Review of Fault-tolerant Control for Motor Inverter Failure with Operational Quality Considered

In recent years,motor drive systems have garnered increasing attention due to their high efficiency and superior control performance.This is especially apparent in aerospace,marine propulsion,and electric vehicles,where high performance,efficiency,and reliability are crucial.The ability of the drive system to maintain long-term fault-tolerant control(FTC)operation after a failure is essential.The likelihood of inverter failures surpasses that of other components in the drive system,highlighting its critical importance.Long-term FTC operation ensures the system retains its fundamental functions until safe repairs or replacements can be made.The focus of developing a FTC strategy has shifted from basic FTC operations to enhancing the post-fault quality to accommodate the realities of prolonged operation post-failure.This paper primarily investigates FTC strategies for inverter failures in various motor drive systems over the past decade.These strategies are categorized into three types based on post-fault operational quality:rescue,remedy,and reestablishment.The paper discusses each typical control strategy and its research focus,the strengths and weaknesses of various algorithms,and recent advancements in FTC.Finally,this review summarizes effective FTC techniques for inverter failures in motor drive systems and suggests directions for future research.

A Planning Method for Operational Test of UAV Swarm Based on Mission Reliability

The unmanned aerial vehicle(UAV)swarm plays an increasingly important role in the modern battlefield,and the UAV swarm operational test is a vital means to validate the combat effectiveness of the UAV swarm.Due to the high cost and long duration of operational tests,it is essential to plan the test in advance.To solve the problem of planning UAV swarm operational test,this study considers the multi-stage feature of a UAV swarm mission,composed of launch,flight and combat stages,and proposes a method to find test plans that can maximize mission reliability.Therefore,a multi-stage mission reliability model for a UAV swarm is proposed to ensure successful implementation of the mission.A multi-objective integer optimization method that considers both mission reliability and cost is then formulated to obtain the optimal test plans.This study first constructs a mission reliability model for the UAV swarm in the combat stage.Then,the launch stage and flight stage are integrated to develop a complete PMS(Phased Mission Systems)reliability model.Finally,the Binary Decision Diagrams(BDD)and Multi Objective Quantum Particle Swarm Optimization(MOQPSO)methods are proposed to solve the model.The optimal plans considering both reliability and cost are obtained.The proposed model supports the planning of UAV swarm operational tests and represents a meaningful exploration of UAV swarm test planning.

Improving the operational stability of perovskite solar cells with cesium-doped graphene oxide interlayer

Perovskite solar cells(PSCs)have made great advances in terms of power conversion efficiency(PCE),yet their subpar stability continues to hinder their commercialization.The interface between the perovskite layer and the charge-carrier transporting layers plays a crucial role in undermining the stability of PSCs.In this work,we propose a strategy to stabilize high-performance PSCs with PCE over 23%by introducing a cesium-doped graphene oxide(GO-Cs)as an interlayer between the perovskite and hole-transporting material.The GO-Cs treated PSCs exhibit excellent operational stability with a projected T80(the time where the device PCE reduces to 80%of its initial value)of 2143 h of operation at the maximum powering point under one sun illumination.

Operational optimization of copper flotation process based on the weighted Gaussian process regression and index-oriented adaptive differential evolution algorithm

Concentrate copper grade(CCG)is one of the important production indicators of copper flotation processes,and keeping the CCG at the set value is of great significance to the economic benefit of copper flotation industrial processes.This paper addresses the fluctuation problem of CCG through an operational optimization method.Firstly,a density-based affinity propagationalgorithm is proposed so that more ideal working condition categories can be obtained for the complex raw ore properties.Next,a Bayesian network(BN)is applied to explore the relationship between the operational variables and the CCG.Based on the analysis results of BN,a weighted Gaussian process regression model is constructed to predict the CCG that a higher prediction accuracy can be obtained.To ensure the predicted CCG is close to the set value with a smaller magnitude of the operation adjustments and a smaller uncertainty of the prediction results,an index-oriented adaptive differential evolution(IOADE)algorithm is proposed,and the convergence performance of IOADE is superior to the traditional differential evolution and adaptive differential evolution methods.Finally,the effectiveness and feasibility of the proposed methods are verified by the experiments on a copper flotation industrial process.

Operational requirements analysis method based on question answering of WEKG

The weapon and equipment operational requirement analysis(WEORA) is a necessary condition to win a future war,among which the acquisition of knowledge about weapons and equipment is a great challenge. The main challenge is that the existing weapons and equipment data fails to carry out structured knowledge representation, and knowledge navigation based on natural language cannot efficiently support the WEORA. To solve above problem, this research proposes a method based on question answering(QA) of weapons and equipment knowledge graph(WEKG) to construct and navigate the knowledge related to weapons and equipment in the WEORA. This method firstly constructs the WEKG, and builds a neutral network-based QA system over the WEKG by means of semantic parsing for knowledge navigation. Finally, the method is evaluated and a chatbot on the QA system is developed for the WEORA. Our proposed method has good performance in the accuracy and efficiency of searching target knowledge, and can well assist the WEORA.

Holistic Approach to Safety and Operational Stability: Analyzing VVER-1200 Reactor Dynamics in SGTR and AC Power Loss

VVER-1200 (Water-Water Energetic Reactor) represents a significant advancement in nuclear power generation, emphasizing the continuous analysis and enhancement of safety systems for reliable operation. The proposed study focuses on simulating combined scenarios involving steam generator tube rupture (SGTR) and AC power loss using core algorithms and models within personal computer transient analyzer (PCTRAN). Reactor kinetic equations, thermal-hydraulic balance, and safety system models are discussed to elucidate their role in simulating SGTR and AC power loss. Safety criteria, boundaries and initial conditions are outlined to provide a comprehensive understanding of the simulation framework. The analysis delves into dynamic behavior of VVER-1200, placing emphasis on thermal-hydraulic implications, essential reactor parameters, and radiation monitoring to facilitate impact evaluation. Continuous monitoring and maintenance of safety systems are underscored to ensure stable core cooling, particularly during proposed transient conditions. Through meticulous analysis and comparison with established benchmarks, this study contributes to bolstering the safety and reliability of VVER-1200 reactors by identifying vulnerabilities, assessing mitigation strategies, and refining emergency response protocols. Practical implications of this study offer a crucial understanding of reactor behavior, safety system performance, and emergency response strategies, thereby improving safety, optimizing operational practices, and reducing risks in nuclear reactor accidents.

Operational Problems and Countermeasures of Public Elective Courses in Higher Vocational Colleges and Universities Based on the Perspective of Academic Affairs Management:Taking Guangdong C Vocational College as an Example

With the vigorous development of higher vocational education,public elective courses,as one of the core components of the higher vocational curriculum system,occupy a pivotal position.Based on the perspective of academic affairs management and taking Guangdong C Vocational College as an example,this paper meticulously analyzes the operational problems in the declaration,setting,teaching,and management of public elective courses through questionnaire surveys and other methods.It also puts forward a series of targeted solutions,with a view to continuously improving the teaching quality and management level of public elective courses.

Interpretable machine learning optimization(InterOpt)for operational parameters:A case study of highly-efficient shale gas development

An algorithm named InterOpt for optimizing operational parameters is proposed based on interpretable machine learning,and is demonstrated via optimization of shale gas development.InterOpt consists of three parts:a neural network is used to construct an emulator of the actual drilling and hydraulic fracturing process in the vector space(i.e.,virtual environment);:the Sharpley value method in inter-pretable machine learning is applied to analyzing the impact of geological and operational parameters in each well(i.e.,single well feature impact analysis):and ensemble randomized maximum likelihood(EnRML)is conducted to optimize the operational parameters to comprehensively improve the efficiency of shale gas development and reduce the average cost.In the experiment,InterOpt provides different drilling and fracturing plans for each well according to its specific geological conditions,and finally achieves an average cost reduction of 9.7%for a case study with 104 wells.

Technical development of operational in-situ marine monitoring and research on its key generic technologies in China

In China,operational in-situ marine monitoring is the primary means of directly obtaining hydrological,meteorological,and oceanographic environmental parameters across sea areas,and it is essential for applications such as forecast of marine environment,prevention and mitigation of disaster,exploitation of marine resources,marine environmental protection,and management of transportation safety.In this paper,we summarise the composition,development courses,and present operational status of three systems of operational in-situ marine monitoring,namely coastal marine automated network station,ocean data buoy and voluntary observing ship measuring and reporting system.Additionally,we discuss the technical development in these in-situ systems and achievements in the key generic technologies along with future development trends.

Fractal Fractional Order Operators in Computational Techniques for Mathematical Models in Epidemiology

New fractional operators, the COVID-19 model has been studied in this paper. By using different numericaltechniques and the time fractional parameters, the mechanical characteristics of the fractional order model areidentified. The uniqueness and existence have been established. Themodel’sUlam-Hyers stability analysis has beenfound. In order to justify the theoretical results, numerical simulations are carried out for the presented methodin the range of fractional order to show the implications of fractional and fractal orders.We applied very effectivenumerical techniques to obtain the solutions of themodel and simulations. Also, we present conditions of existencefor a solution to the proposed epidemicmodel and to calculate the reproduction number in certain state conditionsof the analyzed dynamic system. COVID-19 fractional order model for the case of Wuhan, China, is offered foranalysis with simulations in order to determine the possible efficacy of Coronavirus disease transmission in theCommunity. For this reason, we employed the COVID-19 fractal fractional derivative model in the example ofWuhan, China, with the given beginning conditions. In conclusion, again the mathematical models with fractionaloperators can facilitate the improvement of decision-making for measures to be taken in the management of anepidemic situation.

Analysis on Operational Safety and Efficiency of FAO System in Urban Rail Transit

This paper discusses two urgent problems that need to be solved in fully automatic operation(FAO)for urban rail transit.The first is the analysis of safety in FAO,while another is the analysis of efficiency in FAO.Firstly,this paper establishes an operational safety evaluation index system from the perspective of operation for the unique or typical risk sources of the FAO system,and uses the analytic hierarchy process(AHP)to evaluate the indicators,analyzes various factors that affect the safe operation of FAO,and provides safety management recommendations for FAO lines operation to maintain the FAO system specifically.Secondly,taking the Yanfang Line as an example,this paper uses OpenTrack software to analyze the efficiency of FAO operation,and conducts simulation calculations for key links such as the mainline tracking interval,train entry and exit,and return limit interval.The fault impact surface of the FAO trains is simulated and discussed to verify whether FAO can meet the long-term operation requirements of Yanfang Line.Finally,this paper compares the simulation data of FAO on the Yanfang Line with manual operation(MO)to verify the advantages of FAO and guide the engineering construction of subsequent fully automated driving lines.

Study of Axial Vibration of a Motor-Compressor System Using Operational Modal Analysis

A case study of excessive vibration on a motor-compressor system is presented in this paper.After barely two months of operation,the reciprocating compressor motor’s routine monitoring revealed excessive axial vibration amplitude.For this reason,the Operational Modal Analysis(OMA)was carried out in order to identify the pri-mary cause.According to the investigation,one of the harmonic components which was 18 times the motor’s running speed matched with a resonance frequency of 112 Hz.According to OMA study,the motor was vibrating in torsional motion because the compressor’s load had stimulated the entire motor-compressor unit at this reso-nance frequency.The analysis also demonstrates the bulging effect of the motor shaft’s axial vibration on the motor’s endplate.

Novel Investigation of Stochastic Fractional Differential Equations Measles Model via the White Noise and Global Derivative Operator Depending on Mittag-Leffler Kernel

Because of the features involved with their varied kernels,differential operators relying on convolution formulations have been acknowledged as effective mathematical resources for modeling real-world issues.In this paper,we constructed a stochastic fractional framework of measles spreading mechanisms with dual medication immunization considering the exponential decay and Mittag-Leffler kernels.In this approach,the overall population was separated into five cohorts.Furthermore,the descriptive behavior of the system was investigated,including prerequisites for the positivity of solutions,invariant domain of the solution,presence and stability of equilibrium points,and sensitivity analysis.We included a stochastic element in every cohort and employed linear growth and Lipschitz criteria to show the existence and uniqueness of solutions.Several numerical simulations for various fractional orders and randomization intensities are illustrated.

AN EXPLANATION ON FOUR NEW DEFINITIONS OF FRACTIONAL OPERATORS

Fractional calculus has drawn more attentions of mathematicians and engineers in recent years.A lot of new fractional operators were used to handle various practical problems.In this article,we mainly study four new fractional operators,namely the CaputoFabrizio operator,the Atangana-Baleanu operator,the Sun-Hao-Zhang-Baleanu operator and the generalized Caputo type operator under the frame of the k-Prabhakar fractional integral operator.Usually,the theory of the k-Prabhakar fractional integral is regarded as a much broader than classical fractional operator.Here,we firstly give a series expansion of the k-Prabhakar fractional integral by means of the k-Riemann-Liouville integral.Then,a connection between the k-Prabhakar fractional integral and the four new fractional operators of the above mentioned was shown,respectively.In terms of the above analysis,we can obtain this a basic fact that it only needs to consider the k-Prabhakar fractional integral to cover these results from the four new fractional operators.

A MULTIPLE q-EXPONENTIAL DIFFERENTIAL OPERATIONAL IDENTITY

Using Hartogs’fundamental theorem for analytic functions in several complex variables and q-partial differential equations,we establish a multiple q-exponential differential formula for analytic functions in several variables.With this identity,we give new proofs of a variety of important classical formulas including Bailey’s 6ψ6 series summation formula and the Atakishiyev integral.A new transformation formula for a double q-series with several interesting special cases is given.A new transformation formula for a 3ψ3 series is proved.

GENERALIZED FORELLI-RUDIN TYPE OPERATORS BETWEEN SEVERAL FUNCTION SPACES ON THE UNIT BALL OF C^(N)

In this paper,we investigate sufficient and necessary conditions such that generalized Forelli-Rudin type operators T_(λ,τ,k),S_(λ,τ,k),Q_(λ,τ,k)and R_(λ,τ,k)are bounded between Lebesgue type spaces.In order to prove the main results,we first give some bidirectional estimates for several typical integrals.

An Intelligent MCGDM Model in Green Suppliers Selection Using Interactional Aggregation Operators for Interval-Valued Pythagorean Fuzzy Soft Sets

Green supplier selection is an important debate in green supply chain management(GSCM),attracting global attention from scholars,especially companies and policymakers.Companies frequently search for new ideas and strategies to assist them in realizing sustainable development.Because of the speculative character of human opinions,supplier selection frequently includes unreliable data,and the interval-valued Pythagorean fuzzy soft set(IVPFSS)provides an exceptional capacity to cope with excessive fuzziness,inconsistency,and inexactness through the decision-making procedure.The main goal of this study is to come up with new operational laws for interval-valued Pythagorean fuzzy soft numbers(IVPFSNs)and create two interaction operators-the intervalvalued Pythagorean fuzzy soft interaction weighted average(IVPFSIWA)and the interval-valued Pythagorean fuzzy soft interaction weighted geometric(IVPFSIWG)operators,and analyze their properties.These operators are highly advantageous in addressing uncertain problems by considering membership and non-membership values within intervals,providing a superior solution to other methods.Moreover,specialist judgments were calculated by the MCGDM technique,supporting the use of interaction AOs to regulate the interdependence and fundamental partiality of green supplier assessment aspects.Lastly,a statistical clarification of the planned method for green supplier selection is presented.

Weighted multilinear p-adic Hardy operators and commutators on p-adic Herz-type spaces

In this paper,we introduce the weighted multilinear p-adic Hardy operator and weighted multilinear p-adic Ces`aro operator,we also obtain the boundedness of these two operators on the product of p-adic Herz spaces and p-adic Morrey-Herz spaces,the corresponding operator norms are also established in each case.Moreover,the boundedness of commutators of these two operators with symbols in central bounded mean oscillation spaces and Lipschitz spaces on p-adic Morrey-Herz spaces are also given.

Application of Specialized Group Management in the Quality Control of Perioperative Nursing

Objective:To explore the role of specialized group management in the quality control of perioperative nursing.Methods:45 surgical nurses from our hospital were selected as the research subjects.Traditional operating room management was adopted from July 2019 to June 2020,and specialized group management was adopted from July 2020 to June 2021.The surgeon’s satisfaction,surgical nurses’core professional competence,and surgical patients’satisfaction were obtained through surveys and the results were analyzed.Results:Surgeon satisfaction before the implementation of specialized group management was significantly lower than after its implementation(P<0.05).Besides,surgical nurses’core professional competency scores before the implementation of specialized group management were significantly lower than after its implementation(P<0.05).Lastly,surgical patients’satisfaction before the implementation of specialized group management was significantly lower than after its implementation(P<0.05).Conclusion:Specialized group management helps to improve the quality of perioperative care and should be applied in clinical practice.

Maximal operators of pseudo-differential operators with rough symbols

Consider a pseudo-differential operator T_(a)f(x)=∫_(R^(n))e^(ix,ζ)a(x,ζ)f(ζ)dζwhere the symbol a is in the rough Hormander class L^(∞)S_(ρ)^(m)with m∈R andρ∈[0,1].In this note,when 1≤p≤2,if n(ρ-1)/p and a∈L^(∞)S_(ρ)^(m),then for any f∈S(R^(n))and x∈R^(n),we prove that M(T_(a)f)(x)≤C(M(|f|^(p))(x))^(1/p) where M is the Hardy-Littlewood maximal operator.Our theorem improves the known results and the bound on m is sharp,in the sense that n(ρ-1)/p can not be replaced by a larger constant.