Vibration analysis of electrical rotating machines using FFT: A method of predictive maintenance

Patil, Suhas S.; Gaikwad, Jitendra A.

doi:10.1109/icccnt.2013.6726711

Cited by 30 publications

(21 citation statements)

References 5 publications

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“…The foundation of predictive maintenance is the condition monitoring (CM) process [ 16 ], where sensors are applied in machinery to continuously monitor signals, or other appropriate indicators, to assess the health of the equipment [ 27 ]. To give some examples, the ac component of the output of pressure sensor (e.g., noise) can be used to detect blockages in the pipe of a plant [ 28 ], and vibration analysis gives an indication about the reliability and safety of a rotating machine [ 29 ].…”

Section: Introductionmentioning

confidence: 99%

A Model for Predictive Maintenance Based on Asset Administration Shell

Cavalieri

Salafia

2020

Sensors

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Maintenance is one of the most important aspects in industrial and production environments. Predictive maintenance is an approach that aims to schedule maintenance tasks based on historical data in order to avoid machine failures and reduce the costs due to unnecessary maintenance actions. Approaches for the implementation of a maintenance solution often differ depending on the kind of data to be analyzed and on the techniques and models adopted for the failure forecasts and for maintenance decision-making. Nowadays, Industry 4.0 introduces a flexible and adaptable manufacturing concept to satisfy a market requiring an increasing demand for customization. The adoption of vendor-specific solutions for predictive maintenance and the heterogeneity of technologies adopted in the brownfield for the condition monitoring of machinery reduce the flexibility and interoperability required by Industry 4.0. In this paper a novel approach for the definition of a generic and technology-independent model for predictive maintenance is presented. Such model leverages on the concept of the Reference Architecture Model for Industry (RAMI) 4.0 Asset Administration Shell, as a means to achieve interoperability between different devices and to implement generic functionalities for predictive maintenance.

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Section: Introductionmentioning

confidence: 99%

A Model for Predictive Maintenance Based on Asset Administration Shell

Cavalieri

Salafia

2020

Sensors

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“…Vibration analysis not only able to detect the machine failure but also provides prognosis i.e. possible failure mode and remaining runtime of the machine [1, 6 ]. Predictive maintenance or condition‐based maintenance is a well‐renowned maintenance strategy that gained much acceptance in recent years in machine condition monitoring due to its ability to provide reliable prediction of machine health [7 ].…”

Section: Introductionmentioning

confidence: 99%

Calibrated non‐contact vibrational harmonics measurement based on self‐vibration compensated 2D‐PSD with MEMS accelerometer using FFT analysis

Das¹,

Saha²,

Kumar³

2020

IET sci. meas. technol.

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This study presents a novel fast Fourier transform (FFT)‐based non‐contact vibrational harmonics measurement system using a position sensitive detector (PSD) along with calibration using a piezoelectric accelerometer. Frequency‐domain vibrational analysis is required as the changes in machine dynamics are directly related to its failures and could provide more insight into the vibration signal. In this regard, FFT is used for spectral analysis to detect the harmonics in the vibration signal. The novelty of the applied technique for detecting vibrational harmonics lies in its innate contactless nature where the vibration detection sensor i.e. PSD is placed at a particular distance from the vibrating target. Additionally, the parasitic and external vibrations, which might pose unforeseen errors in the detected vibration data, have been nullified by employing a self‐vibration technique using an ADXL‐345 three‐axis accelerometer. The results obtained through PSD have been calibrated via a standard Brüel & Kjaer (B & K) vibration measurement system which uses a piezoelectric accelerometer (B & K accelerometer). The proposed measurement technique is equipped with NI compact RIO‐9074 that features a real‐time processor and an FPGA. The system was observed to effectively measure the frequency range 5–600 Hz with a maximum relative error of 2% in FFT amplitudes.

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“…It can follow the state of the rotating machine during the functioning to avoid unwanted stops. In regards to this, several detection indicators have been proposed and used as global measure of vibration level such as: the peak value, energy, RMS, average value, and others [2,3].…”

Section: Introductionmentioning

confidence: 99%

The modeling of the effect of lubricant viscosity on the vibration of a gear system

Krika

Bouzaouit

2018

Eng. rev. (Online)

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As a part of conditional maintenance, rotating machines are monitored and diagnosed in real time to increase their service life and ensure their availability in the industry. Our work aims to follow the evolution of the vibration for rotating machines through the integration of inverse problems such as degradation of the lubricant quality. Experimental tests were made in order to characterize the influence of quality lubricant (viscosity) on the vibration of a component of a rotating machine. Realized experimental bench is composed of gear device lubricated with lubricants of different viscosity grades and rotated at a variable rotational speed. In each case we measure the value of vibration. Following this experience, a vibration model has been developed depending on the change of state of lubricants, based on the results of planned experience. Further, a correlation analysis on the model obtained was realized and the results show an agreement between theory and experiment.

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Vibration analysis of electrical rotating machines using FFT: A method of predictive maintenance

Cited by 30 publications

References 5 publications

A Model for Predictive Maintenance Based on Asset Administration Shell

A Model for Predictive Maintenance Based on Asset Administration Shell

Calibrated non‐contact vibrational harmonics measurement based on self‐vibration compensated 2D‐PSD with MEMS accelerometer using FFT analysis

The modeling of the effect of lubricant viscosity on the vibration of a gear system

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