The performance of the critical systems is one of the major concerns in modern industrial plants. The workhorses of these systems are induction motors consuming around 80% of the power. Periodic monitoring of these motors is based on a personal computer implementation that is performed offline. Such a monitoring system requires an expert interpretation. This paper presents a new methodology for fault detection, which is based on observing some frequency components of zero crossing points by using signal spectrum. The amplitude of ZCT signal and amplitude of fault related frequency are evaluated by fuzzy inference system to identify broken rotor bar faults. The proposed system is implemented on single low-cost field-programmable gate-arrays (FPGA). The algorithm was performed using some experimental tests for validating the implementation.