A monitoring method, device, and metering box

Abstract

The monitoring method, device, and metering box provided in this application include: acquiring historical environmental data; determining the optimal tap weight based on the historical environmental data and expected response; predicting the current environmental data based on the optimal tap weight and historical environmental data; and if the predicted environmental data meets the fault judgment conditions, controlling the measurement switch to open to disconnect the internal circuit of the metering box. By determining the optimal tap weight based on historical environmental data and expected response, and predicting the current environmental data based on the optimal tap weight, accurate and clean predicted environmental data can be obtained. The predicted environmental data and fault judgment conditions are used to determine whether a fault has occurred in the internal circuit of the metering box. If a fault occurs, the measurement switch needs to be opened to protect the metering box and promptly eliminate the fault.

Description

Technical Field

[0001] This application relates to the field of metering box monitoring technology, specifically to a metering box monitoring method, device, and metering box. Background Technology

[0002] Low-voltage metering boxes, as the final stage of the power grid, are a key focus in the construction of the power Internet of Things (IoT) and a primary source of end-point data sensing. While metering boxes physically manage assets such as electricity meters and data collectors, they fail to provide real-time, comprehensive monitoring of these assets, and are unable to promptly report various fault parameters to the main station for early warning.

[0003] Traditional low-voltage metering boxes only have overload and short-circuit protection for their incoming and outgoing line switches. However, in some short-circuit fault scenarios, the incoming and outgoing line switches cannot work effectively together. Furthermore, when obtaining environmental data from the metering box, the presence of a lot of interference data makes it impossible to quickly confirm whether a safety problem is about to occur inside the metering box, thus failing to troubleshoot the fault in time and causing damage to the metering box. Summary of the Invention

[0004] To address the aforementioned technical problems, this application is proposed. Embodiments of this application provide a monitoring method, device, and metering box, solving the problem in the prior art where the presence of numerous interfering data makes it impossible to quickly confirm whether environmental data threatens the safety of the metering box, thus hindering timely fault diagnosis and causing damage to the metering box.

[0005] According to one aspect of this application, a method for monitoring a metering box is provided, comprising:

[0006] Obtain historical environmental data;

[0007] Determine the optimal tap weight based on the historical environmental data and the expected response;

[0008] Based on the optimal tap weights and the historical environmental data, predict the forecast environmental data for the current moment;

[0009] If the predicted environmental data meets the fault judgment conditions, the measurement switch is turned on to disconnect the internal circuit of the metering box.

[0010] In one embodiment, the step of controlling the measurement switch to turn on if the predicted environmental data meets the fault judgment conditions includes:

[0011] Obtain the three-phase incoming current of the metering box at the current moment;

[0012] Obtain the three-phase outgoing current of the metering box at the current moment;

[0013] Calculate the differential current of each phase based on the three-phase incoming current and the three-phase outgoing current;

[0014] If the values ​​corresponding to the predicted environmental data are all greater than the preset environmental threshold and the differential current of each phase is less than the preset differential current threshold, then the measurement switch is controlled to turn on.

[0015] In one embodiment, obtaining the three-phase outgoing current of the metering box at the current moment includes:

[0016] Obtain the three-phase incoming current of the metering box at the first historical moment;

[0017] The three-phase incoming current of the metering box is obtained at a second historical moment; wherein the second historical moment is later than the first historical moment;

[0018] Based on the three-phase incoming current of the metering box at the current moment, the three-phase incoming current of the metering box at the first historical moment, and the three-phase incoming current of the metering box at the second historical moment, determine whether to initiate the fault judgment operation.

[0019] If the fault diagnosis operation is initiated, the three-phase outgoing current of the metering box at the current moment is obtained.

[0020] In one embodiment, determining whether to initiate a fault diagnosis operation based on the three-phase incoming current of the metering box at the current moment, the three-phase incoming current of the metering box at a first historical moment, and the three-phase incoming current of the metering box at a second historical moment includes:

[0021] Calculate the first difference between the incoming current of each phase of the metering box at the current moment and its corresponding incoming current at the first historical moment;

[0022] Calculate the second difference between the incoming current of each phase of the metering box at the first historical moment and its corresponding incoming current at the second historical moment.

[0023] Calculate the third difference between the first difference and the second difference;

[0024] If the third difference satisfies the difference judgment condition, then the fault judgment operation is initiated.

[0025] In one embodiment, determining to initiate a fault judgment operation if the third difference satisfies the difference judgment condition includes:

[0026] Obtain the maximum current value of the electricity meter in the metering box;

[0027] If the third difference is greater than the maximum current value, then the fault diagnosis operation is initiated.

[0028] In one embodiment, determining the optimal tap weight based on the historical environmental data and the expected response includes:

[0029] Determine the filter order and step size;

[0030] Initialize the weights of the filter order taps to 0 and construct a weight vector;

[0031] The historical environmental data is used to construct an input vector;

[0032] Arrange the expected responses into a column vector in chronological order to obtain the expected response vector;

[0033] The actual output vector is calculated based on the weight vector and the input vector.

[0034] The deviation vector is calculated based on the actual output vector and the expected response vector.

[0035] Based on the weight vector, the bias vector, the step size, and the input vector, estimate the tap weight vector of the weight vector at the next time step;

[0036] Obtain the offset parameters;

[0037] If the misalignment parameter is less than a preset misalignment threshold, then the tap weight vector at the next moment of the weight vector is determined as the optimal tap weight.

[0038] In one embodiment, obtaining the offset parameters includes:

[0039] Obtain the largest eigenvalue of the autocorrelation matrix of the input vector;

[0040] The offset parameter is calculated based on the step size, the filter order, and the maximum eigenvalue.

[0041] In one embodiment, calculating the actual output vector based on the weight vector and the input vector includes:

[0042] The weight vector is transposed to obtain the transposed vector;

[0043] The actual output vector is calculated by multiplying the transposed vector with the input vector.

[0044] According to another aspect of this application, a monitoring device for a metering box is provided, comprising:

[0045] The acquisition module is used to acquire historical environmental data;

[0046] The calculation module is used to determine the optimal tap weight based on the historical environmental data and the expected response;

[0047] The determination module is used to predict the predicted environment data at the current moment based on the optimal tap weight and the historical environment data.

[0048] The control module is used to control the measurement switch to turn on and disconnect the internal circuit of the metering box if the predicted environmental data meets the fault judgment conditions.

[0049] According to another aspect of this application, a measuring box is provided, comprising:

[0050] The metering box body contains a smoke sensor, a temperature and humidity sensor, a controller, a measuring switch, an electricity meter, and a current transformer. The smoke sensor, temperature and humidity sensor, electricity meter, measuring switch, and current transformer are all electrically connected to the controller. The output terminal of the current transformer is electrically connected to the measuring switch. The smoke sensor detects smoke inside the metering box body. The temperature and humidity sensor detects the temperature and humidity inside the metering box body. The electricity meter detects the current value transmitted by the transformer. The controller executes any of the aforementioned metering box monitoring methods. The current transformer detects the three-phase output current value of the electricity meter. The controller controls the opening and closing of the measuring switch.

[0051] The monitoring method, device, and metering box provided in this application include: acquiring historical environmental data; determining the optimal tap weight based on the historical environmental data and expected response; predicting the current environmental data based on the optimal tap weight and historical environmental data; and controlling the measurement switch to open if the predicted environmental data meets the fault judgment conditions to disconnect the internal circuit of the metering box. By determining the optimal tap weight based on historical environmental data and expected response, and predicting the current environmental data based on the optimal tap weight, accurate and clean predicted environmental data can be obtained. Furthermore, the internal circuit of the metering box can be determined based on the predicted environmental data and fault judgment conditions. If a fault occurs, the measurement switch needs to be opened to protect the metering box and promptly eliminate the fault. Attached Figure Description

[0052] The above and other objects, features, and advantages of this application will become more apparent from the more detailed description of the embodiments of this application in conjunction with the accompanying drawings. The drawings are provided to further illustrate the embodiments of this application and form part of the specification. They are used together with the embodiments of this application to explain this application and do not constitute a limitation thereof. In the drawings, the same reference numerals generally represent the same components or steps.

[0053] Figure 1This is a flowchart illustrating a monitoring method for a metering box provided in an exemplary embodiment of this application.

[0054] Figure 2 This is a schematic flowchart of a measurement switch control method provided in an exemplary embodiment of this application.

[0055] Figure 3 This is a graph of differential protection under proportional braking provided in an exemplary embodiment of this application.

[0056] Figure 4 This is a schematic diagram of the structure of the monitoring device for the metering box provided in an exemplary embodiment of this application.

[0057] Figure 5 This is a schematic diagram of the structure of a monitoring device for a metering box provided in another exemplary embodiment of this application.

[0058] Figure 6 This is a schematic diagram of the metering box provided in an exemplary embodiment of this application.

[0059] Figure 7 This is a structural diagram of an electronic device provided in an exemplary embodiment of this application. Detailed Implementation

[0060] Hereinafter, exemplary embodiments according to this application will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments of this application. It should be understood that this application is not limited to the exemplary embodiments described herein.

[0061] Figure 1 This is a flowchart illustrating a monitoring method for a metering box provided in an exemplary embodiment of this application. Figure 1 As shown, the monitoring methods for the metering box include:

[0062] Step 110: Obtain historical environmental data.

[0063] In this embodiment, environmental data at any given moment can be collected by sensors installed inside the metering chamber. Historical environmental data includes temperature, humidity, and other parameters. By analyzing this historical data, changes in the internal environment of the metering chamber over a historical period can be anticipated, and the predicted environmental data for the current moment can be forecasted based on this historical data. This allows for timely intervention to prevent damage to the metering chamber.

[0064] Step 120: Determine the optimal tap weights based on historical environmental data and expected responses.

[0065] In this embodiment, the LMS (Least Mean Square) adaptive filtering method is used to predict the environmental data at the current moment. The LMS method is a commonly used adaptive filtering algorithm used to adjust the filter weights so that its output signal is as close as possible to the desired signal. This application requires pre-determining the desired response and determining the optimal tap weights using the desired response and historical environmental data. Then, the current environmental data is predicted using the tap weights and historical environmental data. The desired response refers to the output response that the system expects to obtain under a given input. In the context of an adaptive filter, the desired response represents the target value that we expect the filter output signal to reach. In an adaptive filter, the filter weight parameters can be adjusted based on the difference between the desired response and the actual output of the filter, so that the actual output gradually approaches the desired output.

[0066] Step 130: Based on the optimal tap weights and historical environment data, predict the forecast environment data for the current moment.

[0067] In this embodiment of the application, the predicted environment data at the current moment is the product of the optimal tap weight and the historical environment data.

[0068] Step 140: If the predicted environmental data meets the fault judgment conditions, then control the measurement switch to turn on to disconnect the internal circuit of the metering box.

[0069] In this embodiment of the application, in order to determine whether the predicted environmental data is abnormal, it is necessary to set fault judgment conditions. The abnormality of the predicted environmental data is determined by the fault judgment conditions. If the predicted environmental data is abnormal, the measurement switch is turned on in time to disconnect the internal circuit of the metering box.

[0070] The metering box contains a measuring switch, an energy meter, a circuit breaker, and a current transformer, all electrically connected in sequence. The output of the current transformer is electrically connected to the measuring switch. An abnormality in the internal circuitry of the metering box indicates a problem in the circuit between the energy meter and the circuit breaker. If the predicted environmental data is abnormal, it indicates an anomaly within the metering box, possibly due to an internal short circuit causing increased current and potential sparking. Therefore, it is crucial to predict the current environmental data before a short circuit occurs to quickly determine if there is an anomaly within the metering box. If an anomaly is detected, the measuring switch should be immediately used to short-circuit the internal circuitry to ensure the safety of the metering box.

[0071] The monitoring method for the metering box provided in this application includes: acquiring historical environmental data; determining the optimal tap weight based on the historical environmental data and the expected response; predicting the predicted environmental data at the current moment based on the optimal tap weight and the historical environmental data; and controlling the measurement switch to open if the predicted environmental data meets the fault judgment conditions to disconnect the internal circuit of the metering box. By determining the optimal tap weight based on historical environmental data and the expected response, and predicting the predicted environmental data at the current moment based on the optimal tap weight, the method can accurately obtain clean predicted environmental data. Furthermore, by using the predicted environmental data and the fault judgment conditions, the method can determine whether a fault has occurred in the internal circuit of the metering box. If a fault occurs, the measurement switch needs to be opened to protect the metering box and promptly eliminate the fault.

[0072] Figure 2 This is a schematic flowchart of a measurement switch control method provided in an exemplary embodiment of this application. Figure 2 As shown, step 140 may include:

[0073] Step 141: Obtain the three-phase incoming current of the metering box at the current moment.

[0074] In this embodiment, the transformer is electrically connected to the measuring switch. The current transmitted from the transformer to the measuring switch is the three-phase incoming current. The measuring switch is equipped with a current transformer sampling interface to collect the three-phase incoming current. The current transformer detects the three-phase outgoing current. When there is a short circuit fault inside the metering box, or when there is aging, leakage, or electricity theft, a significant difference will occur between the incoming and outgoing currents. The differential protection operates within the metering box and can achieve fault isolation without delay. The differential protection detects whether there is any phase-to-phase short circuit or grounding fault in the meter box. The differential protection is based on comparing the currents entering and leaving the equipment; that is, the currents flowing into and leaving the equipment should be balanced. If the currents are unbalanced, it indicates that a fault may have occurred inside the equipment, and the differential protection will operate to isolate the fault.

[0075] Step 142: Obtain the three-phase outgoing current of the metering box at the current moment.

[0076] In this embodiment of the application, the three-phase outgoing current of the metering box at the current moment can be detected by a current transformer connected to the circuit breaker.

[0077] Step 143: Calculate the differential current of each phase based on the three-phase incoming current and the three-phase outgoing current.

[0078] This application implements two methods: Fourier filtering is performed on the incoming and outgoing currents of each phase to obtain the outgoing current vector and the incoming current vector for each phase. Then, differential current calculation is performed on each phase current vector. The formula for calculating the difference between the incoming and outgoing currents of the differential protection can be expressed as: in, It is differential current. It is the vector of the A, B, or C phase incoming current flowing into the measuring switch. This refers to the vector current of phase A, B, or C after the meter flows out of the meter box, which can be acquired through a current transformer. The differential current of each phase can be calculated using the formula described above. This involves calculating the difference between the incoming and outgoing currents of phase A, phase B, and phase C.

[0079] Step 144: Determine whether the differential current of each phase is less than the preset differential current threshold.

[0080] In this embodiment of the application, if the judgment result of step 144 is yes, that is, the differential current of each phase is less than the preset differential current threshold, then step 145 is executed; if the judgment result of step 144 is no, that is, the differential current of each phase is greater than or equal to the preset differential current threshold, then step 146 is executed.

[0081] Step 145: Determine whether the values ​​corresponding to the predicted environment data are all greater than the preset environment threshold.

[0082] In this embodiment of the application, if the judgment result of step 145 is yes, that is, the values ​​corresponding to the predicted environmental data are all greater than the preset environmental threshold, then step 146 is executed. If the judgment result of step 145 is no, that is, the values ​​corresponding to the predicted environmental data are all less than the preset environmental threshold, then step 110 is executed.

[0083] Step 146: Turn on the measurement switch.

[0084] In addition, if the predicted environmental data contains a value lower than the preset environmental threshold, an alarm signal will be generated to prompt maintenance personnel to repair the metering box.

[0085] In one embodiment, step 141 may be specifically implemented as follows: obtaining the three-phase incoming current of the metering box at a first historical moment; obtaining the three-phase incoming current of the metering box at a second historical moment; wherein the second historical moment is later than the first historical moment; determining whether to start the fault judgment operation based on the three-phase incoming current of the metering box at the current moment, the three-phase incoming current of the metering box at the first historical moment, and the three-phase incoming current of the metering box at the second historical moment; if it is determined to start the fault judgment operation, then obtaining the three-phase outgoing current of the metering box at the current moment.

[0086] In this embodiment, the fault start function makes the system easier to maintain and manage. When a system failure occurs, the cause of the failure can be quickly identified, and repairs or switching to a backup system can be performed, reducing maintenance time and costs.

[0087] Specifically, the three-phase incoming current of the metering box at the current moment is obtained, the three-phase incoming current of the metering box at the first historical moment is obtained, and the three-phase incoming current of the metering box at the second historical moment is obtained. Then, the first difference between the current phase incoming current of each phase at the current moment and the incoming current of the corresponding phase at the first historical moment is calculated, and the second difference between the current phase incoming current of each phase at the first historical moment and the incoming current of the corresponding phase at the second historical moment is calculated. The difference between the first difference and the second difference is calculated, and the fault judgment operation is determined by the difference. If the fault judgment operation is determined to be started, the three-phase outgoing current of the metering box at the current moment is obtained.

[0088] In one embodiment, step 141 may be specifically implemented as follows: calculating the first difference between the incoming current of each phase of the metering box at the current time and its corresponding incoming current at the first historical time; calculating the second difference between the incoming current of each phase of the metering box at the first historical time and its corresponding incoming current at the second historical time; calculating the third difference between the first difference and the second difference; if the third difference satisfies the difference judgment condition, then determining to start the fault judgment operation.

[0089] In this embodiment of the application, the formula for calculating the third difference is:

[0090] ||I k -I k-N |-|I k-N -I k-2N ||, where N represents the number of sampling points per cycle, I k I represents the current value of the three-phase incoming line current at the current moment. k-N This represents the three-phase incoming current value at the second historical moment (which could be the current value from one week prior), I k-2N This represents the three-phase incoming current value at the second historical moment (which could be the current value from two weeks ago).

[0091] Set the difference judgment conditions, and determine whether to initiate fault diagnosis operation based on the third difference value. If the third difference value meets the difference judgment conditions, then determine whether to initiate fault diagnosis operation.

[0092] In one embodiment, step 141 can be specifically implemented as follows: obtaining the maximum current value of the electricity meter in the metering box; if the third difference is greater than the maximum current value, then determining to start the fault judgment operation.

[0093] In this embodiment of the application, the maximum current value of the electricity meter in the metering box is set to I. qd If the third difference is greater than the maximum current value, then the fault diagnosis operation is initiated. That is, the condition ||I is determined by the difference. k -I k-N |-|I k-N -I k-2N||>I qd This allows us to determine when a fault diagnosis operation needs to be initiated.

[0094] Figure 3 This is a graph illustrating the differential protection under proportional braking provided in an exemplary embodiment of this application. (As shown...) Figure 3 As shown, during normal operation, the fault initiation judgment will not activate. During this period, differential current calculation is continuously performed, and this differential current serves as a floating threshold. After the fault initiation judgment activates, it is determined whether the differential current is less than a preset differential current threshold. If the differential current is greater than or equal to the preset differential current threshold and the braking current is greater than or equal to the preset braking current threshold, the measuring switch is opened to disconnect the internal circuit of the metering box. The braking current is the maximum value among the three-phase outgoing currents.

[0095] Specifically, Icdd represents the differential current, Izdd represents the braking current, Icd represents the preset differential current threshold, and Icd represents the preset braking current threshold. When both the differential current and braking current are greater than or equal to the preset differential current threshold and the braking current is greater than or equal to the preset braking current threshold, it indicates that the relationship between the differential current and braking current is within the specified range, requiring the measurement switch to be turned on. In other words, when the ratio between the differential current and braking current is within the specified range, the internal circuitry of the metering box is faulty. When it is outside the specified range, it indicates a fault in the external circuitry of the metering box.

[0096] In one embodiment, step 120 can be specifically implemented as follows: determining the filter order and step size; initializing the filter order and tap weights to 0 and constructing a weight vector; constructing an input vector from historical environmental data; arranging the expected response into a column vector in chronological order to obtain the expected response vector; calculating the actual output vector based on the weight vector and the input vector; calculating the bias vector based on the actual output vector and the expected response vector; estimating the tap weight vector at the next moment based on the weight vector, bias vector, step size, and input vector; obtaining the offset parameter; if the offset parameter is less than a preset offset threshold, determining the tap weight vector at the next moment as the optimal tap weight.

[0097] In this embodiment, to achieve comprehensive monitoring and accurate measurement of characteristic quantities in complex environments, a multi-characteristic acquisition and data processing scheme for the metering box is proposed. This scheme monitors multiple status information of the electricity metering box, including temperature, humidity, and vibration. The acquired data undergoes LMS adaptive filtering to obtain highly reliable data, which is then transmitted in real-time via bus communication. For the processing of predicted environmental data, an LMS adaptive filtering method is employed, comprising two parts: a filtering process and an adaptive process. The filtering process first calculates the response of the linear filter to the input signal, then compares the output result with the expected response to generate an estimation error. The adaptive process automatically adjusts the filter parameters based on the estimation error, and an adaptive control algorithm is used to find suitable transverse filter tap weights.

[0098] Specifically, the filter order M and step size μ are determined, and the tap weights are initialized to 0, that is, the M tap weights w are pre-set to 0 as the initial state of the tap weights, to obtain a weight vector denoted as w(n). Then, the data is updated. First, the historical environment data is constructed into an M×1 input vector, which yields:

[0099] u = [u(n), (n-1), ..., u(n-M+1)], where historical environmental data at different times can be arranged chronologically to obtain the u vector. The desired response is constructed into a desired response vector, d(n), where n represents time. Due to the change in time, the historical environmental data and the desired response need to be updated, i.e., the input vector and the desired response vector need to be updated. Then, based on the weight vector and the input vector, the actual output vector is calculated. The specific calculation formula is: y(n) = w T Let u(n) and y(n) be the actual output vectors. Then, calculate the deviation vector based on the actual output vector and the expected response vector. The specific calculation formula is: e(n) = d(n) - y(n), where d(n) represents the expected response vector, y(n) is the actual output vector, and e(n) is the deviation vector. Adaptive processing is performed on the weight vector, that is, the tap weight vector at the next time step is estimated. The specific calculation formula is: w(n+1) = w(n) + 2μe(n)u(n) (n = 0, 1, 2, ...). Then, obtain the offset parameter. Determine whether the calculated tap weight vector at the next time step can be used as the optimal tap weight through the offset parameter. Set the preset offset threshold to 10%. If the offset parameter is less than the preset offset threshold, that is, the offset parameter is less than 10%, then the tap weight at the next time step of the weight vector is determined as the optimal tap weight. The offset parameter refers to the deviation between the actual output and the expected output of the filter.

[0100] In one embodiment, step 120 may be specifically implemented as follows: obtaining the maximum eigenvalue of the autocorrelation matrix of the input vector; calculating the offset parameter based on the step size, filter order, and the maximum eigenvalue.

[0101] In this embodiment, the largest eigenvalue of the autocorrelation matrix of the input vector is set to λ. k Then, based on the step size, filter order, and maximum eigenvalue, the offset parameter is calculated using the following formula: J(∞) is the steady-state value of the additional mean square error, J min The minimum mean square error is given by M, where M is the filter order, μ is the step size, and λ is the step size. k It is the largest eigenvalue of the autocorrelation matrix of the input vector.

[0102] In one embodiment, step 120 can be specifically implemented as follows: transpose the weight vector to obtain the transposed vector; calculate the product between the transposed vector and the input vector as the actual output vector.

[0103] In this embodiment, the weight vector w(n) is transposed to obtain the transposed vector, which is w T Then, the product of the transposed vector and the input vector u is calculated to obtain the actual output vector, and its calculation formula is y(n) = w T (n)u.

[0104] Figure 4 This is a schematic diagram of the structure of a monitoring device for a metering box provided in an exemplary embodiment of this application. Figure 4 As shown, the monitoring device 20 of the metering box includes: an acquisition module 201 for acquiring historical environmental data; a calculation module 202 for determining the optimal tap weight based on the historical environmental data and the expected response; a determination module 203 for predicting the predicted environmental data at the current moment based on the optimal tap weight and the historical environmental data; and a control module 204 for controlling the measurement switch to open to disconnect the internal circuit of the metering box if the predicted environmental data meets the fault judgment conditions.

[0105] Figure 5 This is a schematic diagram of the structure of a monitoring device for a metering box provided in another exemplary embodiment of this application. (See diagram below.) Figure 5 As shown, the control module 204 may include: a first acquisition unit 2041, used to acquire the three-phase incoming current of the metering box at the current moment; a second acquisition unit 2042, used to acquire the three-phase outgoing current of the metering box at the current moment; a calculation unit 2043, used to calculate the differential current of each phase based on the three-phase incoming current and the three-phase outgoing current; and a control subunit 2044, used to control the measurement switch to open if the values ​​corresponding to the predicted environmental data are all greater than the preset environmental threshold and the differential current of each phase is less than the preset differential current threshold.

[0106] In one embodiment, such as Figure 5As shown, the first acquisition unit 2041 can be specifically configured to: acquire the three-phase incoming current of the metering box at a first historical moment; acquire the three-phase incoming current of the metering box at a second historical moment; wherein the second historical moment is later than the first historical moment; determine whether to start the fault judgment operation based on the three-phase incoming current of the metering box at the current moment, the three-phase incoming current of the metering box at the first historical moment and the three-phase incoming current of the metering box at the second historical moment; if it is determined to start the fault judgment operation, acquire the three-phase outgoing current of the metering box at the current moment.

[0107] In one embodiment, such as Figure 5 As shown, the first acquisition unit 2041 can be specifically configured to: calculate the first difference between the incoming current of each phase of the metering box at the current time and its corresponding incoming current at the first historical time; calculate the second difference between the incoming current of each phase of the metering box at the first historical time and its corresponding incoming current at the second historical time; calculate the third difference between the first difference and the second difference; if the third difference meets the difference judgment condition, then determine to start the fault judgment operation.

[0108] In one embodiment, such as Figure 5 As shown, the first acquisition unit 2041 can be specifically configured to: acquire the maximum current value of the electricity meter in the metering box; if the third difference is greater than the maximum current value, then determine to start the fault judgment operation.

[0109] In one embodiment, the calculation module 202 may be specifically configured to: determine the filter order and step size; initialize the filter order and tap weights to 0 and construct a weight vector; construct an input vector from historical environmental data; arrange the expected response into a column vector in chronological order to obtain the expected response vector; calculate the actual output vector based on the weight vector and the input vector; calculate the deviation vector based on the actual output vector and the expected response vector; estimate the tap weight vector of the weight vector at the next time step based on the weight vector, deviation vector, step size, and input vector; obtain the offset parameter; if the offset parameter is less than a preset offset threshold, determine the tap weight vector of the weight vector at the next time step as the optimal tap weight.

[0110] In one embodiment, the calculation module 202 may be specifically configured to: obtain the maximum eigenvalue of the autocorrelation matrix of the input vector; and calculate the offset parameter based on the step size, the filter order, and the maximum eigenvalue.

[0111] In one embodiment, the calculation module 202 may be specifically configured to: transpose the weight vector to obtain the transposed vector; and calculate the product between the transposed vector and the input vector as the actual output vector.

[0112] Figure 6 This is a schematic diagram of the structure of a metering box provided in an exemplary embodiment of this application. Figure 6 As shown, the metering box includes: a metering box body, inside which are installed a smoke sensor, a temperature and humidity sensor, a controller, a measuring switch, an energy meter, and a current transformer. The smoke sensor, temperature and humidity sensor, energy meter, measuring switch, energy meter, and current transformer are electrically connected to the controller. The output terminal of the current transformer is electrically connected to the measuring switch. The smoke sensor is used to detect smoke inside the metering box body, the temperature and humidity sensor is used to detect the temperature and humidity inside the metering box body, the energy meter detects the current value transmitted by the transformer, the controller is used to execute any of the metering box monitoring methods, the current transformer is used to detect the three-phase output current value of the energy meter, and the controller controls the opening or closing of the measuring switch.

[0113] In this embodiment, the measuring switch is equipped with a current transformer sampling interface to collect three-phase incoming current. A voltage transformer or current transformer can be installed inside the measuring switch to collect the three-phase incoming current. A smoke sensor, temperature and humidity sensor, and water immersion sensor are installed inside the metering box. The measuring switch monitors the environmental status inside the metering box in real time, automatically issues warnings for environmental anomalies, and proactively pushes alerts to on-site maintenance personnel for timely handling. The smoke sensor detects smoke inside the metering box, while the temperature and humidity sensor detects humidity and temperature. The water immersion sensor detects the water level inside the metering box. The management unit communicates with the controller and incorporates a pyroelectric infrared human body detection sensor, a strong magnetic induction module, an evidence-collecting camera, and a BeiDou positioning module. The BeiDou positioning module features high sensitivity, low power consumption, and miniaturization. Its extremely high tracking sensitivity greatly expands its positioning coverage, meeting the requirements for high-precision positioning of equipment. Combined with the sensing module, it automatically reports fault events, enabling repair personnel to determine the optimal path and provide real-time map navigation. The pyroelectric infrared human body detection sensor can detect whether personnel are operating in front of the equipment. When unauthorized intrusion occurs, the protection module triggers the evidence-collecting camera to take continuous photos, store them on the SD card, and upload them to the main station via the sensing module, triggering an alert. In actual operation, the strong magnetic induction module detects the presence of strong magnetic interference, enabling real-time monitoring of abnormal behaviors such as unauthorized opening of boxes and electricity theft.

[0114] In addition, an accelerometer sensor is installed inside the metering box, featuring low power consumption, high shock resistance, and programmable standby wake-up functionality, enabling functions such as tilt detection, vibration detection, and movement detection. A door lock control module is also installed inside the metering box, providing intelligent lock management and control functions, supporting remote unlocking and local Bluetooth authentication unlocking, and providing real-time feedback on the door lock's open / closed status. The management unit uses broadband power line carrier (HPLC) for uplink communication with the distribution area concentrator; the downlink communication RS-485 interface is used for smart meter reading, supporting DL / T645 and DL / T698.4 communication protocols; a low-power Bluetooth module is configured at the near end, supporting short-range wireless and local maintenance and upgrades.

[0115] Figure 7 A block diagram of an electronic device according to an embodiment of this application is illustrated.

[0116] like Figure 7 As shown, the electronic device 10 includes one or more processors 11 and memory 12.

[0117] The processor 11 may be a central processing unit (CPU) or other form of processing unit with data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device 10 to perform desired functions.

[0118] The memory 12 may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 11 may execute the program instructions to implement the monitoring methods of the metering box in the various embodiments of this application described above, and / or other desired functions. Various contents such as input signals, signal components, and noise components may also be stored in the computer-readable storage medium.

[0119] In one example, the electronic device 10 may also include an input device 13 and an output device 14, which are interconnected via a bus system and / or other forms of connection mechanism (not shown).

[0120] When the electronic device is a standalone device, the input device 13 can be a communication network connector for receiving the collected input signals from the first device and the second device.

[0121] In addition, the input device 13 may also include, for example, a keyboard, a mouse, etc.

[0122] The output device 14 can output various information to the outside, including determined distance information, direction information, etc. The output device 14 may include, for example, a display, a speaker, a printer, and a communication network and its connected remote output devices, etc.

[0123] Of course, for the sake of simplicity, Figure 7 Only some of the components of the electronic device 10 relevant to this application are shown in this illustration; components such as buses, input / output interfaces, etc., are omitted. In addition, the electronic device 10 may include any other suitable components depending on the specific application.

[0124] The computer program product can be written in any combination of one or more programming languages ​​to perform the operations of the embodiments of this application. The programming languages ​​include object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0125] The computer-readable storage medium may be any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may, for example, include, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatuses, or devices, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: electrical connections having one or more wires, portable disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0126] The above description has been given for purposes of illustration and description. Furthermore, this description is not intended to limit the embodiments of this application to the forms disclosed herein. Although numerous exemplary aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations thereof.

Claims

1. A method for monitoring a metering box, characterized in that, include: Obtain historical environmental data; Determine the optimal tap weight based on the historical environmental data and the expected response; Based on the optimal tap weights and the historical environmental data, predict the forecast environmental data for the current moment; If the predicted environmental data meets the fault judgment conditions, the measurement switch is turned on to disconnect the internal circuit of the metering box.

2. The monitoring method for the metering box according to claim 1, characterized in that, The step of controlling the measurement switch to turn on if the predicted environmental data meets the fault judgment conditions includes: Obtain the three-phase incoming current of the metering box at the current moment; Obtain the three-phase outgoing current of the metering box at the current moment; Calculate the differential current of each phase based on the three-phase incoming current and the three-phase outgoing current; If the values ​​corresponding to the predicted environmental data are all greater than the preset environmental threshold and the differential current of each phase is less than the preset differential current threshold, then the measurement switch is controlled to turn on.

3. The monitoring method for the metering box according to claim 2, characterized in that, The process of obtaining the three-phase outgoing current of the metering box at the current moment includes: Obtain the three-phase incoming current of the metering box at the first historical moment; The three-phase incoming current of the metering box is obtained at a second historical moment; wherein the second historical moment is later than the first historical moment; Based on the three-phase incoming current of the metering box at the current moment, the three-phase incoming current of the metering box at the first historical moment, and the three-phase incoming current of the metering box at the second historical moment, determine whether to initiate the fault judgment operation. If the fault diagnosis operation is initiated, the three-phase outgoing current of the metering box at the current moment is obtained.

4. The monitoring method for the metering box according to claim 3, characterized in that, The step of determining whether to initiate a fault diagnosis operation based on the three-phase incoming current of the metering box at the current moment, the three-phase incoming current of the metering box at the first historical moment, and the three-phase incoming current of the metering box at the second historical moment includes: Calculate the first difference between the incoming current of each phase of the metering box at the current moment and its corresponding incoming current at the first historical moment; Calculate the second difference between the incoming current of each phase of the metering box at the first historical moment and its corresponding incoming current at the second historical moment. Calculate the third difference between the first difference and the second difference; If the third difference satisfies the difference judgment condition, then the fault judgment operation is initiated.

5. The monitoring method for the metering box according to claim 4, characterized in that, If the third difference satisfies the difference judgment condition, then determining to initiate the fault judgment operation includes: Obtain the maximum current value of the electricity meter in the metering box; If the third difference is greater than the maximum current value, then the fault diagnosis operation is initiated.

6. The monitoring method for the metering box according to claim 1, characterized in that, The process of determining the optimal tap weight based on the historical environmental data and the expected response includes: Determine the filter order and step size; Initialize the weights of the filter order taps to 0 and construct a weight vector; The historical environmental data is used to construct an input vector; Arrange the expected responses into a column vector in chronological order to obtain the expected response vector; The actual output vector is calculated based on the weight vector and the input vector. The deviation vector is calculated based on the actual output vector and the expected response vector. Based on the weight vector, the bias vector, the step size, and the input vector, estimate the tap weight vector of the weight vector at the next time step; Obtain the offset parameters; If the misalignment parameter is less than a preset misalignment threshold, then the tap weight vector at the next moment of the weight vector is determined as the optimal tap weight.

7. The monitoring method for the metering box according to claim 6, characterized in that, The acquisition of the offset parameters includes: Obtain the largest eigenvalue of the autocorrelation matrix of the input vector; The offset parameter is calculated based on the step size, the filter order, and the maximum eigenvalue.

8. The monitoring method for the metering box according to claim 6, characterized in that, The step of calculating the actual output vector based on the weight vector and the input vector includes: The weight vector is transposed to obtain the transposed vector; The actual output vector is calculated by multiplying the transposed vector with the input vector.

9. A monitoring device for a metering box, characterized in that, include: The acquisition module is used to acquire historical environmental data; The calculation module is used to determine the optimal tap weight based on the historical environmental data and the expected response; The determination module is used to predict the predicted environment data at the current moment based on the optimal tap weight and the historical environment data. The control module is used to control the measurement switch to turn on and disconnect the internal circuit of the metering box if the predicted environmental data meets the fault judgment conditions.

10. A measuring box, characterized in that, include: The metering box body contains a smoke sensor, a temperature and humidity sensor, a controller, a measuring switch, an energy meter, and a current transformer. The smoke sensor, temperature and humidity sensor, energy meter, measuring switch, and current transformer are electrically connected to the controller. The output terminal of the current transformer is electrically connected to the measuring switch. The smoke sensor detects smoke inside the metering box body. The temperature and humidity sensor detects the temperature and humidity inside the metering box body. The energy meter detects the current value transmitted by the transformer. The controller executes the monitoring method for the metering box according to any one of claims 1-8. The current transformer detects the three-phase output current value of the energy meter. The controller controls the opening and closing of the measuring switch.

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