EPE Association: NORpie 2004 - Topic 04: Monitoring

NORpie 2004 - Topic 04: Monitoring
You are here: EPE Documents > 05 - EPE Supported Conference Proceedings > NORpie - Proceedings > NORpie 2004 > NORpie 2004 - Topic 04: Monitoring

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   Requirements for embedded analysis concept of bearing condition monitoring
By P. Spatenka; T. Lindth; J. Ahola; J. Partanen [View]
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Abstract: Rotating machinery maintenance cost is a signifi- cant part of total expenses of industrial plants. Current needs to reduce such expenses has risen the importance of condition monitoring. Condition monitoring and diagnostics allow the maintenance that is based on current condition instead of the maintenance based on statistically estimated lifetime. If prognostic estimation is also a part of the condition monitoring system, the maintenance task can be scheduled in advance to order the necessary parts, and to reduce the overall expenses. Our research deals with a vibration–based bearing condition monitoring. This paper presents the requirements for embedded analysis concept in an industrial infrastructure, i.e. the condition monitoring system where analysis and diagnosis are done locally by embedded sensor at the field level. The requirements discussed in this paper are based on the results obtained from our current research. We also present a DSP based testing platform that has been developed in our laboratory in order to research the embedded analysis concept.

   A Low-Cost Measurement and Data Collection System for Electric Motor Condition Monitoring
By A-L. Rautiainen; R. Tiainen; J. Ahola; T. Lindh [View]
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Abstract: In this paper, a low-cost measurement and data collection system for on-line condition monitoring of electrical machines is presented. The system is located on the motor level of an industrial plant and contains no embedded analysis. A pilot installation of the system is described. Additionally, the usability of an analogue-output temperature sensor in the presence of a frequency converter is discussed.

   Automatic bearing fault classification combining statistical classification and fuzzy logic
By T. Lindh; J. Ahola; P. Spatenka; A-L Rautiainen [View]
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Abstract: In this paper, a new automatic analysis method for the detection of cyclic bearing faults is introduced. The method uses a multivariate statistical fault classification and fuzzy logic. Features are extracted from an envelope spectrum of the frame acceleration of a motor frame. Qualitative and quantitative measures of the features are utilized.

   Remote Monitoring System for Transformer Substations
By T. Vekara; S. Pettissalo; N. Rajkumar [View]
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Abstract: This paper presents a new distribution transformer monitoring system (DTMS), called Wimo, which utilizes the existing communication network, has low investment and operation costs and is easy to install and use. The system is able to provide following benefits for utilities: warnings and alarms in real time, measured and registered data of loadings, reactive power, earth current and power quality at the transformer substation, and more reliable and effective maintenance. Also, transformer capacity can be utilized more effectively and the control of power quality can be improved. The field tests of the first two installations in Finland have been promising and the system is shown to be compatible with the commercial GSM networks and with the information systems used in power networks.

   Modeling the High Frequency Characteristics of Industrial Low Voltage Distribution Network
By J. Ahola; T. Lindh; V. Särkimäki; R. Tiainen [View]
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Abstract: In this paper, the characteristics of an industrial low voltage distribution network are considered in the frequency band 100 kHz – 30 MHz. The modeling, simulation and measurements for the pilot distribution network are presented.

NORpie 2004 - Topic 04: Monitoring
You are here: EPE Documents > 05 - EPE Supported Conference Proceedings > NORpie - Proceedings > NORpie 2004 > NORpie 2004 - Topic 04: Monitoring
	[return to parent folder]

	Requirements for embedded analysis concept of bearing condition monitoring By P. Spatenka; T. Lindth; J. Ahola; J. Partanen	[View] [Download]
Abstract: Rotating machinery maintenance cost is a signifi- cant part of total expenses of industrial plants. Current needs to reduce such expenses has risen the importance of condition monitoring. Condition monitoring and diagnostics allow the maintenance that is based on current condition instead of the maintenance based on statistically estimated lifetime. If prognostic estimation is also a part of the condition monitoring system, the maintenance task can be scheduled in advance to order the necessary parts, and to reduce the overall expenses. Our research deals with a vibration–based bearing condition monitoring. This paper presents the requirements for embedded analysis concept in an industrial infrastructure, i.e. the condition monitoring system where analysis and diagnosis are done locally by embedded sensor at the field level. The requirements discussed in this paper are based on the results obtained from our current research. We also present a DSP based testing platform that has been developed in our laboratory in order to research the embedded analysis concept.

	A Low-Cost Measurement and Data Collection System for Electric Motor Condition Monitoring By A-L. Rautiainen; R. Tiainen; J. Ahola; T. Lindh	[View] [Download]
Abstract: In this paper, a low-cost measurement and data collection system for on-line condition monitoring of electrical machines is presented. The system is located on the motor level of an industrial plant and contains no embedded analysis. A pilot installation of the system is described. Additionally, the usability of an analogue-output temperature sensor in the presence of a frequency converter is discussed.

	Automatic bearing fault classification combining statistical classification and fuzzy logic By T. Lindh; J. Ahola; P. Spatenka; A-L Rautiainen	[View] [Download]
Abstract: In this paper, a new automatic analysis method for the detection of cyclic bearing faults is introduced. The method uses a multivariate statistical fault classification and fuzzy logic. Features are extracted from an envelope spectrum of the frame acceleration of a motor frame. Qualitative and quantitative measures of the features are utilized.

	Remote Monitoring System for Transformer Substations By T. Vekara; S. Pettissalo; N. Rajkumar	[View] [Download]
Abstract: This paper presents a new distribution transformer monitoring system (DTMS), called Wimo, which utilizes the existing communication network, has low investment and operation costs and is easy to install and use. The system is able to provide following benefits for utilities: warnings and alarms in real time, measured and registered data of loadings, reactive power, earth current and power quality at the transformer substation, and more reliable and effective maintenance. Also, transformer capacity can be utilized more effectively and the control of power quality can be improved. The field tests of the first two installations in Finland have been promising and the system is shown to be compatible with the commercial GSM networks and with the information systems used in power networks.

	Modeling the High Frequency Characteristics of Industrial Low Voltage Distribution Network By J. Ahola; T. Lindh; V. Särkimäki; R. Tiainen	[View] [Download]
Abstract: In this paper, the characteristics of an industrial low voltage distribution network are considered in the frequency band 100 kHz – 30 MHz. The modeling, simulation and measurements for the pilot distribution network are presented.