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dsPIC-based signal processing techniques and an IT-enabled distributed system for intelligent process monitoring and management

Siddiqui, Raees Ahmed 2008. dsPIC-based signal processing techniques and an IT-enabled distributed system for intelligent process monitoring and management. PhD Thesis, Cardiff University.

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dsPIC Technology employs a powerful 16-bit architecture into single-chip devices that seamlessly integrate the diverse attributes of a microcontroller with the computation and throughput capabilities of a digital signal processor in a single core. The key element of this dissertation is to explore how dsPIC has influenced the applicability of research in e-Monitoring systems. At the same time dsPIC has offered the opportunity to develop methodologies which were previously not even considered. The dsPIC devices are used, in this research, for front end data acquisition, signal processing and communication tools within a proposed monitoring architecture. In this work, novel digital signal processing (DSP) techniques are developed for the monitoring of an example application, namely the challenging one of tool breakage in milling operations. The monitoring regime is implemented on the dsPIC and its capabilities for real-time frequency analysis using overlap FFT and Multiband IIR Filters with dynamic coefficient selection techniques is explored. The developed systems are tested for various cutting conditions using existing machine tool signals and tool breakage is detected reliably in real-time. In attempting to enhance the accuracy of tool monitoring it is evident that the depth of cut (DOC) is an important parameter and achieving its on-line monitoring provides valuable information for condition monitoring. A systematic approach is adopted for the analysis and selection of ultrasonic sensors for distance measurement. A DOC monitoring system is developed using the dsPIC as the data acquisition and processing core. To achieve reliable results, various DSP algorithms are developed, implemented and verified for their effectiveness. The system integration stage combines the above elements for robust and reliable decision making and provides communication of the generated information to support management function using the internet and GSM connectivity. This integration enables an enhanced process management system which is capable of identifying all significant events, for offline analysis and subsequent diagnosis in addition to the real time diagnostic mode.

Item Type: Thesis (PhD)
Status: Unpublished
Schools: Engineering
Subjects: Q Science > QA Mathematics > QA76 Computer software
T Technology > TJ Mechanical engineering and machinery
ISBN: 9781303213298
Date of First Compliant Deposit: 30 March 2016
Last Modified: 10 Oct 2017 15:24

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