Use of Orthogonal Arrays in Design of a Fuzzy Logic Controller to Predict the Proof Stress for the TIG Welded Al-65032
K. Ankamma1, P.V.R. Ravindra Reddy2
1Dr. K.Ankamma*, Professor, Mahatma Gandhi Institute of Technology, Gandipet, Hyderabad, India.
2Dr.P.V.R.Ravindra Reddy, Professor, Department of Mechanical Engg., Chaitanya Bharathi Institute of Technology, Gandipet, Hyderabad, India,
Manuscript received on April 20, 2020. | Revised Manuscript received on May 01, 2020. | Manuscript published on May 10, 2020. | PP: 996-1001 | Volume-9 Issue-7, May 2020. | Retrieval Number: G5857059720/2020©BEIESP | DOI: 10.35940/ijitee.G5857.059720
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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: Fuzzy logic controller (FLC) is well suited where there is a considerable amount of uncertainty in the process. The material properties of a weldment in TIG welding depend on welding parameters like shielding gas pressure, current, torch angle, Electrode size, electrode projection, arc length etc. It is also influenced by the joint parameters like groove angle, land, root gap, preheating temperature. But a lot of noise parameters like variation of base material properties, variation in quality of inert gas used, variation in ambient conditions, variation in workman ship etc introduce uncertainties in the into the process. To deal with such uncertainties an FLC is designed and validated. In the current work, four parameters namely inert gas pressure, current, groove angle of the joint and preheating temperature of base metal are considered as input variables and the influence of these variables on the 0.2% proof stress is studied. Three linguistic terms are used for each parameter. To minimise the number of experiments in designing data base an L-9 orthogonal array is chosen for experimentation. TIG welding is carried and data base with 9 rules are formulated. For the input and out variables Triangular membership function is selected and FLC is designed. The FLC is validated with 5 more experiments. Mamdani approach is used to develop the Fuzzy controller.
Keywords: Orthogonal array, Fuzzy logic controller, TIG welding, Triangular function, Mamdani approach, crisp value, Membership function.
Scope of the Article: Fuzzy Logics