to a method for diagnosing an electrical device that generates reverse power at night, the present invention provides a plurality of characteristic information of the reverse power. Determining abnormality-related characteristic information of the electric device based on the characteristic information of the reverse power and the operation log of the electric device includes: Based on the time resolution of the time series of the electric energy meter operation log, convert the electric device operation log to obtain the time series of the electric device operation log; Based on the characteristic information of the plurality of reverse electric quantities and their respective weights, the distance value between the reverse electric quantity event at the i-th time point in the time series of the electric energy meter operation log and the electric device operation log at the j-th time point in the time series of the electric device operation log is determined. ; 1≤i≤N, 1≤j≤M, N is the length of the time series of the electricity meter operation log, N is the length of the time series of the electrical equipment operation log; Based on the time series of the electricity meter operation log and the time series of the electrical equipment operation log, a cumulative distance matrix is ​​constructed. ; Based on the distance value , a preset dynamic time adjustment algorithm and a preset constraint path slope, to determine the cumulative distance matrix The global minimum distance of Based on the minimum distance and the cumulative distance matrix, a correlation score between the electric device and the reverse power event is determined as abnormal correlation feature information of the electric device.

[0008] According to the present invention, a method for diagnosing electrical equipment that generates reverse power at night is provided, wherein the characteristic information of the reverse power includes the reverse power period, the reverse power duration, the reverse power frequency distribution, and the current distortion rate of the reverse power; Based on the characteristic information of the plurality of reverse electric quantities and their respective weights, the distance value between the reverse electric quantity event at the i-th time point in the time series of the electric energy meter operation log and the electric device operation log at the j-th time point in the time series of the electric device operation log is determined. ,include: Determine the time period distance between the reverse power event at the i-th time point and the operation log of the electric device at the j-th time point based on the reverse power period corresponding to the i-th time point and the time period corresponding to the j-th time point; Determine the duration distance between the reverse power event at the i-th time point and the operation log of the electric device at the j-th time point based on the reverse power duration corresponding to the i-th time point and the duration corresponding to the j-th time point; Determine the frequency distribution distance between the reverse power event at the i-th time point and the power operation log at the j-th time point based on the reverse power frequency distribution corresponding to the i-th time point and the power frequency distribution corresponding to the j-th time point; Determine, based on the current distortion rate corresponding to the i-th time point and the current distortion rate corresponding to the j-th time point, a current distortion rate distance between the reverse power event at the i-th time point and the operation log of the electric device at the j-th time point; Perform weighted summation on the time period distance, the duration distance, the frequency distribution distance and the current distortion rate distance to obtain the distance value .

[0009] According to a method for diagnosing an electrical device that generates reverse power at night, the present invention provides a method for determining, based on the reverse power period corresponding to the i-th time point and the time period corresponding to the j-th time point, a time period distance between the reverse power event at the i-th time point and the operation log of the electrical device at the j-th time point, including: Calculating a first absolute difference between a reverse power period corresponding to the i-th time point and a period corresponding to the j-th time point; The ratio of the first absolute difference to the preset number of nighttime minutes is calculated as the time period distance.

[0010] According to a method for diagnosing an electrical device that generates reverse power at night, the present invention provides a method for determining the duration distance between the reverse power event at the i-th time point and the operation log of the electrical device at the j-th time point based on the reverse power duration corresponding to the i-th time point and the duration corresponding to the j-th time point, including: The reverse power duration corresponding to the i-th time point and the duration corresponding to the j-th time point are input into a preset Gaussian kernel function for calculation to obtain the duration distance.

[0011] According to a method for diagnosing an electrical device that generates reverse power at night, the method includes determining, based on the reverse power frequency distribution corresponding to the i-th time point and the power frequency distribution corresponding to the j-th time point, a frequency distribution distance between the reverse power event at the i-th time point and the electrical device operation log at the j-th time point, including: The reverse power frequency distribution corresponding to the i-th time point and the power frequency distribution corresponding to the j-th time point are input into a preset cosine similarity calculation formula for calculation to obtain the frequency distribution distance.

[0012] According to a method for diagnosing an electrical device that generates reverse power at night, the present invention provides a method for determining, based on the current distortion rate corresponding to the i-th time point and the current distortion rate corresponding to the j-th time point, a current distortion rate distance between the reverse power event at the i-th time point and the electrical device operation log at the j-th time point, including: A second absolute difference between the current distortion rate corresponding to the i-th time point and the current distortion rate corresponding to the j-th time point is calculated as the current distortion rate distance.

[0013] According to the present invention, a method for diagnosing an electrical device that generates reverse power at night, outputting prompt information, includes: Determining the current status of the user, and determining the safety risk level of the electrical equipment based on the operation log of the electrical equipment; If the security risk level is greater than a preset risk level and the user's current state indicates sleeping, triggering an emergency receiving mode of the user's receiving terminal, and outputting the prompt information to the user's receiving terminal in an emergency reminder manner; If the security risk level is greater than a preset risk level and the current state of the user indicates that the user is not asleep, the prompt information is output to the receiving end of the user in a default reminder manner.

[0014] According to the present invention, a method for diagnosing electrical equipment that generates reverse power at night also includes: If the security risk level is less than or equal to the preset risk level, and the current state of the user indicates sleeping, and the receiving terminal of the user is not set to the do not disturb mode, triggering that the receiving terminal of the user is not set to the do not disturb mode, and outputting the prompt information to the receiving terminal of the user in the do not disturb mode; If the security risk level is less than or equal to the preset risk level, and the current state of the user indicates that the user is not asleep, the prompt information is output to the receiving end of the user in a default reminder manner.

[0015] On the other hand, the present invention also provides a method and system for diagnosing electrical equipment that generates reverse power at night, comprising: An acquisition module is used to obtain the operation log of the electric energy meter and the operation log of the electric device, and extract characteristic information of the reverse power based on the operation log of the electric energy meter; a determination module, configured to determine abnormality-related characteristic information of the electric device based on the characteristic information of the reverse power and the operation log of the electric device; an identification module, configured to input abnormality-related characteristic information of the electrical device into a pre-selected reverse electrical quantity device identification model for identification, and obtain a diagnosis result of the electrical device; The output module is used to output a prompt message if the diagnosis result of the electrical device indicates that reverse power is generated.

[0016] On the other hand, the present invention also provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, a method for diagnosing an electrical device that generates reverse power at night as described in any one of the above-mentioned methods is implemented.

[0017] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a method for diagnosing electrical equipment that generates reverse power at night as described in any of the above.

[0018] On the other hand, the present invention further provides a computer program product, comprising a computer program, which, when executed by a processor, implements any of the above-mentioned methods for diagnosing electrical equipment that generates reverse power at night.

[0019] The present invention provides a diagnostic system and method for electrical equipment that generates reverse power at night, which obtains an electric energy meter operation log and an electric equipment operation log; extracts characteristic information of the reverse power based on the electric energy meter operation log; determines abnormal associated characteristic information of the electric equipment based on the characteristic information of the reverse power and the electric equipment operation log; inputs the abnormal associated characteristic information of the electric equipment into a pre-selected reverse power equipment identification model for identification; if the diagnostic result of the electric equipment indicates that reverse power is generated, outputs a prompt message, thereby realizing real-time and accurate monitoring and early warning of the electric equipment and improving the level of electricity safety management. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the present invention or the prior art, a brief introduction is given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0021] Figure 1 This is a flow chart of a method for diagnosing electrical equipment that generates reverse power at night, provided by an embodiment of the present invention; Figure 2 It is a flowchart for determining abnormal correlation characteristic information of electrical equipment; Figure 3 2 is a schematic structural diagram of a diagnostic system for electrical equipment generating reverse power at night, provided by an embodiment of the present invention; Figure 4 It is a structural diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0022] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0023] Figure 1 The figure is a flow chart of a method for diagnosing electrical equipment that generates reverse power at night, provided by an embodiment of the present invention.

[0024] like Figure 1 As shown, the method for diagnosing an electrical device that generates reverse power at night provided by an embodiment of the present invention can be executed by an electronic device. The method mainly includes the following steps: 101. Obtain the operation log of the electricity meter and the operation log of the electrical equipment; In a specific implementation, the electric energy meter has a high-precision metering chip inside that monitors the status of the user's electrical equipment in real time, including voltage, current, etc., measures the forward active electrical energy and reverse active electrical energy in real time, and generates its own operation log. The electrical equipment can record its own operation log through its own functional module, or it can use other smart devices to record its own operation log. Therefore, in this embodiment, the electric energy meter operation log and the electric equipment operation log can be actively obtained, or the electric energy meter operation log and the electric equipment operation log uploaded by the electric energy meter can be received. The data exchange method can include RS485 or power line carrier.

[0025] The specific data interaction process is as follows: a. Setting of night time period: By querying the user's electricity consumption, a specific night time period is set in the electricity consumption information collection system, such as 10 pm to 7 am the next day.

[0026] b. Monitoring data and metering data: The electric energy meter has a minute freezing function. The minute freezing time can be set (for example, 5 minutes). Every 5 minutes, the electric energy meter records the voltage value, current value, reverse active electric energy indication, etc.

[0027] c. Data collection and transmission: The collection terminal collects the monitoring data and metering data of the electric energy meter through RS485 or power line carrier at regular intervals (the time can be set, for example, 10 minutes), and transmits it to the electricity consumption information collection system in the electronic device.

[0028] 102. Extracting characteristic information of reverse power based on the electric energy meter operation log; In a specific implementation, the operation log of the electric energy meter can be analyzed to extract characteristic information of the reverse power, including the reverse power period, reverse power duration, reverse power frequency distribution, and reverse power current distortion rate.

[0029] The process of extracting the reverse power period includes: dividing the time series of the electricity meter operation log into equally spaced windows (for example, 5 minutes / window), extracting the absolute timestamp t of the reverse power occurrence, and treating the window with the absolute timestamp t of the reverse power occurrence as a reverse power period.

[0030] The extraction process of reverse power duration includes: calculating the duration of continuous reverse power events D = t end -t start (in minutes).

[0031] The process of extracting the reverse power frequency distribution includes: performing fast Fourier transform on the reverse current sequence to extract the reverse power frequency distribution.

[0032] The extraction process of the current distortion rate of the reverse power includes: calculating the current distortion rate of the reverse power based on the total harmonic distortion calculation formula. The total harmonic distortion calculation formula is as follows (1): (1) in, The current distortion rate indicating the reverse amount of electricity, Indicates the effective value of the fundamental current, Indicates the effective value of the hth harmonic current.

[0033] 103. Determine abnormality-related characteristic information of the electric device based on the characteristic information of the reverse power and the operation log of the electric device; In a specific implementation process, you can refer to Figure 2 The flowchart shown implements step 103 . Figure 2 It is a flowchart for determining abnormal correlation characteristic information of electrical equipment.

[0034] 201. Convert the electric device operation log based on the time resolution of the time series of the electric energy meter operation log to obtain the time series of the electric device operation log; In a specific implementation process, the time resolution of the time series of the electricity meter operation log is used as a benchmark to convert the electric equipment operation log to obtain the time series of the electric equipment operation log, so as to align the time series of the electricity meter operation log with the time series of the electric equipment operation log at the same time resolution.

[0035] 202. Based on the characteristic information of the plurality of reverse electric quantities and their respective weights, determine the distance value between the reverse electric quantity event at the i-th time point in the time series of the electric energy meter operation log and the electric device operation log at the j-th time point in the time series of the electric device operation log. ; In a specific implementation, 1≤i≤N, 1≤j≤M, N is the length of the time series of the electricity meter operation log, and N is the length of the time series of the electrical equipment operation log. Step 202 can be implemented as follows: a1. Determine the time period distance between the reverse power event at the i-th time point and the operation log of the electric device at the j-th time point based on the reverse power period corresponding to the i-th time point and the time period corresponding to the j-th time point; Specifically, the first absolute difference between the reverse power period corresponding to the i-th time point and the period corresponding to the j-th time point can be calculated; and the ratio of the first absolute difference to the preset number of nighttime minutes can be calculated as the period distance. For details, please refer to calculation formula (2): (2) in, Indicates the time period distance, represents the reverse power period corresponding to the i-th time point, represents the time period corresponding to the j-th time point, Indicates the preset night time minutes.

[0036] In other words, we can use the normalized absolute difference method to measure the time alignment between the reverse power occurrence time and the time when the power-consuming device log status changes. This allows us to map the time difference to the [0, 1] interval, eliminating the influence of time scale and facilitating cross-scenario comparisons.

[0037] b1. Determine the duration distance between the reverse power event at the i-th time point and the operation log of the electric device at the j-th time point based on the reverse power duration corresponding to the i-th time point and the duration corresponding to the j-th time point; In a specific implementation process, the reverse power duration corresponding to the i-th time point and the duration corresponding to the j-th time point can be input into a preset Gaussian kernel function for calculation to obtain the duration distance.

[0038] The expression of the preset Gaussian kernel function can refer to formula (3): (3) in, Indicates the duration distance, Indicates the duration of reverse power corresponding to the i-th time point, represents the duration corresponding to the jth time point, represents the standard deviation of duration.

[0039] In a specific implementation process, this can soften the time difference between the reverse power duration corresponding to the i-th time point and the duration corresponding to the j-th time point, avoiding misjudgment caused by slight time difference.

[0040] c1. Determine the frequency distribution distance between the reverse power event at the i-th time point and the power operation log at the j-th time point based on the reverse power frequency distribution corresponding to the i-th time point and the power frequency distribution corresponding to the j-th time point; Specifically, the reverse power frequency distribution corresponding to the i-th time point and the power frequency distribution corresponding to the j-th time point may be input into a preset cosine similarity calculation formula for calculation to obtain the frequency distribution distance.

[0041] Among them, the cosine similarity calculation formula is formula (4): (4) in, represents the frequency distribution distance, represents the frequency distribution of reverse power corresponding to the i-th time point, Represents the frequency distribution of electricity corresponding to the j-th time point.

[0042] In a specific implementation process, the power frequency distribution describes the energy distribution of the signal at different frequency components. The cosine similarity is independent of the amplitude and can better measure the similarity of the vector direction.

[0043] d1. Determine the current distortion rate distance between the reverse power event at the i-th time point and the operation log of the electrical device at the j-th time point based on the current distortion rate corresponding to the i-th time point and the current distortion rate corresponding to the j-th time point; Specifically, a second absolute difference between the current distortion rate corresponding to the i-th time point and the current distortion rate corresponding to the j-th time point may be calculated as the current distortion rate distance.

[0044] Among them, the calculation formula (5) of the current distortion rate distance is as follows: (5) in, Indicates the current distortion rate distance, represents the current distortion rate corresponding to the i-th time point, Indicates the current distortion rate corresponding to the j-th time point.

[0045] e1. Perform weighted summation on the time period distance, the duration distance, the frequency distribution distance, and the current distortion rate distance to obtain the distance value. .

[0046] In a specific implementation process, the distance value can be calculated according to the following weighted summation formula (6): : (6) in, represents the weight of the time period distance, represents the weight of duration distance, represents the weight of the frequency distribution distance, Indicates the weight of the current distortion rate distance.

[0047] 203. Construct a cumulative distance matrix based on the time series of the electric energy meter operation log and the time series of the electric equipment operation log. ; In a specific implementation process, a cumulative distance matrix can be constructed based on the length of the time series of the electricity meter operation log and the length of the time series of the electrical equipment operation log. .

[0048] 204. Based on the distance value , a preset dynamic time adjustment algorithm and a preset constraint path slope, to determine the cumulative distance matrix The global minimum distance of In a specific implementation process, the constraint path slope can be within [1 / 2, 2], so as to avoid unreasonable alignment. Under this constraint path slope, the cumulative distance matrix can be calculated according to formula (7): The first row and first column of the distance matrix are calculated step by step, and the cumulative distance matrix is ​​finally obtained. The value of the Nth row and Mth column of The global minimum distance.

[0049] (7) in, Represents the cumulative distance matrix The value of the i-th row and j-th column of Represents the value of the i-1th row and jth column after left shift, Represents the value of the i-th row and j-1-th column after moving up, Represents the value in the i-1th row and j-1th column after diagonal shift.

[0050] 205. Based on the minimum distance and the cumulative distance matrix, determine a correlation score between the electric device and the reverse power event as abnormal correlation feature information of the electric device.

[0051] In a specific implementation process, when the cumulative distance matrix is ​​obtained After taking the value of as the minimum distance, the association score between the electric device and the reverse power event can be obtained according to formula (8), which is used as the abnormal association feature information of the electric device.

[0052] (8) in, Indicates the correlation score between the power-consuming device and the reverse power event.

[0053] 104. Inputting the abnormality-related characteristic information of the electric device into a pre-selected reverse electric quantity device identification model for identification, thereby obtaining a diagnosis result of the electric device; In a specific implementation, abnormality-related feature information of an electrical device can be input into a pre-selected reverse power device identification model, and the reverse power device identification model performs identification to obtain a diagnosis result of the electrical device. The diagnosis result of the electrical device can include whether the electrical device generates reverse power or whether the electrical device does not generate reverse power.

[0054] Specifically, the reverse power device identification model can be a support vector machine model, and its corresponding function can be a function of the optimal classification hyperplane. The function formula is shown in formula (9): (9) in, represents the function value of the optimal classification hyperplane, represents the first parameter of the support vector machine model, Represents the second parameter of the support vector machine model.

[0055] In a specific implementation process, the abnormal correlation feature information of the electrical equipment is input into the above calculation formula (9). If the value is less than 0, it can be determined that the electrical equipment generates reverse power. Otherwise, if If the value of is greater than or equal to 0, it can be determined that the electrical device does not generate reverse power, but other electrical devices generate reverse power.

[0056] In a specific implementation process, the process of building the reverse power device identification model includes: a2. Select the sample set {(x1, y1), (x2, y2), ..., (xn, yn)} and divide it into a training set and a test set; where xn represents the abnormal correlation feature information of the sample electrical equipment, and yn represents the category label of the sample electrical equipment; b2. Using the training set, the goal of the support vector machine model is to find an optimal classification hyperplane , so that the interval between the two types of training samples is maximized, and the first model parameter of the support vector machine model is obtained and the second model parameter .

[0057] In a specific implementation process, for the linearly separable case, the optimization objective function is The constraints are: , i=1,2,,,p, where p is the number of samples in the training set. For the case of linear inseparability, a slack variable is introduced , the optimization objective function becomes , C represents the penalty parameter. The constraints are: , , i=1,2,,,p.

[0058] c2. Use the validation set to verify. The validation result indicates that the final first model parameter of the support vector machine model is obtained when the training is stopped. and the second model parameter .

[0059] 105. If the diagnosis result of the electrical device indicates that reverse power is generated, output a prompt message.

[0060] In a specific implementation, if an electrical device generates reverse power, it may cause a safety incident (for example, if the device is powered on for an extended period of time, causing a malfunction and fire, or if the device is aging or high-risk, which may easily cause fire, casualties, or property damage). The safety risk level of the device can be determined based on the device's operation log. For example, the device's current, voltage, operating time, and other information can be obtained from the device's operation log to determine the device's safety risk level.

[0061] In a specific implementation process, the user's current status can be obtained based on relevant data from the user's wearable devices, indoor cameras, smart home devices, etc. The user's current status may include sleeping or not sleeping.

[0062] In a specific implementation, if the security risk level is greater than a preset risk level and the user's current state indicates sleep, then, for the user's safety, an emergency receiving mode can be triggered on the user's receiving terminal, and a prompt message can be output to the user's receiving terminal in the form of an emergency reminder. The user's receiving terminal needs to be authorized before the emergency receiving mode is triggered. The user's receiving terminal will also periodically check whether the emergency receiving mode is authorized. If not, an authorization prompt request will be sent.

[0063] In a specific implementation, if the security risk level is greater than a preset risk level and the user's current state indicates that they are awake, the prompt message is output to the user's receiving terminal in a default prompting manner. In other words, if the user's current state indicates that they are awake, they are generally enabled to receive the message by default. Therefore, the prompt message can be output to the user's receiving terminal in a default prompting manner, and the user can receive the prompt message.

[0064] In a specific implementation process, if the security risk level is less than or equal to the preset risk level, and the current state of the user indicates sleeping, and the receiving end of the user is not set to do not disturb mode, the receiving end of the user is triggered to not set to do not disturb mode, and the prompt information is output to the receiving end of the user in a do not disturb manner. That is to say, if the user is already asleep and does not want to be disturbed, but the receiving end of the user is not set to do not disturb mode, and although the electrical equipment has generated reverse power, the electrical equipment is also relatively safe, at this time, the receiving end of the user can be actively triggered to not set to do not disturb mode, and the prompt information is output to the receiving end of the user in a do not disturb manner, so as to avoid disturbing the user. Similarly, the triggering of the do not disturb mode of the user's receiving end also requires the user's authorization.

[0065] In a specific implementation, if the security risk level is less than or equal to the preset risk level, and the user's current state indicates that they are awake, the prompt message is output to the user's receiving terminal in a default reminder mode. In other words, if the user's current state indicates that they are awake, they are generally enabled to receive the message by default. Therefore, the prompt message can be output to the user's receiving terminal in a default reminder mode, and the user can receive the prompt message.

[0066] The diagnostic method of the electrical equipment that generates reverse power at night in this embodiment obtains the operation log of the electricity meter and the operation log of the electrical equipment; extracts the characteristic information of the reverse power based on the operation log of the electricity meter; determines the abnormal related characteristic information of the electrical equipment based on the characteristic information of the reverse power and the operation log of the electrical equipment; inputs the abnormal related characteristic information of the electrical equipment into a pre-selected and constructed reverse power equipment identification model for identification; if the diagnosis result of the electrical equipment indicates that reverse power is generated, outputs a prompt message, thereby realizing real-time and accurate monitoring and early warning of the electrical equipment and improving the level of electricity safety management.

[0067] Based on the same general inventive concept, the present invention also protects a diagnostic system for electrical equipment that generates reverse electricity at night. The diagnostic system for electrical equipment that generates reverse electricity at night provided by the present invention is described below. The diagnostic system for electrical equipment that generates reverse electricity at night described below and the diagnostic method for electrical equipment that generates reverse electricity at night described above can be referenced to each other.

[0068] Figure 3 FIG. 1 is a schematic diagram of a diagnostic system for electrical equipment generating reverse power at night provided by an embodiment of the present invention. Figure 3 As shown, the diagnostic system for electrical equipment generating reverse power at night in this embodiment includes a structure acquisition module 31 , a determination module 32 , an identification module 33 and an output module 34 .

[0069] The acquisition module 31 is used to obtain the operation log of the electric energy meter and the operation log of the electric device, and extract the characteristic information of the reverse power based on the operation log of the electric energy meter; A determination module 32 is configured to determine abnormality-related characteristic information of the electric device based on the characteristic information of the reverse power and the operation log of the electric device; The identification module 33 is used to input the abnormality-related characteristic information of the electrical device into a pre-selected reverse power device identification model for identification, thereby obtaining a diagnosis result of the electrical device; The output module 34 is configured to output a prompt message if the diagnosis result of the electrical device indicates that reverse power is generated.

[0070] Figure 44 is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. The diagnostic system for electrical equipment that generates reverse power at night may include: a processor (processor) 410, a communications interface (Communications Interface) 420, a memory (memory) 430, and a communication bus 440. The processor 410, the communications interface 420, and the memory 430 communicate with each other via the communication bus 440. The processor 410 can call the logic instructions in the memory 430 to execute the diagnostic method for electrical equipment that generates reverse power at night.

[0071] Furthermore, the logic instructions in the aforementioned memory 430 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product, stored in a storage medium, includes instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, a mobile hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0072] On the other hand, the present invention also provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the diagnostic methods for electrical equipment that generates reverse power at night provided by the above methods.

[0073] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the diagnostic method for electrical equipment that generates reverse power at night provided by the above methods.

[0074] It should be noted that the relevant user personal information that may be involved in the various embodiments of this application is strictly in accordance with the requirements of laws and regulations, follows the principles of legality, legitimacy and necessity, and is based on the reasonable purposes of business scenarios to process personal information that users actively provide during the use of products / services or generated due to the use of products / services, as well as personal information obtained with the user's authorization.

[0075] The user personal information processed by this application will vary depending on the specific product / service scenario and must be based on the specific scenario in which the user uses the product / service. This may involve the user's account information, device information, driving information, vehicle information, or other related information. This application will treat the user's personal information and its processing with a high degree of diligence.

[0076] This application attaches great importance to the security of user personal information and has taken reasonable and feasible security protection measures that comply with industry standards to protect user information and prevent personal information from being accessed, disclosed, used, modified, damaged or lost without authorization.

[0077] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0078] Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented using software plus a necessary general-purpose hardware platform, or of course, hardware. Based on this understanding, the essence of the above technical solution, or the portion that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, or an optical disk, and includes a number of instructions for causing a computer device (such as a personal computer, server, or network device) to execute the methods described in each embodiment or certain portions of the embodiments.

[0079] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A method for diagnosing electrical equipment that generates reverse power at night, characterized in that: include: Obtain the operation logs of electricity meters and electrical equipment; Extracting characteristic information of reverse power based on the electric energy meter operation log; Determining abnormality-related characteristic information of the electric device based on the characteristic information of the reverse power and the operation log of the electric device; Inputting the abnormal correlation feature information of the electric device into a pre-selected reverse electric quantity device identification model for identification, thereby obtaining a diagnosis result of the electric device; If the diagnosis result of the electrical device indicates that reverse power is generated, a prompt message is output.

2. The method for diagnosing electrical equipment that generates reverse power at night according to claim 1, characterized in that: The number of the characteristic information of the reverse power is multiple; Determining abnormality-related characteristic information of the electric device based on the characteristic information of the reverse power and the operation log of the electric device includes: Based on the time resolution of the time series of the electric energy meter operation log, convert the electric device operation log to obtain the time series of the electric device operation log; Based on the characteristic information of the plurality of reverse electric quantities and their respective weights, the distance value between the reverse electric quantity event at the i-th time point in the time series of the electric energy meter operation log and the electric device operation log at the j-th time point in the time series of the electric device operation log is determined. ; 1≤i≤N, 1≤j≤M, N is the length of the time series of the electricity meter operation log, N is the length of the time series of the electrical equipment operation log; Based on the time series of the electricity meter operation log and the time series of the electrical equipment operation log, a cumulative distance matrix is ​​constructed. ; Based on the distance value , a preset dynamic time adjustment algorithm and a preset constraint path slope, to determine the cumulative distance matrix The global minimum distance of Based on the minimum distance and the cumulative distance matrix, a correlation score between the electric device and the reverse power event is determined as abnormal correlation feature information of the electric device.

3. The method for diagnosing electrical equipment that generates reverse power at night according to claim 2, characterized in that: The characteristic information of the reverse power includes the reverse power period, the reverse power duration, the reverse power frequency distribution and the current distortion rate of the reverse power; Based on the characteristic information of the plurality of reverse electric quantities and their respective weights, the distance value between the reverse electric quantity event at the i-th time point in the time series of the electric energy meter operation log and the electric device operation log at the j-th time point in the time series of the electric device operation log is determined. ,include: Determine the time period distance between the reverse power event at the i-th time point and the operation log of the electric device at the j-th time point based on the reverse power period corresponding to the i-th time point and the time period corresponding to the j-th time point; Determine the duration distance between the reverse power event at the i-th time point and the operation log of the electric device at the j-th time point based on the reverse power duration corresponding to the i-th time point and the duration corresponding to the j-th time point; Determine the frequency distribution distance between the reverse power event at the i-th time point and the power operation log at the j-th time point based on the reverse power frequency distribution corresponding to the i-th time point and the power frequency distribution corresponding to the j-th time point; Determine, based on the current distortion rate corresponding to the i-th time point and the current distortion rate corresponding to the j-th time point, a current distortion rate distance between the reverse power event at the i-th time point and the operation log of the electric device at the j-th time point; Perform weighted summation on the time period distance, the duration distance, the frequency distribution distance and the current distortion rate distance to obtain the distance value .

4. The method for diagnosing electrical equipment that generates reverse power at night according to claim 3, characterized in that: Determining, based on the reverse power time period corresponding to the i-th time point and the time period corresponding to the j-th time point, a time period distance between the reverse power event at the i-th time point and the operation log of the electric device at the j-th time point, includes: Calculating a first absolute difference between a reverse power period corresponding to the i-th time point and a period corresponding to the j-th time point; The ratio of the first absolute difference to the preset number of nighttime minutes is calculated as the time period distance.

5. The method for diagnosing electrical equipment that generates reverse power at night according to claim 3, characterized in that: Determining, based on the reverse power duration corresponding to the i-th time point and the duration corresponding to the j-th time point, a duration distance between the reverse power event at the i-th time point and the operation log of the electric device at the j-th time point, includes: The reverse power duration corresponding to the i-th time point and the duration corresponding to the j-th time point are input into a preset Gaussian kernel function for calculation to obtain the duration distance.

6. The method for diagnosing electrical equipment that generates reverse power at night according to claim 3, characterized in that: Determining, based on the reverse power frequency distribution corresponding to the i-th time point and the power frequency distribution corresponding to the j-th time point, a frequency distribution distance between the reverse power event at the i-th time point and the electric device operation log at the j-th time point, including: The reverse power frequency distribution corresponding to the i-th time point and the power frequency distribution corresponding to the j-th time point are input into a preset cosine similarity calculation formula for calculation to obtain the frequency distribution distance.

7. The method for diagnosing electrical equipment that generates reverse power at night according to claim 3, characterized in that: Determining, based on the current distortion rate corresponding to the i-th time point and the current distortion rate corresponding to the j-th time point, a current distortion rate distance between the reverse power event at the i-th time point and the electric device operation log at the j-th time point, including: A second absolute difference between the current distortion rate corresponding to the i-th time point and the current distortion rate corresponding to the j-th time point is calculated as the current distortion rate distance.

8. The method for diagnosing electrical equipment that generates reverse power at night according to any one of claims 1 to 7, characterized in that: Output prompt information, including: Determining the current status of the user, and determining the safety risk level of the electrical equipment based on the operation log of the electrical equipment; If the security risk level is greater than a preset risk level and the user's current state indicates sleeping, triggering an emergency receiving mode of the user's receiving terminal, and outputting the prompt information to the user's receiving terminal in an emergency reminder manner; If the security risk level is greater than a preset risk level and the current state of the user indicates that the user is not asleep, the prompt information is output to the receiving end of the user in a default reminder manner.

9. The method for diagnosing electrical equipment that generates reverse power at night according to claim 8, characterized in that: Also includes: If the security risk level is less than or equal to the preset risk level, and the current state of the user indicates sleeping, and the receiving terminal of the user is not set to the do not disturb mode, triggering that the receiving terminal of the user is not set to the do not disturb mode, and outputting the prompt information to the receiving terminal of the user in the do not disturb mode; If the security risk level is less than or equal to the preset risk level, and the current state of the user indicates that the user is not asleep, the prompt information is output to the receiving end of the user in a default reminder manner.

10. A diagnostic method and system for electrical equipment that generates reverse power at night, characterized in that: include: An acquisition module is used to obtain the operation log of the electric energy meter and the operation log of the electric device, and extract characteristic information of the reverse power based on the operation log of the electric energy meter; a determination module, configured to determine abnormality-related characteristic information of the electric device based on the characteristic information of the reverse power and the operation log of the electric device; an identification module, configured to input abnormality-related characteristic information of the electrical device into a pre-selected reverse electrical quantity device identification model for identification, and obtain a diagnosis result of the electrical device; The output module is used to output a prompt message if the diagnosis result of the electrical device indicates that reverse power is generated.

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