Track longitudinal irregularity amplitude value estimation method based on evidential reasoning rule

Abstract

The invention relates to a track longitudinal irregularity amplitude value estimation method based on an evidential reasoning rule and belongs to the field of track traffic safe running maintenance. The method includes the steps that frequency domain characteristic signals and a longitudinal irregularity amplitude value of axles and a vehicle body are obtained from a track inspection vehicle; reference values of input characteristics and the irregularity amplitude value are determined, and synthesis similarity distribution of a sample is calculated; a setting point statistical table reflecting the relationship between input and the irregularity amplitude value is established and converted to obtain an evidence matrix table of the input; the reliability of an input information source is confirmed; the evidential reasoning rule is used for fusing evidences activated by the sample input, and the longitudinal irregularity amplitude value is reasoned according to a fusion result; and optimization model training parameters are established, and the track longitudinal irregularity amplitude value of the tested sample can be reasoned on the basis of an optimal parameter set. By the adoption of the method, the track longitudinal irregularity estimated value can be effectively estimated through vibration signals obtained by sensors installed on a common train, cost is low, accuracy is high, and therefore the track longitudinal irregularity amplitude value is monitored in real time.

Description

technical field [0001] The invention relates to a method for estimating the amplitude of track irregularities based on evidence reasoning rules, belonging to the field of rail transit safety operation and maintenance. Background technique [0002] As the railway system infrastructure that carries trains, any damage or failure of the track will have an important impact on the efficiency and safety of the train. Track dynamic inspection is an important means to inspect railway track defects, guide maintenance and ensure traffic safety, among which the level of track irregularity is an important detection index, which can reflect the degree of vertical geometric deformation of the track. Under the normal smoothness of the track, the interaction force between the train and the track is uniform, and the train runs smoothly; when the track is uneven, abnormal vibrations will occur during the operation of the train, which causes the vertical force between the train and the track to...

AI Technical Summary

Problems solved by technology

However, although the rail inspection car can provide more accurate estimation of uneven displacement, it also has two unavoidable problems: one is that the rail inspection car needs to be equipped with very expensive goniometers and gyroscopes, and the The installation requires an extremely harsh design structure, which has led to the high cost of the rail inspection vehicle; second, the rail inspection vehicle needs to occupy the driving route, and the time occupied by the line is long, which is necessary for the domestic railway network to meet such intensive traffic across the country. Under the background of demand, the detection cycle interval of the rail inspection vehicle is forced to be too long, which makes it difficult for the rail inspection vehicle to meet the needs of the current railway department for all-weather monitoring of the line, and it is not enough to meet the real-time monitoring needs of China's huge railway network

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