Jiahao Fu
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Jiahao Fu has a total of 6 co-authors. Here are the top co-authors by number of shared publications:
- Bing Chen
Memorial University
1 shared publication - Dongliang Li
Hunan Provincial Key Laboratory of High Efficiency and Precision Machining of Difficult-to-Cut Material, College of Mechanical Engineering, Hunan University of Science and Technology, Xiangtan 411201, China
1 shared publication - Guoyue Liu
Hunan Provincial Key Laboratory of High Efficiency and Precision Machining of Difficult to Machine Material, Hunan University of Science and Technology, Xiangtan 411201, China
1 shared publication - Junchang Liu
Hunan Provincial Key Laboratory of High Efficiency and Precision Machining of Difficult-to-Cut Material, College of Mechanical Engineering, Hunan University of Science and Technology, Xiangtan 411201, China
1 shared publication - Wenchu Ou
Hunan Provincial Key Laboratory of High Efficiency and Precision Machining of Difficult-to-Cut Material, College of Mechanical Engineering, Hunan University of Science and Technology, Xiangtan 411201, China
1 shared publication - Zihao Liu
Hunan Provincial Key Laboratory of High Efficiency and Precision Machining of Difficult-to-Cut Material, College of Mechanical Engineering, Hunan University of Science and Technology, Xiangtan 411201, China
1 shared publication
Latest Publications
- Open Access
Evaluation Method of the Band Saw Blade Wear State Based on Current Signals
The band saw blade is distinguished by its multi-point and flexible cutting capability when sawing materials. Its wear form is significantly more intricate than that of traditional cutting tools, such as the lathe tool and the milling cutter. Preliminary experimental observations suggest a close correlation between the wear of band saw blades and the motor current of the driving wheel. Therefore, this study evaluates the wear condition of band saw blades using current signals. A mathematical correlation model was established between the driving wheel motor current signals and the load on the band saw. A comprehensive experimental study was conducted on the band saw blade, encompassing the entire lifecycle of sawing operations. The average wear width of the tooth tip was utilized as an indicator of tooth wear, and an investigation was conducted into the correlation between the driving wheel motor current signals and the wear state. The findings indicated that the driving wheel motor current signals could be utilized to assess the blade wear state with high precision, which would facilitate proactive maintenance and replacement strategies to optimize band saw performance and service life.
Open AccessEvaluation Method of the Band Saw Blade Wear State Based on Current Signals
The band saw blade is distinguished by its multi-point and flexible cutting capability when sawing materials. Its wear form is significantly more intricate than that of traditional cutting tools, such as the lathe tool and the milling cutter. Preliminary experimental observations suggest a close correlation between the wear of band saw blades and the motor current of the driving wheel. Therefore, this study evaluates the wear condition of band saw blades using current signals. A mathematical correlation model was established between the driving wheel motor current signals and the load on the band saw. A comprehensive experimental study was conducted on the band saw blade, encompassing the entire lifecycle of sawing operations. The average wear width of the tooth tip was utilized as an indicator of tooth wear, and an investigation was conducted into the correlation between the driving wheel motor current signals and the wear state. The findings indicated that the driving wheel motor current signals could be utilized to assess the blade wear state with high precision, which would facilitate proactive maintenance and replacement strategies to optimize band saw performance and service life.