Tool breakage monitoring based on the feature fusion of spindle acceleration signal

Pan, Tianhang; Zhang, Jun; Yang, Lei; Zhao, Wanhua; Zhang, Huijie; Lu, Bingheng

doi:10.1007/s00170-021-07705-z

“…It has low computational cost and is easy to understand [33]. The frequency domain analysis method uses fast Fourier transform to convert the signal from the time domain to the frequency domain, which will extract the tool status information from the frequency structure and harmonic components of the signal [34]. The time-frequency analysis as a powerful tool to analyze non-stationary signals during the machining process.…”

Section: Introductionmentioning

confidence: 99%

“…The most used time-frequency analysis algorithms include shorttime Fourier transform [35], wavelet transform [36] and empirical mode decomposition [37]. In the tool identification stage, neural networks, fuzzy clustering, hidden Markov models, support vector machines and other methods will be used to make decisions on tool status [34,38,39].…”

Section: Introductionmentioning

confidence: 99%

A State-of-the-art Review on the Intelligent Tool Holders in Machining

An,

Yang,

Li

et al. 2024

Intelligent and Sustainable Manufacturing

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In the manufacturing process, in addition to the properties of material itself, the quality of a product is directly related to the cutting process. Cutting force and cutting heat are two crucial factors in cutting processing. Researchers can analyze various signals during cutting process, such as cutting force signal, vibration signal, temperature signal, etc., which can regulate force and temperature, optimize the cutting process, and improve product quality. Therefore, it is very important to pay attention to various signals in cutting process. Meanwhile, good-quality signal data sets will greatly reduce time, resource and labor costs for subsequent use or analysis of researchers. Therefore, how to collect high-quality signals effectively and accurately is the first step. At present, researchers prefer to use various sensors to collect signals. With the advancement of science and technology, intelligent tool holder appears in researchers' vision. It integrates multiple systems such as sensors, data collection, data transmission, and power supply on the tool holder. It replaces traditional wired sensors, and it is highly interactive with CNC machine tools. This paper will carry out a systematic review and prospect from three aspects: the structural design of the intelligent tool holder, the signal monitoring technology of the intelligent tool holder, and the tool condition monitoring of the intelligent tool holder.

show abstract

“…It has low computational cost and is easy to understand [33]. The frequency domain analysis method uses fast Fourier transform to convert the signal from the time domain to the frequency domain, which will extract the tool status information from the frequency structure and harmonic components of the signal [34]. The time-frequency analysis as a powerful tool to analyze non-stationary signals during the machining process.…”

Section: Introductionmentioning

confidence: 99%

“…The most used time-frequency analysis algorithms include shorttime Fourier transform [35], wavelet transform [36] and empirical mode decomposition [37]. In the tool identification stage, neural networks, fuzzy clustering, hidden Markov models, support vector machines and other methods will be used to make decisions on tool status [34,38,39].…”

Section: Introductionmentioning

confidence: 99%

A State-of-the-art Review on the Intelligent Tool Holders in Machining

An,

Yang,

Li

et al. 2024

Intelligent and Sustainable Manufacturing

2

0

View full text Add to dashboard Cite

In the manufacturing process, in addition to the properties of material itself, the quality of a product is directly related to the cutting process. Cutting force and cutting heat are two crucial factors in cutting processing. Researchers can analyze various signals during cutting process, such as cutting force signal, vibration signal, temperature signal, etc., which can regulate force and temperature, optimize the cutting process, and improve product quality. Therefore, it is very important to pay attention to various signals in cutting process. Meanwhile, good-quality signal data sets will greatly reduce time, resource and labor costs for subsequent use or analysis of researchers. Therefore, how to collect high-quality signals effectively and accurately is the first step. At present, researchers prefer to use various sensors to collect signals. With the advancement of science and technology, intelligent tool holder appears in researchers' vision. It integrates multiple systems such as sensors, data collection, data transmission, and power supply on the tool holder. It replaces traditional wired sensors, and it is highly interactive with CNC machine tools. This paper will carry out a systematic review and prospect from three aspects: the structural design of the intelligent tool holder, the signal monitoring technology of the intelligent tool holder, and the tool condition monitoring of the intelligent tool holder.

show abstract