Design Of An Intelligent Embedded System For Condition Monitoring Of An Industrial Robot
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Design of an Intelligent Embedded System for Condition Monitoring of an Industrial Robot
This thesis introduces a successfully designed and commissioned intelligent health monitoring system, specifically for use on any industrial robot, which is able to predict the onset of faults in the joints of the geared transmissions. However the developed embedded wireless condition monitoring system leads itself very well for applications on any power transmission equipment in which the loads and speeds are not constant, and access is restricted. As such this provides significant scope for future development. Three significant achievements are presented in this thesis. First, the development of a condition monitoring algorithm based on vibration analysis of an industrial robot for fault detection and diagnosis. The combined use of a statistical control chart with time-domain signal analysis for detecting a fault via an arm-mounted wireless processor system represents the first stage of fault detection. Second, the design and development of a sophisticated embedded microprocessor base station for online implementation of the intelligent condition monitoring algorithm, and third, the implementation of a discrete wavelet transform, using an artificial neural network, with statistical feature extraction for robot fault diagnosis in which the vibration signals are first decomposed into eight levels of wavelet coefficients.
Intelligent Agriculture
Author: Gonzalo Maldonado-Guzmán
language: en
Publisher: Emerald Group Publishing
Release Date: 2019-06-10
Intelligent Agriculture presents a real case study on the development of a state-of-the-art technology, the Wireless Sensor Network (WSN), which intends to address fundamental and very current challenges in the agriculture sector using benchmark analysis of the WSN against other similar technologies.
Proceedings of the UNIfied Conference of DAMAS, IncoME and TEPEN Conferences (UNIfied 2023)
This volume gathers the latest advances, innovations and applications in the field of condition monitoring, damage assessment and maintenance engineering, as presented by leading international researchers and engineers at the UNIfied Conference of DAMAS (International Conference on Damage Assessment of Structures), IncoME (International Conference on Maintenance Engineering) and TEPEN (The Efficiency and Performance Engineering) Conferences, held in Huddersfield, UK on August 29 – September 1, 2023. Topics include machinery dynamics, sensors and measurement systems, signal processing, structural damage identification and machine fault diagnosis, plant maintenance and reliability, machine health monitoring, asset management, life-cycle cost optimisation, prognostics and health management, maintenance performance measurement, manufacturing process monitoring, and robot-based monitoring and diagnostics. The contributions, which were selected through a rigorous internationalpeer-review process, share exciting ideas that will spur novel research directions and foster new multidisciplinary collaborations.