A gas sensor array concentration detection method based on fuzzy division and model integration belongs to the field of a gas sensor array signal processing technology. According to the method, time division of baseline drift data is carried out by a fuzzy clustering method, and a source dataset is divided into multiple sub-datasets with different drift degrees; then, regression models of different training datasets are established to obtain several sub-regression models; an optimal weight set of each sub-regression model is obtained within the training dataset, and center of clustering and optimal weight undergo fitting to obtain an optimal weight fitting function; and during the test phase, fitting weight is calculated on the basis of the optimal weight fitting function and clustering center time, and the sub-regression models integrate forecasted results of data to be tested so as to obtain the final gas concentration value. By the method, a pattern recognition model can be changed adaptively, changes of drifting can be traced, the influence of drifting on concentration detection performance is effectively reduced, and long-term accuracy of concentration measurement is guaranteed.