Motor controller service life evaluation method and system, storage medium and terminal
The invention discloses a motor controller service life evaluation method and system, a storage medium and a terminal. The method comprises the following steps: acquiring historical operation data of a motor controller; selecting the number of clusters; randomly selecting data points of which the nu...
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creator | YANG GUOLIANG XU TAO SHI GUANG WANG ZILONG YANG TIAN CHU HONGCHAO TAN JINCHAO MENG CHUNJIANG LIU GUOQIANG XING YALONG WEI ZHICHENG ZHANG PENGQIAO FENG YANDONG |
description | The invention discloses a motor controller service life evaluation method and system, a storage medium and a terminal. The method comprises the following steps: acquiring historical operation data of a motor controller; selecting the number of clusters; randomly selecting data points of which the number is the same as the clustering number from the historical operation data as clustering centers; calculating the distance from each data point to the clustering center; distributing each data point to a cluster represented by the clustering center closest to the data point according to the calculated distance; updating the clustering center by using a K-means clustering algorithm; judging whether convergence is carried out or the maximum number of iterations is reached, and if not, repeating the steps; if yes, outputting a clustering result; and evaluating the service life of the motor controller for each cluster according to a clustering result. According to the method, the K-means clustering algorithm and the |
format | Patent |
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The method comprises the following steps: acquiring historical operation data of a motor controller; selecting the number of clusters; randomly selecting data points of which the number is the same as the clustering number from the historical operation data as clustering centers; calculating the distance from each data point to the clustering center; distributing each data point to a cluster represented by the clustering center closest to the data point according to the calculated distance; updating the clustering center by using a K-means clustering algorithm; judging whether convergence is carried out or the maximum number of iterations is reached, and if not, repeating the steps; if yes, outputting a clustering result; and evaluating the service life of the motor controller for each cluster according to a clustering result. 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The method comprises the following steps: acquiring historical operation data of a motor controller; selecting the number of clusters; randomly selecting data points of which the number is the same as the clustering number from the historical operation data as clustering centers; calculating the distance from each data point to the clustering center; distributing each data point to a cluster represented by the clustering center closest to the data point according to the calculated distance; updating the clustering center by using a K-means clustering algorithm; judging whether convergence is carried out or the maximum number of iterations is reached, and if not, repeating the steps; if yes, outputting a clustering result; and evaluating the service life of the motor controller for each cluster according to a clustering result. 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The method comprises the following steps: acquiring historical operation data of a motor controller; selecting the number of clusters; randomly selecting data points of which the number is the same as the clustering number from the historical operation data as clustering centers; calculating the distance from each data point to the clustering center; distributing each data point to a cluster represented by the clustering center closest to the data point according to the calculated distance; updating the clustering center by using a K-means clustering algorithm; judging whether convergence is carried out or the maximum number of iterations is reached, and if not, repeating the steps; if yes, outputting a clustering result; and evaluating the service life of the motor controller for each cluster according to a clustering result. According to the method, the K-means clustering algorithm and the</abstract><oa>free_for_read</oa></addata></record> |
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subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING CONTROL OR REGULATING SYSTEMS IN GENERAL CONTROLLING COUNTING ELECTRIC DIGITAL DATA PROCESSING FUNCTIONAL ELEMENTS OF SUCH SYSTEMS MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS ORELEMENTS PHYSICS REGULATING |
title | Motor controller service life evaluation method and system, storage medium and terminal |
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