Query: digital twin credibility evaluation

title: An Evaluation of Digital Image Forgery Detection Based Copy Move Image Forgery Detection Techniques
abstract: Image lookalike mechanism use of numerical drawing to hide meaningful tip of your instance. The expose of solid version be necessitated per head right of credibility and to hold integrity of your idea. Reproduction flow twin revelation subject matter victimization sturdy up distribution and feature motive factor analogous is submitted. The schemed theory integrates both stall based totally and key point primarily based dual uncovering strategies. The purposed flexible extra vivisection algorithm segments the pick out up the check drawing in the route of thru to non traverselylapping and irregular impedes robustly. Then, the star points are extracted from every stall as intercept stars, and the clog articles are matched conjointly to discover the categorized trait points; this plan can especially factor out the suspected phony areas. To discover the imitation regions extra correctly, we recommend the work alike place extraction set of rules which replaces the spotlights point with small notable pixels as article close offs and them merges the neighboring impedes that have similar local coloration advertises in the path of via to the issue deter to generate the merged regions. Finally, it applies the morphological operation to merged areas to generate the detected lookalike areas. In reduce paste version imposture ferreting out, schemed microcomputer idea forensic techniques capable of detecting worldwide and local assessment enhancement, figuring out the usage of histogram equalization

title: Digital twin based process reuse and evaluation approach for smart process planning
abstract: With the advances in new generation information technologies, smart process planning is becoming the focus for smart process planning with less time and lower cost. Big data based reusing and evaluating the multi dimensional process knowledge is widely accepted as an effective strategy for improving competitiveness of enterprises. However, there was little research on how to reuse and evaluate process knowledge with dynamical changing machining status. In this paper, we propose a novel digital twin based approach for reusing and evaluating process knowledge. First, the digital twin based process knowledge model which contains the geometric information and real time process equipment status is introduced to represent the purpose and requirement of machining planning. Second, the process big data is constructed based on the three layer and its association rules for accumulating process knowledge. Moreover, the similarity calculation algorithm of the scene model is proposed to filter the unmatched process knowledge. For accurately reusing the process knowledge, the process reusability evaluation approach of the candidate knowledge set is presented based on the real time machining status and the calculated confidence. Finally, the diesel engine parts are applied in the developed prototype module to verify the effectiveness of the proposed method. The proposed method can promote the development and application of the smart process planning.

title: Digital Twin based Safety Evaluation of Prestressed Steel Structure
abstract: The safety of prestressed steel structures in service has been studied widely. However, traditional safety assessment methods for prestressed steel structures involve few sample points, do not provide accurate predictions, and consume substantial human and material resources. The digital twin technology can be used to monitor the structural behavior, state, and activity of a steel structure throughout its life cycle, which is equivalent to performing a safety assessment of the structure. The purpose of this study is to establish a digital twin multidimensional model of prestressed steel structures. Based on this model, the support vector machine and prediction model are trained using the relevant structural history data, and the safety risk level of the structure is then predicted based on the measured data. Finally, a proportional reduction model of the wheel spoke cable truss structure is used to verify the feasibility of the proposed method. The results show that digital twin technology can achieve real time monitoring of prestressed steel structures in use and can provide timely predictions of the safety level. This represents a new method for the safety risk assessment of prestressed steel structures.

title: Lithium ion battery performance degradation evaluation in dynamic operating conditions based on a digital twin model
abstract: The performance of lithium ion batteries degrades over time. Evaluating the performance degradation for lithium ion batteries is essential to ensure the operational reliability and reduces the risk of host system downtime. The battery capacity that is obtained by completely charging and discharging a battery cell, directly reflects the performance of a lithium ion battery. But in practical applications, the battery is dynamically charged and discharged. This makes it difficult to measure the actual capacity and further evaluate battery performance degradation to ensure the battery operating safety. To address this challenging issue, this paper proposes a performance degradation evaluation model by estimating the battery actual capacity in dynamic operating conditions. A health indicator (HI) is extracted from the measurable parameters to reflect the battery performance degradation. A battery digital twin model that describes the relationship between the cell voltage and the cell state of charge (SOC) are modelled by the long short term memory (LSTM) algorithm, which takes the HI as a temporal measurement. The battery actual capacity can be obtained by virtually completely discharging this digital twin model. The experimental results illustrate the potential of the proposed method applying in dynamic operating conditions.

title: Digital Twin Driven Green Performance Evaluation Methodology of Intelligent Manufacturing: Hybrid Model Based on Fuzzy Rough Sets AHP, Multistage Weight Synthesis, and PROMETHEE II
abstract: The design, planning, and implementation of intelligent manufacturing are mainly carried out from the perspectives of meeting the needs of mass customization, improving manufacturing capacity, and innovating business pattern currently. Environmental and social factors should be systematically integrated into the life cycle of intelligent manufacturing. In view of this, a green performance evaluation methodology of intelligent manufacturing driven by digital twin is proposed in this paper. Digital twin framework, which constructs the bidirectional mapping and real time data interaction between physical entity and digital model, provides the green performance evaluation with a total factor virtual image of the whole life cycle to meet the monitoring and simulation requirements of the evaluation information source and demand. Driven by the digital twin framework, a novel hybrid MCDM model based on fuzzy rough sets AHP, multistage weight synthesis, and PROMETHEE II is proposed as the methodology for the green performance evaluation of intelligent manufacturing. The model is tested and validated on a study of the green performance evaluation of remote operation and maintenance service project evaluation for an air conditioning enterprise. Testing demonstrates that the proposed hybrid model driven by digital twin can enable a stable and reasonable evaluation result. A sensitivity analysis was carried out by means of 27 scenarios, the results of which showed a high degree of stability.

title: Dynamic Evaluation Method of Machining Process Planning Based on Digital Twin
abstract: Process evaluation is widely accepted as an effective strategy to improve product quality and shorten its development cycle. However, there has been very little research on how to evaluate the process plan with the dynamic change of the machining condition and uncertain available manufacturing resources. This paper proposes a novel process evaluation method based on digital twin technology. Three core technologies embodied in the proposed method are illustrated in details: 1) real time mapping mechanism between the collected data in machining and the process design information; 2) construction of the digital twin based machining process evaluation (DT MPPE) framework; and 3) process evaluation driven by digital twin data. To elaborate on how to apply the proposed method to the reality, we present a detailed implementation process of the proposed DT MPPE method for the key parts of the marine diesel engine. Meanwhile, the future work to completely fulfill digital twin based smart process planning for complex products is discussed.

title: Evaluation of Industry 4.0 Data formats for Digital Twin of Optical Components
abstract: A wide range of software and hardware components are present in today's production systems and plants using a variety of interfaces and data formats for information exchange on different levels of the system. To increase the traceability, the lifecycle management and providing a single point of source of component specific data, the Digital Twin technology is proposed, linking different data sets tailored to the requirements of different kind of users (e.g. machines, technicians, logistics, manufacturing execution systems) The data exchange between entities in the manufacturing network relies on machine readable, flexible and self describing data formats. When implementing or integrating different components into complex systems, the interoperability challenge is a major concern to address by the system designers and becomes a central task for the creation and integration of Digital Twin technology. In this paper, we evaluate different formats that are used in real environments and create a requirements framework for an ideal format for exchanging flexible and self describing data in context of optical components manufacturing process and their special requirements.

title: A Digital Twin for Operational Evaluation of Vertical Transportation Systems
abstract: The Digital Twin (DT) is a promising concept which aims at creating a virtual replica of an individual system, that can provide information otherwise not available. This paper presents a DT of a vertical transportation system, focusing on how to model this DT, and using it to evaluate the system condition and potential corrective solutions. Exploiting the advantages of object oriented modeling, this DT has been built ensuring that it may be dynamically adapted to different monitoring scenarios. Moreover, its adaptability is tested showing that reduced models behave similarly. The resulting reduced models are used to estimate installation parameters in a bottom up way, using the measurements of a scaled test bench. The estimated parameters are used to update a high fidelity model and simulate the effect of corrective actions.

title: Digital twin driven process design evaluation
abstract: Due to continuously changing conditions of production resources, process design evaluation plays an increasingly important role in helping enterprises to save time and cost. To further improve the applicability of the process plan to dynamic manufacturing environment, a novel process design evaluation method that responds to the real time machining status based on the digital twin (DT) technology is proposed. First, the reconfigurable process design method is proposed based on the model based definition technology. In the method the 3D process models and their machining information are managed by a hierarchically structured model. Second, the DT data including the process design data and real time data is generated. Finally, the evaluation method of the process plan is proposed based on the DT data. Key parts of a marine diesel engine are chosen for the case study to demonstrate effectiveness of the proposed method.

title: Assembly process planning and dynamic evaluation method based on digital twin
abstract: In the dynamic product assembly environment, assembly process evaluation has become the key problem to improve process execution and assembly efficiency in intelligent manufacturing mode. For this reason, the assembly process planning and dynamic evaluation method driven by digital twin is proposed. Based on the five dimensional model, the architecture of assembly process digital twin system is established, facing with ergonomics, the digital twin modeling and optimization of all elements of "human machine object environment" in workshop assembly process was completed, the expression model and perception framework of assembly process real time data are created, and the real time mapping logic structure of assembly workshop operation is put forward, and the twin data of assembly process evaluation are created. The dynamic evaluation process of assembly process driven by twin data is described and then the validity of the proposed method is verified by an example of a car rear axle assembly process.