A Noise Suppression Method for Speech Signal by Jointly Using Bayesian Estimation and Fuzzy Theory

Ikuta, Akira; Orimoto, Hisako; Hasegawa, Kouji

doi:10.4236/jsea.2021.1412037

Cited by 1 publication

(1 citation statement)

References 15 publications

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“…Zhang et al introduced dynamic integrated convolutional neural networks in fault diagnosis, which constructed a multilevel wavelet coefcient matrix based on wavelet packets for the description of nonsmooth vibration signals, and the fusion of its dynamic ensemble layer and multilevel wavelet packets enhanced the efectiveness of diagnosis [15]. In addition to neural networks, Ikuta et al introduced the fuzzy theory into the feld of signal processing and combined it with other algorithms to achieve the fusion of vibration signals and enhance their efectiveness and accuracy [16]. Other scholars have combined multisensor technology and fuzzy information fusion algorithms to improve the accuracy and reliability of chemical enterprise safety assessment systems in the analysis of chemical enterprise accidents and related casualty probabilities [17].…”

Section: Status Of Vibration Signal Fusion Technology and Industrial ...mentioning

confidence: 99%

Designing and Manufacturing of Industrial Robots with Dual-Angle Sensors Taking into Account Vibration Signal Fusion

Yan¹,

Cheng

2023

Journal of Robotics

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Industrial robots are an important way to realize the development of industrial industry intelligence and automation, an important driving force to accelerate the construction of Industry 4.0, and an important basic force to improve the professional level of industrial industry. The development of industrial robot technology has enhanced the requirements of its detection quality and the demand for data comprehensiveness. Most of the previous robots obtain the corresponding data through a single sensor system, which has a large error and a high limitation of the range of data obtained. The detection method of industrial robots has the problems of high cost and high professionalism. Therefore, this paper constructs a dual-angle sensor industrial robot detection system based on the fusion of multisource vibration signals and achieves the fusion of multisensor signals through Kalman filtering to provide reliable analysis data for the dual-angle sensor detection system. The experimental results show that Kalman filtering can effectively remove noise while preserving the original vibration signal characteristics and structure and improve the reliability and validity of the vibration signal. In addition, the dual-angle sensor detection system can realize the position detection of industrial robots according to the command standard and obtain the corresponding residual and standard values through system data analysis. The overall optimization of the system algorithm enhances the accuracy and reliability of the measurement.

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Section: Status Of Vibration Signal Fusion Technology and Industrial ...mentioning

confidence: 99%

Designing and Manufacturing of Industrial Robots with Dual-Angle Sensors Taking into Account Vibration Signal Fusion

Yan¹,

Cheng

2023

Journal of Robotics

View full text Add to dashboard Cite

show abstract

A Noise Suppression Method for Speech Signal by Jointly Using Bayesian Estimation and Fuzzy Theory

Cited by 1 publication

References 15 publications

Designing and Manufacturing of Industrial Robots with Dual-Angle Sensors Taking into Account Vibration Signal Fusion

Designing and Manufacturing of Industrial Robots with Dual-Angle Sensors Taking into Account Vibration Signal Fusion

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