Publications

Abstract : Radiator cooling fan assembly in an internal combustion engine-driven automobile ensures that the heat evacuated by radiator from the engine is safely evacuated to the surrounding air. Any malfunction of this assembly is hence, likely to be detrimental to the functioning of the engine itself. In this paper, a low-cost machine learning-based technique to monitor and detect six operating conditions in an automotive radiator cooling fan assembly is presented. Twenty-six machine learning-based systems are empirically evaluated for their effectiveness. Results indicate that the proposed technique is capable of a detection accuracy in excess of 98%.