An In-Process Direct Monitoring Method for Milling Tool Failures Using a Laser Sensor

Ryabov, Oleg; Mori, Kazuo; Kasashima, Nagayoshi; Uehara, Kunio

doi:10.1016/s0007-8506(07)63024-8

Cited by 26 publications

(14 citation statements)

References 3 publications

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“…As in many applications using machine vision, object illumination notably impacts the process and for industrial applications can lead to process unreliability. Ryabov et al [57] used lasers to examine the profile of the cutting edge of milling cutter inserts. A 3D tool image was realised using this technique.…”

Section: Other Sensor Typesmentioning

confidence: 99%

“…Lee et al [24] present a real-time tool breakage monitoring system for milling based on cutting force indirect measurement through feed drive AC motor current, whose sensitivity is sufficient to identify tool breakage. Ryabov et al [57] develop an online tool geometry measurement system based on a laser displacement meter. Ahn et al [134] build up a vision system to detect small diameter tap breaks hardly perceived by indirect in-process monitoring methods as AE, torque and motor current; in [135], they propose an online drill wear estimation method based on spindle motor power signal during drilling.…”

Section: Tool Conditionsmentioning

confidence: 99%

“…Brophy et al [141] classify drilling operations as 'normal' or 'abnormal' (tool breakage or missing tool) using spindle power AE [131][132][133]193,194,204,205], vibrations [132,133,[195][196][197], cutting force [24,133,192,[195][196][197]203,210], hydraulic pressure [133], motor power [14,135], laser [57], camera [134], thermal imaging [136], audible sound [133,200], multiple sensors [210,211,227] Wavelet transform [131,193,197], time and frequency domain analysis [133,192,200,[203][204][205]210,227], image analysis [134,136,227], histogram method [57], thermal analy...…”

Section: Process Conditionsmentioning

confidence: 99%

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Advanced monitoring of machining operations

et al. 2010

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Section: Other Sensor Typesmentioning

confidence: 99%

Section: Tool Conditionsmentioning

confidence: 99%

Section: Process Conditionsmentioning

confidence: 99%

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Advanced monitoring of machining operations

et al. 2010

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“…LoCasto et al 4 used CCD camera for tool wear measurement. Ryabov et al 5 used laser displacement sensor for online measurement of tool geometry in the milling process. They evaluated tool geometry failure through intensity and displacement of laser beam simultaneously.…”

Section: Introductionmentioning

confidence: 99%

Fault diagnosis studies of face milling cutter using machine learning approach

Madhusudana

Budati

Gangadhar

et al. 2016

Journal of Low Frequency Noise, Vibration and Active Control

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Successful automation of a machining process system requires an effective and efficient tool condition monitoring system to ensure high productivity, products of desired dimensions, and long machine tool life. As such the component's processing quality and increased system reliability will be guaranteed. This paper presents a classification of healthy and faulty conditions of the face milling tool by using the Naïve Bayes technique. A set of descriptive statistical parameters is extracted from the vibration signals. The decision tree technique is used to select significant features out of all statistical extracted features. The selected features are fed to the Naïve Bayes algorithm. The output of the algorithm is used to study and classify the milling tool condition and it is found that the Naïve Bayes model is able to give 96.9% classification accuracy. Also the performances of the different classifiers are compared. Based on the results obtained, the Naïve Bayes technique can be recommended for online monitoring and fault diagnosis of the face milling tool.

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“…Siguiendo la idea de un monitoreo directo, los trabajos realizados en el Laboratorio de Ingeniería Mecánica en Tsukuba, Japón, presentan en [10] un método para detectar fractura en la herramienta usando un sensor de proximidad de tipo láser. Sin embargo, como es bien conocido, los reflejos de la luz láser pueden producir daños en los ojos.…”

Section: Introductionunclassified

Un Método De Monitoreo Del Desgaste De Una Herramienta De Corte Basado en Un Sensor De Proximidad De Fibra Óptica

Anda-Rodriguez

Castillo-Castañeda

2006

Ingeniare. Rev. chil. ing.

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RESUMENEste documento presenta una técnica novedosa para el monitoreo en línea del desgaste de una herramienta de fresado. El desgaste es estimado directamente a partir de un sensor de proximidad de fibra óptica (SPFO) con características de alta resolución y alto ancho de banda. El SPFO proporciona una medida de la distancia entre su extremo y el perfil de la herramienta. La principal contribución de este trabajo es la aplicación del SPFO para monitorear en línea el desgaste de una herramienta de fresado. Puesto que la luz emitida por el SPFO proviene de un fotodiodo, esta no produce daño a los ojos, lo que la hace más segura que los sensores de desplazamiento de tipo láser. Esta técnica permite monitorear el desgaste de la herramienta en tiempo real, mientras la herramienta gira, con una precisión inferior a 1 micra. Se presentan resultados experimentales para una herramienta de fresado vertical de cuatro filos que gira a 300 rpm.Palabras clave: Inspección óptica, detección de desgaste, monitoreo de herramientas, sensores de fibra óptica. ABSTRACT A novel technique for on-line wear monitoring of a milling tool is presented. The tool wear is estimated directly from a fiber optic proximity sensor (FOPS) with high resolution and high bandwidth characteristics. The FOPS provides a distance measurement between its probe and the tool profile. The main contribution of this work is the application of

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An In-Process Direct Monitoring Method for Milling Tool Failures Using a Laser Sensor

Cited by 26 publications

References 3 publications

Advanced monitoring of machining operations

Advanced monitoring of machining operations

Fault diagnosis studies of face milling cutter using machine learning approach

Un Método De Monitoreo Del Desgaste De Una Herramienta De Corte Basado en Un Sensor De Proximidad De Fibra Óptica

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