A Novel Ultrasound Technique Based on Piezoelectric Diaphragms Applied to Material Removal Monitoring in the Grinding Process

The interest of the scientific community for ultrasound techniques has increased in recent years due to its wide range of applications. A continuous effort of researchers and industries has been made in order to improve and increase the applicability of non-destructive evaluations (NDE). In this context, the monitoring of manufacturing processes, such as the grinding process, arises. This work proposes a novel technique of ultrasound monitoring (chirp-through-transmission) through low-cost piezoelectric diaphragms and digital signal processing. The proposed technique was applied to the monitoring of material removal during the grinding process. The technique is based on changes in ultrasonic waves when propagated through the material under study, with the difference that this technique does not use traditional parameters of ultrasonic techniques but digital signal processing (RMS and Counts). Furthermore, the novelty of the proposed technique is also the use of low-cost piezoelectric diaphragms in the emission and reception of ultrasonic waves, enabling the implementation of a low-cost monitoring system. The results show that the monitoring technique proposed in this work, when used in conjunction with the frequency band selection, is sensitive to the material removal in the grinding process and therefore presents an advance for monitoring the grinding processes.

[1]  Eduardo C. Bianchi,et al.  Feature extraction using frequency spectrum and time domain analysis of vibration signals to monitoring advanced ceramic in grinding process , 2019, IET Science, Measurement & Technology.

[2]  Eduardo Carlos Bianchi,et al.  Tool condition monitoring of aluminum oxide grinding wheel in dressing operation using acoustic emission and neural networks , 2015 .

[3]  Victor Giurgiutiu,et al.  Recent advancements in the electromechanical (E/M) impedance method for structural health monitoring and NDE , 1998, Smart Structures.

[4]  S. Na,et al.  Steel wire electromechanical impedance method using a piezoelectric material for composite structures with complex surfaces , 2013 .

[5]  Jeong-Beom Ihn,et al.  Pitch-catch Active Sensing Methods in Structural Health Monitoring for Aircraft Structures , 2008 .

[6]  Piervincenzo Rizzo,et al.  Monitoring concrete by means of embedded sensors and electromechanical impedance technique , 2010, Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring.

[7]  Andre Luiz Andreoli,et al.  Study of a Low-Cost Piezoelectric Sensor for Three Phase Induction Motor Load Estimation , 2019 .

[8]  B. A. de Castro,et al.  Equivalent Circuit of Piezoelectric Diaphragms for Impedance-Based Structural Health Monitoring Applications , 2017, IEEE Sensors Journal.

[9]  M. M. Youssef,et al.  Applications of ultrasound in analysis, processing and quality control of food: A review , 2012 .

[10]  W. P. Dong,et al.  Raw Acoustic Emission Signal Analysis of Grinding Process , 1996 .

[11]  Snr. D. E. Dimla The Correlation of Vibration Signal Features to Cutting Tool Wear in a Metal Turning Operation , 2002 .

[12]  Sergej Hloch,et al.  Online-monitoring for Abrasive Waterjet Cutting of CFRP via Acoustic Emission: Evaluation of Machining Parameters and Work Piece Quality Due to Burst Analysis , 2016 .

[13]  D. V. Nehete,et al.  Dynamics and Vibration Measurements in Engines , 2018 .

[14]  Petra Wiederkehr,et al.  Stochastic modeling of grain wear in geometric physically-based grinding simulations , 2018 .

[15]  Roberto Teti,et al.  Prediction of Dressing in Grinding Operation via Neural Networks , 2017 .

[16]  Daniel J. Inman,et al.  Influence of Excitation Signal on Impedance-based Structural Health Monitoring , 2010 .

[17]  Eduardo Carlos Bianchi,et al.  In-process grinding monitoring by acoustic emission , 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[18]  Danilo Ecidir Budoya,et al.  A Comparative Study of Impedance Measurement Techniques for Structural Health Monitoring Applications , 2018, IEEE Transactions on Instrumentation and Measurement.

[19]  Eduardo Carlos Bianchi,et al.  Digital signal processing of acoustic emission signals using power spectral density and counts statistic applied to single-point dressing operation , 2017 .

[20]  S. Agarwal,et al.  Experimental investigation of surface/subsurface damage formation and material removal mechanisms in SiC grinding , 2008 .

[21]  Paulo R. Aguiar,et al.  Spectra Measurements Using Piezoelectric Diaphragms to Detect Burn in Grinding Process , 2017, IEEE Transactions on Instrumentation and Measurement.

[22]  Fabricio Guimarães Baptista,et al.  New signal processing approach for structural health monitoring in noisy environments based on impedance measurements , 2019, Measurement.

[23]  Victor Giurgiutiu,et al.  Damage Detection in Thin Plates and Aerospace Structures with the Electro-Mechanical Impedance Method , 2005 .

[24]  Eduardo Carlos Bianchi,et al.  Damage detection in grinding of steel workpieces through ultrasonic waves , 2018 .

[25]  C. Rogers,et al.  Modeling of the Electro-Mechanical (E/M) Impedance Response of a Damaged Composite Beam , 1999, Adaptive Structures and Material Systems.

[26]  Qian Feng,et al.  Loosening Monitoring of a Threaded Pipe Connection Using the Electro-Mechanical Impedance Technique—Experimental and Numerical Studies , 2018, Sensors.

[27]  Congbo Li,et al.  An Internet of Things based energy efficiency monitoring and management system for machining workshop , 2018, Journal of Cleaner Production.

[28]  José Alfredo Covolan Ulson,et al.  Partial Discharge Monitoring in Power Transformers Using Low-Cost Piezoelectric Sensors , 2016, Sensors.

[29]  F. Baptista,et al.  Impedance-based damage detection under noise and vibration effects , 2018 .

[30]  A. Voleišis,et al.  Application of the through transmission ultrasonic technique for estimation of the phase velocity dispersion in plastic materials , 2008 .

[31]  George Chryssolouris,et al.  Monitoring and Control of Manufacturing Processes: A Review☆ , 2013 .

[32]  Wenfeng Ding,et al.  Wear behavior and mechanism of single-layer brazed CBN abrasive wheels during creep-feed grinding cast nickel-based superalloy , 2010 .

[33]  I. Gallego,et al.  Intelligent grinding: sensorless instabilities detection , 2006, IEEE Instrumentation & Measurement Magazine.

[34]  Luis Elvira,et al.  Monitoring of lactic acid fermentation in culture broth using ultrasonic velocity , 2007 .

[35]  Valder Steffen,et al.  Impedance-Based Structural Health Monitoring , 2016 .

[36]  Vitaly Buckin,et al.  High-resolution ultrasonic spectroscopy , 2018 .

[37]  Felipe Alexandre,et al.  Emitter-Receiver Piezoelectric Transducers Applied in Monitoring Material Removal of Workpiece during Grinding Process , 2018, Proceedings.

[38]  Myung-Chang Kang,et al.  Tool condition and machined surface monitoring for micro-lens array fabrication in mechanical machining , 2008 .

[39]  Eduardo Carlos Bianchi,et al.  In-process grinding monitoring through acoustic emission , 2006 .

[40]  Jurgen Deveugele,et al.  Two-dimensional simulation of the single-sided air-coupled ultrasonic pitch-catch technique for non-destructive testing. , 2010, Ultrasonics.

[41]  Jürg Schweizer,et al.  Measuring and localizing acoustic emission events in snow prior to fracture , 2015 .

[42]  Ronald A. Kohser,et al.  DeGarmo's Materials and Processes in Manufacturing , 2020 .

[43]  Eduardo Carlos Bianchi,et al.  Chatter vibration monitoring in the surface grinding process through digital signal processing of acceleration signal , 2017, ECSA 2017.

[44]  Fabricio Guimarães Baptista,et al.  Experimental analysis of the feasibility of low-cost piezoelectric diaphragms in impedance-based SHM applications , 2016 .

[45]  David Dornfeld,et al.  Application of AE Contact Sensing in Reliable Grinding Monitoring , 2001 .

[46]  Roberto Teti,et al.  Dressing Tool Condition Monitoring through Impedance-Based Sensors: Part 1—PZT Diaphragm Transducer Response and EMI Sensing Technique , 2018, Sensors.

[47]  José Viterbo Filho,et al.  A New Impedance Measurement System for PZT-Based Structural Health Monitoring , 2009, IEEE Transactions on Instrumentation and Measurement.

[48]  Constantinos Soutis,et al.  Structural health monitoring techniques for aircraft composite structures , 2010 .

[49]  Eduardo Carlos Bianchi,et al.  Study on the effect of the temperature in Acoustic Emission Sensor by the Pencil Lead Break Test , 2018, IEEE International Conference on Industry Applications.

[50]  Ikuo Ihara,et al.  Ultrasonic Monitoring of Internal Temperature Distribution in a Heated Material , 2008 .

[51]  Eduardo Carlos Bianchi,et al.  A Contribution to the Monitoring of Ceramic Surface Quality Using a Low-Cost Piezoelectric Transducer in the Grinding Operation , 2018, Proceedings.

[52]  Mark J. Jackson,et al.  Low-Cost Piezoelectric Transducer for Ceramic Grinding Monitoring , 2019, IEEE Sensors Journal.

[53]  José Alfredo Covolan Ulson,et al.  An Experimental Study on the Effect of Temperature on Piezoelectric Sensors for Impedance-Based Structural Health Monitoring , 2014, Sensors.

[54]  Xun Chen,et al.  Classification of the acoustic emission signals of rubbing, ploughing and cutting during single grit scratch tests , 2006 .

[55]  Fabricio Guimarães Baptista,et al.  Performance of three transducer mounting methods in impedance-based structural health monitoring applications , 2017 .

[56]  Eduardo Carlos Bianchi,et al.  Grinding process monitoring based on electromechanical impedance measurements , 2015 .

[57]  C. Herrmann,et al.  Determining optimal process parameters to increase the eco-efficiency of grinding processes , 2014 .

[58]  Hui Luo,et al.  Mechanical impedance-based technique for steel structural corrosion damage detection , 2016 .

[59]  K. Wegener,et al.  Conditioning and monitoring of grinding wheels , 2011 .

[60]  Krzysztof Jemielniak,et al.  Advanced monitoring of machining operations , 2010 .

[61]  Fabricio Guimarães Baptista,et al.  Signal Acquisition from Piezoelectric Transducers for Impedance-Based Damage Detection , 2017, ECSA 2017.

[62]  Tadeusz Uhl,et al.  Application of electromechanical impedance-based SHM for damage detection in bolted pipeline connection , 2016 .

[63]  Ikuo Ihara,et al.  Non-invasive monitoring of temperature distribution inside materials with ultrasound inversion method , 2009, Int. J. Intell. Syst. Technol. Appl..

[64]  Weichung Yeih,et al.  Detection of the corrosion damage in reinforced concrete members by ultrasonic testing , 1998 .

[65]  Hosseini Sadegh,et al.  Classification of acoustic emission signals generated from journal bearing at different lubrication conditions based on wavelet analysis in combination with artificial neural network and genetic algorithm , 2016 .

[66]  Tribikram Kundu,et al.  An Introduction to Failure Mechanisms and Ultrasonic Inspection , 2010 .

[67]  Yavuz Ege,et al.  Discontinuity inspection in pipelines: A comparison review , 2017 .

[68]  Roberto Teti,et al.  Dressing Tool Condition Monitoring through Impedance-Based Sensors: Part 2—Neural Networks and K-Nearest Neighbor Classifier Approach , 2018, Sensors.