Research on Data Cleansing Method of Elevator Based on Time Series Data
In order to perform the data cleaning of aperiodic,non-Gaussian and intermittent traction type elevator and troubleshoot the abnormal data in the process of elevator operation,this paper proposes a data cleaning mode of modified long short-term memory network.Based on the IoT technology using a database to store the time-series data of abnormal data cleaning,the time series data of different lengths are extracted for division and filling,the long and short time neural network is used for modeling,and the initial abnormal data detection and cleaning are carried out.Data cleaning and data optimization are completed before the realization of fault prediction,life analysis and visualization of the elevator fault system.
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