In the modern automotive industry, more and more manufacturers recognise that vehicle paint appearance makes an important contribution to customer satisfaction. Attractive appearance has become one of the important factors for customers in making a decision to purchase a car. Objective measurement of the quality of autobody paint appearance, as perceived by the customer, in a repeatable, reproducible, continuous scale manner is an important requirement for improving the paint appearance. It can provide car manufacturers a standard reference to evaluate the quality of the paint appearance. This thesis mainly deals with the measurement of paint appearance quality in the automotive industry by investigating, identifying and developing measurement methods in this area. First of all, the 'state of the art' in the area of paint appearance measurement was presented, which summarised the concept of appearance, models, attributes and definitions. To further identify the parameters and instruments used in the automotive industry, a round robin test was launched to perform visual assessment and instrument measurements on a set of panels in some European car manufacturers. A summary of the correlation found between measurable parameters and visual assessment provided the basis of the further work. Based on the literature survey and round robin test results, the next work is mainly concentrated on the two most important parameters, 'orange peel' and 'metal texture effect', how to separate and evaluate them. Digital signal processing technique, FFT and Filtering, have been employed to separate them and a set of measures have been provided for evaluation. At the same time, the technique for texture pattern recognition was introduced to evaluate the texture effect when a fine texture comparison was needed. A set of computable textural parameters based on grey-tone spatial-dependence matrices gives good correlation directly corresponding to visual perception. To resolve the overall appearance modelling problem, two novel and more powerful modelling tools, artificial neural networks and fuzzy logic, are introduced to model the overall appearance. The test results showed that both of them are able to reflect the correlation between overall appearance and the major parameters measured from a painted surface. Finally, an integrated measurement system, 'Smart Appearance', was developed using the image processing techniques and the artificial neural network model. The implement results show that this system can measure the major attributes of paint appearance and provide an overall appearance index corresponding to human visual perception. This system is helpful to product quality control on car body paint. It also could be used on the paint production line for dynamic measurement.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:445938 |
| Date | January 2000 |
| Creators | Kang, Hai-zhuang |
| Contributors | Butler, C. : Yang, Q. |
| Publisher | Brunel University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://bura.brunel.ac.uk/handle/2438/7900 |
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