Fault Isolation by Partial Dynamic Principal Component Analysis in Dynamic Process

Principal component analysis （PCA） is a useful tool in process fault detection, but offers little support on fault isolation. In this article, structured residual with strong isolation property is introduced. Although it is easy to get the residual by transformation matrix in static process, unfortunately, it becomes hard in dynamic process under control loop. Therefore, partial dynamic PCA（PDPCA） is proposed to obtain structured residual and enhance the isolation ability of dynamic process monitoring, and a compound statistic is introduced to resolve the problem resulting from independent variables in every variable subset. Simulations on continuous stirred tank reactor （CSTR） show the effectiveness of the proposed method.

Cycle temporal algorithm-based multivariate statistical methods for fault diagnosis in chemical processes

Multivariate statistical process monitoring methods are often used in chemical process fault diagnosis.In this article,(I)the cycle temporal algorithm(CTA)combined with the dynamic kernel principal component analysis(DKPCA)and the multiway dynamic kernel principal component analysis(MDKPCA)fault detection algorithms are proposed,which are used for continuous and batch process fault detections,respectively.In addition,(II)a fault variable identification model based on reconstructed-based contribution(RBC)model that paves the way for determining the cause of the fault are proposed.The proposed fault diagnosis model was applied to Tennessee Eastman(TE)process and penicillin fermentation process for fault diagnosis.And compare with other fault diagnosis methods.The results show that the proposed method has better detection effects than other methods.Finally,the reconstruction-based contribution(RBC)model method is used to accurately locate the root cause of the fault and determine the fault path.

An efficient formulation based on the Lagrangian method for contact–impact analysis of flexible multi-body system

In this paper,an efficien formulation based on the Lagrangian method is presented to investigate the contact–impact problems of f exible multi-body systems.Generally,the penalty method and the Hertz contact law are the most commonly used methods in engineering applications.However,these methods are highly dependent on various non-physical parameters,which have great effects on the simulation results.Moreover,a tremendous number of degrees of freedom in the contact–impact problems will influenc thenumericalefficien ysignificantl.Withtheconsideration of these two problems,a formulation combining the component mode synthesis method and the Lagrangian method is presented to investigate the contact–impact problems in fl xible multi-body system numerically.Meanwhile,the finit element meshing laws of the contact bodies will be studied preliminarily.A numerical example with experimental verificatio will certify the reliability of the presented formulationincontact–impactanalysis.Furthermore,aseries of numerical investigations explain how great the influenc of the finit element meshing has on the simulation results.Finally the limitations of the element size in different regions are summarized to satisfy both the accuracy and efficien y.

New Fuzzy Approach for Modeling Random Disturbances

The guaranty of power system stability during a random disturbances, requires systematically a wide knowledge of the disturbance components in one hand and their range of variation in the other hand. The major problem lies in the approach taken to the identification of the main components of this type of disturbances, Control strategy will only be effective if these disturbances are acceptably modeled. A better approximation of the dynamic components of these disturbances likely to affect power systems, leading to the implementation of a highly reliable control strategy. The identification and evaluation of dynamic components of these disturbances will be the major objective of this study. The control strategy of such disturbances, random, will be develooed to adant itto a wind farm connected to an electrical network.

Extraction and application of the low dimensional dynamical component from underwater acoustic target radiating noise

Signal processing in phase space based on nonlinear dynamics theory is a new method for underwater acoustic signal processing. One key problem when analyzing actual acoustic signal in phase space is how to reduce the noise and lower the embedding dimen- sion. In this paper, local-geometric-projection method is applied to obtain fow dimensional element from various target radiating noise and the derived phase portraits show obviously low dimensional attractors. Furthermore, attractor dimension and cross prediction error are used for classification. It concludes that combining these features representing the geometric and dynamical properties respectively shows effects in target classification.

Multivariate error assessment of response time histories method for dynamic systems

In this paper, an integrated validation method and process are developed for multivariate dynamic systems. The principal component analysis approach is used to address multivariate correlation and dimensionality reduction, the dynamic time warping and correlation coefficient are used for error assessment, and the subject matter experts (SMEs)’ opinions and principal component analysis coefficients are incorporated to provide the overall rating of the dynamic system. The proposed method and process are successfully demonstrated through a vehicle dynamic system problem.

Actuator Fault Monitoring and Fault Tolerant Control in Distillation Columns

This paper presents, from a practical viewpoint accommodation in distillation columns. Addressing faults in an investigation of real-time actuator fault detection, propagation and industrial processes, coupled with the growing demand for higher performance, improved safety and reliability necessitates implementation of less complex alternative control strategies in the events of malfunctions in actuators, sensors and or other system components. This work demonstrates frugality in the design and implementation of fault tolerant control system by integrating fault detection and diagnosis techniques with simple active restructurable feedback controllers and with backup feedback signals and switchable reference points to accommodate actuator fault in distillation columns based on a priori assessed control structures. A multivariate statistical process monitoring based fault detection and diagnosis technique through dynamic principal components analysis is integrated with one-point control or alternative control structure for prompt and effective fault detection, isolation and accommodation. The work also investigates effects of disturbances on fault propagation and detection. Specifically, the reflux and vapor boil-up control strategy used for a binary distillation column during normal operation is switched to one point control of the more valued product by utilizing the remaining healthy actuator. The proposed approach was implemented on two distillation processes： a simulated methanol-water separation column and the benchmark Shell standard heavy oil fractionation process to assess its effectiveness.

Interharmonic Analysis Model of Photovoltaic Grid-connected System with Extended Dynamic Phasors

The interactions between randomly fluctuating power outputs from photovoltaic(PV) at the DC side and background voltage distortions at the AC side could generate interharmonics in the PV grid-connected system(PVGS). There is no universal method that can reveal the transmission mechanism of interharmonics and realize accurate calculation in different scenarios where interharmonics exist in the PVGS. Therefore, extended dynamic phasors(EDPs) and EDP sequence components(EDPSCs) are employed in the interharmonic analysis of the PVGS. First, the dynamic phasors(DPs) and dynamic phasor sequence components(DPSCs) are extended into EDPs and EDPSCs by selecting a suitable fundamental frequency other than the power frequency. Second, an interharmonic analysis model of the PVGS is formulated as a set of state space equations. Third, with the decoupling characteristics of EDPSCs,generation principles and interactions among the interharmonics in the PVGS are presented by the sequence components,and its correctness is verified by simulation and experiment.The presented model can be used to accurately calculate the interharmonics generated in the PVGS both at the AC and DC sides. Because of the decoupling among the EDPSCs, the set of state space equations can effectively describe the principle.