Non-contact measurement of grinding pins by means of a 2D laser micrometer

Valiño, G.; Wdowik, Roman; Misiura, J.; Zapico, Pablo

doi:10.1016/j.promfg.2017.09.080

Cited by 5 publications

(4 citation statements)

References 10 publications

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“…Strug [106] 等采用激光三角法测量了磨粒形貌, 并定义了代表砂轮磨损状况的特征形貌值. Valino 等 [107] 使用激光点测量法研究了 CBN 砂轮的磨损情况. Denkena [108] , Nadolny K 等 [109] 采用激光点测量法对砂轮表面磨粒状况进行了评估.…”

Section: F O R R E V I E W O N L Yunclassified

Research on grinding wheel wear measurement methods: Current status and future perspectives

LI,

BAO,

WANG

et al. 2024

Sci. Sin.-Tech.

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Section: F O R R E V I E W O N L Yunclassified

Research on grinding wheel wear measurement methods: Current status and future perspectives

LI,

BAO,

WANG

et al. 2024

Sci. Sin.-Tech.

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“…It is only possible to measure the wheel wear when the condition of the rotating wheel speed is adjusted up to 30 m/s (63). Additionally, a 2D laser micrometer is developed as a non-contact measurement system to measure the macrogeometric feature like the diameter deviation of the small grinding pin (64). Many attempt have been made to form a relationship between the wear pattern and the surface finish of the ground surface but resulted in failure.…”

Section: Figure 11 Triangular Laser For Monitoring Of Grinding Wheel ...mentioning

confidence: 99%

A Review on Advanced Monitoring and Identifying the Status of Grinding Machine Using Machine Learning Algorithms

Anand¹,

Sivakumar²,

Prabadevi³

2022

ECS Trans.

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Recently, the development of the grinding process is improved by including automatic sensors, actuators, control systems, artificial intelligence, and industrial internet of things in the grinding machine. Already existing contact type techniques are replaced with the automatic sensor system to incorporate artificial intelligence in the normal grinding process. Therefore, optical and laser technology is emerging as a smart device to observe the surface topography of the grinding wheel, surface finish of the ground surface, and automatic dressing process. Moreover, artificial intelligence consists of machine learning, which teaches the grinding machine based on the existing data available to improve the quality and the production rate of the grinding process. This can be achieved by controlling the process parameter, monitoring the machine health, and attaining optimum condition. The present review paper addresses the existing problems associated with the contact type and non-contact type measurement. The study also emphasizes the importance of machine learning algorithms to predict the failure of the grinding wheel and surface roughness of workpiece material in the grinding process.

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“…The laser detection technique is a nondestructive measuring tool based on the theory of laser diffraction or charge-coupled device (CCD) light projection. Laser detection techniques have been used in many industries, such as on-line detection of particle size in pharmaceuticals [19][20][21][22], production and detection of parts in manufacturing [23][24][25][26], and material determination in medicine [27]. Considering laser detection technique and its wider applications, the present study was conducted to develop an on-line analysis and monitoring system based on a high-detection sensitivity CCD laser micrometer for the quantitative visualization of droplets during the dripping process.…”

Section: Introductionmentioning

confidence: 99%

Real‐time droplet size analysis using laser micrometer as a process analytical technology tool for continuous dripping process

Wang

Tian

Zhang

et al. 2022

Engineering in Life Sciences

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Process analysis and monitoring during the manufacturing of the dripping pills are essential. However, research on developing sensor-based technology or process analytical technology (PAT) tools to analyze and monitor the dripping process is minimal. The purpose of this work is to develop a fast and non-destructive laser detection system for quantitative visualization of droplets, which involves detecting the size of the droplet and calculating the weight of the dripping pills during the dripping process. Several factors influencing the detection performance of the detection system and the detection system capability for quantitation of the pill weight were explored. The laser detection system accurately detects the weight of the dripping pills with the coefficients of determination (R 2 ) higher than 0.99. It was also robust concerning the variation in critical process parameters and critical material attributes. Furthermore, the laser detection system was successfully applied to the production line of Ginkgo biloba leaf dripping pills to monitor the dripping pills weight. The proposed laser detection system can analyze and monitor the dripping process in dripping pill manufacturing with stable performance, high accuracy, and high efficiency.

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Non-contact measurement of grinding pins by means of a 2D laser micrometer

Cited by 5 publications

References 10 publications

Research on grinding wheel wear measurement methods: Current status and future perspectives

Research on grinding wheel wear measurement methods: Current status and future perspectives

A Review on Advanced Monitoring and Identifying the Status of Grinding Machine Using Machine Learning Algorithms

Real‐time droplet size analysis using laser micrometer as a process analytical technology tool for continuous dripping process

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