Overload detection method and overload detection system for train

Abstract

The invention provides an overload detection method and system for a train, and relates to the field of industrial detection. The method specifically comprises the steps: when a target train is detected, obtaining measurement data of the target train through a measurement instrument; inputting the measurement data into an input layer of the radial basis function neural network measurement data model, and obtaining dynamic weighing data of the target train at an output layer, wherein the radial basis function neural network measurement data model comprises an input layer, a hidden layer and an output layer; and if the dynamic weighing data is greater than the checked load data of the target train, determining that the target train is overloaded. According to the method and system, the measurement data of the target train is obtained and input into the radial basis function neural network measurement data model for calculation and statistics, so that the dynamic weighing data of the target train is obtained, whether a compartment is overloaded or not can be automatically judged, and a powerful guarantee is provided for safety management of railway freight vehicles.

Description

technical field [0001] The present application relates to the field of industrial detection, in particular to a train overload detection method and an overload detection system. Background technique [0002] In recent years, with the continuous increase of the speed of freight trains, railway safety accidents have occurred from time to time. Overloading and unbalanced loading of freight vehicles are important factors that cause vehicle derailment and affect the safety of railway traffic, directly endangering the safety of railway cargo transportation. At present, it mainly uses the radio frequency identification (RFID) system and the dynamic track scale system for over-eccentric load detection, and there are the following problems: on the one hand, the weighing data of the dynamic track scale is affected by factors such as vehicle speed, vibration, and track inequality, and the accuracy is poor; on the other hand, the radio frequency There are many problems in identifying an...

AI Technical Summary

Problems solved by technology

At present, it mainly uses the radio frequency identification (RFID) system and the dynamic track scale system for over-eccentric load detection, and there are the following problems: on the one hand, the weighing data of the dynamic track scale is affected by factors such as vehicle speed, vibration, and track inequality, and the accuracy is poor; on the other hand, the radio frequency There are many problems in identifying and reading the car information, such as missing numbers, easy damage and loss of car chips, and failure to update car information in time. In addition, non-national railway vehicles are not equipped with electronic tags, which has brought many problems to the detection of overload and unbalanced load.

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