Vibration monitoring of motorized spindles using spectral analysis techniques

Chang, Ching Feng; Chen, Jin-Jia

doi:10.1016/j.mechatronics.2009.02.009

Cited by 25 publications

(15 citation statements)

References 10 publications

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“…Further advancements include shaped transducers that have been used to reduce the sensitivity of sensor output in structural health monitoring which entails that the response can be made sensitive to particular regions of interest (18) . In addition, a monitoring system has been proposed to warn the operator of impending problems in the machining process and allows to alter and shutting down of the machining process to preserve the machine components (19) . As a result, the spectral analysis techniques can record the condition of machinery rotation even under the condition of misoperation.…”

Section: Introductionmentioning

confidence: 99%

Technique for optimal placement of transducers for fault detection in rotating machines

Fatima

Dastidar

Mohanty

et al. 2013

Proceedings of the Institution of Mechanical Engineers, Part O:

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Online fault detection and diagnosis of rotating machinery requires a number of transducers which can be significantly expensive for industrial processes. The sensitivity of various transducers and their appropriate positioning are dependent on different types of fault conditions. It is critical to formulate a method to systematically determine the effectiveness of transducer locations for monitoring the condition of a machine. In this paper, Number of Independent Sources analysis is used as an effective tool for reducing the number of vibration sources within the system which is then followed by Principal Component Analysis to identify the incoherent transducers to be employed for fault detection. This experiment is conducted on a machine fault simulator for unbalanced rotor, 1 misaligned shaft and cracked shaft. The validation of the proposed selection process is illustrated using spectral analysis for each defect.

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Section: Introductionmentioning

confidence: 99%

Technique for optimal placement of transducers for fault detection in rotating machines

Fatima

Dastidar

Mohanty

et al. 2013

Proceedings of the Institution of Mechanical Engineers, Part O:

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“…Furthermore, the machining parts are no longer required to move between different machines and set up fixtures from time to time, allowing for better performance. High-speed machining is one of the key factors in leading machining technology [4].…”

Section: Investigation Of Spindle Failurementioning

confidence: 99%

Study of Motorized Spindle Reliability Monitoring

Chiang

Chang

Chen

et al. 2018

2018 International Conference on Applied Electronics (AE)

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This paper proposes an intelligent monitoring system to adapt motorized high speed spindle on machine tools to meet the requirement of Industries 4.0, based on the techniques of power electronic engineering, mechatronics and reliability engineering. In this paper, a force-sensor-integrated spindle is proposed to monitor the bearing stress during operation. The implementation of charge amplifier and mechanical design are described as well. As a result, raw data is transmitted through a filter to create fruitful information and allow the remote monitoring system to operate effectively. The information supports predictive maintenance plans and improves the quality of after-sales service.

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“…In that model, not only the relationship between thermal deformation and its lagged value but also the relationship between thermal deformation and the present and lagged value of temperature rise was counted into consideration. Chang et al [4] applied a piezo transducer to check and record the condition of spindle rotation through monitoring the vibration signals. Deng et al [5] used envelope spectrum and wavelet analysis to extract the information of fault from the noise signals of spindles for fault detection in machine tools.…”

Section: Introductionmentioning

confidence: 99%

Applying Radial Basis Function Networks to Fault Diagnosis of Motorized Spindle

Li¹,

Wang²,

Yang³

et al. 2016

Proceedings of the 6th International Workshop of Advanced Manufacturing and Automation

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In a motorized spindle, due to the complexity of the system and nonlinear relationship between features and types of faults, it is difficult and inefficient to use traditional methods or physical models for the fault diagnosis. This paper focuses on the research on applying Radial Basis Function (RBF) Networks for fault detection and classification in the motorized spindle. As a data driven model with high efficiency, RBF networks has the advantage solving the nonlinear problems and dealing with the contradictory samples in the training process. In this research, the data, including rotating speed, temperature, and acceleration signals with three axes (X, Y and Z), are collected from a dynamic balancing platform to evaluate the working condition and detect the potential faults of the motorized spindle.

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Vibration monitoring of motorized spindles using spectral analysis techniques

Cited by 25 publications

References 10 publications

Technique for optimal placement of transducers for fault detection in rotating machines

Technique for optimal placement of transducers for fault detection in rotating machines

Study of Motorized Spindle Reliability Monitoring

Applying Radial Basis Function Networks to Fault Diagnosis of Motorized Spindle

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