Embedded Sensing and Characterization of Pressure Distribution in Electrically Enhanced Micro-Rolling

In Micro-rolling process, metal sheet is imprinted with micron level textures by feeding into the gap between one smooth roll and one textured roll. To enhance the rollability of thin metal sheet and dimensional accuracy, high density current is sent through workpiece to soften the material by increasing temperature. This manufacturing process is called by Electrically-Assisted Micro-rolling (EAμR). EAμR, as a high efficiency and environment protection manufacturing process, can be used for production of key components in Micro-electromechanical Systems and bio-engineering. To control the quality of product, it is essential to monitor the pressure distribution in workpiece-roll interface during micro-rolling process. Comparing with process monitoring in conventional rolling process, sensing method in micro-rolling process monitoring not only demands to maintain surface integrity of roll surface, but also is limited by narrow space for sensors installation. Thus, a new sensing method based on embedded capacitance sensor array has been developed and prototyped for real-time monitoring in Electrically-Assisted Micro-rolling process. In the optimal structural design of embedded sensor, Finite element modeling is investigated to study the influence of sensor parameters and electrical current on sensor. To improve the spatial resolution of embedded sensor array mounted in a limited space, a new pressure reconstruction algorithm is presented to retrieve continuous spatial distribution of rolling pressure from a limited number of measured points. In this context, three research tasks has been identified and examined during the course of this thesis: 1) Design of a new embedded sensing method and its modeling The new sensing method monitors micro-rolling process by an embedded capacitance sensor array integrated into smooth roll of micro-rolling mill. The new embedded sensor using limited sensor installation space provides a new method to measure contact pressure between roller and workpiece without damaging the roller surface. It consists of a cylindrical plastic rod as the physical carrier of sensor array, a group of metal foils attached on cylindrical surface as receiving layer of capacitance array, and a thin plastic film as dielectric material of capacitance. The excitation layer of capacitance sensor is attached on inner surface of mounting hole in smooth roll. When the sensing rod is mounted into mounting hole, a series of capacitance is formed along axial direction of roll. In the design of mechatronics system, multi-physics modeling, based on finite element method, is developed not only to study the relationship between sensor parameters and the sensitivity of sensor, but to understand the thermal and electro-magnetic effect of electrical current passing through workpiece quantitatively as well. 2) Development of prototyping micro-rolling sensing system Micro-rolling sensing system is developed for real-time monitoring of Electrical-Assisted Micro-Rolling process. The whole system consists of one or two embedded capacitance sensor arrays, smooth roll, and capacitance measurement electronic device. Two 1 x 12 pixel capacitance sensor arrays are inserted into sensor mounting holes in smooth roll. Two pieces of printed circuit boards (PCB) are mounted at both ends of smooth roll for capacitance measurement and wireless data transmission. The electronic device measures capacitance in sensing rod using capacitance-to-digital converter chip for stable and precise capacitance measurement. To decrease the noise caused by signal cable, ZigBee communication module is used to transmit the digital signal from circuit to remote PC. In PC receiver, software interface has been developed for real-time monitoring and data analysis. A calibration process on micro-rolling mill has been investigated to calibrate the relationship between capacitance increase of each electrode and rolling pressure. 3) Reconstruction of Spatio-Temporal Distribution of rolling pressure Since roll misalignment and unevenness of workpiece can cause unexpected pressure distribution, monitoring of spatio-temporal distribution of rolling pressure at workpiece-roll interface is critical to control the accuracy of channel dimension. During micro-rolling process, micro-rolling sensing system embedded in rolling mill can transfer a set of capacitance data. To convert capacitance increases of one dimensional sensor array to pressure distribution along axial direction of roll, Back-proejection method is investigated to solve the inverse problem. The pressure-to-capacitance transducer is calculated by numerical method. To increase the spatial resolution of pressure-to-capacitance conversion, interpolation method is investigated to estimate the continuous deformation of dielectric layer under rolling pressure from limited number of sensing points. In this context, three interpolation methods (Kriging, Thin Plated Spline, and Bezier interpolation) and four back-projection methods (Tikhonov regularization, iterative Tikhonov regularization, Landweber iteration, and Offline Iteration Online Reconstruction) are discussed. The best combination of interpolation and back-projection method is determined by numerical experiment. In addition to these focal areas, prototyped micro-rolling sensing system has been equipped to micro-rolling mill for pressure monitoring during EAμR. Pressure reconstruction algorithm has also been tested by outputs of micro-rolling sensing system. The experimental verification was utilized for reliability evaluation of embedded sensing method and pressure reconstruction algorithm