A DSP-based FFT-analyzer for the fault diagnosis of rotating machine based on vibration analysis

Betta, G.; Liguori, Consolatina; Paolillo, Alfredo; Pietrosanto, Antonio

doi:10.1109/imtc.2001.928883

Cited by 41 publications

(42 citation statements)

References 19 publications

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“…Vibration that generated on a machine can describe the condition of unwanted movements on machine components. The total number of cycles of movement in every second is called "Frequency" and is expressed in "Hertz" (Hz) [6][7][8][9]. Vibration is caused by force and responded with the form of oscillation movement.…”

Section: A Vibrationmentioning

confidence: 99%

Vibration Spectrum Analysis for Indicating Damage on Turbine and Steam Generator Amurang Unit 1

Cahyono¹,

Priyanta²,

Ramadhan

2017

IJMEIR

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Abstract maintenance on machines is a mandatory asset management activity to maintain asset reliability in order to reduce losses due to failure. 89% of defects have random failure mode, the proper maintenance method is predictive maintenance. Predictive maintenance object in this research is Steam Generator Amurang Unit 1, which is predictive maintenance is done through condition monitoring in the form of vibration analysis. The conducting vibration analysis on Amurang Unit 1 Steam Generator is because vibration analysis is very effective on rotating objects. Vibration analysis is predicting the damage based on the vibration spectrum, where the vibration spectrum is the result of separating time-based vibrations and simplifying them into vibrations based on their frequency domain. The transformation of time-domain-wave into frequency-domain-wave is using the application of FFT, namely AMS Machinery. The measurement of vibration value is done on turbine bearings and steam generator of Unit 1 Amurang using Turbine Supervisory Instrument and CSI 2600 instrument. The result of this research indicates that vibration spectrum from Unit 1 Amurang Power Plant indicating that there is rotating looseness, even though the vibration value does not require the Unit 1 Amurang Power Plant to stop operating (shut down). This rotating looseness, at some point, can produce some indications that similar with the unbalance. In order to avoid more severe vibrations, it is necessary to do inspection on the bearings in the Amurang Unit 1 Power Plant.

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Section: A Vibrationmentioning

confidence: 99%

Vibration Spectrum Analysis for Indicating Damage on Turbine and Steam Generator Amurang Unit 1

Cahyono¹,

Priyanta²,

Ramadhan

2017

IJMEIR

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“…In 0 an embedded discrete wavelet transform and time-sample averaging technique is implemented on a microprocessor to monitor gear faults. Different implementations using a dedicated DSP or FPGA are presented in [2][3][4] [5], however dedicated DSP and FPGA design is not the best solution for enabling on-node signal processing in a sensor network. Apart from 0, no other implementations of entire on-node vibration monitoring algorithms, i.e., in the microprocessor of sensor nodes, was found in literature.…”

Section: A Related Workmentioning

confidence: 99%

Energy-efficient on-node signal processing for vibration monitoring

Ramachandran

Ramirez

Zwaag

et al. 2014

2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP)

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Abstract-In recent years, the use of wireless sensor networks for vibration monitoring is emphasized, because of its capability to continuously monitor at hard-to-reach locations of complex machines. Low power consumption is one of the main requirements for the sensor nodes in continuous and long-term vibration monitoring. However, the power consumption of state-of-the-art wireless sensor nodes is significantly increased by wireless radio in continuously transmitting the raw vibration data to the base station. One of the ways to reduce the power consumption is to reduce the duty-cycle of wireless transmission. Accurately processing the vibration data on the sensor node and transmitting only the critical information, such as natural frequency, defective frequency and amplitude of the vibration, will not only reduce the amount of data transmitted but also the duty cycle of the wireless communication. It eventually leads to reduction of total power consumed by the sensor nodes. In this paper the capability of a sensor node to accurately process the real-time vibration data is analyzed and the corresponding power consumption is measured. In particular, impact-based analysis of real-time vibration data is performed by breaking complex signal-processing tasks into manageable segments on the sensor nodes to minimize algorithmic complexity while still meeting real-time deadlines of the algorithm. As a result, it is found that the accuracy of the on-node signal processing is comparable with conventional off-node monitoring methods, whilst reducing total power consumption.

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“…The time domain approaches provide the physical nature of the vibrations, become practically impossible to analysis in presence of multi-tone vibration signals. Vice versa frequency domain approaches provide the amplitude and phase spectrum to identified the fault and more useful for the vibration analysis [1][2][3]. Vibration analysis is widely used by industries and researchers to predict the health condition of the rotating machines.…”

Section: Introductionmentioning

confidence: 99%

“…This approach demonstrated an acceptable accuracy in condition monitoring of defective mechanical parts, which can be easily used to develop handheld diagnostic tools for the technicians [6]. This monitoring system is depends upon vibration signal so this system is also called as vibration monitoring system .In Present days, Vibration monitoring and vibration diagnosis of machines are done by Vibration analyzer .This vibration analyzer is portable instrument so we have to take that to near the machine for diagnostic [1].This vibration analyzer is converted into software using LABVIEW so we can do diagnosis without going to near the machine. This monitoring system is based on vibration sensor or acceleration senor.…”

Section: Introductionmentioning

confidence: 99%

REVIEW ON VIBRATION SENSOR BASED MONITORING SYSTEM FOR FAULT DETECTION IN MECHANICAL INSTRUMENTs using labview

2017

IJRTER

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Abstract-This system is a portable multi-function monitoring system that bridges the gap between the overall level vibration meter. Vibration meter is converted into LabVIEW based system. This system can do FFT data analysis and collection. It is a complete machine condition diagnostic tool that produces results on computer. It is designed for the technician, engineer and consultant who require portability; they can use and speed to identify prime machinery faults without taking expensive delicate instruments to plant sites. This is an industrial product that is used for system monitoring. In this we can find the mechanical instrument working properly or not based on the FFT of sensor output. By using some standard values we can find the fault in the mechanical instrument.This monitoring system identifies machine faults like Unbalance, Looseness and Alignment. An anti-friction bearing health level indication is also incorporated. This single system undertakes overall Vibration Measurement means acceleration, velocity, displacement, FFT Spectrum, Time Wave Form, Diagnostics and Temperature.

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A DSP-based FFT-analyzer for the fault diagnosis of rotating machine based on vibration analysis

Cited by 41 publications

References 19 publications

Vibration Spectrum Analysis for Indicating Damage on Turbine and Steam Generator Amurang Unit 1

Vibration Spectrum Analysis for Indicating Damage on Turbine and Steam Generator Amurang Unit 1

Energy-efficient on-node signal processing for vibration monitoring

REVIEW ON VIBRATION SENSOR BASED MONITORING SYSTEM FOR FAULT DETECTION IN MECHANICAL INSTRUMENTs using labview

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