Onboard detection of railway axle bearing defects using envelope analysis of high frequency acoustic emission signals

Amini, Arash; Entezami, Mani; Papaelias, Mayorkinos

doi:10.1016/j.csndt.2016.06.002

Cited by 58 publications

(35 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Various types of wayside detection systems are commonly used today, including hot axle bearing (or hot axle box) detector (HABD), track acoustic array detector (TAAD), wheel impact load detector (WILD), weigh-inmotion detector, wheel profile detector (WPD), automatic vehicle identification (AVI) units, track circuit, fiber-optic sensor, and axle counter [12,13].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Monitoring Large-Scale Rail Transit Systems Based on an Analytic Hierarchy Process/Gradient-Based Cuckoo Search Algorithm (GBCS) Scheme

et al. 2020

View full text Add to dashboard Cite

Condition monitoring is used as a tool for maintenance management and function as input to decision support. Thus the key parameters in preventing severe damage to railway assets can be determined by automatic real-time monitoring. The technique of radio-frequency identification (RFID) is increasingly applied for the automatic real-time monitoring and control of railway assets, which employs radio waves without the use of physical contact. In this work, a 243-km 2 area of Kuala Lumpur was selected. Because of its large size, determining the locations in which to install the RFID readers for monitoring the bogie components in the Kuala Lumpur railway system is a very complex task. The task involved three challenges: first, finding an optimal evolutionary method for railway network planning in order to deploy the RFID system in a large-area; second, identifying the large area that involved functional features; third, determining which station or stations should be given priority in applying the RFID system to achieve the most effective monitoring of the trains. The first challenge was solved by using a gradientbase cuckoo search algorithm for RFID system deployment. The second challenge was solved by determining all necessary information using geographic information system (GIS) resources. Because of the huge volume of data collected from GIS, it was found that the best method for eliminating data was to develop a new clustering model to separate the useful from the unuseful data and to identify the most suitable stations. Finally, the data set was reduced by developing a specific filter, and the information collected was tested by an analytic hierarchy process as a technique to determine the best stations for system monitoring and control. The results showed the success of the proposed method in solving the significant challenge of large-scale area conditions correlated with multi-objective RFID functions. The method provides high reliability in working with complex and dynamic data. Keywords Geographic information system (GIS) Á Analytic hierarchy process (AHP) Á Radio-frequency identification (RFID) Á Gradient-based cuckoo search algorithm (GBCS) Á Condition monitoring Á Bogie system Á Railway maintenance

show abstract

Section: Introductionmentioning

confidence: 99%

“…These sensors use infrared beams to measure critical parameters and then send the measured values wirelessly to the depot. However, a major obstacle to the use of optical sensors is the need to maintain a line of sight to detect the part status [9,13,14].…”

Section: Introductionmentioning

confidence: 99%

Monitoring Large-Scale Rail Transit Systems Based on an Analytic Hierarchy Process/Gradient-Based Cuckoo Search Algorithm (GBCS) Scheme

et al. 2020

View full text Add to dashboard Cite

show abstract

“…Even though many bearing fault diagnosis techniques are available but still there is a need of a comprehensive method to be developed for accurate detection of the fault. Several methods have been proposed in the literature for bearing fault detection [1,2]. However, an effective bearing fault diagnostic technique is critically needed to support industries for the detection of faulty bearing so as to prevent system performance degradation and malfunction.…”

Section: Introductionmentioning

confidence: 99%

Virtual Instrumentation Programming and Psoc Embedded Design for Bearing Fault Detection: Uses Impulse Excitation Technique

Jayakanth¹,

Chandrasekaran²

2018

IJET

View full text Add to dashboard Cite

This paper describes, a novel innovative design for generating vibration signals in a bearing, which is in static mode not in dynamic mode like other usual measurements reported in literatures, for various types of bearing faults analysis supports users with a technique based on monitoring vibration signals. This paper reports the computed power spectrum from vibration signal clearly identifies the fault signature with its raise in amplitude. Hence, in an impulse excitation technique vibration analysis with computed power spectrum provides an efficient monitoring of fault in axle bearings in a short timing. Programmable System on Chip (PSoC) creator design and Virtual Instrument program written in LabVIEW, a graphical language, provides efficient implementation of impulse excitation technique possible in static test method in a minimal time.

show abstract

“…addition, together with the fiber communication technology, it is easier to establish a multifunctional sensing network consisting of all-fiber sensors to monitor acceleration, strain, temperature and other physical parameters such as axle number, train speed etc [16][17][18][19], which is ideal for a railway system.…”

mentioning

confidence: 99%

Novel accelerometer realized by a polarization-maintaining photonic crystal fiber for railway monitoring applications

Liu¹,

Htein²,

Gunawardena³

et al. 2019

Opt. Express

View full text Add to dashboard Cite

In this paper, we present a novel accelerometer based on the Sagnac interferometer configuration using a polarization-maintaining photonic crystal fiber (PM-PCF), which has a sensitivity of ~8 pm/G, and a resonant frequency exceeding 2.5 kHz. The proposed accelerometer is capable of functioning with a constant sensitivity in a large frequency range from 0 to 1 kHz which is much wider than many FBG-based accelerometers. Experimental results obtained from a field test in railway monitoring, demonstrate a broader frequency range for the proposed accelerometer compared to that of the FBG based accelerometer and is comparable to the conventional piezoelectric sensor. The abrupt change in the acceleration measured by the sensor aids in locating any defect or crack present on the railway track. To the best of our knowledge, this is the first demonstration of an accelerometer based on a fiber interferometer aimed for the railway industry. The proposed accelerometer operating at high accelerations (>40 G) and capable of functioning at a broad frequency range, shows significant potential in being used in applications which require detection of strong and fast vibrations, especially in structural health monitoring of trains and railway tracks in real time.

show abstract

Onboard detection of railway axle bearing defects using envelope analysis of high frequency acoustic emission signals

Cited by 58 publications

References 3 publications

Monitoring Large-Scale Rail Transit Systems Based on an Analytic Hierarchy Process/Gradient-Based Cuckoo Search Algorithm (GBCS) Scheme

Monitoring Large-Scale Rail Transit Systems Based on an Analytic Hierarchy Process/Gradient-Based Cuckoo Search Algorithm (GBCS) Scheme

Virtual Instrumentation Programming and Psoc Embedded Design for Bearing Fault Detection: Uses Impulse Excitation Technique

Novel accelerometer realized by a polarization-maintaining photonic crystal fiber for railway monitoring applications

Contact Info

Product

Resources

About