In-operation electric energy meter batch fault diagnosis method based on operation characteristics of dismantled and returned meter
A technology of operating characteristics and fault diagnosis, applied in the direction of measuring electrical variables, instruments, measuring devices, etc., can solve the problem of low accuracy of failure rate of electric energy meters, achieve high accuracy and prevent harm
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Embodiment 1
[0033] A method for diagnosing faults in batches of in-transit electric energy meters based on the operation characteristics of disassembled meters, comprising the following steps:
[0034] S1: Use the data cleaning method to process the missing value and abnormal value of the dismantled electric energy meter sorting data and collected abnormal data;
[0035] S2: Input the processed data into the LASSO regression model for automatic learning, extract the regular characteristics of the failure rate of the dismantled electric energy meter batches, and build a fault diagnosis model;
[0036] S3: Use the fault diagnosis model to diagnose the batch failure rate of the electric energy meter in operation.
[0037] In S1, the processed data is used as the independent variable of the LASSO regression model, and the independent variables include the average number of occurrences of uneven power values in this batch, the average number of occurrences of flying away of this batch of ele...
Embodiment 2
[0058] like figure 1 As shown, the method for diagnosing faults in batches of electric energy meters in operation based on the operating characteristics of the dismantled electric energy meters in the embodiment of the present invention differs from Embodiment 1 in that it includes the following steps: (1) Obtaining the sorting result data of electric energy meters that are folded back , Collect abnormal (operating characteristics) data and electric energy meter archive data; (2) Process the above data, including data cleaning, data conversion and data structure; (3) Build a model with the processed data, and use LASSO to build a regression (4) Use the model to diagnose batch failures of electric energy meters in operation.
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