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This paper deals with the data-driven design of parity space based fault detection (FD) systems. The central idea is to identify parity space and the related matrices directly from test data. The method is applied to fault diagnosis of imperial smelting furnace. Firstly, select correlation process variables according to the expert experience and the correlation test result. And then the residual signal is obtained by the method of direct identification based FD systems. The real application results show that the method has an excellent performance.