Development of anomalous bogie detection method by the monitoring of the air spring pressure

Kita, Shigemitsu; Nishimura, Kazuhiko; Kobayashi, Gakuji; Ebina, Suetaka; Hanai, Katsuhisa

doi:10.1299/jsmetld.2018.27.1213

Cited by 4 publications

(2 citation statements)

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“…These systems consist of temperature sensors or vibration acceleration sensors in axle boxes, and crews are warned when a monitored value exceeds a threshold. Some monitoring systems for bogies using air spring pressure sensors are also in practical use [2]. In other cases, there are also monitoring systems installed on the ground side that detect anomalies in axle boxes, brake discs, wheel treads, pantographs, and other components.…”

Section: Introductionmentioning

confidence: 99%

“…In the previous stage of development [1,2], the purpose was to demonstrate the possibility of driving a railway vehicle using traction equipment such as a FC unit, a Bat unit and power converters. During this first stage therefore, the traction equipment was installed in space usually occupied by passengers because of the size of the equipment, and the acceleration performance was limited to that of DMU (approximately 0.4 m/s 2 ).…”

Section: Introductionmentioning

confidence: 99%

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<b>Anomaly Detection for Railway Vehicle Equipment Using Condition Monitoring Data</b>

Yokouchi¹,

TAKASHIGE²,

Kondo³

2022

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In recent years, some railway vehicles have been equipped with condition monitoring devices, which constantly record the operating condition of railway vehicle equipment. For more effective use of condition monitoring devices, we propose an anomaly detection method for railway vehicle equipment using Long Short-Term Memory (LSTM), which is a deep learning method suitable for learning time-series data. In this paper, we apply the proposed method to data on engines and air-conditioning units recorded on vehicles in operations. Results confirmed that the anomaly score for anomalous data increases by using the proposed method, and that anomalies are detected in railway vehicle equipment before faults appear.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

<b>Anomaly Detection for Railway Vehicle Equipment Using Condition Monitoring Data</b>

Yokouchi¹,

TAKASHIGE²,

Kondo³

2022

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LSTM-based Anomaly Detection for Railway Vehicle Air-conditioning Unit using Monitoring Data

Yokouchi

Kondo

2021

IECON 2021 – 47th Annual Conference of the IEEE Industrial Electronics Society

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Damage detection of bearing in gear case by using piezoelectric element incorporated in hanging rubber for gear case of rolling stock (Evaluation of defection performance by bench test)

Mamada

Takenaka²,

Ohta

et al. 2020

Transactions of the JSME (In Japanese)

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A gear case used at a bogie of a rolling stock is an important part to pack a small gear and a large gear that pass the driving force from a main mortar to a wheel. An axle, to which the small gear and the large gear connect, is housed in a gear case through an axle bearing for rotation. The defect of the axle bearings can affect the running safety of rolling stock. In this context we investigate a sensor using a hanging rubber, which can detect of damage of axle bearing in gear case. The hanging rubber is used as a fixing device, which attaches the gear case firmly to the bogie frame. By using hanging rubber for sensor, it can be easily installed for bogie. In addition, the loss of the sensor installed on the bogie and the risk of impact with flying object can be reduce. The sensor using the hanging rubber is incorporated with a piezoelectric elements. The piezoelectric elements can convert mechanical energy to electric energy, and vice versa. The defection of axle bearing in gear case can be detect by the electric signal generated from piezoelectric elements. The rotation test by rotation testing machine of gear system with sensor using hanging rubber is carried out. As the result of rotation test with damaged and normal small gears, it is confirmed that the damage can be detected by amplitude of electric voltage from piezoelectric element when the rotation speed is higher than 50km/h. In case of the rotation speed is lower than 50km/h, the damage can be detected by the frequency analysis of time wave.

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Development of anomalous bogie detection method by the monitoring of the air spring pressure

Cited by 4 publications

References 0 publications

<b>Anomaly Detection for Railway Vehicle Equipment Using Condition Monitoring Data</b>

<b>Anomaly Detection for Railway Vehicle Equipment Using Condition Monitoring Data</b>

LSTM-based Anomaly Detection for Railway Vehicle Air-conditioning Unit using Monitoring Data

Damage detection of bearing in gear case by using piezoelectric element incorporated in hanging rubber for gear case of rolling stock (Evaluation of defection performance by bench test)

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