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The permeability of sand covered with geotextile is affected by the permeability of geotextile, which is related to the tensile state of the geotextile. Considering the weaving mode of geotextile, the effects of warp tension and weft tension on the permeability of sand covered with geotextile were studied by experiment. Four different specifications of geotextiles were selected for warp and weft tension respectively. The changes of permeability parameters of sand covered with geotextile under non tension, warp and weft tension were measured by vertical permeability instrument, and the effects of warp and weft tension on permeability parameters such as seepage velocity, sand loss and gradient ratio were analyzed. The test results show that the water permeability and anti silting performance of the geotextile increase with the increase of tensile strain, and the soil conservation performance decreases with the tensile strain increasing. Meanwhile, the relationship between permeability and warp tensile strain is not monotonic. When the warp tensile strain 3%, the water permeability and anti silting performance of geotextile are the weakest, and the soil conservation performance is the strongest.

Traditional process monitoring methods construct a single monitoring model to detect if a fault happened. But the development of industrial technology has made industrial processes increasingly com...

To properly monitor dynamic large-scale processes, a new distributed dynamic process monitoring strategy named multi-block dynamic weighted principal component regression (DWPCR) is developed in this paper. Because complex plant-wide processes have multiple operation units and complex correlations among variables, traditional global process monitoring models may suppress local fault information and fail to identify incipient faults and local faults for large-scale processes. Besides, product quality determines the economic benefits of the enterprise. Motivated by these problems, this work studies the distributed quality monitoring strategy. At first, the idea of community partition in complex networks is used for multiple subblock division for a large number of process variables in this new monitoring framework. Then, the monitoring model for each subblock is established by the proposed DWPCR approach. Moreover, a novel weighting key components strategy based on fault information is proposed to monitor the process. Finally, the comprehensive monitoring result is fused by Bayesian inference. The superiority of the proposed distributed DWPCR strategy is testified in the case study.