科创中国

利用衡水市1956年-2010年降水量资料,分析该区域降水量变化情况.采用数理统计法、PCI法对降水量的年内变化与年际变化进行分析,年内降水比较集中,季节分配不均匀,80%左右的降水量集中在夏季汛期,年际变化大,极值比为3.45.采用Mann-Kendall非秩次相关检验法、线性回归法对降水量序列进行趋势分析,降水量呈递减趋势,平均每年递减2.0mm,但没有出现明显的突变.采用距平分析和模比系数差积曲线法对降水量进行了阶段性分析,降水系列包括一个丰枯周期,大约为50年左右.采用自相关分析法对降水量系列进行随机成分分析,降水量系列的独立性强,相依性很弱.

The existing research of process capability indices of multiple quality characteristics mainly focuses on nonconforming of process output, the concept development of univariate process capability indices, quality loss function and various comprehensive evaluation methods. The multivariate complexity increases the computation difficulty of multivariate process capability indices(MPCI), which makes them hard to be used in practice. In this paper, a new PCA-based MPCI approach is proposed to assess the production capability of the processes that involve multiple product quality characteristics. This approach first transforms the original quality variables into standardized normal variables. MPCI measures are then provided based on the Taam index. Moreover, the statistical properties of these MPCIs, such as confidence intervals and lower confidence bound, are given to let the practitioners understand the capability indices as random variables instead of deterministic variables. A real manufacturing data set and a synthetic data set are used to demonstrate the effectiveness of the proposed method. An implementation procedure is also provided for quality engineers to apply our MPCI approach in their manufacturing processes. The case studies demonstrate the effectiveness and feasibility of this new kind of MPCI, which is easier to be used in production practice. The proposed research provides a novel approach of MPCI calculation.

Multi-way principal component analysis(MPCA)has received considerable attention and been widely used in process monitoring.A traditional MPCA algorithm unfolds multiple batches of historical data into a two-dimensional matrix and cut the matrix along the time axis to form subspaces.However,low efficiency of subspaces and difficult fault isolation are the common disadvantages for the principal component model.This paper presents a new subspace construction method based on kernel density estimation function that can effectively reduce the storage amount of the subspace information.The MPCA model and the knowledge base are built based on the new subspace.Then,fault detection and isolation with the squared prediction error(SPE)statistic and the Hotelling(T2)statistic are also realized in process monitoring.When a fault occurs,fault isolation based on the SPE statistic is achieved by residual contribution analysis of different variables.For fault isolation of subspace based on the T2 statistic,the relationship between the statistic indicator and state variables is constructed,and the constraint conditions are presented to check the validity of fault isolation.Then,to improve the robustness of fault isolation to unexpected disturbances,the statistic method is adopted to set the relation between single subspace and multiple subspaces to increase the corrective rate of fault isolation.Finally fault detection and isolation based on the improved MPCA is used to monitor the automatic shift control system(ASCS)to prove the correctness and effectiveness of the algorithm.The research proposes a new subspace construction method to reduce the required storage capacity and to prove the robustness of the principal component model,and sets the relationship between the state variables and fault detection indicators for fault isolation.

为了评价各因素对大坝监测效应量的综合影响程度,提出一种新的灰色距离测度,并应用于大坝效应量分量比例确定中.首先利用主成分确定各分量真实系数,然后应用该理论确定各个分量的比例.工程实例表明,该方法简单可行,能科学有效地确定大坝效应量分量比例.

选择在螺旋卷式反渗透膜元件组件设计中,对影响膜元件使用寿命的抗污染性能及影响膜元件系统运行能耗的工艺参数进行理论模拟实验,并与实际生产运行相结合,得出最优化的设计组合.主要工艺参数为给水流道布宽度、深度、入水角度、及膜元件卷制页数的优化选择,筛选出提高抗污染性能及低能耗、高经济性的膜元件,并对螺旋卷式膜元件的设计起指导作用.