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Fault Detection of Mobile Bracket with MATLAB

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Shruti Lohade, Roshni John, Ekta Bhojwani, Abhijeet Chavan

Shruti Lohade, Roshni John, Ekta Bhojwani and Abhijeet Chavan. Fault Detection of Mobile Bracket with MATLAB. International Journal of Computer Applications 161(10):38-40, March 2017. BibTeX

	author = {Shruti Lohade and Roshni John and Ekta Bhojwani and Abhijeet Chavan},
	title = {Fault Detection of Mobile Bracket with MATLAB},
	journal = {International Journal of Computer Applications},
	issue_date = {March 2017},
	volume = {161},
	number = {10},
	month = {Mar},
	year = {2017},
	issn = {0975-8887},
	pages = {38-40},
	numpages = {3},
	url = {},
	doi = {10.5120/ijca2017913351},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


An internal mobile bracket, also known as its metal body, is the main supporting structure of a mobile phone to which all other components are attached, comparable to the skeleton of an organism. The goal of fault detection system is to handle occurring faults in the bodt as in the dimensions, the slots of the small bolts, the camera placement slots, the sensors of the reciever and trmsmitter, the battery connecting slots etc. as all these slots re very small in some may be visibly detected but some may not.

Quality control, cost reduction and above all, human and environmental safety are great reasons that stimulate the investments in technologies like automatic inspection. The automatic inspection of connecting lines in the mobile metal body is of special interest, due to the fact that such connecting lines are not visible by the human eye. Visual inspection is one highest cost in metal frame.

The main motive of the fault detection is that it may reduce human efforts mainly, secondly the error will be more precisely detected which would have being missed out by the human or the machine due misplacements. The machine used for this detection may be time consuming, or if in any case the detction is not done after its making, requires large overhead costs and results in high wastage. After manufacturing product; to make decision of rejecting or accepting is taken by measuring quality parameters. To measure quality parameters such as dimensions and features of manufactured product inspection is many a times not done.

To overcome these problems quality control and quality management for sensitive product is feasible by use of image processing techniques. This technique will detect all the fault in the frame, like the connecting lines, the dimensions, bends, cracks, change in positions of parts like minute nuts and bolts, the missed slots etc. This activity completely captures any metal body of any brand then compares it with the ideal frame then checks each and every fault from all the parts. If the body matches with the ideal body using the image processing technique then the product is forwarded for further process. And if the chassis does not match the ideal one then it is rejected.


  1. Murthad Al- Yoonus, Mohammed Saeed Jawad, M. F. L.Abdullah and Fares Al-Shargie, ”Enhance Quality Control Management for Sensitive Industrial Products Using 2D/3D Image Processing Algorithms,” Electrical Power, Electrcs, Communications, Controls, and Informatics Seminar (EECCIS), 2014.
  2. S. Vasilic and Z. Hocenski, ”Detecting Methods in Ceramic Defects Detection”, In Industrial Electronics, 2006 IEEE International Symposium, vol. 1, pp. 469472, 2006.
  3. Szkilnyk, G., 2012. Vision-based Fault Detection in Assembly Automation. M. A. Sc. Thesis, Queen’s University, Kingston, ON.
  4. R. Poli, “Genetic programming for feature detection and image segmentation,” The University of Birmingham, School of Computer Science, The University of Birmingham, Edgbaston, Birmingham B 15 2TT, UK, Tech. Rep., 2000.


MATLAB, controller, LED’S, Cameras, TxRx (Wireless)