Running state detection and performance evaluation method for feed mechanism of numerical control machine

Zhang, Xun; Zhang, Qing; Tan, Luyao; Xu, Guanghua

doi:10.1109/icphm.2017.7998332

Cited by 3 publications

(3 citation statements)

References 4 publications

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“…Another technique for condition monitoring is torque signal analysis [25]. This technique involves analysing the torque signal generated by the servomotors of the sliding system and their controllers.…”

Section: Condition Monitoring and Diagnostics Of Sliding Systemsmentioning

confidence: 99%

Method of Machining Centre Sliding System Fault Detection using Torque Signals and Autoencoder

Augustyn,

Fidali

2023

Acta Mechanica Et Automatica

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The sliding system of machining centres often causes maintenance and process problems. Improper operation of the sliding system can result from wear of mechanical parts and drives faults. To detect the faulty operation of the sliding system, measurements of the torque of its servomotors can be used. Servomotor controllers can measure motor current, which can be used to calculate motor torque. For research purposes, the authors used a set of torque signals from the machining centre servomotors that were acquired over a long period. The signals were collected during a diagnostic test programmed in the machining centre controller and performed once per day. In this article, a method for detecting anomalies in torque signals was presented for the condition assessment of the machining centre sliding systems. During the research, an autoencoder was used to detect the anomaly, and the condition was assessed based on the value of the reconstruction error. The results indicate that the anomaly detection method using an autoencoder is an effective solution for detecting damage to the sliding system and can be easily used in a condition monitoring system.

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Section: Condition Monitoring and Diagnostics Of Sliding Systemsmentioning

confidence: 99%

Method of Machining Centre Sliding System Fault Detection using Torque Signals and Autoencoder

Augustyn,

Fidali

2023

Acta Mechanica Et Automatica

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“…Current [72,73], torque [73] Vibration [38,40,74,75] PSD [40], OT [75], STFT [38,40], HHT [74,72,73], MSE [74,72,73] Backlash -Vibration [76], camera [53] Statistical [53], FFT [76] Fault detection/ diagnosis -Vibration [77] PCT [77] Prognosis/RUL --Sensing methods/ technologies -Wireless vibration [78], hybrid sensor [46] FFT [78], OT [46] Other methods Linear encoder [79,80], torque [80,81] -Statistical [81], FFT [79,80] Linear guide/slide Wear/degradation Rotary encoder [82], linear encoder [82], current [82,83] IMU [56][57][58], ball-end probe [83] Statistical [56,58,83], EMD [82], filtering [57] Preload and force -Vibration…”

Section: Preload Lossmentioning

confidence: 99%

“…Zhang et al [81] use NC-measured motor torque to monitor the performance condition of rack and pinion and two different ball screw feed drives. The data are analyzed for transient impacts, longterm trends, and short-term fluctuations using least-squares.…”

Section: Wear and Performance Degradationmentioning

confidence: 99%

Condition Monitoring of Machine Tool Feed Drives: A Review

Butler

Ziada

Stephenson

et al. 2022

Journal of Manufacturing Science and Engineering

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The innovations propelling the manufacturing industry towards Industry 4.0 have begun to maneuver into machine tools. Machine tool maintenance primarily concerns the feed drives used for workpiece and tool positioning. Condition monitoring of feed drives is the intermediate step between smart data acquisition and evaluating machine health through diagnostics and prognostics. This review outlines the techniques and methods that recent research presents for feed drive condition monitoring, diagnostics and prognostics. The methods are distinguished between being sensorless and sensor-based, as well as between signal-, model- and machine learning-based techniques. Close attention is given to the components of feed drives (ball screws, linear guideways and rotary axes) and the most notable parameters used for monitoring. Commercial and industry solutions to Industry 4.0 condition monitoring are described and detailed. The review is concluded with a brief summary and the observed research gaps.

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Application of Torque Signal Analysis of Servomotors to Assess of Support System Condition of Industrial Machining Centre

Augustyn,

Fidali

2023

Applied Condition Monitoring

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Running state detection and performance evaluation method for feed mechanism of numerical control machine

Cited by 3 publications

References 4 publications

Method of Machining Centre Sliding System Fault Detection using Torque Signals and Autoencoder

Method of Machining Centre Sliding System Fault Detection using Torque Signals and Autoencoder

Condition Monitoring of Machine Tool Feed Drives: A Review

Application of Torque Signal Analysis of Servomotors to Assess of Support System Condition of Industrial Machining Centre

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