The invention belongs to the technical field of integrated circuits, and particularly relates to a
chip-level
integrated circuit fault diagnosis method based on improved
wavelet entropy, which comprises the following steps: S1, acquiring an original
signal of a
chip-level
integrated circuit, and reconstructing the original
signal by using a VMD
signal reconstruction technology; s2, performing
deep processing on the reconstructed signal by adopting an improved
wavelet entropy method, and extracting key features of a fault signal; s3, monitoring the
voltage change of each node through the key characteristics of the fault signal, and effectively positioning the fault position; and S4, setting a fault factor which can comprehensively consider the fault position, the attenuation degree and the fault length, comparing the fault factor with a set threshold value, and judging the severity of the fault, thereby realizing the online diagnosis of the fault of the
chip-level
integrated circuit. According to the invention, by introducing the
adaptive wavelet basis selection and multi-scale
wavelet entropy fusion technology, the accuracy and efficiency of diagnosis are significantly improved, the
repeatability of fault signal
feature extraction is reduced, and the real-time performance and stability of a diagnosis
system are improved.