Complex Electromechanical System Research Articles

A Performance degradation assessment method for complex electromechanical systems based on adaptive evidential reasoning rule

A Performance degradation assessment method for complex electromechanical systems based on adaptive evidential reasoning rule

Research on operating characteristics of V-shaped ultrasonic motor based on improved electromechanical coupling model

Abstract As a complex electromechanical coupling system, evaluating the motion characteristics of an ultrasonic motor via an accurate theoretical model is challenging due to the strong coupling between its electrical and mechanical properties. To address this issue, the paper first establishes a complete dynamic model of the V-shaped ultrasonic motor (VUSM). In contrast to the traditional dynamic model, the proposed model incorporates the centroid vibration of the stator and applies the weighted residual method to reduce the computational complexity by simplifying the dynamic model from infinite-dimensional degrees of freedom to two degrees of freedom. Subsequently, the finite element method is employed to determine the vibration mode of the stator structure and derive the two-phase operational mode of the motor. Using these two-phase working modes, the model is then solved to predict the motor's output characteristics under any operational condition. Furthermore, an electrical model accounting for preload nonlinearity was developed based on the dynamic model and compared with the model without considering preload nonlinearity, supported by experimental verification. The findings demonstrate that the established dynamic model and electrical model can accurately simulate the changing laws of the input and output characteristics of the motor, which provides assistance for the subsequent operation status evaluation of the motor and fault diagnosis during operation.

Tutorial on Signal Processing Impacts of ICP(r) Accelerometer Limit Violations

Accelerometers with embedded Integrated Circuit Piezoelectric (ICP) circuitry are complex electro-mechanical systems. The mechanical and electrical components are designed to provide wide ranges of linear response (voltage induced by a given acceleration) over amplitude and time (frequency). However, every sensor has limits, and exceeding those permissible limits can lead to attenuated, amplified, and even clipped signals. Sometimes, signals are unmeasurable due to 'noise floors.' This tutorial explains: piezoelectric sensor operating principles; how ICP-powered accelerometers measure fluctuating vibrations; the lower and upper limits of linear response and what causes them, both in amplitude and frequency; and the effects of violating those limits on response frequency spectra using signal processing theory and examples.

MBRB: Micro-belief rule Base model based on cautious conjunctive rule for interpretable fault diagnosis

—In aerospace engineering, implementing interpretable fault diagnosis technology is critical for improving the credibility of diagnostic results and ensuring the reliability of complex electromechanical systems. As a typical interpretable modeling method, the belief rule base (BRB) approach still faces two challenges that need to be addressed for its application in interpretable fault diagnosis: 1) The lengthy rule structures raise the cost of model interpretability, and 2) over-optimization of parameters diminishes the interpretability. To solve these problems, this paper proposes a modified micro-belief rule structure and develops a new micro-belief rule base (MBRB) model based on this structure. In addition, considering the independence of rules and the correlations between multiple BRBs, a cautious conjunctive rule-based reasoning process is established as the inference engine of MBRB. Moreover, an interpretable optimization method based on projection covariance matrix adaptive evolutionary strategy (PCMAES-I) is proposed for the MBRB model to balance model interpretability and diagnostic accuracy. Finally, the availability and effectiveness of the proposed MBRB is verified through an electromagnetic relay experiment.

A Novel Polynomial-Time Algorithm for Automatic Layout of Branching Cables in a Fixed Topology

Designing the layout for complex electromechanical products involves the challenging task of automatically laying out cables. This challenge is particularly pronounced in the case of branch cables, which are more intricate due to their multiple connection terminals and branches. This paper presents a polynomial-time wiring algorithm based on dynamic programming to determine branching point locations in the layout design of cables, given the electrical definition of the wire harness. The method considers various engineering constraints, including obstacle avoidance, wall adherence, minimum bend radius, and gray areas. To validate our method, we implemented a branch cable auto-layout system through secondary development based on the UG platform. The experimental results indicate the effectiveness of our approach, demonstrating promising performance in terms of time and high-quality layouts. This showcases its potential for practical application in cable layout design for complex electromechanical systems.

A review on the magnetorheological materials and applications

Magnetorheological materials refer to field-response smart materials whose properties are controllable with a magnetic field, including fluid, grease, elastomer, and gel. The unique magnetorheological effect exhibited by these smart materials is a physical phenomenon where physics and engineering intersect and has extensive application prospects in modern machinery. In electro-mechanical systems, magnetorheological materials offer a superior design method for mechanical devices used in the fields of transmission, damping, and braking. It is important to control the magnetorheological materials for advancing the design philosophy of modern electro-mechanical devices. Hence, this paper presents a recent progressive review on the fundamentals of magnetorheological materials and numerous applications. Firstly, an introduction to the magnetorheological effect and different types of magnetorheological materials are presented in this review. Then, the individual and coupled effects of sedimentation, temperature, and magnetic field on magnetorheological materials are discussed. Finally, magnetorheological materials-based devices have been extensively reviewed, including actuator, clutch, damper, brake, pump, valve, and robot, thus aiming to provide useful information for facilitating the design of complex electro-mechanical systems.

Effectiveness evaluation of complex electromechanical system based on improved analytic hierarchy process - entropy weight method - fuzzy synthesis evaluation method

At present, complex electromechanical systems are widely used in modern society. By evaluating complex electromechanical systems, it is of great value to improve and upgrade them. Given the complex and interrelated characteristics of performance indicators, this paper establishes the performance evaluation indicator system of a complex electromechanical system, proposes to calculate the weight of each indicator by an improved analytic hierarchy process, revises the indicator weight by entropy weight method, and then adopts fuzzy synthesis evaluation method to evaluate the comprehensive effectiveness of a complex electromechanical system quantitatively. Through the example analysis, it is proved that this method provides an effective way for the effectiveness evaluation of complex electromechanical systems.

A novel conceptual design approach for autonomous underwater helicopter based on multidisciplinary collaborative optimization

Autonomous underwater helicopters (AUHs) are complex electromechanical systems consisting of multiple interconnected sub-disciplines, posing a significant challenge for traditional sequential design strategies in managing their interactions. To address this challenge, a multidisciplinary collaborative optimization (MCO) strategy is proposed, integrating structural, hydrodynamic, and energy disciplines to enhance AUH cruising range. Additionally, a novel approximation model is introduced, combining the Logistic-Tent chaos sparrow search algorithm (LTC-SSA) with the backpropagation neural network (BPNN) algorithm. This method aims to replace costly computational fluid dynamics (CFD) and structural mechanics calculations, thus reducing AUH optimization costs. The laminate design of the composite pressure hull follows classic lamination theory (CLT) and the Tsai-Wu failure criterion. Results demonstrate that the multidisciplinary co-design strategy significantly reduces optimization time costs of AUH, from several months to several days. Furthermore, the proposed LTC-SSA-BPNN algorithm accurately evaluates sailing resistance and Tsai-Wu failure index, with maximum errors of 1.64% and 9.32% respectively. Additionally, the composite pressure shell achieves a 30.4% weight reduction and a 4.1% reduction in sailing resistance while maintaining structural stability. Moreover, the maximum cruising range increases by 34.4%. This strategy offers theoretical support for AUH conceptual design and promises performance enhancement in practical engineering applications.

A generative adversarial networks based methodology for imbalanced multidimensional time-series augmentation of complex electromechanical systems

Multidimensional monitoring time-series of complex electromechanical systems (CESs) plays a foundational role in data-based state management, maintenance, and performance adjustment. However, it is still a challenging work to extract valuable and complete information due to the imbalanced data. To address this issue, a methodology called GAN4MTS (Generative Adversarial Networks for Multidimensional Time-Series) that generates synthetic data closely mimicking the characteristics of real data was proposed, thus directly tackling the problem of data imbalance. First, the uniqueness of multidimensional time series of CESs was analyzed to identify the requirements for data augmentation and to define the problem formulations. Second, the architecture and loss functions of GAN4MTS model were designed based on generative adversarial networks and three specific constraints. Finally, the effectiveness of the proposed work was validated through comparative analysis. Furthermore, the intrinsic mechanisms of data augmentation in enhancing the model capabilities were discussed. The proposed methodology serves as a comprehensive technical solution for data augmentation, enabling the generation of high-quality synthetic data that adheres to the constraints of multidimensional time series in CESs. Additionally, as an open architecture model, this work provides novel methods for time-series data augmentation, addressing the issues of low accuracy and limited model generalization in state classification, identification, and prediction tasks for CESs caused by the presence of highly imbalanced data.

Reliability analysis for complex electromechanical multi-state systems utilizing universal generating function techniques

The large-scale adoption of complex electromechanical systems (CMESs) renders it challenging to perform reliability assessments for such systems. In terms of the reliability evaluation of CMESs, previous studies generally assume that only binary states exist within the systems. However, owing to the stochastic failures and various operating characteristics of the system components, not only the good/bad states but also the performance levels within the system should be taken into account when analyzing the reliability of CMESs. Hence, we abstract the CMES as a multi-layer and multi-state network in which minimum maintenance units (MMUs) and three types of connections constitute nodes and edges in different layers. Furthermore, multi-state models for different MMUs in the CMES are developed based on universal generating functions (UGFs). Aggregation operators are then utilized to aggregate these UGFs to obtain the multi-state models. Subsequently, a cascading failure model is introduced to incorporate MMUs into the system reliability assessment. Thus, the effects of the operating mechanism and topological attributes can be considered in the reliability evaluation of the CEMS. Finally, the CRHX high-speed train system is used as an example to demonstrate the applicability and effectiveness of the proposed method in the reliability assessment of the CMES.

A method for reliability assessment of complex electromechanical system based on improved network connectivity entropy

The interconnectivity of components in complex electromechanical system (CMES) plays a critical role in ensuring system reliability. To examine the effect of component failures on system reliability, this work proposes a new reliability assessment method for CEMS based on improved network connectivity entropy. This method takes into account the mechanical, electrical, and information characteristics of components, and employs a comprehensive component importance calculation approach based on PageRank, which considers the functional impact of components. The reliability assessment model, considering both functional and topological attributes of the system, is established through the theory of network connectivity entropy. The proposed method is then demonstrated through an application to a bogie system of the CRH2008A high-speed railway. The proposed approach, rooted in topological networks, integrates component degradation into the physical structure of CEMS, providing a comprehensive way to deduce the impact of component failures on system reliability. Validity is demonstrated through case studies.

Precision local anomaly positioning technology for large complex electromechanical systems

In recent years, Prognostics Health Management (PHM) technology has become an important reference technology in fields such as avionics and electromechanical systems due to its ability to reduce costs and achieve state based maintenance and autonomous support. However, with the operation of large and complex electromechanical systems (ES), the data generated gradually ages the status of components, and traditional PHM technology is difficult to solve the problem of electromechanical system components becoming more complex. Based on this, this study takes the hydraulic actuator cylinder as an example to construct a local component fault detection model. Firstly, fault data features are extracted using wavelet packet energy spectrum, and then a fault detection model is constructed based on support vector machine (SVM). In response to the shortcomings of SVM, a smooth support vector machine (SSVM) is proposed to replace SVM, and an improved crow search algorithm (ICSA) is used to improve SVM. Finally, an intelligent detection model for hydraulic actuator cylinder faults based on ICSA-SSVM was constructed based on the above algorithms. The experimental results show that the ICSA-SSVM model has the fastest Rate of convergence, among which, the positioning accuracy is 0.96, the fitting degree is 0.984, the fault detection accuracy is 99.16 %, the recall value is 94.52 %, and the AUC value is 0.986, all of which are better than the existing fault detection models. From this, it can be seen that the precise local anomaly localization technology for large-scale complex electromechanical systems based on the ICSA-SSVM algorithm proposed in this study can improve the efficiency and accuracy of fault detection, achieve accurate and intelligent detection of ES local anomalies, and have certain positive significance for the development of China’s industry.

Simulation Model of Double Motors Screw Unit with a Solid Rotor in ANSYS Twin Builder

This article is devoted to solving the problem of simulation modeling of the electric drive system of two induction machines with an external solid rotor, rigidly connected to each other. This design is due to research aimed at optimizing mechanical characteristics and increasing the stability of the mixing regime of mixtures of loose materials of different dispersions using a multifunctional screw-type energy converter (MFEC). The task presents difficulties from the point of view of ensuring the productivity of drying wet loose material. On the one hand, in order to ensure a given percentage of moisture reduction during its advancement along the surface of the screw, it is necessary to have a low speed of rotation of the rotor to increase the contact time of the material with the hot surface of the rotor. On the other hand, reducing the rotation speed of the rotor reduces the intensity of its heating, which negatively affects the performance of the unit as a whole. A third challenge is to provide high torque at low rotational speed to prevent high-density material from buckling. In the previous publications of the authors, a study was conducted to solve such problems due to a specific combination of motor and brake modules of the auger, but such an approach did not give positive results. Solving the specified problems is possible due to the reproduction of such a complex electromechanical system and electric drive system in the ANSYS Twin Builder software. The article shows a detailed vector field-oriented control (FOC) system applied to two modules of the screw unit. Each of the modules represents a reduced-order model (ROM) that works in coupling simulation with the electromechanical processes in ANSYS Twin Builder. This paper will be useful both for specialists in the field of electric drive and for researchers who are engaged in the development of digital twins of complex systems.

Failure Propagation Prediction of Complex Electromechanical Systems Based on Interdependence

Interdependence is an inherent feature of the cyber-physical system. Small damage to one component in the system may affect several other components, leading to a series of failures, thus collapsing the entire system. Therefore, the system failure is often caused by the failure of one or more components. In order to solve this problem, this paper focuses on a failure propagation probability prediction method for complex electromechanical systems, considering component states and dependencies between components. Firstly, the key component set in the system is determined based on the reliability measure. Considering the three coupling mechanisms of mechanical, electrical, and information, a topology network model of the system is constructed. Secondly, based on the topology network model and fault data, the calculation method of influence degree between components is proposed. Three state parameters are used to express the risk point state of each component in the system through mathematical representation, and the correlation coefficient between the risk point state parameters is calculated and measured based on the uncertainty evaluation. Then, the influence matrix between the system risk points is constructed, and the fault sequence is predicted by using the prediction function of an Artificial Neural Network (ANN) to obtain the fault propagation probability. Finally, the method is applied to the rail train braking system, which verifies that the proposed method is feasible and effective.

Modeling failure propagation to analyze the vulnerability of the complex electromechanical systems under network attacks

Since the complex electromechanical system (CMES) is a complex integration of multiple minimum maintenance units (MMUs), a single faulty MMU can trigger multi-step failures and eventually damage a substantial portion of the CMES. To investigate the failure propagation process and analyze the impact of the CMES under MMU attacks, we first abstract the system as a directed network composed of MMUs, machine-electricity-information connections, and functional properties. Subsequently, a fault propagation model is constructed based on the fault occurrence probability and matrix transformation, which considers the topological and functional attributes of the system. Then, we build the attack graphs to evaluate the faulty edges on the system’s vulnerability and propose some vulnerable indices based on the node attack strategies to quantify the attack impact of the malfunctioning nodes on the CMES network. Finally, a bogie system of the high-speed train is selected as a case study to verify the validity of the proposed method. Based on the findings, we can clarify the failure propagation behavior and quantify the impact of the faulty nodes and edges on the CMES network. Furthermore, the critical connections and nodes that significantly impact system vulnerability can be identified. Hence, our work can provide guiding significance for developing maintenance strategies to reduce losses and optimize the management scheme.

Review on Solar Photovoltaic-Powered Pumping Systems

Water and energy are becoming more and more important in agriculture, urban areas and for the growing population worldwide, particularly in developing countries. To provide access to water it is necessary to use appropriate pumping systems and supply them with enough energy for operation. Pumps powered by solar photovoltaic energy are complex electromechanical systems that include hydraulic equipment, electrical machines, sensors, power converters, and control units. Therefore, solar photovoltaic pumping systems are associated with various fields of science and engineering. In remote, less-populated areas without electricity, where it is either challenging to connect to the grid or it is not possible, solar photovoltaic water pumping systems can play a significant role. To see whether solar photovoltaic pumping systems may be a practical, viable, and affordable method of pumping water it is necessary to study different aspects of their operation. The goal of this current article is to evaluate and outline recent research and advancement in the field of solar photovoltaic pumping systems. The major focus is on the standalone photovoltaic pumping system’s components, factors that affect system efficiency, performance evaluation, system optimization, and the potential for integration with modern control techniques. The main objective of this article is to give a broader overview of solar photovoltaic technologies for researchers, engineers, and decision-makers.

Study of the dynamics of the movement mechanism of an overhead crane as a complex electromechanical system

The article studies the dynamics of the crane movement mechanism to take measures for their reliable operation and reduce the wear of movement mechanisms. For this, the following assumptions are accepted: transverse motion is not considered, the dynamics of engines and electric drive is not considered; the crane is presented in the form of a seven–mass system, the load suspension is adopted as rigid.
 It has been established that account of flexibility of the rope, with which the load is suspended, does not significantly affect (no more than 10%) the values of the largest dynamic loads in elastic connections; therefore, when determining the loads in the elastic connections of the movement mechanisms, it is possible to use a system with an elastic mechanism and a rigid suspension of the load. The processes in the movement mechanisms of load-lifting cranes are considered, using the calculated seven-mass dynamic scheme of structures. During the mechanism operation the oscillations occur in its metal structures and transmission shafts, in addition, the load sways (which, together with a rope of length Ls, forms a pendulum with a moving suspension point).
 The graphs show the forces in the longitudinal, transverse beams of the crane and the linear speeds of wheels, with an external force applied to each wheel of 21700 N. All three types of oscillations have different frequencies, which allows them to be considered on simpler two-mass models. But when using synchronous rotation systems (SRS) on the movement mechanism, which are often prone to oscillations, the proposed model is better suited, because it takes into account the interaction of the SRS and the mechanism at different vibration frequencies. With these loads, the mismatch of the path of the sides Dxc does not exceed 0,025 m, the relative swing of the load xl is not more than 0,25 m.
 The article found that according to the seven-mass model, when a driving force is applied, mechanical oscillations arise in which three frequencies of interaction are observed. For the crane designs discussed in the article, these frequencies are 0,2, 0,95 and 6,4 Hz; to study a more complete picture of the processes, it is necessary to consider the transverse displacement of the crane and the dynamics of electric drive movement.
 The parameters of the calculated scheme for output data of the bridge are determined. Based on obtained results the calculated scheme of crane movement mechanism was constructed. The system is converted into a three-axle, the first of which is the rotor of engine, the second - the first gear together with the coupling, and the third - the axle with two gears.

Physics‐data‐fusion based decoupling model for coupled faults of complex electromechanical systems

AbstractCoupled faults are formed by the nonlinear coupling of multiple lower‐level faults in complex electromechanical systems (CES). Although fault decoupling plays a crucial role in locating fault cause and isolating fault components, it still faces challenges due to the harsh reality of common mode failure, networked propagation, and a lack of accurate fault mechanism knowledge in the fault coupling process. A novel physics‐data‐fusion‐based decoupling model for coupled faults of CES was proposed using standard meta components, rigorous formulation, and intuitive representation. First, a hierarchical graph representing the static complex decoupling model was defined by composing proposed meta models. Second, the dynamic model parameters inspired by the time‐varying fault characteristics were determined using real‐time operation data analysis. Then, based on a proposed numerical reasoning formula, the most likely fault cause was determined, which can also identify fault level by level. Finally, the decoupling model was proved to be reasonable and effective with an offshore wind turbine case. As a graphical modelling method, it handles the decoupling process by fusing static physics and dynamic data of coupled faults. While inheriting the benefits of conventional models, it overcomes the limitations of these existing methods for real‐time results. Moreover, the proposed method provided a foundation for tracing the root cause of performance fluctuations, fault detection, and isolation of CES.

A Study on Trajectory Control System of Hydraulic Excavators Based on Multi-Domain Physical Model*

Hydraulic excavators are complex mechatronics construction machinery with characteristics of multidiscipline intersection and multi-domain close coupling. To analyze the comprehensive property of its trajectory control system, a method of multi-system hybrid modeling and simulation based on MATLAB is proposed and described. In this paper, the multi-domain physical model of a medium-sized hydraulic excavator is established. The considered model is mainly comprised of four other subsystems: a machine system, a hydraulic system, a trajectory control system and a sensor system. Moreover, a fuzzy neural network (FNN) PID strategy is introduced to the trajectory control system to guarantee the accuracy of automatic operation. On the basis of the multi-domain physical model, typical simulation experiments for working patterns were performed to validate the performance of the FNNPID controller. Comparison results demonstrate that the precision and velocity response of the FNNPID controller is better than that of the PID with traditional algorithm. The tracking errors of the boom, the arm, the bucket and the swing are decreased by 3∘, 3.2∘, 5.5∘ and 7.5∘, respectively. Establishment of the multi-domain physical model offers technical means for optimization design and rapid modeling of the complex electromechanical system.

Reliability analysis of complex electromechanical systems: State of the art, challenges, and prospects

AbstractAs the core foundation of reliability engineering and one of the most crucial aspects of general quality, reliability has been attracting increasing attention from industry and academia. Numerous publications on reliability analysis (RA) have appeared in academic journals, conference proceedings, and technical reports. However, there has not been a systematic summary that covers RA data, models, methods, indicators, and software comprehensively. To fill this gap, this paper analyzed the challenges and the state of the art, as well as determined the future prospects for research on RA. This paper introduces the features of modern complex electromechanical systems (CES), then summarizes the current challenges to the RA of CES. Next, it reviews the latest developments, such as reliability theories, models, methods, and software, then summarizes and compares their advantages and limitations. Finally, it discusses future prospects from the perspectives of reliability data, modeling, decoupling, evaluation indicators, and timely prediction. It is expected that this paper would serve as an introduction to RA for researchers new to this field and as a summary of the current frontiers of RA for experienced researchers.