Degradation in the cooling effectiveness of a charge-air cooler (CAC) in a medium-duty turbocharged diesel engine has significant impact on engine performance. This degradation lowers the boost pressure and raises the intake manifold temperature. As a result, the engine provides lower horsepower and higher hydrocarbon levels than the rated values. The objective of this research is to monitor the health of the charge-air cooler by analyzing the intake manifold temperature signal. Experiments were performed on a Cummins ISB series turbocharged diesel engine, a 6-cylinder inline configuration with a 5.9 l displacement volume. Air flowing over the cooler was blocked by varying amounts, while various engine temperatures and pressures were monitored at different torque-speed conditions. Similarly, data were acquired without the introduction of any fault in the engine. For the construction of the manifold temperature trajectory vector, average mutual information estimates and a global false nearest neighbor analysis were used to find the optimal time parameter and embedding dimensions, respectively. The prediction of the healthy temperature vector was done by local linear regression using torque, speed, and their interaction as exogenous variables. Analysis of residuals generated by comparing the predicted healthy temperature vector and the observed temperature vector was successful in detecting the degradation of the charge-air cooler. This degradation was quantified by using box plots and probability density functions of residuals generated by comparing intake manifold temperature of healthy and faulty charge-air coolers. The general applicability of the model was demonstrated by successfully diagnosing a fault in the exhaust gas recirculation cooler of a different engine.

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