An inProcess Inspection System to Detect Noise Originating from within the Interior Trim Panels of Car Doors Car body parts are sometimes responsible for irritating noise caused by assembly defects. Typically, various types of noise are known to originate from within the interior trim panels of car doors. This noise is considered to be an important factor that degrades the emotional satisfaction of the driver of the car. This research suggests an inprocess inspection system consisting of an inspection workstation and a noise detection method. The inspection workstation presses down the car door trim panel by using a pneumatic pusher while microphones record the acoustic signals directly above the door trim panel and on the four sides of the workstation. The collected signals are analyzed by the proposed noise detection method after applying noise reduction. The noise detection method determines the presence of irritating noise by using noise source localization in combination with the time difference of arrival method and the relative signal strengths. The performance of the inprocess noise detection system was evaluated by conducting experiments on faulty and healthy car door trim panels.

Car Wiper Arm Defect Detection Using Gabor Filter In car industry, both accuracy and efficiency are equally crucial at the production line to supply high demands of wiper blades in car industry. Since the current production line is mostly employed using manpower, defect detection of car wiper arm remains a huge impact in the quality control process. However, the consistency and the accuracy of identifying defects are still not up to optimum state as the current defect detection method still heavily relies on human vision. To date, the defect detection of car wipers using machine vision has not been extensively implemented in the current car wipers industry. Hence in this paper, we proposed a very first machine vision method to identify defects on car wiper arm. We implemented Gabor filter to detect different kind of defects on wiper arm, such as scratch, bump, and orange skin. The proposed automated defect detection system for car wiper arm has achieved impressive detection accuracy with 81% within a short average processing time of 3.47 seconds.