Cluster industrial robot failure diagnosis method based on outlier excavation

Abstract

The invention relates to a fault diagnosis method for trunked industrial robots based on outliers mining, belonging to the filed of fault diagnosis of electromechanical equipment. The method comprises the following steps of: firstly collecting data of original operating state of the trunked industrial robots and carrying out preprocessing operation of classifying and the like; then using a cluster analysis method to carry out analysis by taking a plurality of robots as a group, so as to lead a plurality of equipment to carry out classification according to operational state; based on clustering, utilizing an outliers mining method to calculate outlier factors of each industrial robot and then obtaining outlier degree thereof; separating outliers according to outlier degree and further determining that whether individual industrial robot represented by the outlier occurs fault or not; and judging the specific parts of faults of the robots according to the types of abnormal operation parameters and obtaining fault diagnosis results. By utilizing the fault diagnosis results, the method can implement targeted and predictive maintenance, thus avoiding the occurrence of faults of equipment, improving the reliability of equipment and guaranteeing reliable operation of trunked operational robots.

Description

technical field [0001] The invention relates to an industrial robot fault diagnosis method, in particular to a cluster industrial robot fault diagnosis method based on outlier point mining, and belongs to the technical field of electromechanical equipment fault diagnosis. Background technique [0002] Looking at the development status of the entire assembly manufacturing industry, it is not difficult to analyze its future development trend: the continuous development of automated flexible production systems. Because of the characteristics of automatic production and flexible production, industrial robots have been used on a large scale in the assembly manufacturing industry in recent years to improve production efficiency, such as stamping, welding, painting, and final assembly in automobile production. Industrial robots are widely used in industrial processes. Industrial robots are complex systems that integrate various types of components such as machinery, hydraulics, el...

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Problems solved by technology

On this basis, the systemic algorithm proposed by the author, which can deal with a class of nonlinear system parameter deviation faults, successfully detects and diagnoses these faults. The simulation results show that the method in this paper has the advantage of small detection delay, not only The fault can be isolated and the size of the fault can be estimated at the same time". Its shortcoming is that the dynamic diagnosis of industrial robots can be carried out by establishing a model of known faults, so it is impossible to diagnose unknown faults; in addition, this scheme is only applicable to individual Industrial robots are used for diagnosis, but industrial robots that cannot be used for cluster operations on large-scale production lines

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