An aligned mixture probabilistic principal component analysis for fault detection of multimode chemical processes

A novel approach named aligned mixture probabilistic principal component analysis(AMPPCA) is proposed in this study for fault detection of multimode chemical processes. In order to exploit within-mode correlations,the AMPPCA algorithm first estimates a statistical description for each operating mode by applying mixture probabilistic principal component analysis(MPPCA). As a comparison, the combined MPPCA is employed where monitoring results are softly integrated according to posterior probabilities of the test sample in each local model. For exploiting the cross-mode correlations, which may be useful but are inadvertently neglected due to separately held monitoring approaches, a global monitoring model is constructed by aligning all local models together. In this way, both within-mode and cross-mode correlations are preserved in this integrated space. Finally, the utility and feasibility of AMPPCA are demonstrated through a non-isothermal continuous stirred tank reactor and the TE benchmark process.

Does Quadriceps-sparing Total Knee Arthroplasty Increase the Risk of Lower Limb and Component Malalignment？ A Minimum 5-year Follow-up Study

The conventional total knee arthroplasty （TKA） is the most successful surgical procedure for relieving pain and improving poor function in patients with advanced arthritis. However, postoperative pain and delayed rehabilitation are the greatest complaints for the conventional approach. Recently, various minimally invasive surgery （MIS） TKA-techniques have been developed to address the concern. MIS-TKAs have shown less postoperative pain, shorter hospital stays, and quicker recovery after surgery.

Research on uncertainty in measurement assisted alignment in aircraft assembly

Operations in assembling and joining large size aircraft components are changed to novel digital and flexible ways by digital measurement assisted alignment.Positions and orientations（P＆O）of aligned components are critical characters which assure geometrical positions and relationships of those components.Therefore,evaluating the P＆O of a component is considered necessary and critical for ensuring accuracy in aircraft assembly.Uncertainty of position and orientation（U-P＆O）,as a part of the evaluating result of P＆O,needs to be given for ensuring the integrity and credibility of the result;furthermore,U-P＆O is necessary for error tracing and quality evaluating of measurement assisted aircraft assembly.However,current research mainly focuses on the process integration of measurement with assembly,and usually ignores the uncertainty of measured result and its influence on quality evaluation.This paper focuses on the expression,analysis,and application of U-P＆O in measurement assisted alignment.The geometrical and algebraical connotations of U-P＆O are presented.Then,an analytical algorithm for evaluating the multi-dimensional U-P＆O is given,and the effect factors and characteristics of U-P＆O are discussed.Finally,U-P＆O is used to evaluate alignment in aircraft assembly for quality evaluating and improving.Cases are introduced with the methodology.