An automated industrial fish cutting machine: Control, fault diagnosis and remote monitoring

In this paper, an automated industrial fish cutting machine, which was developed and tested in the Industrial Automation Laboratory (IAL) of the University of British Columbia, is presented including its hardware structure, control sub-system, fault diagnosis sub-system and the remote monitoring sub-system. First, the hardware of the machine including the mechanical conveyer system, pneumatic system and the hydraulic system, and the associated sensors are introduced. Next, a fuzzy position control system is designed for the control of the cutting table moving along the horizontal (x) direction and its performance is compared with that with traditional proportional-integral-derivative (PID) control. A multi-sensor neuro-fuzzy fault diagnosis system is developed as well for the purpose of providing accurate and reliable diagnosis of the machine states in an automated factory environment. Finally, a web-based remote monitoring system is discussed, which allows engineers and researches to remotely monitor the health of the machine from any remote geographic location through the Internet.