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Wireless Fault Detection System for an Industrial Robot Based on Statistical Control ChartAbstract
Industrial robots are now commonly used in production systems to
improve productivity, quality and safety in manufacturing
processes. Recent developments involve using robots
cooperatively with production line operatives. Regardless of
application, there are significant implications for operator
safety in the event of a robot malfunction or failure, and the
consequent downtime has a significant impact on productivity in
manufacturing. Machine healthy monitoring is a type of
maintenance inspection technique by which an operational asset
is monitored and the data obtained is analysed to detect signs
of degradation and thus reducing the maintenance costs.
Developments in electronics and computing have opened new
horizons in the area of condition monitoring. The aim of using
wireless electronic systems is to allow data analysis to be
carried out locally at field level and transmitting the results
wirelessly to the base station, which as a result will help to
overcome the need for wiring and provides an easy and
cost-effective sensing technique to detect faults in machines.
So, the main focuses of this research is to develop an online
and wireless fault detection system for an industrial robot
based on statistical control chart approach. An experimental
investigation was accomplished using the PUMA 560 robot and
vibration signal capturing was adopted, as it responds
immediately to manifest itself if any change is appeared in the
monitored machine, to extract features related to the robot
health conditions. The results indicate the successful detection
of faults at the early stages using the key extracted
parameters.
Keywords
Condition monitoring; Fault detection; Industrial robot;
Statistical control chart; Wireless system
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تاريخ النشر:25/7/2017 |