Partial discharge serves as a typical indicator of insulation defects in high-voltage electrical equipment and is often accompanied by acoustic emission. The online monitoring of partial discharge via acoustic signals makes it essential to investigate the underlying mechanism of acoustic wave excitation by partial discharge. However, experimental investigation is often prohibitively expensive and struggles to capture key discharge parameters. Numerical simulation thus provides a valuable alternative for microscopic analysis. In this study, a typical needle-plane corona discharge model is employed. Based on the theory that acoustic waves are generated by gas disturbances caused by collisions between charged and neutral particles in weakly ionized gases, a numerical model for acoustic wave excitation by positive corona discharge is developed. Simulations and analyses are performed on the acoustic source characteristics and the acoustic field distribution. The results demonstrate that the spatiotemporal evolution of electron density plays a dominant role in the generation of acoustic waves during positive DC corona discharge. The characteristics of the simulated acoustic field agree well with experimental results from relevant studies, validating the effectiveness of the proposed electroacoustic coupling numerical model and providing a new tool for further research into the acoustic features of partial discharge.

Acoustic microimaging (AMI), a technology for high-resolution imaging of materials using a scanning acoustic microscope, has been widely used for non-destructive testing and evaluation of electronic packages. Recently, the internal features and defects of electronic packages have reached the resolution limits of conventional time domain or frequency domain AMI methods with the miniaturization of electronic packages. Various time-frequency domain AMI methods have been developed to achieve super-resolution. In this paper, the sparse representation of AMI signals is studied, and a constraint dictionary-based sparse representation (CD-SR) method is proposed. First, the time-frequency parameters of the atom dictionary are constrained according to the AMI signal to constitute a constraint dictionary. Then, the AMI signal is sparsely decomposed using the matching pursuit algorithm, and echoes selection and echoes reconstruction are performed. The performance of CD-SR was quantitatively evaluated by simulated and experimental ultrasonic A-scan signals. The results demonstrated that CD-SR has superior longitudinal resolution and robustness.