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in the process of studying fault detection method for small electronic devices, when using current algorithm for small electronic equipment fault detection, too many constraints results in incomplete detection, large error and time consuming. To this end, a fault detection method for small electronic devices based on improved immune algorithm is proposed. The method fusing in wavelet analysis technology extracts the fault information of small electronic equipment detection system first, and then uses the wavelet modulus maximum to map the transient response of the fault state. On the basis of the risk theory model, the antigen collection and antibody groups in real-time fault detection system of small electronic equipment are matched with the obtained fault feature information one by one, and a multi threshold is set up to determine whether it is a fault signal, thus, a small electronic equipment fault detection is completed efficiently. The experimental results show that the method of fault detection based on small electronic devices is highly effective. 1 Introduction With the development of electronic information technology, small electronic devices have been used in the construction of various industries due to its small size, light weight and compact structure (1-3). However, small electronic devices are susceptible to environmental impact (such as humidity, mold, salt spray, etc.) and results in a series of failures, and the difficulty of detection is large (4-6). Therefore, how to detect the fault of small electronic devices is the main problem to be solved in this field (7-9). At present, the main method of fault detection is based on genetic algorithm, ant algorithm and neural network algorithm (10). Among them, which often used in the detection of small electronic equipment is based on ant algorithm, but the algorithm has too many constraints, the detection is not comprehensive, and the error is large and time-consuming. To this end, a fault detection method for small electronic devices based on improved immune algorithm is proposed. The method fusing in wavelet analysis technology extracts the fault information of small electronic equipment detection system first, and then uses the wavelet modulus maximum to map the transient response of the fault state. On the basis of the risk theory model, the antigen collection and antibody groups in real-time fault detection system of small electronic equipment are matched with the obtained fault feature information one by one, and a multi threshold is set up to determine whether it is a fault signal, thus, a small electronic equipment fault detection is completed efficiently. The experimental results show that the method of fault detection based on small electronic devices is highly effective. 2 Fault detection principle of small electronic devices During fault detection process for small electronic devices, extract non-stationary time-varying signal of small electronic device detection system and respond, set the appropriate initial threshold, and compare with the extracted fault signal, to determine whether it is a fault signal of small electronic devices. Detailed steps as below: During fault detection process for small electronic devices, set ij d indicating the detection attribute of detection point j

Research and Simulation of fault detection method for small electronic equipment