A method and system for on-line monitoring of long-wave irregularities in a vertical track

Abstract

The invention discloses an on-line vertical track long wave irregularity monitoring method and a system. According to the system, a pitch gyroscope is arranged on a framework above a one-class spring of a train walking part, a speed measuring sensor is arranged inside an automobile end cover of a train, and output ends of the pitch gyroscope and the speed measuring sensor are both accessed to a central processing unit. The monitoring method comprises the following steps: acquiring a framework inclination angle speed signal of the train through the pitch gyroscope, acquiring an operation speed signal of the train through the speed measuring sensor, performing time-space domain conversion on the two acquired signals through the central processing unit so as to obtain a time-space domain sequence, performing quadratic integration on the time-space domain sequence by using a filter method, eliminating a trend term generated in integration by using a trend term elimination method so as to obtain a track vertical displacement estimation value, and establishing a compensation filter for eliminating the amplitude and phase deviation of the tract vertical displacement estimation value. The monitoring method has the advantages of low cost and good engineering implementation property, and on-line real-time monitoring is achieved.

Description

technical field [0001] The invention relates to the technical field of on-line monitoring of track long-wave irregularity, in particular to an online monitoring method and system for vertical track long-wave irregularity. Background technique [0002] Track irregularities are caused by repeated action of wheels and rails and deterioration of track sleepers, and are one of the important excitation sources that cause vehicle and track vibrations. When the track irregularity reaches a certain level, it will affect the stability of the vehicle, the comfort of passengers, the service life of the vehicle and the track, and even endanger the safety of the vehicle. Track irregularity can be divided into local irregularity and long-wave irregularity according to the wavelength. The latter is a key factor affecting vehicle stability and passenger comfort, and its impact increases with the increase of train speed. Its effective detection and management have great impact on Railway ope...

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Problems solved by technology

[0004] Li Chong (Li Chong. Real-time detection and processing of long-wave irregularity of maglev track. Master's thesis of Southwest Jiaotong University, 2006) installed an inertial strapdown system on the car body to monitor the long-wave smooth state of the maglev track, but installed an inertial system on the car body, After the transmission of the primary spring and the secondary spring, it is difficult to specifically evaluate the state of the track

The patent (EP1180175,2002) of German AEAT Company discloses the TrackMon system, which combines the vertical accelerometer installed above the axle box with a series of spring displacement sensors to monitor the state of the track; this method avoids the relatively large dynamic range of the axle box acceleration. Large, the sensor can not guarantee the disadvantage of resolution accuracy; but because the displacement sensor is relatively damaged and will affect the normal maintenance work of the vehicle, the implementation of the system engineering is poor

J.Real (J.I.Real, L.Montalbán, T.Real, V.Puig, Developmentofasystemtoobtainverticaltrackgeometrymeasuringaxle-boxaccelerationsfromin-servicetrains.JournalOfVibroEngineering.JUNE2012.Volume14) detects the vertical irregularity of the track by installing the axlebox vibration sensor, and the vibration of the axlebox The signal is processed in three steps: quadratic integration of the acceleration signal, high-pass filtering and phase compensation, and inverse input of the vibration model; therefore, the interference vibration signal components contained in the vibration acceleration of the axle box include rolling bearing faults, wheel tread faults, wheel and track disengagement, and environmental factors. Noise, etc., will bring certain interference to information extraction

MarijaMolodova's research shows (MarijaMolodova, ZiliLi, RolfDollevoet.Axleboxacceleration:Measurementandsimulationfordetectionofshorttrackdefect.Wear.2011.271(1-2):349-356), when the train passes through local faults such as: wide gauge joints, welds, switches, harmonic irregularities And pine sleepers, etc., the acceleration of the axle box can measure up to 100g, but when detecting long-wave irregularities, the acceleration is often less than 1g, which is far lower than the acceleration caused by local faults on the track. Therefore, if the axle box acceleration sensor detects two types of The unevenness must have the characteristics of low bandwidth lower limit, high linearity and low noise, resulting in low detection accuracy

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