multi sensor signal processing for catastrophic tool failure detection in turning

Abstract This paper presents a methodology aimed at the identification of a catastrophic tool failure (CTF) in turning processes based on multiple sensor monitoring. Experimental turning tests were carried out under various cutting conditions (cutting speed, feed, depth of cut) using a multi-sensor monitoring system consisting of a triaxial force sensor to acquire the three components of the cutting force and an acoustic emission sensor. Signals analysis, interpretation and processing was performed on the multi-sensor signals acquired during the turning process and relevant statistical features were extracted and used to develop a methodology for the automatic CTF detection during turning

Cutting Forces Assessment in CNC Machining Processes: A Critical Review

Machining processes remain an unavoidable technique in the production of high-precision parts. Tool behavior is of the utmost importance in machining productivity and costs. Tool performance can be assessed by the roughness left on the machined surfaces, as well as of the forces developed during the process. There are various techniques to determine these cutting forces, such as cutting force prediction or measurement, using dynamometers and other sensor systems. This technique has often been used by numerous researchers in this area. This paper aims to give a review of the different techniques and devices for measuring the forces developed for machining processes, allowing a quick perception of the advantages and limitations of each technique, through the literature research carried out, using recently published worksThe present work was done and funded under the scope of the project ON-SURF (ANI | P2020 | POCI-01-0247-FEDER-024521, co-funded by Portugal 2020 and FEDER, through COMPETE 2020-Operational Programme for Competitiveness and Internationalisation. F.J.G. Silva also thanks INEGI-Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industria, due to its support.info:eu-repo/semantics/publishedVersio

Real-time performance of mechatronic PZT module using active vibration feedback control

This paper proposes an innovative mechatronic piezo-actuated module to control vibrations in modern machine tools. Vibrations represent one of the main issues that seriously compromise the quality of the workpiece. The active vibration control (AVC) device is composed of a host part integrated with sensors and actuators synchronized by a regulator; it is able to make a self-assessment and adjust to alterations in the environment. In particular, an innovative smart actuator has been designed and developed to satisfy machining requirements during active vibration control. This study presents the mechatronic model based on the kinematic and dynamic analysis of the AVC device. To ensure a real time performance, a H2-LQG controller has been developed and validated by simulations involving a machine tool, PZT actuator and controller models. The Hardware in the Loop (HIL) architecture is adopted to control and attenuate the vibrations. A set of experimental tests has been performed to validate the AVC module on a commercial machine tool. The feasibility of the real time vibration damping is demonstrated and the simulation accuracy is evaluate

Design of piezo-based AVC system for machine tool applications

The goal of machine tools for Ultra High Precision Machining is to guarantee high specified performances and to maintain them over life cycle time. In this paper the design of an innovative mechatronic subsystem (platform) for Active Vibration Control (AVC) of Ultra High Precision micromilling Machines is presented. The platform integrates piezoelectric stack actuators and a novel sensor concept. During the machining process (e.g. milling), the contact between the cutting tool and the workpiece surface at the tool tip point generates chattering vibrations. Any vibration is recorded on the workpiece surface, directly affecting its roughness. Consequently, uncontrolled vibrations lead to poor surface finishing, unacceptable in high precision milling. The proposed Smart Platform aims to improve the surface finishing of the workpiece exploiting a broadband AVC strategy. The paper describes the steps throughout the design phase of the platform, beginning from the actuator/sensor criteria selection taking into account both performance and durability. The novel actuation principle and mechanism and the related FE analysis are also presented. Finally, an integrated mechatronic model able to predict in closed-loop the active damping and vibration-suppression capability of the integrated system is presented and simulation results are discussed

Cutting mechanics and efficiency of forward and reverse multidirectional turning

Open Access via the Elsevier Agreement. This work was partially supported by Sichuan Science and Technology Program (23MZGC0052), the General Research Fund of Hong Kong Research Grant Council (PolyU15500721), National Natural Science Foundation of China (No. 51875480).Peer reviewedPublisher PD

Proceedings of Abstracts Engineering and Computer Science Research Conference 2019

© 2019 The Author(s). This is an open-access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. For further details please see https://creativecommons.org/licenses/by/4.0/. Note: Keynote: Fluorescence visualisation to evaluate effectiveness of personal protective equipment for infection control is © 2019 Crown copyright and so is licensed under the Open Government Licence v3.0. Under this licence users are permitted to copy, publish, distribute and transmit the Information; adapt the Information; exploit the Information commercially and non-commercially for example, by combining it with other Information, or by including it in your own product or application. Where you do any of the above you must acknowledge the source of the Information in your product or application by including or linking to any attribution statement specified by the Information Provider(s) and, where possible, provide a link to this licence: http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/This book is the record of abstracts submitted and accepted for presentation at the Inaugural Engineering and Computer Science Research Conference held 17th April 2019 at the University of Hertfordshire, Hatfield, UK. This conference is a local event aiming at bringing together the research students, staff and eminent external guests to celebrate Engineering and Computer Science Research at the University of Hertfordshire. The ECS Research Conference aims to showcase the broad landscape of research taking place in the School of Engineering and Computer Science. The 2019 conference was articulated around three topical cross-disciplinary themes: Make and Preserve the Future; Connect the People and Cities; and Protect and Care

Smart Sensor Monitoring in Machining of Difficult-to-cut Materials

The research activities presented in this thesis are focused on the development of smart sensor monitoring procedures applied to diverse machining processes with particular reference to the machining of difficult-to-cut materials. This work will describe the whole smart sensor monitoring procedure starting from the configuration of the multiple sensor monitoring system for each specific application and proceeding with the methodologies for sensor signal detection and analysis aimed at the extraction of signal features to feed to intelligent decision-making systems based on artificial neural networks. The final aim is to perform tool condition monitoring in advanced machining processes in terms of tool wear diagnosis and forecast, in the perspective of zero defect manufacturing and green technologies. The work has been addressed within the framework of the national MIUR PON research project CAPRI, acronym for “Carrello per atterraggio con attuazione intelligente” (Landing Gear with Intelligent Actuation), and the research project STEP FAR, acronym for “Sviluppo di materiali e Tecnologie Ecocompatibili, di Processi di Foratura, taglio e di Assemblaggio Robotizzato” (Development of eco-compatible materials and technologies for robotised drilling and assembly processes). Both projects are sponsored by DAC, the Campania Technological Aerospace District, and involve two aerospace industries, Magnaghi Aeronautica S.p.A. and Leonardo S.p.A., respectively. Due to the industrial framework in which the projects were developed and taking advantage of the support from the industrial partners, the project activities have been carried out with the aim to contribute to the scientific research in the field of machining process monitoring as well as to promote the industrial applicability of the results. The thesis was structured in order to illustrate all the methodologies, the experimental tests and the results obtained from the research activities. It begins with an introduction to “Sensor monitoring of machining processes” (Chapter 2) with particular attention to the main sensor monitoring applications and the types of sensors which are employed in machining. The key methods for advanced sensor signal processing, including the implementation of sensor fusion technology, are discussed in details as they represent the basic input for cognitive decision-making systems construction. The chapter finally presents a brief discussion on cloud-based manufacturing which will represent one of the future developments of this research work. Chapters 3 and 4 illustrate the case studies of machining process sensor monitoring investigated in the research work. Within the CAPRI project, the feasibility of the dry turning process of Ti6Al4V alloy (Chapter 3) was studied with particular attention to the optimization of the machining parameters avoiding the use of coolant fluids. Since very rapid tool wear is experienced during dry machining of Titanium alloys, the multiple sensor monitoring system was used in order to develop a methodology based on a smart system for on line tool wear detection in terms of maximum flank wear land. Within the STEP FAR project, the drilling process of carbon fibre reinforced (CFRP) composite materials was studied using diverse experimental set-ups. Regarding the tools, three different types of drill bit were employed, including traditional as well as innovative geometry ones. Concerning the investigated materials, two different types of stack configurations were employed, namely CFRP/CFRP stacks and hybrid Al/CFRP stacks. Consequently, the machining parameters for each experimental campaign were varied, and also the methods for signal analysis were changed to verify the performance of the different methodologies. Finally, for each case different neural network configurations were investigated for cognitive-based decision making. First of all, the applicability of the system was tested in order to perform tool wear diagnosis and forecast. Then, the discussion proceeds with a further aim of the research work, which is the reduction of the number of selected sensor signal features, in order to improve the performance of the cognitive decision-making system, simplify modelling and facilitate the implementation of these methodologies in a cloud manufacturing approach to tool condition monitoring. Sensor fusion methodologies were applied to the extracted and selected sensor signal features in the perspective of feature reduction with the purpose to implement these procedures for big data analytics within the Industry 4.0 framework. In conclusion, the positive impact of the proposed tool condition monitoring methodologies based on multiple sensor signal acquisition and processing is illustrated, with particular reference to the reliable assessment of tool state in order to avoid too early or too late cutting tool substitution that negatively affect machining time and cost

Slender workpiece cutting process stability prediction and monitoring based on internal signals

Chatter is commonly found when machining slender components on a lathe due to the low stiffness and damping. Aspects such as accuracy and roughness are usually compromised owing to large variation in stiffness along the length of the workpiece, which is a problem for the machining industry. The main contributions of this thesis are the proposal of (I) models for determine the chatter-free cutting conditions in slender workpiece machining and (II) a process monitoring system to detect chatter using available internal signals from the regulator. The clamping of a workpiece in the spindle of a lathe is not completely stiff, so the classical boundary conditions such as clamped–free, are not enough. The natural frequencies of the machine-workpiece system are usually lower than the theoretical ones obtained with classical boundary conditions. As the system is different for each machine and clamping method, it is necessary to characterize them. In order to be industrially feasible, a experimental method based on models with elastic boundary conditions is proposed to identify the system parameters. A exciter tool prototype based on a piezo actuator is developed to excite the system and natural frequencies have been measured by an accelerometer. The system parameters for a specific clamping and machine tool have been identified by means of model updating method. Once the system parameters have been identified, the effective stiffness of the system at each tool position of the workpiece is obtained. In slender workpieces, two nearby local modes appear due to the clamping, so workpiece chatter may occur by mode coupling in addition to regenerative. The stability of the process for a facing operation has been modelled in the state space taking into account both phenomena. An eigenvalue analysis is carried out by freezing the physical parameters of the time varying system at each time instant. The stability of the process is determined for certain cutting conditions. The theoretical results are validated by experimental tests. As the system is variant periodically in time due to the workpiece rotation, a Linear Time Periodic (LTP) stability model for slender workpiece machining has been proposed in order to define the process stability for each cutting condition. The stability is analysed by Floquet theory and the Stability Lobe Diagram (SLD) are obtained. Finally, the development and validation of a process monitoring system using internal signals available in the Computer Numerical Control (CNC) is presented. The feasibility of different internal signals for chatter monitoring are evaluated. An internal signal based monitoring system is implemented on a fast prototyping generic hardware and the monitoring system is experimentally evaluated in a CNC lathe.Oso ohikoa da chatterra aurkitzea tornu batean pieza lirainak mekanizatzen direnean, sistemaren zurruntasun eta amortiguazio txikiagatik. Mekanizatzean zehaztasuna oso txikia izan ohi da piezaren zurruntasunaren aldakortasun handiagatik luzeran zehar, eta hori arazo bat da mekanizatu industrian. Tesi honen ekarpen nagusiak (I) pieza lirainak mekanizatzeko chatterrik gabeko ebaketa baldintzak zehazteko modeloak eta (II) erregulatzailean eskuragarri dauden barne seinaleak erabiliz mekanizazio prozesua monitorizatzeko sistema dira. Tornu baten pieza amarratze sistema ez da erabat zurruna, beraz, gainazaleko baldintza klasikoak, ez dira nahikoak. Maiztasun naturalak orokorrean maiztasun teorikoak baino baxuagoak izan ohi dira. Makina eta amarratze metodo bakoitzerako sistema aldatzen denez, beharrezkoa da horiek identifikatzea. Industrialki bideragarria izan dadin, gainazaleko baldintza elastikoak dituen modeloetan oinarritutako metodo esperimental bat proposatzen da, sistemaren parametroak identifikatzeko. Sistema kitzikatzeko, eragingailu piezoelektriko batean oinarritutako erremienta kitzikagailu prototipo bat garatu da, eta maiztasun naturalak azelerometro baten bidez neurtzen dira. Amarre baterako eta makina-erreminta espezifiko baterako sistemaren parametroak identifikatu dira model updating metodoaren bidez. Sistemaren parametroak ezagutu ondoren, sistemaren zurruntasun eraginkorra lortu da piezaren luzeran zehar. Pieza lirainetan, hurbileko bi modu lokal agertzen dira amarratzearen ondorioz. Beraz, chatterra, moduen akoplamenduaren bidez gerta daiteke, birsorkuntza efektuaz gain. Errefrentatze operazio baterako, prozesuaren egonkortasuna modelatu da egoera-eremuan, bi fenomenoak kontuan hartuta. Balio propioak aztertzeko, sistemaren parametro fisikoak izoztu dira une bakoitzean. Ebaketa baldintza jakin batzuetarako prozesuaren egonkortasuna zehaztu da eta emaitza teorikoak proba esperimentalen bidez baliozkotu dira. Sistema denboran zehar aldakorra da periodikoki piezaren errotazioarengatik. Horregatik, denboran zehar periodikoa den egonkortasun modelo bat garatu da pieza lirainentzako eta haren egonkortasuna Floquet teoriaren bidez aztertu da. Ebaketa baldintza bakoitzerako prozesuaren egonkortasuna zehazteko, egonkortasun lobuluen diagrama lortu da. Azkenik, erregulatzailean eskuragarri dauden barne seinaleak erabiliz prozesua monitorizatzeko sistema bat garatu da. Chatterra monitorizatzeko barne seinale desberdinen bideragarritasuna ebaluatu da. Barne seinaleetan oinarritutako monitorizazio sistema implementatu da hardware generiko batean eta monitorizazio sistema esperimentalki balioztatu da tornu batean.El chatter se encuentra comúnmente cuando se mecanizan componentes esbeltos en un torno debido a su baja rigidez y amortiguación. Aspectos como la precisión y la rugosidad suelen verse comprometidos debido a la gran variación de la rigidez a lo largo de la pieza de trabajo, lo que constituye un problema para la industria del mecanizado. Las principales contribuciones de esta tesis son el desarrollo de (I) modelos para determinar las condiciones de corte sin vibraciones en el mecanizado de piezas esbeltas y (II) un sistema de monitorización del proceso para detectar chatter utilizando las señales internas disponibles del regulador. La sujeción de una pieza de trabajo en el husillo de un torno no es completamente rígida, por lo que las condiciones de contorno clásicas, como por ejemplo, viga empotrada-libre, no son suficientes. Las frecuencias naturales son generalmente más bajas que las teóricas obtenidas con las condiciones de contorno clásicas. Como el sistema varía para cada máquina y método de amarre, es necesario caracterizarlos. Para que sea industrialmente viable, se propone un método experimental basado en modelos con condiciones de contorno elásticas para identificar los parámetros del sistema. Es sistema ha sido excitado mediante un prototipo de herramienta excitadora basado en un actuador piezoeléctrico y las frecuencias naturales han sido medidas por un acelerómetro. Los parámetros del sistema para un amarre y una máquina herramienta específica han sido identificados mediante el método de model updating. Una vez identificados los parámetros del sistema, se ha obtenido la rigidez efectiva del sistema en cada posición de la pieza. En piezas esbeltas, aparecen dos modos locales cercanos debido al amarre, por lo que el chatter de pieza puede ocurrir por acoplamiento de modos además del efecto regenerativo. La estabilidad del proceso para una operación de refrentado ha sido modelada en el espacio de estado teniendo en cuenta ambos fenómenos. El análisis de los valores propios se lleva a cabo congelando los parámetros físicos del sistema en cada instante de tiempo. La estabilidad del proceso ha sido determinada para ciertas condiciones de corte. Los resultados teóricos han sido validados por medio de pruebas experimentales. Como el sistema es variante periódicamente en el tiempo debido a la rotación de la pieza, se ha propuesto un modelo de estabilidad lineal periódica en el tiempo para el mecanizado de piezas esbeltas, con el fin de definir la estabilidad del proceso para cada condición de corte. La estabilidad ha sido analizada con la teoría de Floquet y ha sido obtenido el diagrama de lóbulos de estabilidad. Finalmente, se presenta el desarrollo y validación de un sistema de monitorizado de proceso utilizando señales internas disponibles en el regulador. Se evalúa la viabilidad de diferentes señales internas para la monitorización del chatter. El sistema de monitorizado ha sido implementado en hardware genérico de prototipado rápido y el sistema de monitorización ha sido validada experimentalmente en un torno

Design, development, calibration, and testing of indigenously developed strain gauge based dynamometer for cutting force measurement in the milling process

In this work, a milling dynamometer based on strain gauge with an octagonal and square ring was designed and tested. Strain gauges were attached with the mechanical rings to detect the deformation, during the machining process. Wheatstone bridge circuit was equipped with gauges to acquire the strain as voltage owing to the deformation of mechanical rings when machining takes place. The finite element analysis (FEA) was used to identify the location of maximum deformation and stress. The direction of rings and location of gauges were decided to increase the sensitivity and decrease the cross-sensitivity. Then, the cutting force was acquired through NI 6221 M series data acquisition (DAQ) card. The dynamometer had undergone a cycle of tests to verify its static and dynamic characteristics. The metrological characterization was performed according to the calibration procedure based on ISO 376 – 2011 standard. The cutting force was measured with both the dynamometers through milling experiments based on Taguchi’s L9 orthogonal array and the results were recorded. The measured cutting force varied from 300 N to 550 N. The obtained results depicted that low-cost milling dynamometer was reliable to measure the three component machining force. Overall, the square ring based dynamometer provides the better static and dynamic characteristics in terms of linearity, cross-sensitivity (4%), uncertainty (0.054%), and natural frequency (362.41 rev/s)