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This paper introduces cointegration testing method for nonstationary process monitoring, which yields a longrun dynamic equilibrium relationship for nonstationary process systems. The process variables are examined, and then a cointegration model of the tested nonstationary variables is identified. The residual sequence of the cointegration model describes the dynamic equilibrium errors of the nonstationary process system and can be further analyzed for condition monitoring and fault detection purposes. The autocorrelated residual sequence is filtered with AR model first, then compensated to keep the fault signatures from being distorted by the filtering process. An application case study to an industrial distillation unit with a nonstatioanry process shows that a tidy cointegration model can describe the dynamic equilibruim state of the unit and correctly detect abnormal behavior of the process.