Multi-frequency ultrasound tomography based on modified matrix regularization method and wavelet fusion. (1st August 2022)

• Record Type: Journal Article
• Authors: Hou, Wenxiu; Tan, Chao; Bao, Yong; Dong, Feng
• Is Part Of: Measurement science & technology. Volume 33:Number 8(2022)
• Publication Date: 2022-08-01
• Subjects: ultrasound tomography -- multi-frequency -- regularization -- wavelet fusion; Physical measurements -- Periodicals; Scientific apparatus and instruments -- Periodicals; Equipment and Supplies -- Periodicals; Science -- instrumentation -- Periodicals; Technology -- instrumentation -- Periodicals; Mesures physiques -- Périodiques; Physical measurements; Scientific apparatus and instruments; Periodicals; 502.87
• DOI: 10.1088/1361-6501/ac6e2d
• Languages: English
• ISSNs: 0957-0233

Abstract

Abstract: Ultrasound tomography (UT) is a promising sensing technique for industrial processes owing to its advantages non-invasive, low cost, implement flexibility. Traditional UT may lack the distinguishability to resolve the flow with the complicated distribution. We propose a method that exploits the multi-frequency information to improve spatial resolution and resolve different inclusions. Firstly, multi-frequency ultrasound attenuation measurement information was collected and demodulated for tomographic reconstruction. Secondly, a hybrid reconstruction algorithm is proposed consisting of the modified matrix regularization and wavelet fusion methods. The proposed method can effectively reduce the artefact for the inclusion and sharpen the boundary, and detailed information can be reserved from the wavelet fusion. Thirdly, a multi-frequency experimental UT system is established to accomplish the 32 channels ultrasound signal excitation and reception. The performance of the proposed method is validated through numerical simulation and experimental study. The results show that the reconstruction metrics have been improved compared with the linear back projection and Tikhonov algorithms. We believe the proposed method can be used in the flow process prediction and diagnosis for industrial applications.