ArticleSensors (Basel, Switzerland)2020
Grinding Wheel Loading Evaluation by Using Acoustic Emission Signals and Digital Image Processing.
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Review of advanced sensor system applications in grinding operations.Journal of advanced research · 2025Review
- Prediction of Tool Forces in Manual Grinding Using Consumer-Grade Sensors and Machine Learning.Sensors (Basel, Switzerland) · 2021Article
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Authors and funding
2 authors.
Funding
Abstract
In the manufacturing industry, grinding is used as a major process for machining difficult-to-cut materials. Grinding is the most complicated and precise machining process. For grinding machines, continuous generating gear grinding machines are widely used to machine gears which are essential machine elements. However, due to its complicated process, it is very difficult to design a reliable measurement method to identify the grinding wheel loading phenomena during the grinding process. Therefore, this paper proposes a measurement method to identify the grinding wheel loading phenomenon in the grinding process for continuous generating gear grinding machines. In the proposed approach, an acoustic emission (AE) sensor was embedded to monitor the grinding wheel conditions; an offline digital image processing technique was used to determine the loading areas over the surface of Al
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Registered trials
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