Monitoring of the Grinding Process with an AE Sensor Integrated CBN Wheel.

Wakuda, Manabu; Inasaki, Ichiro; Ogawa, Koji; Takahara, Motoaki

doi:10.2493/jjspe.59.275

Cited by 7 publications

(7 citation statements)

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“…The AE generated during a grinding process has been proven to contain information strongly related to the condition changes in the grinding zone [13]. According to [14], frequency range of AE sensor goes from 50KHz to up to 1000KHz, which is above the range of many noises coming from sources outside of the grinding process.…”

Section: Methodsmentioning

confidence: 99%

The Application of Artificial Intelligence in Grinding Operation Using Sensor Fusion

Junejo¹

2017

Geomate

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ABSTRACT:The application of multi-sensor systems for the monitoring of machining processes is becoming more commonplace to improve productivity, automation and reliability. In order to enhance knowledge in this area of applications, this study proposes a novel approach for the continuous on-line condition monitoring of grinding operation using low cost infrared and visual imager alongside with more commonly used sensors i.e. AE sensor, accelerometer and dynamometer. To achieve this aim a multi-sensor system is developed and installed for the monitoring of grinding operation. The signals acquired and analyzed by the system include visual, thermal, force, vibration and AE under different grinding conditions. Image processing techniques are used to establish that an increase in sparks within grinding zone results in rise of grinding zone temperature, which in turn results in increased surface roughness. Signal processing techniques are used to establish that dressing of wheel is most influential factor for surface roughness of workpiece. Artificial intelligence is then used successfully on both infrared and visual data to establish an automated continuous on-line monitoring system for grinding operation with an accuracy of 95 percent.

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Section: Methodsmentioning

confidence: 99%

The Application of Artificial Intelligence in Grinding Operation Using Sensor Fusion

Junejo¹

2017

Geomate

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“…''Intelligent'' grinding wheels. [44][45][46][47][48][49][50] Characteristics of modification Construction scheme…”

Section: Characteristics Of Modificationmentioning

confidence: 99%

Potential for improving efficiency of the internal cylindrical grinding process by modification of the grinding wheel structure—Part II: Grinding wheels made of superabrasive grains

Nadolny

Habrat

2016

Proceedings of the Institution of Mechanical Engineers, Part E:

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This article offers an overview of 11 grinding wheel construction modifications used in the peripheral grinding of flat, shaped, internal, and external cylindrical surfaces, when grinding wheels made of superabrasive grains are used (natural and synthetic diamonds, as well as mono-and microcrystalline cubic boron nitride). The text contains characteristics of grinding wheels with: bubble corundum grains, glass-crystalline bond, conic chamfer, zones of different diameters, a centrifugal provision of the coolant into the grinding zone, aggregate grains, zone-diversified structure, as well as impregnated (self-lubricating), multiporous, segment and ''intelligent'' grinding wheels. Each of the presented structural modifications were described by giving construction scheme, used abrasive grains, range of applications, advantages as well as disadvantages. Modifications of the grinding wheel construction allow for effective improvement of both the conditions and the results of the grinding process. A wide range of the known modifications allow for their proper selection depending on the required criteria of effective evaluation and taking into account the specific characteristics of superabrasive grains. As a result, it is possible to obtain positive influence on a number of technological factors of the grinding process. The described modifications of the grinding wheel structure can be also an inspiration and the basis for creating new solutions in this field.

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“…On the other side, waviness monitoring can be performed through indirect monitoring methods. Cutting forces and acoustic emission (AE) signals [6][7][8] are ideal monitoring solutions when a pulsed chip formation occurs with consequent cutting pressure modulation (since the main source of the AE signal is the mechanical stress generated in the wheel-workpiece contact zone). In [9], the roundness profile of the workpiece in cylindrical plunge grinding is correlated with AE signals captured in process.…”

Section: Xsensmentioning

confidence: 99%

A model-based approach for online estimation of surface waviness in roll grinding

Parenti

Leonesio²,

Cassinari³

et al. 2015

Int J Adv Manuf Technol

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Vibrations onset represents a paramount issue in all grinding processes. The related surface defects appear in the form of micrometric waviness that decreases the finishing quality and in some cases the functionality of the ground workpieces: sometimes, these defects can be also marked on the grinding wheel surface. This paper presents an online model-based approach to identify and quantify the level of waviness starting from multiple acceleration measurements, allowing a continuous monitoring of wheel and/or workpiece defects. The identification algorithm, that exploits a linear model of machine and process dynamics, is based on the application of Least Squares method in the frequency domain. Experiments confirm the good performance of the algorithm that, hence, can be exploited for developing advanced control schemes of the grinding process

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Monitoring of the Grinding Process with an AE Sensor Integrated CBN Wheel.

Cited by 7 publications

References 0 publications

The Application of Artificial Intelligence in Grinding Operation Using Sensor Fusion

The Application of Artificial Intelligence in Grinding Operation Using Sensor Fusion

Potential for improving efficiency of the internal cylindrical grinding process by modification of the grinding wheel structure—Part II: Grinding wheels made of superabrasive grains

A model-based approach for online estimation of surface waviness in roll grinding

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