Wireless sensor Networks will not working due to some fault and due to link failure, resource failure or by any other reason is to be tolerated for continued working of the system smoothly and accurately. A fault in one sensor may result in the isolation of other sensors that are connected to it, but that doesn‟t mean that they stop working. In fact, the programs on them may not be able to detect whether the network has failed or has become unusually slow .Faults may affect the nodes of the system at any time. So diagnosing the faulty nodes in the wireless sensor system is one of the requirements to make the system more reliable and efficient. These faults can be detected and recovered by many techniques according to the requirement. An appropriate fault detector can avoid loss due to system crash by activating the required fault tolerance mechanism. In our work we showed that the Fuzzy-Genetic approach for detection of faults in wireless sensor systems with at most one less than half which means if we have 20 sensors we need at most 9 sensors to be faulty systems out of the total systems. These faults are tested using a robust stochastic search method based on Genetic algorithm with Fuzzy controlled mutation and Tournament selection. This work provides how a fuzzy-genetic algorithm can be applied to detect permanent faults in a k-connected Wireless sensor Systems. The program is implemented in C++ and was tested with random test graphs. Simulation results show that the performance of proposed fault detection algorithm is satisfactory and demonstrated the efficiency of genetic operators used for this study.