The health monitoring of a machine is an assessment wherein the significant change in performance parameters is observed and analyzed with an intention to predict the failure. In this context, many types of analyzers are available but the overall cost is very high and may not be affordable to all. Hence this research work presents a low-cost solution for the development of a novel machine health monitoring system that is reliable, accurate and easy to handle. An open-source platform Arduino Mega 2560 along with the ADXL335 accelerometer is integrated with MATLAB to store & display the acquired data. The program is designed to convert time domain response to frequency domain response using classic Fast Fourier Transform. The system exhibits time domain and frequency domain response to interpret the state of a machine component. The experimental assessment of the developed system with respect to the standard commercially available analyzer is carried out and showed equivalent competency. This system can be used as a monitoring tool in small scale industries & for laboratory work in engineering colleges.
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The health monitoring of a machine is an assessment wherein the significant change in performance parameters is observed and analyzed with an intention to predict the failure. In this context, many types of analyzers are available but the overall cost is very high and may not be affordable to all. Hence this research work presents a low-cost solution for the development of a novel machine health monitoring system that is reliable, accurate and easy to handle. An open-source platform Arduino Mega 2560 along with the ADXL335 accelerometer is integrated with MATLAB to store & display the acquired data. The program is designed to convert time domain response to frequency domain response using classic Fast Fourier Transform. The system exhibits time domain and frequency domain response to interpret the state of a machine component. The experimental assessment of the developed system with respect to the standard commercially available analyzer is carried out and showed equivalent competency. This system can be used as a monitoring tool in small scale industries & for laboratory work in engineering colleges. 124 pp. Englisch. Nº de ref. del artículo: 9786202519953
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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The health monitoring of a machine is an assessment wherein the significant change in performance parameters is observed and analyzed with an intention to predict the failure. In this context, many types of analyzers are available but the overall cost is very high and may not be affordable to all. Hence this research work presents a low-cost solution for the development of a novel machine health monitoring system that is reliable, accurate and easy to handle. An open-source platform Arduino Mega 2560 along with the ADXL335 accelerometer is integrated with MATLAB to store & display the acquired data. The program is designed to convert time domain response to frequency domain response using classic Fast Fourier Transform. The system exhibits time domain and frequency domain response to interpret the state of a machine component. The experimental assessment of the developed system with respect to the standard commercially available analyzer is carried out and showed equivalent competency. This system can be used as a monitoring tool in small scale industries & for laboratory work in engineering colleges.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 124 pp. Englisch. Nº de ref. del artículo: 9786202519953
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Librería: AHA-BUCH GmbH, Einbeck, Alemania
Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The health monitoring of a machine is an assessment wherein the significant change in performance parameters is observed and analyzed with an intention to predict the failure. In this context, many types of analyzers are available but the overall cost is very high and may not be affordable to all. Hence this research work presents a low-cost solution for the development of a novel machine health monitoring system that is reliable, accurate and easy to handle. An open-source platform Arduino Mega 2560 along with the ADXL335 accelerometer is integrated with MATLAB to store & display the acquired data. The program is designed to convert time domain response to frequency domain response using classic Fast Fourier Transform. The system exhibits time domain and frequency domain response to interpret the state of a machine component. The experimental assessment of the developed system with respect to the standard commercially available analyzer is carried out and showed equivalent competency. This system can be used as a monitoring tool in small scale industries & for laboratory work in engineering colleges. Nº de ref. del artículo: 9786202519953
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Librería: preigu, Osnabrück, Alemania
Taschenbuch. Condición: Neu. A Novel Machine Health Monitoring System | A comprehensive guide to design of low-cost instrumental framework for condition monitoring | Abhishek Patange (u. a.) | Taschenbuch | 124 S. | Englisch | 2020 | LAP LAMBERT Academic Publishing | EAN 9786202519953 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Nº de ref. del artículo: 118282718
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