Anomaly Detector for Manufacturing Industries using Lab view
Roopa M1, Jagir Hussain S2, Vijayanand S3
1*Dr. Roopa M, Electronics and Communication Engineering, SRMIST, Ramapuram, Chennai, (Tamil Nadu), India.
2Jagir Hussain S, Electronics and Communication Engineering, Dhanalakshmi College of Engineering, Chennai, (Tamil Nadu), India.
3Dr. Vijayanand S, Electronics and Communication Engineering, Dhanalakshmi College of Engineering, Chennai, (Tamil Nadu), India.
Manuscript received on September 22, 2019. | Revised Manuscript received on October 20, 2019. | Manuscript published on October 30, 2019. | PP: 265-269 | Volume-9 Issue-1, October 2019 | Retrieval Number: A1138109119/2019©BEIESP | DOI: 10.35940/ijeat.A1138.109119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In assembling enterprises the extra parts can arrive in a wide scope of various sizes and shapes, yet the essential creation process is large and continues with its different stages. It begins by manufacturing steel wire into the correct shape, trailed by warmth treatment to enhance the quality and surface treatment to enhance strength, before the packaging procedure. Splits or anomaly on the extra parts like bolts are one of the serious issues in the assembling enterprises which lead to parcel of issues when utilized in any machine. By manual investigation it is hard to discover the breaks. As a solution for this problem we have designed, anomaly detector for manufacturing industries using LabVIEW to detect the defected bolts which may cause serious issues in running machines like electromagnetic interference and unnecessary vibrations. In this proposed system, the shapes are detected using geometric matching and the defects are identified by varying the threshold levels. Also, the colour matching is used to find the erosion. The proposed system. The image is converted into gray scale to compare with template image using color plane extraction and the defects are identified comparing the two images i.e., the template and the acquired image using match pattern where the patterns are matched for both the images. The image is taken in real time and compared with template image using web cam and my Rio.
Keywords: Anomaly, Colour plane extraction, Real time acquisition.