Principal Component Analysis based Image Fusion Routine with Application to Stamping Split Detection

This dissertation presents a novel thermal and visible image fusion system with application in online automotive stamping split detection. The thermal vision system scans temperature maps of high reflective steel panels to locate abnormal temperature readings indicative of high local wrinkling pressure that causes metal splitting. The visible vision system offsets the blurring effect of thermal vision system caused by heat diffusion across the surface through conduction and heat losses to the surroundings through convection. The fusion of thermal and visible images combines two separate physical channels and provides more informative result image than the original ones. Principal Component Analysis (PCA) is employed for image fusion to transform original image to its eigenspace. By retaining the principal components with influencing eigenvalues, PCA keeps the key features in the original image and reduces noise level. Then a pixel level image fusion algorithm is developed to fuse images from the thermal and visible channels, enhance the result image from low level and increase the signal to noise ratio. Finally, an automatic split detection algorithm is designed and implemented to perform online objective automotive stamping split detection. The integrated PCA based image fusion system for stamping split detection is developed and tested on an automotive press line. It is also assessed by online thermal and visible acquisitions and illustrates performance and success. Different splits with variant shape, size and amount are detected under actual operating conditions

Diagnosis of sheet metal forming processes based on thermal energy distribution: 3D reconstruction.

Ng Yiu Ming.Thesis (M.Phil.)--Chinese University of Hong Kong, 2005.Includes bibliographical references (leaves 110-114).Abstracts in English and Chinese.Chapter 1. --- Introduction --- p.1Chapter 1.1 --- Diagnosis concept based on thermal energy distribution --- p.6Chapter 1.1.1 --- A cup drawing example --- p.8Chapter 1.2 --- Need for 3D infrared thermal distribution measurement --- p.10Chapter 1.3 --- Outline of the Thesis --- p.11Chapter 2. --- Approach --- p.15Chapter 2.1 --- Similarity and extreme temperature analysis --- p.15Chapter 2.2 --- Thermodynamics for FEA in sheet metal stamping --- p.17Chapter 2.3 --- Acquisition of 3D thermal distribution --- p.20Chapter 3. --- Implementation of the Diagnosis System --- p.23Chapter 3.1 --- Thermograph acquisition --- p.23Chapter 3.2 --- Diagnosis system setup --- p.24Chapter 3.3 --- Perspective camera model --- p.25Chapter 3.4 --- System calibration --- p.27Chapter 3.4.1 --- LEDs calibration board --- p.27Chapter 3.4.2 --- Net-and-board calibration box --- p.29Chapter 3.5 --- Reconstruction algorithm --- p.33Chapter 3.6 --- Summary --- p.37Chapter 4. --- Consistency from Different Viewpoints --- p.38Chapter 4.1 --- Summary --- p.42Chapter 5. --- Visual Reconstruction of Objects --- p.44Chapter 5.1 --- Visual camera calibration --- p.45Chapter 5.2 --- Results --- p.49Chapter 5.2.1 --- "Cartoon model ""SiuSun""" --- p.49Chapter 5.2.2 --- Stamping disc --- p.51Chapter 5.3 --- Summary --- p.53Chapter 6. --- Thermal Distribution Reconstruction of Stamping Workpieces --- p.54Chapter 6.1 --- Infrared camera calibration --- p.54Chapter 6.2 --- Results --- p.57Chapter 6.2.1 --- Air conditioner cap --- p.57Chapter 6.2.2 --- Deep drawing cup --- p.59Chapter 6.2.3 --- Stamping cylinder from KS Factory --- p.61Chapter 6.3 --- Summary --- p.65Chapter 7. --- Infrared Camera on a Robotic Arm --- p.66Chapter 7.1 --- Robotic arm system setup --- p.67Chapter 7.2 --- System calibration --- p.68Chapter 7.3 --- Results --- p.77Chapter 7.3.1 --- Image sequence from horizontal viewpoints --- p.77Chapter 7.3.2 --- Image sequence from inclined viewpoints --- p.80Chapter 7.3.3 --- Image sequence from arbitrary viewpoints --- p.83Chapter 7.4 --- Comparison of the three different viewpoints --- p.85Chapter 7.5 --- Summary --- p.87Chapter 8. --- Compensation of Temperature Fade-out Problem --- p.88Chapter 8.1 --- Causes of temperature fade-out --- p.88Chapter 8.2 --- Solutions --- p.90Chapter 8.3 --- Summary --- p.91Chapter 9. --- Other Applications --- p.92Chapter 9.1 --- Automotive industry --- p.92Chapter 9.1.1 --- Background --- p.93Chapter 9.1.2 --- Experiment and result --- p.94Chapter 9.2 --- General heat transfer analysis --- p.97Chapter 9.3 --- Summary --- p.98Chapter 10. --- Conclusions --- p.99Chapter 10.1 --- Summary --- p.99Chapter 10.2 --- Future work --- p.104Chapter A. --- Transformation Matrices of the System --- p.106Bibliography --- p.11

Industry/University Collaboration at the University of Michigan-Dearborn: A Focus on Relevant Technology

https://deepblue.lib.umich.edu/bitstream/2027.42/154105/1/kampfner1997.pd

Industry/University Collaboration at the University of Michigan-Dearborn: A Focus on Relevant Technology

https://deepblue.lib.umich.edu/bitstream/2027.42/154106/1/kampfner1998.pd

Additive manufacturing of soft magnets for electrical machines—a review

With growing interest in electrification from clean energy technologies, such as wind power and use of pure electric powertrains in various applications, the demand for next-generation, high-performance magnetic materials has risen significantly. Electrical machine design for these applications is facing challenges in terms of meeting very demanding metrics for power densities and conversion efficiencies, thereby motivating the exploration of advanced materials and manufacturing for the next generation of lightweight ultraefficient electric machines. Additive manufacturing (AM), a layer-by-layer three dimensional (3D) printing technology, opens up new venues of improvements for industrial manufacturing of electrical machines via near-net shape printing of complex geometries, reduction of parts count and production lead time, and conservation of expensive critical materials such as rare-earth magnets as well as nanocrystalline and amorphous soft magnetic composites, allowing their use in only critical regions required by desired properties of the printed parts. The magnetic, electrical, thermal, and mechanical properties of the magnetic materials are also greatly influenced by the selection of the AM method. Among the seven major American Standard Testing and Materials-defined standard modes of 3D printing, selective laser melting, fused deposition modeling, and binder jetting technology dominate the AM processing of soft magnetic materials and their integration in electrical machines. In this work, the state of the art in printability and performance characteristics of soft magnetic materials for electric machines is summarized and discussed. The prospects of soft magnetic materials selection in terms of price, printability, weight, and performance of the electrical machines are also discussed. This review highlights the current status of AM of large electrical machines, AM process selection guidelines, hybrid printing technologies, and the associated opportunities and challenges. An emphasis is put on multimaterial processing that is essential for electrical machines. Hybrid printing technologies that combine multiple AM processes with adequate automation and enable simultaneous multimaterials dispensing, real-time quality control, postprocessing, and surface finish with integrated subtractive computer numeric control machining are the requirements for progressing toward the end-user electrical machines

Thermal analysis of wood-steel hybrid construction

Main goal of this work is to present a numerical model to study the thermal necrosis due a dental drilling process, with and without water irrigation. Also an experimental methodology is used to measure the thermal occurrence in a pig mandible. Motivation, the assessment of bone damage, using the temperature criterion (above 55ºC

Green Technologies for Production Processes

This book focuses on original research works about Green Technologies for Production Processes, including discrete production processes and process production processes, from various aspects that tackle product, process, and system issues in production. The aim is to report the state-of-the-art on relevant research topics and highlight the barriers, challenges, and opportunities we are facing. This book includes 22 research papers and involves energy-saving and waste reduction in production processes, design and manufacturing of green products, low carbon manufacturing and remanufacturing, management and policy for sustainable production, technologies of mitigating CO2 emissions, and other green technologies

A novel method of detecting galling and other forms of catastrophic adhesion in tribotests

Tribotests are used to evaluate the performance of lubricants and surface treatments intended for use in industrial applications. They are invaluable tools for lubricant development since many lubricant parameters can be screened in the laboratory with only the best going on to production trials. Friction force or coefficient of friction is often used as an indicator of lubricant performance with sudden increases in friction coefficient indicating failure through catastrophic adhesion. Under some conditions the identification of the point of failure can be a subjective process. This raises the question: Are there better methods for identifying lubricant failure due to catastrophic adhesion that would be beneficial in the evaluation of lubricants? The hypothesis of this research states that a combination of data from various sensors measuring the real-time response of a tribotest provides better detection of adhesive wear than the coefficient of friction alone. In this investigation an industrial tribotester (the Twist Compression Test) was instrumented with a variety of sensors to record: vibrations along two axes, acoustic emissions, electrical resistance, as well as transmitted torsional force and normal force. The signals were collected at 10 kHz for the duration of the tests. In the main study D2 tool steel annular specimens were tested on coldrolled sheet steel at 100 MPa contact pressure in flat sliding at 0.01 m/s. The effects of lubricant viscosity and lubricant chemistry on the adhesive properties of the surface were examined. Tests results were analyzed to establish the apparent point of failure based on the traditional friction criteria. Extended tests of one condition were run to various points up to and after this point and the results analyzed to correlate sensor data with the test specimen surfaces. Sensor data features were used to identify adhesive wear as a continuous process. In particular an increase “friction amplitude” related to a form of stick-slip was used as a key indicator of the occurrence of galling. The findings of this research forms a knowledge base for the development of a decision support system (DSS) to identify lubricant failure based on industrial application requirements.Doctoral These