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Number of results: 11
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Experimental Diagnostic of Cavitation Flow in the Centrifugal Pump Under Various Impeller Speeds Based on Acoustic Analysis Method

Ahmed Ramadhan Al-Obaidi
Archives of Acoustics | 2023 | vol. 48 | No 2 | 159-170 | DOI: 10.24425/aoa.2023.145234
Keywords experimental analysis impeller speed cavitation acoustic signals
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Abstract

Condition monitoring in a centrifugal pump is a significant field of study in industry. The acoustic method offers a robust approach to detect cavitations in different pumps. As a result, an acoustic-based technique is used in this experiment to predict cavitation. By using an acoustic technique, detailed information on outcomes can be obtained for cavitation detection under a variety of conditions. In addition, various features are used in this work to analyze signals in the time domain using the acoustic technique. A signal in the frequency domain is also investigated using the fast Fourier method. This method has shown to be an effective tool for predicting future events. In addition, this experimental investigation attempts to establish a good correlation between noise characteristics and cavitation detection in a pump by using an acoustic approach. Likewise, it aims to find a good method for estimating cavitation levels in a pump based on comparing and evaluating different systems.
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Authors and Affiliations

Ahmed Ramadhan Al-Obaidi
1
ORCID: ORCID
  1. Faculty of Engineering, Department of Mechanical Engineering, Mustansiriyah University, Baghdad, Iraq

Fault diagnosis of electrical faults of three-phasei nduction motors using acoustic analysis

Adam Glowacz Maciej Sulowicz Jarosław Kozik Krzysztof Piech Witold Glowacz Zhixiong Li Frantisek Brumercik Miroslav Gutten Daniel Korenciak Anil Kumar Guilherme Beraldi Lucas Muhammad Irfan Wahyu Caesarendra Hui Lui
Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 1 | e148440 | DOI: 10.24425/bpasts.2024.148440
Keywords acoustic signal induction motor fault neural network
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Abstract

Fault diagnosis techniques of electrical motors can prevent unplanned downtime and loss of money, production, and health. Various parts of the induction motor can be diagnosed: rotor, stator, rolling bearings, fan, insulation damage, and shaft. Acoustic analysis is non-invasive. Acoustic sensors are low-cost. Changes in the acoustic signal are often observed for faults in induction motors. In this paper, the authors present a fault diagnosis technique for three-phase induction motors (TPIM) using acoustic analysis. The authors analyzed acoustic signals for three conditions of the TPIM: healthy TPIM, TPIM with two broken bars, and TPIM with a faulty ring of the squirrel cage. Acoustic analysis was performed using fast Fourier transform (FFT), a new feature extraction method called MoD-7 (maxima of differences between the conditions), and deep neural networks: GoogLeNet, and ResNet-50. The results of the analysis of acoustic signals were equal to 100% for the three analyzed conditions. The proposed technique is excellent for acoustic signals. The described technique can be used for electric motor fault diagnosis applications.
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Authors and Affiliations

Adam Glowacz
1
ORCID: ORCID
Maciej Sulowicz
1
ORCID: ORCID
Jarosław Kozik
2
ORCID: ORCID
Krzysztof Piech
2
ORCID: ORCID
Witold Glowacz
3
ORCID: ORCID
Zhixiong Li
4 5
ORCID: ORCID
Frantisek Brumercik
6
ORCID: ORCID
Miroslav Gutten
7
ORCID: ORCID
Daniel Korenciak
7
Anil Kumar
8
ORCID: ORCID
Guilherme Beraldi Lucas
9
ORCID: ORCID
Muhammad Irfan
10
ORCID: ORCID
Wahyu Caesarendra
4 11
ORCID: ORCID
Hui Lui
12
ORCID: ORCID
  1. Cracow University of Technology, Faculty of Electrical and Computer Engineering, Department of Electrical Engineering, ul. Warszawska 24,31-155 Kraków, Poland
  2. AGH University of Krakow, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, Department of PowerElectronics and Energy Control Systems, al. A. Mickiewicza 30, 30-059 Kraków, Poland
  3. AGH University of Krakow, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, Department of AutomaticControl and Robotics, al. A. Mickiewicza 30, 30-059 Krakw, Poland
  4. Faculty of Mechanical Engineering, Opole University of Technology, Opole 45-758, Poland
  5. University of Religions and Denomina, Qom, Iran
  6. University of Zilina, Faculty of Mechanical Engineering, Department of Design and Machine Elements, Univerzitna 1, 010 26 Zilina, Slovakia
  7. University of Zilina, Faculty of Electrical Engineering and Information Technology, 8215/1 Univerzitna, 01026 Zilina, Slovakia
  8. Wenzhou University, College of Mechanical and Electrical Engineering, Wenzhou, 325 035, China
  9. Sao Paulo State University, Department of Electrical Engineering, Av. Eng. Luís Edmundo Carrijo Coube, 14-01, Bauru, Sao Paulo, Brazil
  10. Najran University Saudi Arabia, Electrical Engineering Department, College of Engineering, Najran 61441, Saudi Arabia
  11. Faculty of Integrated Technologies, Universiti Brunei Darusalam, Jalan Tungku Link, Gadong BE1410, Brunei
  12. China Jiliang University, College of Quality and Safety Engineering, Hangzhou 310018, China

Diagnostics of Synchronous Motor Based on Analysis of Acoustic Signals with the use of Line Spectral Frequencies and K-nearest Neighbor Classifier

Adam Glowacz
Archives of Acoustics | 2014 | vol. 39 | No 2 | 189-194 | DOI: 10.2478/aoa-2014-0022
Keywords acoustic signal pattern analysis synchronous motor diagnostics
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Abstract

In industrial processes electrical motors are serviced after a specific number of hours, even if there is a need for service. This led to the development of early fault diagnostic methods. Paper presents early fault diagnostic method of synchronous motor. This method uses acoustic signals generated by synchronous motor. Plan of study of acoustic signal of synchronous motor was proposed. Two conditions of synchronous motor were analyzed. Studies were carried out for methods of data processing: Line Spectral Frequencies and K-Nearest Neighbor classifier with Minkowski distance. Condition monitoring is useful to protect electric motors and mining equipment. In the future, these studies can be used in other electrical devices.

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Authors and Affiliations

Adam Glowacz

Fault diagnostics of DC motor using acoustic signals and MSAF-RATIO30-EXPANDED

Adam Glowacz
Archives of Electrical Engineering | 2016 | vol. 65 | No 4 December | 733-744 | DOI: 10.1515/aee-2016-0051
Keywords acoustic signal analysis diagnostic DC motor machine
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Abstract

An early fault diagnostic method of Direct Current motors was presented in this article. The proposed method used acoustic signals of a motor. A method of feature extraction called MSAF-RATIO30-EXPANDED (method of selection of amplitudes of frequencies – ratio 30% of maximum of amplitude – expanded) was presented and implemented. An analysis of proposed method was carried out for early fault states of a real DC motor. Four following states of the DC motor were measured and analyzed: the healthy DC motor, DC motor with 3 shorted rotor coils, DC motor with 6 shorted rotor coils, DC motor with a broken coil. Measured states were caused by natural degradation of the DC motor. The obtained results of analysis were good. The presented early fault diagnostic method can be used for protection of DC motors.

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Authors and Affiliations

Adam Glowacz

The 8AE-PD computer measurement system for registration and analysis of acoustic emission signals generated by partial discharges in oil power transformers

Franciszek Witos Zbigniew Opilski Grzegorz Szerszeń Maciej Setkiewicz
Metrology and Measurement Systems | 2019 | vol. 26 | No 2 | 403-418 | DOI: 10.24425/mms.2019.128355
Keywords acoustic emission partial discharge multichannel system acoustic signal detection acoustic signal processing signal analysis voltage preamplifier
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Abstract

A computer measurement system, designed and built by authors, dedicated to location and description of partial discharges (PD) in oil power transformers examined by means of the acoustic emission (AE) method is presented. The measurement system is equipped with 8 measurement channels and ensures: monitoring of signals, registration of data in real time within a band of 25–1000 kHz in laboratory and real conditions, basic and advanced analysis of recorded signals. The basic analysis carried out in the time, frequency and time-frequency domains deals with general properties of the AE signals coming from PDs. The advanced analysis, performed in the discrimination threshold domain, results in identification of signals coming from different acoustic sources as well as location of these sources in the examined transformers in terms of defined by authors descriptors and maps of these descriptors on the side walls of the tested transformer tank. Examples of typical results of laboratory tests carried out with the use of the built-in measurement system are presented.

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Authors and Affiliations

Franciszek Witos
Zbigniew Opilski
Grzegorz Szerszeń
Maciej Setkiewicz

DC Motor Fault Analysis with the Use of Acoustic Signals, Coiflet Wavelet Transform, and K-Nearest Neighbor Classifier

Adam Glowacz
Archives of Acoustics | 2015 | vol. 40 | No 3 | 321-327 | DOI: 10.1515/aoa-2015-0035
Keywords acoustic signal Coiflet wavelet fault detection DC motor
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Abstract

This paper focuses on testing the monitoring system of the Direct Current motor. This system gives the possibility of diagnosing various types of failures by means of analysis of acoustic signals. The applied method is based on a study of acoustic signals generated by the DC motor. A study plan of the DC motor’s acoustic signal was proposed. Studies were conducted for a faultless DC motor and Direct Current motor with 3 shorted rotor coils. Coiflet wavelet transform and K-Nnearest neighbor classifier with Euclidean distance were used to identify the incipient fault. This approach keeps the motor operating in acceptable condition for a long time and is also inexpensive.
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Authors and Affiliations

Adam Glowacz

Diagnostics of Rotor Damages of Three-Phase Induction Motors Using Acoustic Signals and SMOFS-20-EXPANDED

Adam Glowacz
Archives of Acoustics | 2016 | vol. 41 | No 3 | 507-515 | DOI: 10.1515/aoa-2016-0049
Keywords induction motor machine acoustic signal acoustic emission fault diagnostics
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Abstract

A fault diagnostics system of three-phase induction motors was implemented. The implemented system was based on acoustic signals of three-phase induction motors. A feature extraction step was performed using SMOFS-20-EXPANDED (shortened method of frequencies selection-20-Expanded). A classification step was performed using 3 classifiers: LDA (Linear Discriminant Analysis), NBC (Naive Bayes Classifier), CT (Classification Tree). An analysis was carried out for incipient states of three-phase induction motors measured under laboratory conditions. The author measured and analysed the following states of motors: healthy motor, motor with one faulty rotor bar, motor with two faulty rotor bars, motor with faulty ring of squirrel-cage. Measured and analysed states were caused by natural degradation of parts of the machine. The efficiency of recognition of the analysed states was good. The proposed method of fault diagnostics can find application in protection of three-phase induction motors.

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Authors and Affiliations

Adam Glowacz

The Application of Selected Hierarchical Clustering Methods for Classification the Acoustic Emission Signals Generated by Partial Discharges

Sebastian Borucki Jacek Łuczak Marcin Lorenc
Archives of Acoustics | 2021 | vol. 46 | No 3 | 409-417 | DOI: 10.24425/aoa.2021.138134
Keywords acoustic emission method acoustic signals partial discharges power transformer clustering method
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Abstract

The paper presents the results of the application of the hierarchical clustering methods for the classification of the acoustic emission (AE) signals generated by eight basic forms of partial discharges (PD), which can occur in paper-oil insulation of power transformers. Based on the registered AE signals from the particular PD forms, using a frequency descriptor in the form of the power spectral density (PSD) of the signal, their representation in the form of the set of points on plane XY was created. Next, these sets were subjected to analysis using research algorithms consisting of selected clustering methods. Based on the suggested numeric performance indicators, the analysis of the degree of reproduction of the actual distribution of points showing the particular time waveforms of the AE signals from eight adopted PD forms (PD classes) in the obtained clusters was carried out. As a result of the analyses carried out, the clustering algorithms of the highest effectiveness in the identification of all eight PD classes, classified simultaneously, where indicated. Within the research carried out, an attempt to draw general conclusions as to the selection of the most effective hierarchical clustering method studied and the similarity function to be used for classification of the selected basic PD forms.
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Bibliography

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25. Soltani A.A., Haghjoo F., Shahrtash S.M. (2012), Compensation of the effects of electrical sensors in measuring PD signals, IET Science, Measurement &Technology, 6(6): 494–501, doi: 10.1049/iet-smt.2012.0001.
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Authors and Affiliations

Sebastian Borucki
1
Jacek Łuczak
1
Marcin Lorenc
1
  1. Opole University of Technology, Opole, Poland

Recognition of Acoustic Signals of Loaded Synchronous Motor Using FFT, MSAF-5 and LSVM

Adam Glowacz
Archives of Acoustics | 2015 | vol. 40 | No 2 | 197-203 | DOI: 10.1515/aoa-2015-0022
Keywords acoustic signal fault detection loaded synchronous motor signal processing pattern recognition
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Abstract

This article discusses a system of recognition of acoustic signals of loaded synchronous motor. This software can recognize various types of incipient failures by means of analysis of the acoustic signals. Proposed approach uses the acoustic signals generated by loaded synchronous motor. A plan of study of the acoustic signals of loaded synchronous motor is proposed. Studies include following states: healthy loaded synchronous motor, loaded synchronous motor with shorted stator coil, loaded synchronous motor with shorted stator coil and broken coil, loaded synchronous motor with shorted stator coil and two broken coils. The methods such as FFT, method of selection of amplitudes of frequencies (MSAF-5), Linear Support Vector Machine were used to identify specific state of the motor. The proposed approach can keep high recognition rate and reduce the maintenance cost of synchronous motors.
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Authors and Affiliations

Adam Glowacz

EtCO2-Based Biofeedback Method of Breath Regulation Increases Speech Fluency of Stuttering People

Barbara Stankiewicz Krzysztof Zieliński Marek Darowski Marcin Michnikowski
Archives of Acoustics | 2015 | vol. 40 | No 4 | 469-474 | DOI: 10.1515/aoa-2015-0046
Keywords stuttering therapy respiratory disturbances end-tidal CO2 an acoustic signal of an utterance visual feedback
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Abstract

Respiratory disturbances frequently accompany stuttering. Their influence on lung ventilation can be assessed by measurement of the end-tidal CO2 concentration (EtCO2). The effectiveness of the CO2-based visual feedback method of breath regulation (VF) designed for stuttering therapy was tested in this study. The aim of the study was to answer the question if the VF helps to reduce respiratory disturbances in stuttering and increase speech fluency. 20 stuttering volunteers aged 13-45 years took part in the 3-parts test consisting of: 1. speaking without any techniques improving speech fluency, 2. learning the VF method, 3. VF-assisted speaking. The CO2/time signal and an acoustic signal of an utterance were recorded during the test. Significant increase of FE - the factor of breath ergonomics during speaking (based on both signals), from 47% to 71% (P < 0.01), and significant decrease of %SS - the percent of syllables stuttered, from 14% to 10% (P < 0.01) were received for VF-assisted utterances compared to the utterances without VF assistance. The results indicate that the VF can help to eliminate respiratory disturbances in stuttering and increase speech fluency.
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Authors and Affiliations

Barbara Stankiewicz
Krzysztof Zieliński
Marek Darowski
Marcin Michnikowski

Acoustical Analysis of Enclosure as Initial Approach to Vehicle Induced Noise Analysis Comparatevely Using STFT and Wavelets

Andrzej Błażejewski Piotr Kozioł Maciej Łuczak
Archives of Acoustics | 2014 | vol. 39 | No 3 | 385-394 | DOI: 10.2478/aoa-2014-0042
Keywords modal analysis Short-Time Fourier Transform wavelet transform acoustic signal processing
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Abstract

It is assumed in the paper that the signals in the enclosure in a transient period are similar to a noise induced by vehicles, tracks, cars, etc. passing by. The components of such signals usually points out specific dynamic processes running during the observation or measurements. In order to choose the best method of analysis of these phenomena, an acoustic field in a closed space with a sound source inside is created. Acoustic modes of this space influence the sound field. Analytically, the modal analyses describe the above mentioned phenomena. The experimental measurements were conducted in the room that might comprise the closed space with known boundary conditions and the sound source Brüel & Kjær Omni-directional type 4292 inside. To record sound signals before the field's steady state was reached, the microphone type 4349 and the 4-channel frontend 3590 had been used. The obtained signals have been analysed by using two approaches, i.e. Fourier and the wavelet analysis, with the emphasis on their efficiency and the capability to recognise important details of the signal. The results obtained for the enclosure might lead to the formulation of a methodology for an extended investigation of a rail track or vehicles dynamics.
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Authors and Affiliations

Andrzej Błażejewski
Piotr Kozioł
Maciej Łuczak

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