DPC-based method and system for detecting abnormality of multi-door system of rail vehicle

Abstract

The invention discloses a DPC-based method and system for detecting abnormality of a multi-door system of a rail vehicle. The method comprises the following steps that: feature extraction is carried out on main track data of a vehicle door system, each door opening-closing process is segmented, time-domain feature extraction and frequency-domain feature extraction are carried out respectively on aplurality of motor parameter value of each segment, the time-domain features and frequency-domain features are combined to generate system state variables of the vehicle door system; on the basis ofa DPC method, a system multi-door health degree model is established for the extracted system state variables; and an e abnormal state of the vehicle door is identified by using an Euclidean distance.According to the invention, mathematical modeling is carried out based on a density peak clustering algorithm and the health degree model of the multi-vehicle door system is established; periodical horizontal comparison is carried out on the obtained multi-vehicle door model by using the established model to complete abnormality detection of the vehicle multi-door system. Therefore, the repetitive experimental design and data collection work are reduced. The density peak clustering algorithm is applied to the rail vehicle door fault detection technology first time; the influence on the vehicle door type or locking device type is eliminated; and the universality is high.

Description

technical field [0001] The invention relates to a method and system for abnormality detection of a rail vehicle multi-door system based on density peak clustering, and belongs to the technical field of urban rail transit. Background technique [0002] With the continuous development of the national economy, my country's urbanization process is gradually accelerating. The development of economy, the advancement of science and technology, the improvement of residents' living standards, the rapid increase of urban population, the expansion of city scale, the high frequency of residents' travel and material exchange, have caused the urban transportation system to face a severe situation. As a key mode of transportation in the comprehensive transportation system, urban rail transit, with its unique technical and economic advantages such as large capacity, high efficiency, low cost, and low energy consumption, shoulders an important mission in alleviating urban traffic congestion ...

AI Technical Summary

Problems solved by technology

The existing performance degradation prediction methods of other systems, such as the research on the performance degradation of fuel cells, mainly measure the AC impedance and compare the measured AC impedance value with the degradation reference value to evaluate the performance degradation, but the subway vehicle door There are many components in the system and the degradation of different components causes different abnormal states. This method cannot be used to detect the abnormality of the subway vehicle door system.

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