Backward elimination procedures for testing multiple hypotheses: application to optimal sensor location

In this study, we propose a method for finding optimum sensor positions in a group of vibration sensors for knock detection in spark ignition engines. It differs from other techniques in that only signal processing and statistical tests are used. Our method is based on linearly predicting a reference signal from the output signals of an array of sensors, distributed arbitrarily on the engine block. We derive a linear regression model in the frequency domain and discuss parametric tests for various hypotheses that are tested with respect to the model parameters. This leads us to a technique for testing irrelevancy of sensors in the considered group. Simulation and experimental results emphasize the applicability of the method