Design of a Fuzzy Intelligent Diagnostic System for Milling Machines

This study presents an intelligent diagnostic system for milling machines equipped with electric actuators and lubrication systems. The fuzzy system takes three input parameters: oil temperature (°C), vibration level (dB), and electric power (KW). Based on these inputs, the machine diagnoses faults and reports them online. To enhance computational efficiency, fuzzy rules were developed, categorized, and optimized, reducing the number of rules from ۱۸ to ۷. The key advantages of the proposed method are its high accuracy in fault detection and automation, leading to extended machine lifespan, prevention of severe damages, and reduced maintenance costs.

Keywords:

Condition Monitoring , Microprocessor , Fuzzy , Diagnostic System