Track profile irregularity amplitude estimation method employing optimal belief rules based inference

Abstract

The invention relates to a track profile irregularity amplitude estimation method employing optimal belief rules based inference. According to the method, the mapping relationship between parametric variable input and yield output is modeled by a belief rule base. A corresponding change relationship between vibration frequency domain characteristic data of different measurement points and a track profile irregularity amplitude is described by building the belief rule base. By a sequence linear programming method, an initial belief rules based (BRB) model is optimized through limited historical data; and the effects on the model caused by subjective factors are reduced. According to the sequence linear programming (SLP) method, a nonlinear optimization problem of an original model is converted into a step-by-step linear optimization problem; and various parameters of the optimization model can be relatively simply and rapidly calculated, so that the track profile irregularity amplitude can be accurately and rapidly estimated through belief inference under the condition of given vibration frequency domain characteristic. According to the track profile irregularity amplitude estimation method, the estimation accuracy and the calculation efficiency of the model are improved; and the method has the advantage of being relatively efficient on a track profile irregularity system which needs to be monitored in real time.

Description

Technical field [0001] The invention relates to a method for estimating the amplitude of track irregularities based on reasoning of optimized confidence rules, and belongs to the field of safe operation and maintenance of track transportation. Background technique [0002] With the rapid development of railway technology in the world, railway transportation, as a transportation method with large carrying capacity, high speed, safety, comfort and environmental protection, has gradually become an important trend in the development of the world transportation industry. With the increase in operating hours of passenger dedicated lines and heavy-haul railway lines and the increase in traffic density, railway line equipment will inevitably experience performance degradation and reduced reliability, and track irregularities are the most common phenomenon, which seriously affects The safety of the ride affects the speed of the train and the comfort of passengers. In view of the current ...

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Problems solved by technology

Although the track inspection vehicle can provide accurate track height and irregularity amplitude, it needs to install very expensive sensors such as inclinometers and gyroscopes, and has strict requirements for the installation of sensors, so there are currently limited rail inspection vehicles It cannot cover the detection of all railway lines, and the rail inspection vehicle can only conduct regular detection on the main line, and the detection cycle interval is relatively long (for example, the entire line of Beijing-Guangzhou line is detected 2 to 3 times a month), and it takes up the running time of the line, so It reduces the economic benefits of running the line, and it is difficult 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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