WO2021237579A1 - 基于统计分析的直线电机定子异物粘连故障诊断方法 - Google Patents

基于统计分析的直线电机定子异物粘连故障诊断方法 Download PDF

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WO2021237579A1
WO2021237579A1 PCT/CN2020/092966 CN2020092966W WO2021237579A1 WO 2021237579 A1 WO2021237579 A1 WO 2021237579A1 CN 2020092966 W CN2020092966 W CN 2020092966W WO 2021237579 A1 WO2021237579 A1 WO 2021237579A1
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air gap
value
foreign body
linear motor
stator
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PCT/CN2020/092966
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English (en)
French (fr)
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魏世通
王慧
邢宗义
李福芳
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南京睿速轨道交通科技有限公司
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B21/00—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant
    • G01B21/02—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant for measuring length, width, or thickness
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B21/00—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant
    • G01B21/16—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant for measuring distance of clearance between spaced objects
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/34—Testing dynamo-electric machines

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  • the invention relates to the technical field of motor fault diagnosis, in particular to a linear motor stator foreign body adhesion fault diagnosis method based on statistical analysis.
  • a linear motor is a motor that can directly convert electrical energy into linear motion. It can directly obtain linear motion without a conversion mechanism. There is no wear and tear of transmission machinery. The structure is simple, the response is fast, and the operation and maintenance are simple. Therefore, it is used in industrial equipment, logistics and transportation. , Information and automation systems, transportation and other fields have been widely used.
  • the linear motor stator is exposed to the external environment, which may cause foreign objects such as plastic sheets in the environment to adhere to some of the teeth, resulting in foreign object adhesion failure, which affects driving safety.
  • the purpose of the present invention is to provide an efficient and accurate method for diagnosing the stator foreign body adhesion fault of a linear motor based on statistical analysis, which can realize the fault diagnosis of the stator foreign body adhesion fault.
  • the technical solution to achieve the objective of the present invention is: a method for diagnosing foreign body adhesion faults in a linear motor stator based on statistical analysis, including the following steps:
  • Step 1 Install a distance measuring sensor under the linear motor stator, and use the distance measuring sensor to measure the air gap value and slot wedge value of the motor stator;
  • Step 2 Perform statistical analysis on the measurement data of the ranging sensor, and judge whether the linear motor has a stator foreign body adhesion failure by judging whether the slot wedge value is lower than the air gap average value.
  • the distance measuring sensor described in step 1 is arranged in the gap between two sleeper rails, and the probe of the distance measuring sensor is vertically upward and perpendicular to the running direction of the train.
  • stator air gap value of the motor described in step 1 is the height of the boss on both sides of the stator groove from the sensor, and the slot wedge value is the height of the bottom of the stator groove from the sensor.
  • step 2 the measurement data of the ranging sensor is statistically analyzed, and by judging whether the slot wedge value is lower than the average value of the air gap, it is judged whether the linear motor has a stator foreign body adhesion failure, which is specifically as follows:
  • Is the average value of the normal air gap Is the number of normal air gap values remaining after excluding abnormal air gap values, Is the air gap value corresponding to the i-th air gap;
  • the measurement index of the foreign body adhesion failure of the stator includes the height H of the foreign body and the width W of the foreign body, wherein:
  • the air gap height When a foreign body adhesion failure occurs, the air gap height will become smaller. The smaller the air gap height, the larger the foreign body height. Therefore, the difference between the normal air gap average value and the minimum air gap value is used to measure the foreign body height H:
  • MIN() represents the minimum value operation
  • the present invention has significant advantages as follows: (1) For trains driven by linear motors, an air gap online detection/monitoring system is installed on the line, and the online air gap waveform is analyzed to determine whether there is a motor Stator foreign body adhesion failure; (2) Based on the statistical analysis method to judge the motor stator foreign body adhesion failure, a strict mathematical derivation is provided, and the judgment is made through the slot wedge value and the air gap value, and the result is accurate and reliable.
  • Fig. 1 is a flowchart of the method for diagnosing the foreign body adhesion fault of the linear motor stator based on statistical analysis of the present invention.
  • Figure 2 is a schematic diagram of the positional relationship between the ranging sensor, the stator air gap and the slot wedge.
  • Fig. 3 is a schematic diagram of the air gap slot gap measurement value obtained by the measurement of the stator air gap and the slot gap distance by the sensor.
  • Figure 4 is a schematic diagram of the air gap and slot gap measurement values when the motor stator foreign body adhesion failure occurs.
  • the method for diagnosing the foreign body adhesion fault of linear motor stator based on statistical analysis of the present invention includes the following steps:
  • Step 1 Install a distance measuring sensor under the linear motor stator, and use the distance measuring sensor to measure the air gap value and slot wedge value of the motor stator;
  • Step 2 Perform statistical analysis on the measurement data of the ranging sensor, and judge whether the linear motor has a stator foreign body adhesion failure by judging whether the slot wedge value is lower than the air gap average value.
  • the distance measuring sensor described in step 1 is arranged in the gap between two sleeper rails, and the probe of the distance measuring sensor is vertically upward and perpendicular to the running direction of the train.
  • the motor stator air gap value in step 1 is the height of the boss on both sides of the stator groove from the sensor, and the slot wedge value is the height of the bottom of the stator groove from the sensor.
  • step 2 the measurement data of the ranging sensor is statistically analyzed, and by judging whether the slot wedge value is lower than the average value of the air gap, it is judged whether the linear motor has a stator foreign body adhesion failure, which is specifically as follows:
  • Is the average value of the normal air gap Is the number of normal air gap values remaining after excluding abnormal air gap values, Is the air gap value corresponding to the i-th air gap;
  • the measurement index of the foreign body adhesion failure of the stator includes the height H of the foreign body and the width W of the foreign body, wherein:
  • the air gap height When a foreign body adhesion failure occurs, the air gap height will become smaller. The smaller the air gap height, the larger the foreign body height. Therefore, the difference between the normal air gap average value and the minimum air gap value is used to measure the foreign body height H:
  • MIN() represents the minimum value operation
  • the distance measuring sensor is installed under the linear motor stator. When the stator passes over the sensor, the sensor can measure the distance between the stator air gap and the slot gap.
  • the air gap and slot gap measurement value output by a single sensor is shown in Figure 3.
  • the slot wedge value or air gap value of each tooth of the motor stator remains basically unchanged, and its change value is only affected by the overhang of the stator plate and is very small; when a foreign body adhesion failure occurs, the slot wedge value will occur A large change and lower than the normal air gap average value, as shown in Figure 4, so whether the slot wedge value is lower than the normal air gap average value can be used as the basis for judging whether a foreign body adhesion failure occurs.
  • N the number of slot wedges and the number of air gaps are 80
  • the i-th slot The slot wedge value corresponding to the wedge is x i
  • the air gap value corresponding to the i-th air gap is
  • the present invention uses the average value-variance method to eliminate abnormal air gap values (this method is a commonly used method for removing abnormal data and may not be a patent right), that is, data that exceeds the average value ⁇ 3 times the standard deviation is abnormal data.
  • this method is a commonly used method for removing abnormal data and may not be a patent right
  • the remaining normal air gap value is calculated by the average value.
  • the slot wedge value x i is obviously smaller than the average value of the normal air gap
  • x 15 20.729
  • x 17 16.061
  • x 18 18.148
  • x 19 16.928,
  • x 22 14.386,
  • x 23 14.135,
  • x 24 14.117
  • x 25 14.535
  • x 26 15.934,
  • the present invention uses the following two indicators to measure: the height H of the foreign body and the width W of the foreign body.
  • the H value to measure the height of the foreign body is:
  • the present invention is directed to trains driven by linear motors.
  • An air gap online detection/monitoring system is installed on the line.
  • By analyzing the online air gap waveforms it is determined whether there is a motor stator foreign body adhesion failure; based on statistical analysis methods
  • the judgment of the foreign body adhesion failure of the motor stator provides strict mathematical derivation. The judgment is made through the slot wedge value and the air gap value, and the result is accurate and reliable.

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  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Manufacture Of Motors, Generators (AREA)

Abstract

一种基于统计分析的直线电机定子异物粘连故障诊断方法，该方法包括以下步骤：在直线电机定子下方安装测距传感器，利用测距传感器进行电机定子气隙值以及槽楔值的测量；将测距传感器的测量数据进行统计分析，通过判断槽楔值是否低于气隙均值，来确定直线电机是否发生定子异物粘连故障。该方法通过判断槽楔值是否低于正常气隙均值，作为定子是否发生异物粘连故障的判断依据，提高了故障诊断结果的准确性。

Description

基于统计分析的直线电机定子异物粘连故障诊断方法 技术领域
本发明涉及电机故障诊断技术领域，特别是一种基于统计分析的直线电机定子异物粘连故障诊断方法。
背景技术
直线电机是一种能将电能直接转换成直线运动的电机，它无需转换机构即可直接获得直线运动，没有传动机械的磨损，结构简单，响应快速，操作维护简单，因此在工业设备、物流运输、信息与自动化系统、交通等领域得到了广泛应用。
直线电机定子暴露在外部环境中，可能会导致环境中的塑料片等异物粘连在部分齿上，形成异物粘连故障，影响行车安全。
针对直线电机的故障诊断，较多集中在气隙偏心故障、绕组匝间短路等方向，而针对现场运行中经常遇到的电机定子异物粘连故障，尚未有明确的诊断方法，目前一般是在电机停机静止状态下，采用人工目视检查，可靠性差且漏检率高。针对采用直线电机驱动的列车，且在线路上安装了气隙在线检测/监测系统，则可以通过对在线气隙波形的分析，人工判定是否存在电机定子异物粘连故障，但判定依据仍是靠经验，存在劳动强度大且可靠性差等问题。
发明目的
本发明的目的在于提供一种高效、准确的基于统计分析的直线电机定子异物粘连故障诊断方法，可以实现定子异物粘连故障的故障诊断。
实现本发明目的的技术解决方案为：一种基于统计分析的直线电机定子异物粘连故障诊断方法，包括以下步骤：
步骤1、在直线电机定子下方安装测距传感器，利用测距传感器进行电机定子气隙值以及槽楔值的测量；
步骤2、将测距传感器的测量数据进行统计分析，通过判断槽楔值是否低于气隙均值，判断直线电机是否发生定子异物粘连故障。
进一步地，针对采用直线电机驱动的列车，步骤1所述测距传感器设置于两个枕轨之间的空隙，测距传感器的探头竖直向上，垂直于列车运行方向。
进一步地，步骤1所述电机定子气隙值即定子凹槽两侧凸台距离传感器的高度，槽 楔值即定子凹槽底部距离传感器的高度。
进一步地，步骤2所述的将测距传感器的测量数据进行统计分析，通过判断槽楔值是否低于气隙均值，判断直线电机是否发生定子异物粘连故障，具体如下：
采用平均值-方差法进行异常气隙值的剔除，即超过平均值±3倍标准差的数据为异常数据；
剔除异常气隙值后，对剩下的正常气隙值进行平均值计算：
Figure PCTCN2020092966-appb-000001
其中
Figure PCTCN2020092966-appb-000002
为正常气隙值的平均值，
Figure PCTCN2020092966-appb-000003
为剔除异常气隙值后剩余的正常气隙值的数量，
Figure PCTCN2020092966-appb-000004
为第i个气隙对应的气隙值；
如果第i个槽楔对应的槽楔值小于正常气隙平均值
Figure PCTCN2020092966-appb-000005
则发生异物粘连故障：
Figure PCTCN2020092966-appb-000006
其中
Figure PCTCN2020092966-appb-000007
表示至少存在一个序号i，使得
Figure PCTCN2020092966-appb-000008
进一步地，所述定子异物粘连故障的衡量指标包括异物高度H和异物宽度W，其中：
发生异物粘连故障时，气隙高度会变小，气隙高度变的越小代表异物高度越大，因此采用正常气隙平均值与最小气隙值的差值来衡量异物高度H：
Figure PCTCN2020092966-appb-000009
其中MIN()表示取最小值操作，
Figure PCTCN2020092966-appb-000010
为第i个气隙对应的气隙值；
异物宽度W为满足
Figure PCTCN2020092966-appb-000011
条件的所有气隙数量之和。
本发明与现有技术相比，其显著优点为：(1)针对采用直线电机驱动的列车，在线路上安装了气隙在线检测/监测系统，通过对在线气隙波形的分析，判定是否存在电机定子异物粘连故障；(2)基于统计分析方法来判断电机定子异物粘连故障，提供了严格的数学推导，通过槽楔值与气隙值进行判断，结果准确可靠。
附图说明
图1是本发明基于统计分析的直线电机定子异物粘连故障诊断方法的流程图。
图2是测距传感器与定子气隙、槽楔之间的位置关系示意图。
图3是通过传感器对定子气隙与槽隙距离的测量得出的气隙槽隙测量值示意图。
图4是发生电机定子异物粘连故障时的气隙与槽隙测量值示意图。
具体实施方式
结合图1，本发明基于统计分析的直线电机定子异物粘连故障诊断方法，包括以下步骤：
步骤1、在直线电机定子下方安装测距传感器，利用测距传感器进行电机定子气隙值以及槽楔值的测量；
步骤2、将测距传感器的测量数据进行统计分析，通过判断槽楔值是否低于气隙均值，判断直线电机是否发生定子异物粘连故障。
进一步地，针对采用直线电机驱动的列车，步骤1所述测距传感器设置于两个枕轨之间的空隙，测距传感器的探头竖直向上，垂直于列车运行方向。
结合图2，步骤1所述电机定子气隙值即定子凹槽两侧凸台距离传感器的高度，槽楔值即定子凹槽底部距离传感器的高度。
进一步地，步骤2所述的将测距传感器的测量数据进行统计分析，通过判断槽楔值是否低于气隙均值，判断直线电机是否发生定子异物粘连故障，具体如下：
采用平均值-方差法进行异常气隙值的剔除，即超过平均值±3倍标准差的数据为异常数据；
剔除异常气隙值后，对剩下的正常气隙值进行平均值计算：
Figure PCTCN2020092966-appb-000012
其中
Figure PCTCN2020092966-appb-000013
为正常气隙值的平均值，
Figure PCTCN2020092966-appb-000014
为剔除异常气隙值后剩余的正常气隙值的数量，
Figure PCTCN2020092966-appb-000015
为第i个气隙对应的气隙值；
如果第i个槽楔对应的槽楔值小于正常气隙平均值
Figure PCTCN2020092966-appb-000016
则发生异物粘连故障：
Figure PCTCN2020092966-appb-000017
其中
Figure PCTCN2020092966-appb-000018
表示至少存在一个序号i，使得
Figure PCTCN2020092966-appb-000019
进一步地，所述定子异物粘连故障的衡量指标包括异物高度H和异物宽度W，其中：
发生异物粘连故障时，气隙高度会变小，气隙高度变的越小代表异物高度越大，因此采用正常气隙平均值与最小气隙值的差值来衡量异物高度H：
Figure PCTCN2020092966-appb-000020
其中MIN()表示取最小值操作，
Figure PCTCN2020092966-appb-000021
为第i个气隙对应的气隙值；
异物宽度W为满足
Figure PCTCN2020092966-appb-000022
条件的所有气隙数量之和。
在直线电机定子下方安装测距传感器，当定子经过传感器上方时，传感器可以实现 对定子气隙与槽隙距离的测量，单个传感器输出的气隙槽隙测量值如图3所示。
当电机处于正常工作状态时，电机定子各个齿的槽楔值或气隙值基本保持不变，其变化值仅仅受定子板悬垂影响且非常小；当发生异物粘连故障时，槽楔值会发生很大变化且低于正常的气隙均值，如图4所示，因此可以将槽楔值是否低于正常气隙均值作为是否发生异物粘连故障的判断依据。
在电机定子异物粘连故障时，由于存在部分齿被异物遮挡，因此会造成部分气隙值异常，也就是说对于N个气隙值，存在若干个气隙值会明显小于其它正常气隙值，需要在计算正常气隙值时去除。
下面结合具体实施例对本发明做进一步详细说明。
实施例
结合图4，本实施例提供一种直线电机的齿数对N为80，即槽楔数量和气隙数量为80，则i＝1，2，…80表示槽楔或气隙序号，第i个槽楔对应的槽楔值为x i，第i个气隙对应的气隙值为
Figure PCTCN2020092966-appb-000023
本发明采用平均值-方差法进行异常气隙值的剔除(该方法为常用异常数据剔除方法，可不作为专利权利)，即超过平均值±3倍标准差的数据为异常数据。按照上述发明方法中所示，剔除异物遮挡造成的气隙异常值后，剩下的正常气隙值进行平均值计算所得的
Figure PCTCN2020092966-appb-000024
如下：
Figure PCTCN2020092966-appb-000025
其中被剔除的气隙值序号i＝17,18,19,20,21,22,23,24,25,26,27,28；那么，剩下的正常气隙值的个数
Figure PCTCN2020092966-appb-000026
结合图4，槽楔值x i明显有小于正常气隙平均值
Figure PCTCN2020092966-appb-000027
如x 15＝20.729,x 17＝16.061,x 18＝18.148,x 19＝16.928,x 20＝15.811,x 21＝14.684,x 22＝14.386,x 23＝14.135,x 24＝14.117,x 25＝14.535,x 26＝15.934,x 27＝16.235,x 28＝17.133。
以上序列的槽楔值明显满足
Figure PCTCN2020092966-appb-000028
那么可以判断此电机发生异物粘连故障。
在确定发生了异物粘连故障时，需要对故障严重程度进行衡量，本发明采用如下两 个指标来衡量：异物高度H和异物宽度W。
结合图4，发生异物粘连故障时，气隙高度会变小，气隙高度变的越小代表异物高度越大，因此实施例中得到采用正常气隙平均值与最小气隙值的差值来衡量异物高度H值为：
Figure PCTCN2020092966-appb-000029
其中最小气隙值序号i为25，那么
Figure PCTCN2020092966-appb-000030
按照异物宽度W的定义，W为满足
Figure PCTCN2020092966-appb-000031
条件的所有气隙数量之和,那么异物宽度W＝13。
综上所述，本发明针对采用直线电机驱动的列车，在线路上安装了气隙在线检测/监测系统，通过对在线气隙波形的分析，判定是否存在电机定子异物粘连故障；基于统计分析方法来判断电机定子异物粘连故障，提供了严格的数学推导，通过槽楔值与气隙值进行判断，结果准确可靠。

Claims (5)

  1. 一种基于统计分析的直线电机定子异物粘连故障诊断方法，其特征在于，包括以下步骤：
    步骤1、在直线电机定子下方安装测距传感器，利用测距传感器进行电机定子气隙值以及槽楔值的测量；
    步骤2、将测距传感器的测量数据进行统计分析，通过判断槽楔值是否低于气隙均值，判断直线电机是否发生定子异物粘连故障。
  2. 根据权利要求1所述的基于统计分析的直线电机定子异物粘连故障诊断方法，其特征在于，针对采用直线电机驱动的列车，步骤1所述测距传感器设置于两个枕轨之间的空隙，测距传感器的探头竖直向上，垂直于列车运行方向。
  3. 根据权利要求1所述的基于统计分析的直线电机定子异物粘连故障诊断方法，其特征在于，步骤1所述电机定子气隙值即定子凹槽两侧凸台距离传感器的高度，槽楔值即定子凹槽底部距离传感器的高度。
  4. 根据权利要求1、2或3所述的基于统计分析的直线电机定子异物粘连故障诊断方法，其特征在于，步骤2所述的将测距传感器的测量数据进行统计分析，通过判断槽楔值是否低于气隙均值，判断直线电机是否发生定子异物粘连故障，具体如下：
    采用平均值-方差法进行异常气隙值的剔除，即超过平均值±3倍标准差的数据为异常数据；
    剔除异常气隙值后，对剩下的正常气隙值进行平均值计算：
    Figure PCTCN2020092966-appb-100001
    其中
    Figure PCTCN2020092966-appb-100002
    为正常气隙值的平均值，
    Figure PCTCN2020092966-appb-100003
    为剔除异常气隙值后剩余的正常气隙值的数量，
    Figure PCTCN2020092966-appb-100004
    为第i个气隙对应的气隙值；
    如果第i个槽楔对应的槽楔值小于正常气隙平均值
    Figure PCTCN2020092966-appb-100005
    则发生异物粘连故障：
    Figure PCTCN2020092966-appb-100006
    其中
    Figure PCTCN2020092966-appb-100007
    表示至少存在一个序号i，使得
    Figure PCTCN2020092966-appb-100008
  5. 根据权利要求1所述的基于统计分析的直线电机定子异物粘连故障诊断方法，其特征在于，所述定子异物粘连故障的衡量指标包括异物高度H和异物宽度W，其中：
    发生异物粘连故障时，气隙高度会变小，气隙高度变的越小代表异物高度越大，因此采用正常气隙平均值与最小气隙值的差值来衡量异物高度H：
    Figure PCTCN2020092966-appb-100009
    其中MIN()表示取最小值操作，
    Figure PCTCN2020092966-appb-100010
    为第i个气隙对应的气隙值；
    异物宽度W为满足
    Figure PCTCN2020092966-appb-100011
    条件的所有气隙数量之和。
PCT/CN2020/092966 2020-05-26 2020-05-28 基于统计分析的直线电机定子异物粘连故障诊断方法 WO2021237579A1 (zh)

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