Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Anomaly detection algorithm configuration method and device, electronic equipment and storage medium

A technology of abnormal detection and configuration method, applied in the field of automobile production lines, can solve the problems of multiple manpower and material resources, consumption, high cost of automobile production lines, etc., and achieve the effect of reducing manpower and material resources and reducing costs.

Pending Publication Date: 2021-11-26
SIEMENS FACTORY AUTOMATION ENG
View PDF5 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Since the automobile production line includes various types of equipment, different types of equipment require different anomaly detection algorithms, and the same type of equipment with different operating conditions also requires different anomaly detection algorithms. Therefore, when realizing predictive maintenance of automobile production lines, users It is necessary to analyze each device included in the automobile production line, and then configure an anomaly detection algorithm for each device included in the automobile production line according to the analysis results, which will consume more manpower and material resources, resulting in a higher predictive maintenance of the automobile production line. cost

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Anomaly detection algorithm configuration method and device, electronic equipment and storage medium
  • Anomaly detection algorithm configuration method and device, electronic equipment and storage medium
  • Anomaly detection algorithm configuration method and device, electronic equipment and storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0130] figure 1 It is a flowchart of a method 100 for configuring an anomaly detection algorithm provided in Embodiment 1 of the present application, as shown in figure 1 As shown, the configuration method 100 of the anomaly detection algorithm includes the following steps:

[0131] 101. Obtain the operating data of the device.

[0132] The automobile production line includes multiple devices that require predictive maintenance. For each device that requires predictive maintenance, a corresponding anomaly detection algorithm is configured, but the parameters of the anomaly detection algorithm may not be suitable for the actual operating conditions of the equipment. This requires tuning the parameters of the anomaly detection algorithm. Equipment in an automotive production line that requires predictive maintenance can be a single component, such as a bearing, or an assembly of multiple components, such as a high-speed lift.

[0133] For the equipment that needs predictive m...

Embodiment 2

[0144] On the basis of the configuration method of the abnormality detection algorithm provided in Embodiment 1, if it is determined that the abnormality detection frequency of the equipment detected by the abnormality detection algorithm is stable, an alarm message can be sent to the user after the abnormality detection algorithm detects that the equipment is abnormal, and the The user further confirms whether the device is indeed abnormal, and then adjusts the parameters of the abnormality detection algorithm according to the user's confirmation result, thereby improving the accuracy of the abnormality detection algorithm for detecting device abnormalities.

[0145] figure 2 It is a schematic diagram of a parameter adjustment method 200 of an abnormality detection algorithm provided in Embodiment 2 of the present application, as shown in figure 2 As shown, after the data processing program 202 obtains the operating data of the equipment according to the configuration infor...

Embodiment 3

[0155] exist figure 1 On the basis of the configuration method 100 of the abnormality detection algorithm shown, step 104 judges whether the abnormality frequency of the equipment detected by the abnormality detection algorithm is stable, and can detect the difference in the abnormality frequency of the equipment according to the abnormality detection algorithm in different detection periods, To determine whether the abnormal frequency detected by the abnormality detection algorithm is stable. image 3 It is a flow chart of a method 300 for judging the stability of abnormal occurrence frequency provided by Embodiment 3 of the present application, as shown in image 3 As shown, the abnormal occurrence frequency stability judgment method 300 includes the following steps:

[0156] 301. Calculate a first abnormality frequency according to an abnormality detection result, where the first abnormality frequency is used to represent a frequency at which an abnormality detection algor...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention provides a configuration method and device of an anomaly detection algorithm, electronic equipment and a storage medium, the configuration method of the anomaly detection algorithm is used for configuring the anomaly detection algorithm of equipment in predictive maintenance of an automobile production line, and the configuration method of the anomaly detection algorithm comprises the following steps: obtaining operation data of the equipment; determining variable information of the equipment according to the operation data, wherein the variable information is directly obtained from the operation data or obtained by processing the operation data; inputting the variable information into the anomaly detection algorithm to obtain an anomaly detection result output by the anomaly detection algorithm; according to the anomaly detection result, judging whether the anomaly frequency of the equipment detected by the anomaly detection algorithm is stable or not; and if the abnormal frequency of the equipment detected by the abnormal detection algorithm is unstable, adjusting parameters of the abnormal detection algorithm. According to the scheme, the predictive maintenance cost of the automobile production line can be reduced.

Description

technical field [0001] The present application relates to the technical field of automobile production lines, and in particular to a configuration method, device, electronic equipment and storage medium of an abnormality detection algorithm. Background technique [0002] Automobile production line is a kind of assembly line for automobile production, including stamping production line, welding production line, painting production line and final assembly production line. When the automobile production line fails, it will affect the production efficiency of the automobile. For this reason, it is necessary to carry out predictive maintenance on the automobile production line to solve the possible failures of the automobile production line in advance, to ensure that the automobile production line can work normally during the automobile production process, and then to ensure the safety of the automobile. Productivity. [0003] The predictive maintenance of the automobile product...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G05B19/418G06K9/62
CPCG05B19/4184G05B2219/31088G06F18/23G06F18/24G06F18/214Y02P90/02Y02P90/80
Inventor 于禾王琪郑智鹏田德钰张海涛周文晶李虎宋振国张见平张宇乐
Owner SIEMENS FACTORY AUTOMATION ENG
Features
  • Generate Ideas
  • Intellectual Property
  • Life Sciences
  • Materials
  • Tech Scout
Why Patsnap Eureka
  • Unparalleled Data Quality
  • Higher Quality Content
  • 60% Fewer Hallucinations
Social media
Patsnap Eureka Blog
Learn More