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Abnormal state detection method and detection system of mechanical parts

A technology of mechanical components and detection methods, applied in the field of data analysis, can solve problems such as false positive detection errors, and achieve the effects of improving detection, avoiding detection anomalies, and improving signal-to-noise ratio.

Active Publication Date: 2020-05-12
CYBERINSIGHT TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In view of the problems in the above-mentioned prior art that easily cause false alarms or large detection errors, the present invention provides a method and system for abnormal detection of mechanical components based on TF-IDF weighted data to amplify the weight of abnormal points

Method used

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  • Abnormal state detection method and detection system of mechanical parts
  • Abnormal state detection method and detection system of mechanical parts

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Embodiment 1

[0036]This embodiment provides a method for abnormal detection of mechanical parts, such as figure 1 and figure 2 As shown in Fig. 1 , the first part to be tested is the bearing set on the motor, and the detected value is the temperature value. For the abnormality of the generator bearing temperature, the temperature rise of the front and rear bearings of the generator can be used as a feature.

[0037] The whole method includes the training step of calculating the comparison reference amount and the prediction step of using the data calculated in the training step as a reference and basis for calculation, wherein the training step is specifically:

[0038] (1) Obtain the monitoring data of the equipment sensor, and select a group of data of earlier equipment and larger data volume as the training data.

[0039] (2) Then the characteristic variable is discretized with a fixed width or a non-fixed width. With a width of 10, the value of the bearing temperature range of [20,1...

Embodiment 2

[0052] A detection system applying the above detection method, including a data acquisition module, a data transmission module and a data analysis module, the data acquisition module is a sensor arranged on a mechanical component, and the characteristic value is collected by the sensor and passed through the data transmission module Pass it to the data analysis module for calculation and judge whether it is abnormal according to the preset threshold.

Embodiment 3

[0054] This embodiment is an example of using simulated data to preview and deduce the simulated calculation process, taking the training process as an example:

[0055] 1. Assuming data data, wherein the characteristic value is temperature rise, two temperature monitoring points are set on the target component, and then the temperature data is monitored in real time.

[0056] time T 1

T 2

2018-01-01 01:00:00 51.2 48.3 2018-01-01 01:00:01 52.1 49.0 2018-01-01 01:00:02 54.3 49.3

[0057] Here is just an example of the first three sets of data, that is to say, the temperature data is collected and recorded every second, and then through T 1 -T 2 = temperature rise to calculate.

[0058] 2. Discretize the temperature rise data. In this example, the temperature rise dispersion width (bin) is taken as 0.5, such as temperature rise 1.3, after discretization is 1, temperature rise 2.83, after discretization is 3, temperature rise 1.57, after...

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Abstract

The invention belongs to the technical field of data analysis and discloses an abnormal state detection method for a mechanical part. The abnormal state detection method includes the steps of selecting and collecting the characteristic value of the mechanical part outside a monitoring section and obtaining a reference value through TF-IDF weighted algorithm, collecting the real-time characteristicvalue in the monitoring section, substituting with the reference value to obtain a result, and comparing the result with a set threshold value to judge whether the abnormality occurs. According to the method, the TF-IDF calculation method is used for processing the discretized characteristic values, the weight of the abnormal points can be effectively enlarged, and the weak anomaly detection canbe improved.

Description

technical field [0001] The invention belongs to the technical field of data analysis, and in particular relates to an abnormal state detection method and detection system of mechanical parts. Background technique [0002] The abnormality of mechanical parts can be characterized by vibration or temperature changes. In most equipment, vibration or temperature sensors are installed to measure one or more positions of mechanical parts and collect data through a monitoring system. Vibration or temperature anomalies are reflected in many aspects, including numerical anomalies and changes in the relationship with surrounding variables. Due to internal and external factors, abnormal vibration or temperature of mechanical equipment is mostly an early sign of mechanical equipment failure. [0003] Existing mechanical component anomaly detection technologies include the threshold judgment method, which is to judge whether there is an abnormality in the mechanical component by setting ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01M13/00
CPCG01M13/00
Inventor 谢鹏李杰刘宗长金超晋文静史喆
Owner CYBERINSIGHT TECH CO LTD