Abstract
To make accurate and comprehensive evaluation of the catenary and diagnose the causes of the catenary fault, a method of catenary state evaluation and diagnosis based on the principal component analysis control chart was proposed, which can make full use of the multidimensional detection parameters of the catenary. The principal component analysis was used to reduce the dimension of catenary parameters, the principal component T2 control chart was calculated to show the change of principal component of catenary state data, the residual SPE control chart was calculated to show the change of their correlation, and the contribution rate control chart was calculated to show the cause of abnormal state data. The method can not only transform the multidimensional detection parameters of the catenary into a statistic to realize the simple and intuitive evaluation of the catenary state but also can accurately determine the cause of the abnormal state, so as to provide technical support for the targeted condition-based maintenance of the catenary.
Highlights
As the only power supply line for electrified railway, catenary’s working environment is harsh, and there is no backup for it, once there is a fault, it will lead to the outage of electrified railway, which will have a huge impact on the railway operation
In order to display the catenary status more intuitively and reflect the development trend of the catenary status, the principal component analysis and the multivariate statistical control chart are combined to obtain the multivariate statistical control chart based on the principal component analysis, which includes principal component T2 control chart, residual SPE control chart, and principal component contribution control chart [29]
E main component T2 control chart uses the T2 statistics to reflect the change of the main metadata, which can realize the status judgment of the main metadata of the detected data. e SPE control chart uses the residual SPE statistics for statistical testing, which reflects the degree of deviation of the data from the pivot space and can reflect the changes in the correlation between the data
Summary
As the only power supply line for electrified railway, catenary’s working environment is harsh, and there is no backup for it, once there is a fault, it will lead to the outage of electrified railway, which will have a huge impact on the railway operation. E principal component contribution control chart calculates the contribution rate of each parameter at the abnormal point to the T2 statistic and the SPE statistic, which can reflect the cause of the abnormality and play a diagnostic role.
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