Electric energy meter cover opening electricity stealing detection method and device based on sine sound wave characteristics

Abstract

The invention provides an electric energy meter cover opening electricity stealing detection method and device based on sine sound wave characteristics, and relates to the technical field of electric energy meter detection. The method comprises the following steps: acquiring a sine sound wave signal and an environmental parameter of a to-be-detected electric energy meter in real time, and calculating a sound wave parameter after temperature and humidity compensation based on the change of the sine sound wave signal in combination with the environmental parameter; dynamically calculating a sound wave parameter threshold value based on the environment parameters, the operation time of the to-be-detected electric energy meter and the signal quality of the sine sound wave signal; determining a judgment result of each sound wave parameter based on each sound wave parameter and the corresponding sound wave parameter threshold, and fusing the judgment results of each sound wave parameter by adopting a weighted voting method to obtain a fused judgment result; according to the judgment result of each sound wave parameter and the fusion judgment result, the state of the to-be-detected electric energy meter is determined, and the states include normality, cover opening early warning and cover opening electricity stealing. The detection accuracy can be improved.

Description

Technical Field

[0001] This application relates to the field of electricity meter testing technology, and in particular to a method and device for detecting electricity theft by opening the cover of an electricity meter based on sinusoidal acoustic characteristics. Background Technology

[0002] As the core equipment for electricity metering, the accuracy of electricity meters directly affects the economic interests of power supply companies and users. Opening the meter casing to steal electricity is a common method; the internal metering components or wiring are altered by opening the meter casing, leading to inaccurate meter readings.

[0003] Existing technologies for detecting unlocked devices mainly include mechanical lock detection, photoelectric sensing detection, and vibration detection. Mechanical locks are easily damaged by force and cannot trigger alarms proactively; photoelectric detection relies on the principle of light path obstruction and is easily affected by strong light interference or physical obstruction, causing it to fail; vibration detection is not sensitive enough to slight unlocking behavior and is easily triggered falsely by environmental vibrations. Existing acoustic detection solutions mostly use fixed threshold judgments, which are prone to false judgments due to factors such as sudden temperature changes, instantaneous airflow, and equipment aging. Therefore, there is an urgent need for a device unlocking and electricity theft detection technology that is highly resistant to interference, accurate in detection, and can effectively prevent false judgments. Summary of the Invention

[0004] This application provides a method and device for detecting electricity theft by opening the cover of an electricity meter based on the characteristics of sinusoidal acoustic waves, in order to solve the problems of existing electricity meter opening acoustic wave detection methods being easily interfered with and having a high false judgment rate.

[0005] Firstly, this application provides a method for detecting electricity theft by opening the cover of an energy meter based on sinusoidal acoustic characteristics, including: The system acquires sinusoidal acoustic wave signals and environmental parameters from the energy meter under test in real time. Based on the changes in the sinusoidal acoustic wave signals and the environmental parameters, it calculates the acoustic wave parameters after temperature and humidity compensation. The acoustic wave parameters include the sound wave propagation speed, the sound wave attenuation coefficient, and the sound wave phase difference. The environmental parameters include temperature and humidity. Based on environmental parameters, the running time of the energy meter under test, and the signal quality of the sinusoidal sound wave signal, the sound wave parameter thresholds are dynamically calculated. The sound wave parameter thresholds include the sound wave propagation speed threshold, the sound wave attenuation coefficient threshold, and the sound wave phase difference threshold. Based on each acoustic parameter and its corresponding threshold, the judgment result for each acoustic parameter is determined, and a weighted voting method is used to fuse the judgment results of each acoustic parameter to obtain a fused judgment result. Based on the judgment results of each acoustic parameter and the fusion judgment results, the state of the energy meter to be tested is determined, including normal, cover opening warning, and cover opening for electricity theft.

[0006] Secondly, this application provides a device for detecting electricity theft by opening the cover of an electricity meter based on sinusoidal acoustic characteristics, comprising: The parameter determination module is used to acquire the sinusoidal acoustic wave signal and environmental parameters of the energy meter under test in real time, and calculate the temperature and humidity compensated acoustic wave parameters based on the changes of the sinusoidal acoustic wave signal and the environmental parameters. The acoustic wave parameters include the sound wave propagation speed, the sound wave attenuation coefficient and the sound wave phase difference. The environmental parameters include temperature and humidity. The threshold calculation module is used to dynamically calculate the acoustic wave parameter thresholds based on environmental parameters, the running time of the energy meter under test, and the signal quality of the sinusoidal acoustic wave signal. The acoustic wave parameter thresholds include the acoustic wave propagation speed threshold, the acoustic wave attenuation coefficient threshold, and the acoustic wave phase difference threshold. The result fusion module is used to determine the judgment result of each acoustic parameter based on each acoustic parameter and the corresponding acoustic parameter threshold, and to fuse the judgment results of each acoustic parameter using a weighted voting method to obtain the fused judgment result. The status judgment module is used to determine the status of the energy meter to be tested based on the judgment results of each acoustic parameter and the fused judgment results. The status includes normal, cover opening warning and cover opening for electricity theft.

[0007] This application provides a method and device for detecting electricity theft by opening a cover of an energy meter based on sinusoidal acoustic characteristics. The method involves acquiring sinusoidal acoustic signals from the energy meter under test and environmental parameters in real time. Based on the changes in the sinusoidal acoustic signals and the environmental parameters, temperature and humidity compensated acoustic parameters are calculated. These acoustic parameters include sound wave propagation speed, sound wave attenuation coefficient, and sound wave phase difference. The environmental parameters include temperature and humidity. Based on the environmental parameters, the operating time of the energy meter under test, and the signal quality of the sinusoidal acoustic signals, acoustic parameter thresholds are dynamically calculated. These thresholds include sound wave propagation speed threshold, sound wave attenuation coefficient threshold, and sound wave phase difference threshold. Based on each acoustic parameter and its corresponding threshold, a judgment result for each acoustic parameter is determined. A weighted voting method is used to fuse the judgment results of each acoustic parameter to obtain a fused judgment result. Based on the judgment results of each acoustic parameter and the fused judgment result, the state of the energy meter under test is determined. The state includes normal, cover-opening warning, and cover-opening electricity theft. This application does not rely solely on a single sinusoidal acoustic parameter, but comprehensively calculates multiple acoustic parameters such as acoustic propagation speed, acoustic attenuation coefficient, and acoustic phase difference. Each parameter reflects the state changes of the electricity meter from different perspectives. By combining multiple parameters for judgment, the limitations that may exist with a single parameter are avoided, greatly improving the accuracy of detection. Considering the influence of temperature and humidity on acoustic propagation, this application acquires temperature and humidity information in real time and calculates temperature and humidity compensated acoustic parameters based on the changes in the sinusoidal acoustic signal and temperature and humidity. Through temperature and humidity compensation, the interference of environmental factors on acoustic parameters is eliminated, making the acoustic parameters more accurately reflect the open state of the electricity meter itself, further improving the accuracy of detection. At the same time, the state of the electricity meter under test is determined by combining the judgment results of each acoustic parameter and the fused judgment results, including normal, open-cover warning, and open-cover theft. This multi-dimensional judgment method evaluates the state of the electricity meter from multiple perspectives, avoiding the errors that may exist with a single judgment result. Attached Figure Description

[0008] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0009] Figure 1 This is a schematic diagram of the structure of the electricity meter opening and electricity theft detection system based on sinusoidal acoustic characteristics provided in the embodiments of this application; Figure 2 This is a flowchart illustrating the electricity theft detection method based on sinusoidal acoustic characteristics for electricity meters with open cover provided in an embodiment of this application. Figure 3This is a schematic diagram of the structure of the electricity meter opening and electricity theft detection device based on sinusoidal acoustic characteristics provided in the embodiments of this application. Detailed Implementation

[0010] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0011] To make the objectives, technical solutions, and advantages of this application clearer, the following description will be provided in conjunction with the accompanying drawings and specific embodiments.

[0012] To address the problems of existing methods for detecting electricity theft by opening the meter casing, which are susceptible to interference and have a high false alarm rate, and considering that when the meter casing is sealed, the interior is a stable, static air medium; however, when the casing is opened, the internal medium circulates with the outside air, causing changes in the medium's density, viscosity, and flow velocity, which in turn alter the propagation characteristics of the sinusoidal sound wave signal, this application proposes a method for detecting electricity theft by opening the meter casing based on sinusoidal sound wave characteristics. This method is applied to an electricity theft detection system based on opening the meter casing based on sinusoidal sound wave characteristics.

[0013] Among them, reference Figure 1 As shown, the electricity meter opening and theft detection system based on sinusoidal acoustic wave characteristics includes an electricity meter housing 1, an acoustic wave transmitting module 2, an acoustic wave receiving module 3, a signal processing module 4, an environmental sensing module 5, and a communication module 6.

[0014] The electricity meter housing 1 has a sealed cavity for accommodating the sound wave transmitting module 2, the sound wave receiving module 3, the signal processing module 4, the environmental sensing module 5, and the communication module 6.

[0015] The acoustic wave transmitting module 2 is fixed on the first side wall A inside the energy meter housing 1 and is used to transmit a sinusoidal acoustic wave signal of a preset frequency. A piezoelectric ceramic acoustic wave transmitter can be selected.

[0016] The sound wave receiving module 3 is fixed inside the energy meter housing 1 on the second side wall B opposite to the first side wall A, and is coaxially arranged with the sound wave transmitting module 2. It is used to receive sinusoidal sound wave signals, or a piezoelectric ceramic sound wave receiver can be selected.

[0017] The signal processing module 4 is electrically connected to the sound wave transmitting module 2 and the sound wave receiving module 3 respectively. It includes a signal generator, amplifier, filter, MCU and algorithm processing unit, and is used to control the transmitted signal parameters, process the received signal and execute the anti-false judgment algorithm.

[0018] The environmental sensing module 5 is electrically connected to the signal processing module 4 and includes a temperature sensor (which collects the internal temperature of the electricity meter housing 1) and a humidity sensor (which collects the internal relative humidity of the electricity meter housing 1).

[0019] The communication module 6 is electrically connected to the signal processing module 4 and is used to upload the detection results and equipment status to the electrical monitoring platform. An RS485 or carrier module can be selected.

[0020] Based on the above Figure 1 The energy meter opening and theft detection system shown herein, based on the characteristics of sinusoidal acoustic waves, involves a sound wave transmitting module 2 emitting a sinusoidal acoustic wave signal at a fixed frequency. The signal processing module 4 then extracts the propagation speed, attenuation coefficient, and phase difference parameters of the received sinusoidal acoustic wave signal. These parameters are then compared with baseline parameters using dynamic threshold adjustment, interference identification, and a multi-parameter fusion algorithm to determine whether the meter has been opened for theft. This system utilizes the change in acoustic parameters caused by the change in the internal dielectric properties of the energy meter casing after opening to achieve detection. It exhibits strong anti-interference capabilities, high detection accuracy, and can effectively identify concealed opening and theft of electricity while reducing the false positive rate.

[0021] Figure 2 The implementation flowchart of the electricity meter theft detection method based on sinusoidal acoustic characteristics provided in the embodiments of this application is described in detail below: In step 101, the sinusoidal acoustic wave signal and environmental parameters of the energy meter under test are acquired in real time. Based on the changes in the sinusoidal acoustic wave signal and combined with the environmental parameters, the acoustic wave parameters after temperature and humidity compensation are calculated. The acoustic wave parameters include the sound wave propagation speed, the sound wave attenuation coefficient and the sound wave phase difference. The environmental parameters include temperature and humidity.

[0022] In this embodiment of the application, the sound wave receiving module in the energy meter under test receives the sinusoidal sound wave signal emitted by the sound wave transmitting module in real time, as well as the temperature and humidity collected by the environmental sensing module. Then, based on the propagation characteristics of the sinusoidal sound wave signal, combined with the temperature and humidity, the sound wave propagation speed, sound wave attenuation coefficient and sound wave phase difference of the energy meter under test after temperature and humidity compensation are calculated.

[0023] The signal formula for the sinusoidal sound wave signal emitted by the sound wave emission module is as follows:

[0024] in, The instantaneous value of the sinusoidal acoustic signal output by the acoustic wave emission module is expressed in V. The initial amplitude of the sinusoidal sound wave signal is expressed in V. The initial phase of the sinusoidal sound wave signal is expressed in rad. The fixed frequency of the sinusoidal sound wave signal is measured in Hz. In this embodiment, the value is 40kHz, which is the ultrasonic frequency band and is resistant to environmental noise interference. The time unit is seconds (s).

[0025] This application's embodiments do not rely solely on a single sinusoidal sound wave parameter, but comprehensively calculate multiple sound wave parameters, such as sound wave propagation speed, sound wave attenuation coefficient, and sound wave phase difference. Each parameter reflects the state changes of the energy meter from different perspectives. For example, the sound wave propagation speed may change due to changes in the internal structure of the energy meter (such as changes in the position of internal components caused by opening the cover); the sound wave attenuation coefficient reflects the energy loss of the sound wave during propagation; opening the cover may introduce new media or change the propagation path, thus affecting the attenuation coefficient; the sound wave phase difference also reflects the characteristic changes during sound wave propagation. By comprehensively judging multiple parameters, the limitations that may exist with a single parameter are avoided, greatly improving the accuracy of detection.

[0026] In one possible implementation, after acquiring the sinusoidal acoustic signal from the energy meter under test in real time, the method may further include: The harmonic distortion of the sinusoidal acoustic signal of the energy meter under test is calculated using Fast Fourier Transform. Based on the harmonic distortion, determine whether the sinusoidal sound wave signal of the energy meter under test is contaminated, and remove the contaminated sinusoidal sound wave signal. Accordingly, based on the changes in the sinusoidal sound wave signal and in conjunction with environmental parameters, the calculated sound wave parameters after temperature and humidity compensation can include: Based on the changes in the sinusoidal acoustic signal after harmonic distortion assessment, and combined with environmental parameters, the acoustic parameters after temperature and humidity compensation are calculated.

[0027] Optionally, a bandpass filter is added to the signal processing module, with a center frequency of 40kHz and a bandwidth of ±1kHz. The total harmonic distortion (THD) of the received sinusoidal sound wave signal is calculated using Fast Fourier Transform (FFT), and the THD is used to determine whether the sinusoidal sound wave signal of the energy meter under test is contaminated. Specifically: If the harmonic distortion is greater than or equal to 15%, the current sinusoidal sound wave signal is determined to be contaminated, and the data set is discarded and re-acquired.

[0028] If the harmonic distortion is less than 15%, the current sinusoidal sound signal is determined to be uncontaminated.

[0029] This application employs Fast Fourier Transform (FFT) to calculate the harmonic distortion of the sinusoidal acoustic signal from the energy meter under test, enabling precise quantification of the harmonic content in the signal. In real-world environments, various electromagnetic interference sources may exist around the energy meter, such as the operation of other electrical equipment and electromagnetic radiation from power lines. These interferences can cause harmonic distortion in the sinusoidal acoustic signal, leading to a decrease in signal quality. By calculating the harmonic distortion, it is possible to accurately determine whether the signal is contaminated, providing a reliable basis for subsequent data processing.

[0030] Meanwhile, by eliminating contaminated signals, the likelihood of misjudgments and missed detections due to signal quality issues is reduced. Misjudgments might mistake a normal electricity meter status for unauthorized electricity theft, causing unnecessary trouble for users; missed detections might fail to detect electricity theft in a timely manner, resulting in losses for the power company. This application's embodiments, by accurately judging signal quality and eliminating contaminated signals, effectively avoid both of these situations, improving the system's stability and reliability.

[0031] In one possible implementation, calculating the temperature and humidity compensated sound wave parameters based on changes in the sinusoidal sound wave signal and in conjunction with environmental parameters can include: The speed of sound wave propagation is calculated using temperature and humidity. Calculate the propagation time of a sinusoidal sound wave using the transmission distance and speed of sound. The phase difference of the sound wave is calculated using the sound wave propagation time and the initial and real-time phases of the sinusoidal sound wave signal. The sound wave attenuation coefficient is calculated using the transmission distance, initial amplitude, and real-time sound wave amplitude of the sinusoidal sound wave signal.

[0032] Optionally, the temperature and humidity compensated acoustic parameters in the embodiments of this application include acoustic propagation speed, acoustic attenuation coefficient, and acoustic phase difference.

[0033] The speed of sound propagation is calculated using the formula for the speed of sound propagation. Temperature and humidity are input into the formula to obtain the speed of sound propagation. The formula for the speed of sound propagation is:

[0034] in, The speed of sound is measured in m / s. The speed of sound in air under standard conditions (20℃, 50%RH) is taken as 343m / s; The temperature coefficient of sound speed, in m / (s) ℃); The sound velocity humidity coefficient is expressed in m / (s). %RH); Temperature, in °C; Humidity, expressed in %RH.

[0035] The sound wave attenuation coefficient is calculated using the formula: The transmission distance, initial amplitude, and real-time amplitude of the sinusoidal sound wave signal are input into the formula to obtain the sound wave attenuation coefficient. The formula for calculating the sound wave attenuation coefficient is as follows:

[0036] in, This is the sound wave attenuation coefficient, with units of dB / m; The initial amplitude of the sinusoidal sound wave signal is expressed in V. The real-time acoustic amplitude of the sinusoidal acoustic signal is expressed in V. The transmission distance of the sinusoidal sound wave signal is the straight-line distance between the sound wave transmitting module and the sound wave receiving module, in meters, and is determined by the size of the electricity meter casing. It is a logarithmic function with base 10.

[0037] The sound wave phase difference is calculated using the sound wave phase difference calculation formula. The sound wave propagation time, the initial phase, and the real-time phase of the sinusoidal sound wave signal are input into the formula to obtain the sound wave phase difference. The sound wave phase difference calculation formula is as follows:

[0038] in, The phase difference of the sound waves is expressed in rad. The initial phase of the sinusoidal sound wave signal is expressed in rad. The real-time phase of the sinusoidal sound wave signal is expressed in rad. The sound wave propagation time is expressed in seconds (s). It is a fixed frequency of a sinusoidal sound wave signal, measured in Hz.

[0039] The sound wave propagation time is calculated using the transmission distance and speed of sound of a sinusoidal sound wave signal, specifically as follows:

[0040] The calculation formulas for sound wave propagation speed, phase difference, and attenuation coefficient in this embodiment are concise, clear, and easy to understand and implement. In engineering applications, only the relevant environmental parameters and sound wave signal parameters need to be obtained, and the required sound wave parameters can be quickly calculated by substituting them into the formula. This concise calculation method reduces the difficulty of engineering implementation and improves the development efficiency and maintainability of the detection system.

[0041] In step 102, based on environmental parameters, the running time of the energy meter under test, and the signal quality of the sinusoidal sound wave signal, the sound wave parameter thresholds are dynamically calculated. The sound wave parameter thresholds include the sound wave propagation speed threshold, the sound wave attenuation coefficient threshold, and the sound wave phase difference threshold.

[0042] In this embodiment of the application, the threshold values ​​of the acoustic parameters, namely the acoustic propagation speed threshold, the acoustic attenuation coefficient threshold, and the acoustic phase difference threshold, are dynamically adjusted by using environmental parameters, the running time of the energy meter under test, and the signal quality of the received sinusoidal acoustic signal.

[0043] Specifically, to address environmental fluctuations and equipment aging, the sound wave parameter thresholds are adjusted in real time. This is achieved by calculating the sound wave parameter thresholds using the first formula:

[0044] in, for The threshold of sound wave propagation speed at a given moment. for The threshold of the sound wave attenuation coefficient at time 1. for The threshold of the phase difference of the sound wave at any given time. Let the initial threshold for the speed of sound propagation under standard conditions be denoted as . ; Let the initial threshold for the sound wave attenuation coefficient under standard conditions be denoted as . ; Let the initial threshold for the phase difference of sound waves under standard conditions be denoted as . ; This is the preset temperature influence coefficient, in units of... , set as ; The preset humidity influence coefficient, in units of , set as ; To preset the signal-to-noise ratio impact coefficient, it can be set to... ; The preset aging compensation coefficient is in units of , can be set to ; The operating time of the electricity meter to be tested is in years. To preset the vibration influence coefficient, it can be set to... ; Vibration acceleration, unit: ; The reference vibration threshold can be set to... ; For the received signal-to-noise ratio, As the standard signal-to-noise ratio reference value, it can be set to... ; Temperature, in °C; Humidity, unit: .

[0045] Among them, the received signal-to-noise ratio The calculation formula is:

[0046] in, For signal power, This represents noise power.

[0047] In one possible implementation, the method may further include: Regular automatic calibration and factory calibration extension of the energy meter under test.

[0048] Optionally, periodic automatic calibration is performed as follows: every 30 days after the electricity meter has been running, the calibration process can be automatically executed between 2:00 AM and 4:00 AM (when electricity consumption is low and the environment is stable). This involves keeping the electricity meter casing sealed, collecting 100 sets of data on temperature, humidity, sound wave propagation speed, sound wave attenuation coefficient, and sound wave phase difference, calculating the average value, and updating the reference parameter, i.e., the sound wave propagation speed reference parameter. Sound wave attenuation coefficient reference parameters Acoustic wave phase difference reference parameters Automatically adjust the preset temperature influence coefficient Preset signal-to-noise ratio influence coefficient and preset vibration influence coefficient It also dynamically adjusts the threshold values ​​of acoustic parameters based on the current environmental parameters.

[0049] The factory calibration is expanded to include multiple environmental calibration steps when each electricity meter leaves the factory. Reference parameters are recorded under 10 typical operating conditions within the range of -20℃ to 80℃ and 30%RH to 70%RH to form a parameter database. When the electricity meter is running, it matches the closest initial reference parameters according to the real-time environment.

[0050] This application's embodiments dynamically calculate acoustic parameter thresholds based on environmental parameters, the operating time of the energy meter under test, and the signal quality of the sinusoidal acoustic signal. Environmental parameters change constantly with time and location, the operating time of the energy meter affects the performance and state of its internal components, and the signal quality of the sinusoidal acoustic signal is also affected by various factors. Traditional fixed thresholds cannot adapt to these changes, while dynamic threshold calculation can adjust the thresholds in real time according to the actual situation, making the judgment criteria more closely match the current environment and energy meter state, thereby improving the accuracy of detection.

[0051] In step 103, based on each acoustic parameter and its corresponding threshold, the judgment result of each acoustic parameter is determined, and the judgment result of each acoustic parameter is fused using a weighted voting method to obtain a fused judgment result.

[0052] Among them, weighted voting is an ensemble learning method that assigns different weights to multiple classifiers or decision-makers based on their respective importance or ability when multiple classifiers or decision-makers participate in the decision-making process, and then synthesizes the results to arrive at the final decision.

[0053] In this embodiment, for each acoustic parameter, the judgment result corresponding to that acoustic parameter is determined using that acoustic parameter and its corresponding threshold. Then, a weighted voting method is used to fuse the judgment results of all acoustic parameters to obtain a fused judgment result, thereby reducing misjudgments caused by fluctuations in a single parameter.

[0054] This application employs a weighted voting method to fuse the judgment results of each acoustic parameter to obtain a fused judgment result. Different acoustic parameters may have varying degrees of importance in reflecting the open state of the electricity meter. The weighted voting method can assign different weights to each parameter based on its importance, making the judgment of the electricity meter's state more scientific and reasonable. Even if a parameter is misjudged due to accidental factors, the judgment results of other parameters can still be corrected using the weighted voting method, thereby enhancing the reliability of the entire detection method.

[0055] In one possible implementation, the judgment result for each acoustic parameter is determined based on each acoustic parameter and its corresponding threshold, including: For each acoustic parameter in the current detection cycle, perform the following steps: Calculate the difference between the acoustic parameter and the first acoustic parameter, and take the absolute value of the difference as the first value. The first acoustic parameter is the acoustic parameter of the previous detection cycle. If the first value does not reach the preset percentage of the corresponding sound wave parameter threshold, the label of the judgment result of the sound wave parameter is set to normal, and the first value corresponding to the sound wave parameter is assigned to the sound wave parameter. If the first value reaches the preset percentage of the corresponding acoustic parameter threshold, the label of the judgment result of the acoustic parameter is set to exceed the limit, and the first data corresponding to the acoustic parameter is assigned to the acoustic parameter.

[0056] In this embodiment of the application, after determining the judgment result (i.e., the first value) of each acoustic parameter, the fusion judgment result is calculated according to the second formula, which is:

[0057] in, To integrate the judgment results, when At that time, it was determined to be stealing electricity by opening the cover; The result of the judgment on the speed of sound propagation (i.e., the first value of the speed of sound propagation). The result of the sound wave attenuation coefficient judgment (i.e., the first value of the sound wave attenuation coefficient). This is the result of judging the phase difference of the sound waves (i.e., the first value of the phase difference of the sound waves). , , Record 0 as normal and 1 as exceeding the limit; The parameter weights corresponding to the speed of sound propagation can be set as follows: ; The parameter weights corresponding to the sound wave attenuation coefficient can be set as follows: ; The parameter weights corresponding to the phase difference of the sound waves can be set as follows: .

[0058] In step 104, the state of the electricity meter to be tested is determined based on the judgment results of each acoustic parameter and the fusion judgment results. The state includes normal, cover opening warning and cover opening for electricity theft.

[0059] In this embodiment of the application, the determination of whether the electricity meter to be detected has been opened to steal electricity is made based on the judgment result of each acoustic parameter judged in step 103 and the fusion judgment result.

[0060] This application's embodiments determine the status of the electricity meter under test based on the judgment results of each acoustic parameter and the fused judgment result, including normal, open-cover warning, and open-cover electricity theft. This multi-dimensional judgment method evaluates the electricity meter status from multiple perspectives, avoiding the errors that may exist in a single judgment result. For example, when the judgment result of a certain acoustic parameter is abnormal, but the fused judgment result is normal, the cause can be further analyzed to avoid false alarms; and when the judgment results of each acoustic parameter and the fused judgment result both point to open-cover electricity theft, it can be more certain that the electricity meter has engaged in open-cover electricity theft, improving the reliability of the detection results.

[0061] In one possible implementation, determining the state of the energy meter to be tested based on the judgment results of each acoustic parameter and the fused judgment results may include: If the judgment result of each acoustic parameter does not reach the preset percentage of the corresponding acoustic parameter threshold, and the fused judgment result is less than the lower limit of the preset range for N consecutive detection cycles, then the state of the energy meter to be tested is determined to be normal, where N is a positive integer greater than or equal to 2. If the judgment result of at least one acoustic parameter reaches the preset percentage of the corresponding acoustic parameter threshold, or if the fusion judgment result is within the preset range, then the state of the energy meter to be tested is determined to be an open cover warning, and the warning information is triggered. If the fusion judgment result is greater than the upper limit of the preset range for N consecutive detection cycles, the state of the electricity meter under test is determined to be that the meter is being used for electricity theft, and an audible and visual alarm is triggered.

[0062] For example, assume that the preset percentage of the acoustic parameter threshold is 70%~100%, and the preset range is 0.3≤ If the value is less than 0.5, N is 3, and each detection cycle can be set to 0.5s, then: If the judgment result of each acoustic parameter (i.e., the first value) does not reach 70%~100% of the acoustic parameter threshold, and the fused judgment result If the value is less than 0.3 for three consecutive testing cycles, the energy meter under test is considered to be in normal condition.

[0063] If at least one acoustic parameter's judgment result (i.e., the first value) reaches 70%~100% of the acoustic parameter threshold, or, the judgment results are merged. In the range of 0.3≤ If the value is less than 0.5, the status of the energy meter to be tested is determined to be an open cover warning. At this time, only the warning information is uploaded to the power monitoring platform, and no audible or visual alarm is triggered.

[0064] If the fusion judgment result If the value is greater than 0.5 for three consecutive detection cycles, the state of the electricity meter under test is determined to be that the cover has been opened to steal electricity, triggering a local audible and visual alarm, such as a flashing red LED light and an intermittent buzzer sound, and the alarm information is uploaded.

[0065] In one possible implementation, after the alarm information is uploaded, the power monitoring platform can instruct the energy meter under test to increase the detection frequency (e.g., 0.1s / time) and upload the original waveform data. At the same time, it can link the voltage and current monitoring data of the energy meter. If only the sound wave parameters are abnormal while the power consumption data is normal, it is judged as a suspected misjudgment and manual on-site verification is required.

[0066] This application provides a method for detecting electricity theft by opening a cover of an energy meter based on sinusoidal acoustic characteristics. The method acquires sinusoidal acoustic signals from the energy meter under test and environmental parameters in real time. Based on the changes in the sinusoidal acoustic signals and the environmental parameters, temperature and humidity compensated acoustic parameters are calculated. These acoustic parameters include sound wave propagation speed, sound wave attenuation coefficient, and sound wave phase difference. The environmental parameters include temperature and humidity. Based on the environmental parameters, the operating time of the energy meter under test, and the signal quality of the sinusoidal acoustic signals, acoustic parameter thresholds are dynamically calculated. These thresholds include sound wave propagation speed threshold, sound wave attenuation coefficient threshold, and sound wave phase difference threshold. Based on each acoustic parameter and its corresponding threshold, a judgment result for each acoustic parameter is determined. A weighted voting method is used to fuse the judgment results of each acoustic parameter to obtain a fused judgment result. Based on the judgment results of each acoustic parameter and the fused judgment result, the state of the energy meter under test is determined. The state includes normal, cover-opening warning, and cover-opening electricity theft. This application does not rely solely on a single sinusoidal acoustic parameter, but comprehensively calculates multiple acoustic parameters such as acoustic propagation speed, acoustic attenuation coefficient, and acoustic phase difference. Each parameter reflects the state changes of the electricity meter from different perspectives. By combining multiple parameters for judgment, the limitations that may exist with a single parameter are avoided, greatly improving the accuracy of detection. Considering the influence of temperature and humidity on acoustic propagation, this application acquires temperature and humidity information in real time and calculates temperature and humidity compensated acoustic parameters based on the changes in the sinusoidal acoustic signal and temperature and humidity. Through temperature and humidity compensation, the interference of environmental factors on acoustic parameters is eliminated, making the acoustic parameters more accurately reflect the open state of the electricity meter itself, further improving the accuracy of detection. At the same time, the state of the electricity meter under test is determined by combining the judgment results of each acoustic parameter and the fused judgment results, including normal, open-cover warning, and open-cover theft. This multi-dimensional judgment method evaluates the state of the electricity meter from multiple perspectives, avoiding the errors that may exist with a single judgment result.

[0067] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0068] The following are device embodiments of this application. For details not described in detail, please refer to the corresponding method embodiments described above.

[0069] Figure 3 A schematic diagram of the structure of the electricity meter opening and theft detection device based on sinusoidal acoustic characteristics provided in this application embodiment is shown. For ease of explanation, only the parts related to this application embodiment are shown, and are described in detail below: like Figure 3 As shown, the electricity meter opening and theft detection device 3 based on sinusoidal acoustic wave characteristics includes: The parameter determination module 31 is used to acquire the sinusoidal sound wave signal and environmental parameters of the energy meter under test in real time, and calculate the temperature and humidity compensated sound wave parameters based on the changes of the sinusoidal sound wave signal and the environmental parameters. The sound wave parameters include the sound wave propagation speed, the sound wave attenuation coefficient and the sound wave phase difference, and the environmental parameters include temperature and humidity. The threshold calculation module 32 is used to dynamically calculate the acoustic parameter thresholds based on environmental parameters, the running time of the energy meter under test, and the signal quality of the sinusoidal acoustic signal. The acoustic parameter thresholds include the acoustic propagation speed threshold, the acoustic attenuation coefficient threshold, and the acoustic phase difference threshold. The result fusion module 33 is used to determine the judgment result of each acoustic parameter based on each acoustic parameter and the corresponding acoustic parameter threshold, and to fuse the judgment results of each acoustic parameter using a weighted voting method to obtain a fused judgment result. The status judgment module 34 is used to determine the status of the energy meter to be tested based on the judgment results of each acoustic parameter and the fusion judgment results. The status includes normal, cover opening warning and cover opening for electricity theft.

[0070] This application provides a device for detecting electricity theft by opening a cover on an energy meter based on sinusoidal acoustic characteristics. It acquires sinusoidal acoustic signals from the energy meter under test and environmental parameters in real time. Based on the changes in the sinusoidal acoustic signals and the environmental parameters, it calculates temperature and humidity compensated acoustic parameters, including sound wave propagation speed, sound wave attenuation coefficient, and sound wave phase difference. The environmental parameters include temperature and humidity. Based on the environmental parameters, the operating time of the energy meter under test, and the signal quality of the sinusoidal acoustic signals, it dynamically calculates acoustic parameter thresholds, including sound wave propagation speed threshold, sound wave attenuation coefficient threshold, and sound wave phase difference threshold. Based on each acoustic parameter and its corresponding threshold, it determines the judgment result for each acoustic parameter and uses a weighted voting method to fuse the judgment results of each acoustic parameter to obtain a fused judgment result. Based on the judgment results of each acoustic parameter and the fused judgment result, it determines the state of the energy meter under test, including normal, cover opening warning, and cover opening for electricity theft. This application does not rely solely on a single sinusoidal acoustic parameter, but comprehensively calculates multiple acoustic parameters such as acoustic propagation speed, acoustic attenuation coefficient, and acoustic phase difference. Each parameter reflects the state changes of the electricity meter from different perspectives. By combining multiple parameters for judgment, the limitations that may exist with a single parameter are avoided, greatly improving the accuracy of detection. Considering the influence of temperature and humidity on acoustic propagation, this application acquires temperature and humidity information in real time and calculates temperature and humidity compensated acoustic parameters based on the changes in the sinusoidal acoustic signal and temperature and humidity. Through temperature and humidity compensation, the interference of environmental factors on acoustic parameters is eliminated, making the acoustic parameters more accurately reflect the open state of the electricity meter itself, further improving the accuracy of detection. At the same time, the state of the electricity meter under test is determined by combining the judgment results of each acoustic parameter and the fused judgment results, including normal, open-cover warning, and open-cover theft. This multi-dimensional judgment method evaluates the state of the electricity meter from multiple perspectives, avoiding the errors that may exist with a single judgment result.

[0071] In one possible implementation, the parameter determination module can be used to: The speed of sound wave propagation is calculated using temperature and humidity. Calculate the propagation time of a sinusoidal sound wave using the transmission distance and speed of sound. The phase difference of the sound wave is calculated using the sound wave propagation time and the initial and real-time phases of the sinusoidal sound wave signal. The sound wave attenuation coefficient is calculated using the transmission distance, initial amplitude, and real-time sound wave amplitude of the sinusoidal sound wave signal.

[0072] In one possible implementation, the parameter determination module can also be used for: Inputting temperature and humidity into the formula for calculating the speed of sound, we obtain the speed of sound. The formula for calculating the speed of sound is:

[0073] in, For the speed of sound wave propagation, The speed of sound in air under standard conditions. The temperature coefficient of sound speed. The humidity coefficient is the velocity of sound. For temperature, Humidity.

[0074] In one possible implementation, the parameter determination module can also be used for: By inputting the sound wave propagation time and the initial and real-time phases of the sinusoidal sound wave signal into the sound wave phase difference calculation formula, the sound wave phase difference is obtained. The sound wave phase difference calculation formula is as follows:

[0075] in, For the phase difference of sound waves, The initial phase of the sinusoidal sound wave signal. The real-time phase of the sinusoidal sound wave signal. For the sound wave propagation time, It is a fixed frequency for a sinusoidal sound wave signal.

[0076] In one possible implementation, the parameter determination module can also be used for: The transmission distance, initial amplitude, and real-time amplitude of the sinusoidal sound wave signal are input into the formula for calculating the sound wave attenuation coefficient to obtain the sound wave attenuation coefficient. The formula for calculating the sound wave attenuation coefficient is as follows:

[0077] in, The sound wave attenuation coefficient, The initial amplitude of the sinusoidal sound wave signal is given. This represents the real-time acoustic amplitude of the sinusoidal acoustic signal. The transmission distance of a sinusoidal sound wave signal. It is a logarithmic function with base 10.

[0078] In one possible implementation, the threshold calculation module can be used to: The acoustic parameter threshold is calculated using the first formula, which is:

[0079] in, for The threshold of sound wave propagation speed at a given moment. for The threshold of the sound wave attenuation coefficient at time 1. for The threshold of the phase difference of the sound wave at any given time. This is the initial threshold for the speed of sound propagation under standard conditions. This is the initial threshold for the sound wave attenuation coefficient under standard conditions. This is the initial threshold for the phase difference of sound waves under standard conditions. The preset temperature influence coefficient, The preset humidity influence coefficient, The preset signal-to-noise ratio influence coefficient, To preset the aging compensation coefficient, The operating time of the electricity meter to be tested. To preset the vibration influence coefficient, For vibration acceleration, As the reference vibration threshold, For the received signal-to-noise ratio, This is the standard signal-to-noise ratio reference value. For temperature, Humidity.

[0080] In one possible implementation, the result fusion module can be used to: Each acoustic parameter is input into the second formula to calculate the fusion judgment result. The second formula is:

[0081] in, To integrate the judgment results, The result of determining the speed of sound wave propagation. The result of judging the sound wave attenuation coefficient. The result of judging the phase difference of sound waves. The parameter weights corresponding to the speed of sound propagation. The parameter weights are those corresponding to the sound wave attenuation coefficient. The parameter weights are the phase differences of the sound waves.

[0082] In one possible implementation, the state determination module can be used for: If the judgment result of each acoustic parameter does not reach the preset percentage of the corresponding acoustic parameter threshold, and the fused judgment result is less than the lower limit of the preset range for N consecutive detection cycles, then the state of the energy meter to be tested is determined to be normal, where N is a positive integer greater than or equal to 2. If the judgment result of at least one acoustic parameter reaches the preset percentage of the corresponding acoustic parameter threshold, or if the fusion judgment result is within the preset range, then the state of the energy meter to be tested is determined to be an open cover warning, and the warning information is triggered. If the fusion judgment result is greater than the upper limit of the preset range for N consecutive detection cycles, the state of the electricity meter under test is determined to be that the meter is being used for electricity theft, and an audible and visual alarm is triggered.

[0083] In one possible implementation, the device may further include a data processing module, which can be used for: The harmonic distortion of the sinusoidal acoustic signal of the energy meter under test is calculated using Fast Fourier Transform. Based on the harmonic distortion, determine whether the sinusoidal sound wave signal of the energy meter under test is contaminated, and remove the contaminated sinusoidal sound wave signal. Accordingly, the parameter determination module can be specifically used for: Based on the changes in the sinusoidal acoustic signal after harmonic distortion assessment, and combined with environmental parameters, the acoustic parameters after temperature and humidity compensation are calculated.

[0084] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0085] Those skilled in the art will recognize that the templates, units, and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0086] If the module / unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium. When executed by a processor, the computer program can implement the steps of the above embodiments of the electricity meter opening and theft detection method based on sinusoidal acoustic characteristics. The computer program includes computer program code, which can be in the form of source code, object code, executable file, or some intermediate form. The computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory, a random access memory, an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0087] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method for detecting electricity theft by opening the cover of an electricity meter based on sinusoidal acoustic characteristics, characterized in that, include: The system acquires sinusoidal acoustic wave signals and environmental parameters from the energy meter under test in real time. Based on the changes in the sinusoidal acoustic wave signals and the environmental parameters, it calculates the acoustic wave parameters after temperature and humidity compensation. The acoustic wave parameters include the sound wave propagation speed, the sound wave attenuation coefficient, and the sound wave phase difference. The environmental parameters include temperature and humidity. Based on the environmental parameters, the running time of the energy meter under test, and the signal quality of the sinusoidal sound wave signal, the sound wave parameter thresholds are dynamically calculated. The sound wave parameter thresholds include the sound wave propagation speed threshold, the sound wave attenuation coefficient threshold, and the sound wave phase difference threshold. Based on each acoustic parameter and its corresponding threshold, the judgment result for each acoustic parameter is determined, and a weighted voting method is used to fuse the judgment results of each acoustic parameter to obtain a fused judgment result. Based on the judgment results of each acoustic parameter and the fusion judgment results, the state of the energy meter to be tested is determined, including normal, cover opening warning, and cover opening for electricity theft.

2. The method for detecting electricity theft by opening the cover of an energy meter based on sinusoidal acoustic characteristics according to claim 1, characterized in that, The calculation of temperature and humidity compensated sound wave parameters based on the changes in the sinusoidal sound wave signal and in conjunction with the environmental parameters includes: The speed of sound wave propagation is calculated using the temperature and humidity. The propagation time of the sound wave is calculated using the transmission distance of the sinusoidal sound wave signal and the propagation speed of the sound wave; The sound wave phase difference is calculated using the sound wave propagation time and the initial and real-time phases of the sinusoidal sound wave signal; The sound wave attenuation coefficient is calculated using the transmission distance, initial amplitude, and real-time sound wave amplitude of the sinusoidal sound wave signal.

3. The method for detecting electricity theft by opening the cover of an energy meter based on sinusoidal acoustic characteristics according to claim 2, characterized in that, The calculation of the sound wave propagation speed using the temperature and humidity includes: The temperature and humidity are input into the formula for calculating the speed of sound propagation to obtain the speed of sound propagation. The formula for calculating the speed of sound propagation is as follows: in, The speed of sound wave propagation. The speed of sound in air under standard conditions. The temperature coefficient of sound speed. The humidity coefficient is the velocity of sound. The temperature is [temperature value]. The humidity is as described.

4. The method for detecting electricity theft by opening the cover of an energy meter based on sinusoidal acoustic characteristics according to claim 2, characterized in that, The step of calculating the sound wave phase difference using the sound wave propagation time and the initial and real-time phases of the sinusoidal sound wave signal includes: The sound wave propagation time and the initial and real-time phases of the sinusoidal sound wave signal are input into the sound wave phase difference calculation formula to obtain the sound wave phase difference. The sound wave phase difference calculation formula is as follows: in, The phase difference of the sound waves, The initial phase of the sinusoidal sound wave signal is given. The real-time phase of the sinusoidal sound wave signal is denoted as . The sound wave propagation time, The fixed frequency of the sinusoidal sound wave signal is denoted as .

5. The method for detecting electricity theft by opening the cover of an energy meter based on sinusoidal acoustic characteristics according to claim 2, characterized in that, The calculation of the sound wave attenuation coefficient using the transmission distance, initial amplitude, and real-time sound wave amplitude of the sinusoidal sound wave signal includes: The transmission distance, initial amplitude, and real-time amplitude of the sinusoidal sound wave signal are input into the sound wave attenuation coefficient calculation formula to obtain the sound wave attenuation coefficient. The sound wave attenuation coefficient calculation formula is as follows: in, The sound wave attenuation coefficient is... The initial amplitude of the sinusoidal sound wave signal is given. The real-time acoustic amplitude of the sinusoidal acoustic signal is given by [the signal name]. The transmission distance of the sinusoidal sound wave signal is given. It is a logarithmic function with base 10.

6. The method for detecting electricity theft by opening the cover of an energy meter based on sinusoidal acoustic characteristics according to claim 1, characterized in that, The dynamic calculation of acoustic parameter thresholds based on environmental parameters, the operating time of the energy meter under test, and the signal quality of the sinusoidal acoustic signal includes: The acoustic parameter threshold is calculated using a first formula, which is: in, for The threshold of sound wave propagation speed at any given moment. for The threshold of the sound wave attenuation coefficient at time 1. for The threshold of the phase difference of the sound wave at any given time. This is the initial threshold for the speed of sound propagation under standard conditions. This is the initial threshold for the sound wave attenuation coefficient under standard conditions. This is the initial threshold for the phase difference of sound waves under standard conditions. The preset temperature influence coefficient, The preset humidity influence coefficient, The preset signal-to-noise ratio influence coefficient, To preset the aging compensation coefficient, The device operating time of the energy meter to be tested. To preset the vibration influence coefficient, For vibration acceleration, As the reference vibration threshold, For the received signal-to-noise ratio, This is the standard signal-to-noise ratio reference value. The temperature is [temperature value]. The humidity is as described.

7. The method for detecting electricity theft by opening the cover of an energy meter based on sinusoidal acoustic characteristics according to claim 1, characterized in that, The weighted voting method is used to fuse the judgment results of each acoustic parameter to obtain a fused judgment result, including: Each acoustic parameter is input into the second formula to calculate the fusion judgment result. The second formula is: in, The fusion judgment result is... The result of the determination of the sound wave propagation speed. The result of determining the sound wave attenuation coefficient. The result of the determination of the acoustic wave phase difference. The parameter weights corresponding to the sound wave propagation speed are: The parameter weights corresponding to the sound wave attenuation coefficient are... The parameter weights are those corresponding to the phase difference of the sound waves.

8. The method for detecting electricity theft by opening the cover of an energy meter based on sinusoidal acoustic characteristics according to claim 1, characterized in that, Determining the state of the energy meter to be tested based on the judgment results of each acoustic parameter and the fused judgment result includes: If the judgment result of each acoustic parameter does not reach the preset percentage of the corresponding acoustic parameter threshold, and the fusion judgment result is less than the lower limit of the preset range for N consecutive detection cycles, then the state of the energy meter to be tested is determined to be normal, where N is a positive integer greater than or equal to 2. If the judgment result of at least one acoustic parameter reaches a preset percentage of the corresponding acoustic parameter threshold, or if the fusion judgment result is within the preset range, then the state of the energy meter to be tested is determined to be an open cover warning, and a warning message is triggered. If the fusion judgment result is greater than the upper limit of the preset range for N consecutive detection cycles, the state of the energy meter to be tested is determined to be that the cover is open and electricity is stolen, and an audible and visual alarm is triggered.

9. The method for detecting electricity theft by opening the cover of an energy meter based on sinusoidal acoustic characteristics according to claim 1, characterized in that, After acquiring the sinusoidal acoustic signal of the energy meter under test in real time, the method further includes: The harmonic distortion of the sinusoidal acoustic signal of the energy meter under test is calculated using Fast Fourier Transform. Based on the harmonic distortion, determine whether the sinusoidal sound wave signal of the energy meter under test is contaminated, and remove the contaminated sinusoidal sound wave signal. Accordingly, the calculation of temperature and humidity compensated sound wave parameters based on the changes in the sinusoidal sound wave signal and in conjunction with the environmental parameters includes: Based on the changes in the sinusoidal acoustic signal after harmonic distortion determination, and combined with the environmental parameters, the acoustic parameters after temperature and humidity compensation are calculated.

10. A device for detecting electricity theft by opening the cover of an electricity meter based on sinusoidal acoustic characteristics, characterized in that, include: The parameter determination module is used to acquire the sinusoidal acoustic wave signal and environmental parameters of the energy meter under test in real time, and calculate the temperature and humidity compensated acoustic wave parameters based on the changes of the sinusoidal acoustic wave signal and the environmental parameters. The acoustic wave parameters include the sound wave propagation speed, the sound wave attenuation coefficient and the sound wave phase difference. The environmental parameters include temperature and humidity. The threshold calculation module is used to dynamically calculate the acoustic parameter thresholds based on the environmental parameters, the running time of the energy meter under test, and the signal quality of the sinusoidal acoustic signal. The acoustic parameter thresholds include the acoustic propagation speed threshold, the acoustic attenuation coefficient threshold, and the acoustic phase difference threshold. The result fusion module is used to determine the judgment result of each acoustic parameter based on each acoustic parameter and the corresponding acoustic parameter threshold, and to fuse the judgment results of each acoustic parameter using a weighted voting method to obtain the fused judgment result. The status judgment module is used to determine the status of the energy meter to be tested based on the judgment results of each acoustic parameter and the fused judgment results. The status includes normal, cover opening warning and cover opening for electricity theft.

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