Open System Architecture for Drives

Pritschow, Günter; Krämer, Christian

doi:10.1016/s0007-8506(07)60126-7

Cited by 14 publications

(3 citation statements)

References 5 publications

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“…2). Pritschow and Kramer [13] proposed a methodology for increased openness in drive controls demonstrating high quality signal information for process and drive condition monitoring. Systems based on power measurement technology have been applied in production, but there are ongoing requirements to investigate the sensitivity of internal signals and the compensation for drive characteristics: e.g.…”

Section: Power and Current Measurement Technologymentioning

confidence: 99%

Advanced monitoring of machining operations

et al. 2010

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Section: Power and Current Measurement Technologymentioning

confidence: 99%

Advanced monitoring of machining operations

et al. 2010

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“…Power and current flow of the spindle delivers the required cutting force. Hence monitoring the power intake and current flow in motors that drive the spindle can be used to understand the MRR [ 16 , 17 ]. However, in robot assisted finishing processes, monitoring and implementing spindle drive control is impractical due to complex architecture compared with traditional milling or turning machines or numerical control (NC) machines.…”

Section: Process Monitoring In Machiningmentioning

confidence: 99%

Frequency Domain Analysis of Sensor Data for Event Classification in Real-Time Robot Assisted Deburring

Pappachan¹,

Caesarendra²,

Tjahjowidodo

et al. 2017

Sensors

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Process monitoring using indirect methods relies on the usage of sensors. Using sensors to acquire vital process related information also presents itself with the problem of big data management and analysis. Due to uncertainty in the frequency of events occurring, a higher sampling rate is often used in real-time monitoring applications to increase the chances of capturing and understanding all possible events related to the process. Advanced signal processing methods are used to further decipher meaningful information from the acquired data. In this research work, power spectrum density (PSD) of sensor data acquired at sampling rates between 40–51.2 kHz was calculated and the corelation between PSD and completed number of cycles/passes is presented. Here, the progress in number of cycles/passes is the event this research work intends to classify and the algorithm used to compute PSD is Welch’s estimate method. A comparison between Welch’s estimate method and statistical methods is also discussed. A clear co-relation was observed using Welch’s estimate to classify the number of cycles/passes. The paper also succeeds in classifying vibration signal generated by the spindle from the vibration signal acquired during finishing process.

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“…5 Web-based integration of maintenance/monitoring system concept [125] Fig. 6 Reconfigurable multisensor monitoring system [19] of control functions allowing for optimisation of machine operation or processes [25,142,146].…”

Section: Cnc Controlmentioning

confidence: 99%

Developments in integration of advanced monitoring systems

Oborski

2014

Int J Adv Manuf Technol

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Monitoring is an important part of manufacturing process control and management. It plays a crucial role in ensuring agility in a manufacturing system, process robustness, responsiveness to client demands, and achievement of a sustainable production environment. Recent developments in information systems and computer technology allows for the implementation of new philosophies that integrate various monitoring applications into one complex system connected through company-wide IT systems and with systems operating throughout the whole supply chain. This paper reviews developments in the area of advanced monitoring and integration. Research on new approaches, standards, developed solutions, and company applications are presented. New directions of research and development in all areas of advanced monitoring and implementation of recent IT solutions are discussed.

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Open System Architecture for Drives

Cited by 14 publications

References 5 publications

Advanced monitoring of machining operations

Advanced monitoring of machining operations

Frequency Domain Analysis of Sensor Data for Event Classification in Real-Time Robot Assisted Deburring

Developments in integration of advanced monitoring systems

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