Dynamically updated digital twin for prognostics and health management:Application in permanent magnet synchronous motor

Current research on Digital Twin(DT)based Prognostics and Health Management(PHM)focuses on establishment of DT through integration of real-time data from various sources to facilitate comprehensive product monitoring and health management.However,there still exist gaps in the seamless integration of DT and PHM,as well as in the development of DT multi-field coupling modeling and its dynamic update mechanism.When the product experiences long-period degradation under load spectrum,it is challenging to describe the dynamic evolution of the health status and degradation progression accurately.In addition,DT update algorithms are difficult to be integrated simultaneously by current methods.This paper proposes an innovative dual loop DT based PHM framework,in which the first loop establishes the basic dynamic DT with multi-filed coupling,and the second loop implements the PHM and the abnormal detection to provide the interaction between the dual loops through updating mechanism.The proposed method pays attention to the internal state changes with degradation and interactive mapping with dynamic parameter updating.Furthermore,the Independence Principle for the abnormal detection is proposed to refine the theory of DT.Events at the first loop focus on accurate modeling of multi-field coupling,while the events at the second loop focus on real-time occurrence of anomalies and the product degradation trend.The interaction and collaboration between different loop models are also discussed.Finally,the Permanent Magnet Synchronous Motor(PMSM)is used to verify the proposed method.The results show that the modeling method proposed can accurately track the lifecycle performance changes of the entity and carry out remaining life prediction and health management effectively.

Searchable Encryption Cloud Storage with Dynamic Data Update to Support Efficient Policy Hiding

Ciphertext policy attribute based encryption(CP-ABE)can provide high finegrained access control for cloud storage.However,it needs to solve problems such as property privacy protection,ciphertext search and data update in the application process.Therefore,based on CP-ABE scheme,this paper proposes a dynamically updatable searchable encryption cloud storage(DUSECS)scheme.Using the characteristics of homomorphic encryption,the encrypted data is compared to achieve efficient hiding policy.Meanwhile,adopting linked list structure,the DUSECS scheme realizes the dynamic data update and integrity detection,and the search encryption against keyword guessing attacks is achieved by combining homomorphic encryption with aggregation algorithm.The analysis of security and performance shows that the scheme is secure and efficient.

Understanding visual-auditory correlation from heterogeneous features for cross-media retrieval

Cross-media retrieval is an interesting research topic,which seeks to remove the barriers among different modalities.To enable cross-media retrieval,it is needed to find the correlation measures between heterogeneous low-level features and to judge the semantic similarity.This paper presents a novel approach to learn cross-media correlation between visual features and auditory features for image-audio retrieval.A semi-supervised correlation preserving mapping(SSCPM)method is described to construct the isomorphic SSCPM subspace where canonical correlations between the original visual and auditory features are further preserved.Subspace optimization algorithm is proposed to improve the local image cluster and audio cluster quality in an interactive way.A unique relevance feedback strategy is developed to update the knowledge of cross-media correlation by learning from user behaviors,so retrieval performance is enhanced in a progressive manner.Experimental results show that the performance of our approach is effective.

Numerical simulation of wheel wear evolution for heavy haul railway

The prediction of the wheel wear is a fundamental problem in heavy haul railway. A numerical methodology is introduced to simulate the wheel wear evolution of heavy haul freight car. The methodology includes the spatial coupling dynamics of vehicle and track, the three-dimensional rolling contact analysis of wheel-rail, the Specht's material wear model, and the strategy for reproducing the actual operation conditions of railway. The freight vehicle is treated as a full 3D rigid multi-body model. Every component is built detailedly and various contact interactions between parts are accurately simulated, taking into account the real clearances. The wheel-rail rolling contact calculation is carried out based on Hertz's theory and Kalker's FASTSIM algorithm. The track model is built based on field measurements. The material loss due to wear is evaluated according to the Specht's model in which the wear coefficient varies with the wear intensity. In order to exactly reproduce the actual operating conditions of railway,dynamic simulations are performed separately for all possible track conditions and running velocities in each iterative step.Dimensionless weight coefficients are introduced that determine the ratios of different cases and are obtained through site survey. For the wheel profile updating, an adaptive step strategy based on the wear depth is introduced, which can effectively improve the reliability and stability of numerical calculation. At last, the wear evolution laws are studied by the numerical model for different wheels of heavy haul freight vehicle running in curves. The results show that the wear of the front wheelset is more serious than that of the rear wheelset for one bogie, and the difference is more obvious for the outer wheels. The wear of the outer wheels is severer than that of the inner wheels. The wear of outer wheels mainly distributes near the flange and the root; while the wear of inner wheels mainly distributes around the nominal rolling circle. For the outer wheel of front wheelset of each bogie, the development of wear is gradually concentrated on the flange and the developing speed increases continually with the increase of traveled distance.

Research on dynamic updating of three dimensional geological modeling based on the OO-Solid model

The dynamic updating of the model included: the change of space border,addi- tion and reduction of spatial component (disappearing,dividing and merging),the change of the topological relationship and synchronous dynamic updating of database.Firstly, arming at the deficiency of OO-Solid model in the aspect of dynamic updating,modeling primitives of OO-Solid model were modified.And then the algorithms of dynamic updating of 3D geological model with the node data,line data or surface data change were dis- cussed.The core algorithms was done by establishing space index,following the way of facing the object from bottom to top,namely the dynamic updating from the node to arc, and then to polygon,then to the face of the component and finally to the geological object. The research has important theoretical and practical values in the field of three dimen- sional geological modeling and is significant in the field of mineral resources.

PRINCIPAL COMPONENT DECOMPOSITION BASED FINITE ELEMENT MODEL UPDATING FOR STRAIN-RATE-DEPENDENCE NONLINEAR DYNAMIC PROBLEMS

Thin wail component is utilized to absorb impact energy of a structure. However, the dynamic behavior of such thin-walled structure is highly non-linear with material, geometry and boundary non-linearity. A model updating and validation procedure is proposed to build accurate finite element model of a frame structure with a non-linear thin-walled component for dynamic analysis. Design of experiments （DOE） and principal component decomposition （PCD） approach are applied to extract dynamic feature from nonlinear impact response for correlation of impact test result and FE model of the non-linear structure. A strain-rate-dependent non-linear model updating method is then developed to build accurate FE model of the structure. Computer simulation and a real frame structure with a highly non-linear thin-walled component are employed to demonstrate the feasibility and effectiveness of the proposed approach.

Secure Multi-keyword Search Supporting Dynamic Update and Ranked Retrieval

As cloud computing is becoming prevalent, data owners are motivated to delegate complex data managements to the commercial cloud for economic savings. Sensitive data is usually encrypted before being uploaded to the cloud, which unfortunately makes the frequently-used search function a challenging problem. In this paper, we present a new multi-keyword dynamic search scheme with result ranking to make search over encrypted data more secure and practical. In the scheme, we employ a powerful function-hiding inner product encryption to enhance the security by preventing the leakage of search pattern. For the concern of efficiency, we adopt a tree-based index structure to facilitate the searching process and updating operations. A comprehensive security analysis is provided and experiments over the real world data show that our scheme is efficient.

Mode of Operation for Modification, Insertion, and Deletion of Encrypted Data

Due to the development of 5G communication,many aspects of information technology(IT)services are changing.With the development of communication technologies such as 5G,it has become possible to provide IT services that were difficult to provide in the past.One of the services made possible through this change is cloud-based collaboration.In order to support secure collaboration over cloud,encryption technology to securely manage dynamic data is essential.However,since the existing encryption technology is not suitable for encryption of dynamic data,a new technology that can provide encryption for dynamic data is required for secure cloudbased collaboration.In this paper,we propose a new encryption technology to support secure collaboration for dynamic data in the cloud.Specifically,we propose an encryption operation mode which can support data updates such as modification,addition,and deletion of encrypted data in an encrypted state.To support the dynamic update of encrypted data,we invent a new mode of operation technique named linked-block cipher(LBC).Basic idea of our work is to use an updatable random value so-called link to link two encrypted blocks.Due to the use of updatable random link values,we can modify,insert,and delete an encrypted data without decrypt it.

Optimal liquidation with dynamic parameter updating: A forward approach

We propose a forward approach to study the performance of liquidation strategies under sequential model parameter updates.The forward liquidation program consists of pasting forward in time and in a time-consistent fashion a series of optimal liquidation problems.They are triggered at the parameter shift instances,thus entirely eliminating model error,and last at most till the next parameter update.However,due to the nature of the model dynamics,solutions may cease to exist in finite time,even before the subsequent parameter update.Furthermore,forward liquidation strategies may never lead to full liquidation,even though they maximize the average utility of revenue and always preserve time-consistency.In juxtaposition,the traditional approach delivers full liquidation at the sought horizon but encounters considerable model error,generates value erosion,and is time-inconsistent.

Differential Game Model of Resource Extraction with Continuous and Dynamic Updating

This paper is devoted to a new class of differential games with continuous and dynamic updating.The direct application of resource extraction in a case of dynamic and continuous updating is considered.It is proved that the optimal control(cooperative strategies)and feedback Nash equilibrium strategies uniformly converge to the corresponding strategies in the game model with continuous updating as the number of updating instants converges to infinity.Similar results are presented for an optimal trajectory(cooperative trajectory),equilibrium trajectory and corresponding payoffs.

A dynamic optical arbitrary waveform generator based on cross phase modulation

In this paper, a dynamic optical arbitrary waveform generator(OAWG) based on cross phase modulation(XPM) is proposed. According to the characteristics of XPM, the nonlinear phase shift of signal can be changed along with the pump power. The amplitude of signal can be changed by controlling the phase shift at one arm of a Mach-Zehnder interferometer(MZI) using XPM effect between signal and pump. Therefore, the phase and amplitude of the optical frequency comb(OFC) can be controlled by two pump arrays. As a result, different kinds of waveforms can be synthesized. Due to the ultrafast response of XPM, the generated waveform could be dynamically updated with an ultrafast frequency. The waveform fidelity is affected by the updating frequency.

TOAST: Automated Testing of Object Transformers in Dynamic Software Updates

Dynamic software update(DSU)patches programs on the fly.It often involves the critical task of object transformation that converts live objects of the old-version program to their semantically consistent counterparts under the new-version program.This task is accomplished by invoking an object transformer on each stale object.However,a defective transformer failing to maintain consistency would cause errors or even crash the program.We propose TOAST(Test Object trAnSformaTion),an automated approach to detecting potential inconsistency caused by object transformers.TOAST first analyzes an update to identify multiple target methods and then adopts a fuzzer with specially designed inconsistency guidance to randomly generate object states to drive two versions of a target method.This creates two corresponding execution traces and a pair of old and new objects.TOAST finally performs object transformation to create a transformed object and detects inconsistency between it and the corresponding new object produced from scratch by the new program.Moreover,TOAST checks behavior inconsistency by comparing the return variables and exceptions of the two executions.Experimental evaluation on 130 updates with default transformers shows that TOAST is promising:it got 96.0%precision and 85.7%recall in state inconsistency detection,and 81.4%precision and 94.6%recall in behavior inconsistency detection.The inconsistency guidance improved the fuzzing efficiency by 14.1%for state inconsistency detection and 40.5%for behavior inconsistency detection.

ACG-TypeMethod for InverseQuadratic Eigenvalue Problems in Model Updating of Structural Dynamics

In this paper we first present a CG-type method for inverse eigenvalue problem of constructing real and symmetric matrices M,D and K for the quadratic pencil Q(λ)=λ^(2)M+λD+K,so that Q(λ)has a prescribed subset of eigenvalues and eigenvectors.This method can determine the solvability of the inverse eigenvalue problem automatically.We then consider the least squares model for updating a quadratic pencil Q(λ).More precisely,we update the model coefficient matrices M,C and K so that(i)the updated model reproduces the measured data,(ii)the symmetry of the original model is preserved,and(iii)the difference between the analytical triplet(M,D,K)and the updated triplet(M_(new),D_(new),K_(new))is minimized.In this paper a computationally efficient method is provided for such model updating and numerical examples are given to illustrate the effectiveness of the proposed method.