Electromechanical Systems Research Articles

Model order reduction and stochastic averaging for the analysis and design of micro-electro-mechanical systems

Electro-mechanical systems are key elements in engineering. They are designed to convert electrical signals and power into mechanical motion and vice-versa. As the number of networked systems grows, the corresponding mathematical models become more and more complex, and novel sophisticated techniques for their analysis and design are required. We present a novel methodology for the analysis and design of electro-mechanical systems subject to random external inputs. The method is based on the joint application of a model order reduction technique, by which the original electro-mechanical variables are projected onto a lower dimensional space, and of a stochastic averaging technique, which allows the determination of the stationary probability distribution of the system mechanical energy. The probability distribution can be exploited to assess the system performance and for system optimization and design. As examples of application, we apply the method to power factor correction for the optimization of a vibration energy harvester, and to analyse a system composed by two coupled electro-mechanical resonators for sensing applications.

Machine Fault Diagnosis through Vibration Analysis: Continuous Wavelet Transform with Complex Morlet Wavelet and Time–Frequency RGB Image Recognition via Convolutional Neural Network

In pursuit of advancing fault diagnosis in electromechanical systems, this research focusses on vibration analysis through innovative techniques. The study unfolds in a structured manner, beginning with an introduction that situates the research question in a broader context, emphasising the critical role of fault diagnosis. Subsequently, the methods section offers a concise summary of the primary techniques employed, highlighting the utilisation of short-time Fourier transform (STFT) and continuous wavelet transform (CWT) for extracting time–frequency components from the signal. The results section succinctly summarises the main findings of the article, showcasing the results of features extraction by CWT and subsequently utilising a convolutional neural network (CNN) for fault diagnosis. The proposed method, named CWTx6-CNN, was compared with the STFTx6-CNN method of the previous stage of the investigation. Visual insights into the time–frequency characteristics of the inertial measurement unit (IMU) data are presented for various operational classes, offering a clear representation of fault-related features. Finally, the conclusion section underscores the advantages of the suggested method, particularly the concentration of single-frequency components for enhanced fault representation. The research demonstrates commendable classification performance, highlighting the efficiency of the suggested approach in real-time scenarios of fault analysis in less than 50 ms. Calculation by CWT with a complex Morlet wavelet of six time–frequency images and combining them into a single colour image took less than 35 ms. In this study, interpretability techniques have been employed to address the imperative need for transparency in intricate neural network models, particularly in the context of the case presented. Notably, techniques such as Grad-CAM (gradient-weighted class activation mapping), occlusion, and LIME (locally interpretable model-agnostic explanation) have proven instrumental in elucidating the inner workings of the model. Through a comparative analysis of the proposed CWTx6-CNN method and the reference STFTx6-CNN method, the application of interpretability techniques, including Grad-CAM, occlusion, and LIME, has played a pivotal role in revealing the distinctive spectral representations of these methodologies.

Measuring power consumption efficiency of an electromechanical system within a long-term period by fuzzy DEA and TOPSIS for sustainability

Measuring power consumption efficiency of an electromechanical system within a long-term period by fuzzy DEA and TOPSIS for sustainability

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.

Research on motor rotation anomaly detection based on improved VMD algorithm

PurposeThe electromechanical brake system is leading the latest development trend in railway braking technology. The tolerance stack-up generated during the assembly and production process catalyzes the slight geometric dimensioning and tolerancing between the motor stator and rotor inside the electromechanical cylinder. The tolerance leads to imprecise brake control, so it is necessary to diagnose the fault of the motor in the fully assembled electromechanical brake system. This paper aims to present improved variational mode decomposition (VMD) algorithm, which endeavors to elucidate and push the boundaries of mechanical synchronicity problems within the realm of the electromechanical brake system.Design/methodology/approachThe VMD algorithm plays a pivotal role in the preliminary phase, employing mode decomposition techniques to decompose the motor speed signals. Afterward, the error energy algorithm precision is utilized to extract abnormal features, leveraging the practical intrinsic mode functions, eliminating extraneous noise and enhancing the signal’s fidelity. This refined signal then becomes the basis for fault analysis. In the analytical step, the cepstrum is employed to calculate the formant and envelope of the reconstructed signal. By scrutinizing the formant and envelope, the fault point within the electromechanical brake system is precisely identified, contributing to a sophisticated and accurate fault diagnosis.FindingsThis paper innovatively uses the VMD algorithm for the modal decomposition of electromechanical brake (EMB) motor speed signals and combines it with the error energy algorithm to achieve abnormal feature extraction. The signal is reconstructed according to the effective intrinsic mode functions (IMFS) component of removing noise, and the formant and envelope are calculated by cepstrum to locate the fault point. Experiments show that the empirical mode decomposition (EMD) algorithm can effectively decompose the original speed signal. After feature extraction, signal enhancement and fault identification, the motor mechanical fault point can be accurately located. This fault diagnosis method is an effective fault diagnosis algorithm suitable for EMB systems.Originality/valueBy using this improved VMD algorithm, the electromechanical brake system can precisely identify the rotational anomaly of the motor. This method can offer an online diagnosis analysis function during operation and contribute to an automated factory inspection strategy while parts are assembled. Compared with the conventional motor diagnosis method, this improved VMD algorithm can eliminate the need for additional acceleration sensors and save hardware costs. Moreover, the accumulation of online detection functions helps improve the reliability of train electromechanical braking systems.

A conical spiral piezoelectric energy harvester with parallel beams for all-directional flow energy harvesting

Piezoelectric energy harvesting technology using flow-induced vibration is a type of interference-resistant and miniaturizable power generation technology, which is promising on powering the wireless micro electromechanical system in flow filed. However, the flow direction of the natural flow field is changeable while most existing flow-induced piezoelectric energy harvesters (PEHs) are limited by their working direction. In this paper, we propose a conical spiral piezoelectric energy harvester with parallel beams (CSPEH-PB) that can collect energy under flow excitation in all directions. Based on the multi-dimensional vibration analysis of conical spiral structure, we investigate the resonance mode and effective flow velocity range of the CSPEH-PB through numerical analysis. In comparative experiments with a bimorph flat PEH, we verify the effective flow velocity range and voltage of the CSPEH-PB and polyvinylidene fluoride (PVDF) films attached. The results demonstrate that the CSPEH-PB generates an effective voltage greater than 0.53 V through the PVDF films under any direction of the water flow, and has a wider resonance bandwidth than PEH with straight beam. This study provides a practical solution for adapting PEHs to changeable flow direction.

WIRELESS COMMUNICATION IN ELECTRO-MECHANICAL SYSTEMS: INVESTIGATING THE RISE AND IMPLICATIONS OF CORDLESS INTERFACES FOR SYSTEM ENHANCEMENT

This study systematically investigates the rise and implications of wireless communication interfaces in electro-mechanical systems, focusing on their technological advancements, economic impacts, and environmental considerations. The primary aim is to explore the transition from wired to wireless technologies and assess their influence on system enhancement across various sectors. Methodologically, the study employs a systematic literature review, sourcing data from key academic databases like IEEE Xplore, PubMed, and ScienceDirect. The search strategy involves keywords related to wireless communication and electro-mechanical systems, adhering to strict inclusion and exclusion criteria to ensure the relevance and quality of the literature. The selection process involves a multi-stage screening, and data analysis is conducted through thematic synthesis. Key findings reveal that the integration of wireless interfaces significantly enhances system performance, efficiency, and scalability. Technological advancements, particularly in wireless communication protocols and miniaturization, have been pivotal. Economically, wireless interfaces introduce cost-effectiveness and new business models, while environmentally, they contribute to sustainable practices through energy efficiency. However, challenges such as security risks and the need for robust regulatory frameworks are identified. The study concludes that wireless technologies have transformed electro-mechanical systems, offering substantial benefits but also presenting new challenges. Future research directions include exploring the integration of emerging technologies like AI and IoT, addressing security concerns, and assessing the socio-economic impacts of wireless technology adoption. This study provides valuable insights for researchers, industry practitioners, and policymakers in the field of wireless communication technologies.
 Keywords: Wireless Communication, Electro-Mechanical Systems, System Enhancement, Cordless Interfaces.

Forensic Engineering Investigation of a Machine Guarding-Related Injury

OSHA regulations and industry-accepted standards are intended to be used in conjunction to help prevent worker injury. Despite the aforementioned intention, a point of operation injury occurred to an employee while he was operating a hydraulic rotary bending machine. The machine had been retrofitted with a two-hand control device that was intended to act as a means of point of operation safeguarding. A forensic engineering analysis of both the electromechanical design and programmable logic code — combined with a performance and prescriptive requirement analysis — ultimately revealed flaws in the design of the electromechanical system and software design. It also demonstrated a lack of adherence to the applicable industry-accepted standards related to machine guarding. These factors led to the point of operation injury.

Observer design method for nonlinear generalized systems with nonlinear algebraic constraints with applications

This paper proposes a new method to estimate the state of nonlinear generalized systems subject to nonlinear algebraic constraints via H∞ observers. Compared with previous research, the proposed approach relaxes the linear algebraic constraint and the infinite observability, making it applicable to a wider range of generalized systems. The generalized inverse technique for matrices avoids the additional structural requirements caused by the nonlinear algebraic constraints. Moreover, we assume an easier-to-implement rank condition than infinite observability, allowing for the handling of two different observability. Building on the above, the method can be extended to systems with nonlinear outputs after converting them to a suitable form. To validate the effectiveness of the proposed method, we demonstrate three practical applications, including observer designing for electromechanical systems, Lithium batteries, and vehicles.

Comparison of Transmission Technologies with Regard to their Contribution to Power System Stability

The amount of power to be transmitted is increasing worldwide. Hence, a considerable number of bulk power transmission projects are going to be realized (e.g. [1]). Taking into account the recent technical development, three technologies are available for bulk power transmission: Direct current applications with voltage sourced or line commutated converters as well as the high-voltage AC technology up to 1200 kV. To select the most suitable technology for a particular project is often anything but trivial for the transmission system operator. Amongst other criteria, the influence on the electromechanical behavior of the power system is a decisive factor for network improvements that should be considered within the decision-making process. This paper aims at categorizing and analyzing this rather abstract term as a major criterion. The goal is to provide an indication, which factors are needed to be evaluated in advance of the well-considered choice. For that reason, several categories are introduced and thoroughly investigated within the scope of a theoretical approach. Where reasonable, simulation results are presented in order to enable the practical assessment of the impact on the electromechanical system behavior. As a conclusion, it is recommended to perform concise ex-ante studies with regard to the electromechanical dynamics as a decision-making basis to identify the most suitable transmission technology for a particular project.

Nanoengineered micro-supercapacitors based on graphene nanowalls for self-powered wireless sensing system

This work presents a comprehensive investigation of micro-supercapacitors (MSCs) based on graphene nanowalls (GNWs), covering core material synthesis, device fabrication, evaluation, and application demonstrations. Three-dimensional hierarchical GNWs structures are grown successfully by a microwave plasma-enhanced chemical vapor deposition (MPECVD), with detailed descriptions of the synthesis process and underlying mechanisms. The structural and morphological properties of the GNWs are thoroughly analyzed. Several types of MSCs are reported, ranging from thin-film to three-dimensional (3D) MSCs, as well as symmetric to asymmetric MSCs. Thin-film MSC is developed by a novel micromachining process for one-step fabricating GNWs-Ni core-shell composite microstructures. A solid-state MSC utilizing 3D hierarchical electrode is created by a fully micro electro mechanical system (MEMS)-compatible process. This involves depositing GNWs-RuOx hybrid nanostructures onto microstructure scaffolds formed using deep reactive ion etching (deep RIE). Additionally, another 3D MSC utilizes GNWs-PANI electrode material deposited on silicon nanowires generated through metal-assisted chemical etching (MACE) method. To enhance MSCs performance, asymmetric MSC is proposed and realized, incorporating GNWs-MnO2 acting as the positive electrode and carbon black serving as the negative electrode. Furthermore, the successfully combination of the fabricated MSCs with an energy harvesting system is demonstrated. The self-powered sensing system driven by solar energy, with the harvested energy stored in MSCs, is effectively showcased, opening up new possibilities for futuristic MSCs to accumulate and store harvested energy as usable electricity. This demonstration has significant potential in fields such as self-powered wireless IoT sensing systems, offering valuable contributions towards sustainable and autonomous energy solutions.

Simulation Study on Dynamic Characteristics of the Chain Drive System for Mining Scraper Conveyor Driven by the Permanent Magnet Synchronous Motor

The chain drive system represents a critical subsystem within the scraper conveyor. This paper proposes a joint simulation model for the drive system of the scraper conveyor, driven by the permanent magnet synchronous motor, in order to conduct a comprehensive analysis of the dynamic characteristics of the chain drive system during the operational process. Firstly, the dynamic simulation model for the mining scraper conveyor’s chain drive system was established in ADAMS, taking into account its structural characteristics. Then, the mathematical model of the permanent magnet synchronous motor was established using the coordinate transformation theory, and the speed controller based on vector control was designed by using the theory related to sliding mode control. The coupling relationship between the chain drive system of the scraper conveyor and the permanent magnet synchronous motor drive system was investigated. Finally, a joint simulation model of the mechanical system and motor control system was created using ADAMS (View 2019) and MATLAB/Simulink (2020a). The dynamic characteristics of the chain drive system were analyzed, and the three typical working conditions of no load, half load, and rated load were considered. The results show that the contact force between the flat ring and the sprocket undergoes an initial increase, followed by a decrease, and finally another increase. As the load increases from no load to full load, there is a marked increase in the contact force between the loaded side chainrings. Due to the polygon effect, both the speed curve of the permanent magnet drive motor and the contact force curve between the ring chains exhibit periodic fluctuations. The research in this paper provides an idea for the coupling analysis of the scraper conveyor electromechanical system.

A framework for dynamic modelling of railway track switches considering the switch blades, actuators and control systems

The main contribution of this paper is the development and demonstration of a novel methodology that can be followed to develop a simulation twin of a railway track switch system to test the functionality in a digital environment. This is important because, globally, railway track switches are used to allow trains to change routes; they are a key part of all railway networks. However, because track switches are single points of failure and safety-critical, their inability to operate correctly can cause significant delays and concomitant costs. In order to better understand the dynamic behaviour of switches during operation, this paper has developed a full simulation twin of a complete track switch system. The approach fuses finite element for the rail bending and motion, with physics-based models of the electromechanical actuator system and the control system. Hence, it provides researchers and engineers the opportunity to explore and understand the design space around the dynamic operation of new switches and switch machines before they are built. This is useful for looking at the modification or monitoring of existing switches, and it becomes even more important when new switch concepts are being considered and evaluated. The simulation is capable of running in real time or faster meaning designs can be iterated and checked interactively. The paper describes the modelling approach, demonstrates the methodology by developing the system model for a novel “REPOINT” switch system, and evaluates the system level performance against the dynamic performance requirements for the switch. In the context of that case study, it is found that the proposed new actuation system as designed can meet (and exceed) the system performance requirements, and that the fault tolerance built into the actuation ensures continued operation after a single actuator failure.

Analysis of a network of FitzHugh-Nagumo neuron circuit coupled to an array of mechanical leg to mimic the locomotion of a multi-legged organism

A bioinspired electromechanical system that employs an array of FitzHugh–Nagumo (FN) neuron circuits designed to drive synchronically an array of mechanical legs is proposed in this paper. The schematic of the electromechanical device is transformed into an equivalent mathematical model thanks to Kirchhoff’s and Newton’s laws. The results of numerical simulations of the model generate an action potential (AP) that follows directly from the excitation of a single block of cell and does not propagate the signal in the neighboring blocks. When the stimulation time is lesser than 3-time units, the AP of the next block is generated during the repolarization of the previous cell, and the instantaneous displacement of the legs of the next block goes operational before the resting state of the previous block of the cell. For stimulation time greater than or equal to 3-time units, the AP is initiated just after the repolarization of the previous block of cells has terminated its activities and the instantaneous displacement of the leg of the next block goes operational, a direct consequence of neuron's communication without loss of amplitude in the permanent regime. Finally, straightforward motion without rotation is achieved.

Complex shell Fe-ZnO derived from ZIF-8 as high-quality acetone MEMS sensor

Zeolitic imidazolate frameworks (ZIFs) are a series of materials composited by metal ions and organic ligands with high specific surface area, which might be great precursors to produce metal oxides by calcination for gas sensor application. However, Zn-ZIF (ZIF-8) is hard to transform as ZnO in air and keeping the unique framework simultaneously. In this work, Fe2+ was introduced into the metal node to replace a part of Zn2+ ions, and it could be oxidized as Fe3+ in the calcination to facilitate the oxidation process of the 2-methylimdazole ligands to give Fe-ZnO complex shell with high specific surface area (108 m2/g) and abundant oxygen vacancies (48 %). The micro electro mechanical systems (MEMS) sensor based on the 6 %-Fe-ZnO complex shell performed outstanding gas sensing properties to the low-concentration acetone vapor, including high response (ΔR/Rg = 11.2 to 5 ppm acetone), superior selectivity (Sacetone/Sethanol = 5.6) and fast response speed (τres = 2.6 s). This work not only provided the research of an exceptional acetone MEMS sensor, but also induced a strategy to produce metal oxide derived from ZIFs with complex structures for the universal synthesis methodology.

Liquid crystal elastomers in soft micro electromechanical systems: a review of recent developments

This review paper explores the potential of liquid crystal elastomers (LCEs) and their ionic counterparts (iLCEs) as versatile materials for soft micro electromechanical systems (MEMS), highlighting their growing interest within the field.

Implantable Neural Electrodes Fabrication Based on Perfluoroalkoxyalkane Film.

In this paper, the fabrication of perfluoro-alkoxy alkane (PFA) film-based planar neural electrodes was proposed. The fabrication of PFA-based electrodes started with cleaning of PFA film. The argon plasma pretreatment was performed on the PFA film surface and attached to a dummy silicon wafer. Metal layers were deposited and patterned using the standard Micro Electro Mechanical Systems (MEMS) process. Electrode-sites and pads were opened using reactive ion etching (RIE). Lastly, the electrode patterned PFA substrate film was thermally laminated with the other bare PFA film. Electrical-physical evaluation tests were conducted along with in vitro tests, ex vivo tests and soak tests to evaluate the electrode performance and biocompatibility. The electrical and physical performance of PFA-based electrodes had better performances compared to other biocompatible polymer-based electrodes. Also, the biocompatibility and longevity were verified by cytotoxicity test, elution test, and accelerated life test. The PFA film-based planar neural electrode fabrication was established and evaluated. The PFA based electrodes showed excellent benefits such as long-term reliability, low water absorption rate, and flexibility using the neural electrode. For implantable neural electrodes, hermetic sealing is required for in vivo durability. PFA fulfilled a low water absorption rate with relatively low Young's modulus to increase the longevity and biocompatibility of the devices.

Numerical Simulation of Highly Sensitive Ga2O3 Pressure Sensor

This article presents beta‐gallium oxide (β‐Ga2O3) micro electro mechanical systems (MEMS) strain/pressure sensors as a way to enhance sensitivity. The model consists of four piezoresistive strain gauges connected in a Wheatstone bridge configuration. The MEMS model is simulated from 0 Pa to 50 kPa, resulting in an output signal range of −3–16 mV and a responsivity of 0.38 mV kPa−1. The simulation also shows that as temperature increases, the resistance of the piezoresistive material in the MEMS decreases, leading to changes in the output signals. The reliable device effectively utilizes the full Wheatstone bridge configuration to compensate for temperature‐related influences. These early results suggest that Ga2O3‐based MEMS devices have great potential for use in high‐temperature pressure sensor applications in the future.

Application of Data Visualization Technology in Fault Diagnosis and Maintenance of Intelligent Electromechanical Systems

There are problems of low efficiency and low accuracy in the fault location and maintenance process of electromechanical systems. In order to solve this problem, this article adopts a comprehensive literature analysis and case study method to conduct in-depth research on the application of data visualization technology in intelligent electromechanical systems. By collecting and analyzing relevant literature, and combining with practical cases, this article explores the specific application methods and effects of data visualization technology in fault diagnosis and maintenance. Research has shown that the diagnostic accuracy of this method is between 94% -99%, and it has good fault diagnosis ability. Data visualization technology plays an important role in the fault diagnosis and maintenance of intelligent electromechanical systems. By visualizing the real-time data and fault information of the system, maintenance personnel can intuitively understand the system status and quickly locate the root cause of the fault.

Molecular dynamics simulation of mechanical strengthening properties of SiC substrate covered with multilayer graphene

A large number of practices have shown that under the coupling influence of complex working conditions and frequent reciprocating contact, the surfaces of semiconductor devices in micro/nano electromechanical systems often produce adhesive wear, which is the essential reason resulting in short durability service life and declining contact mechanical properties for microelectronics semiconductor devices. However, graphene can significantly improve the interface properties of mechanical components and electronic components due to its excellent mechanical properties, such as high carrier concentration, good thermal conductivity, and low shear. Thus, the study of mechanical strengthening properties and plastic deformation of SiC material with covered multi-layer graphene in MEMS devices will play a significant role in improving the durability service life of MEMS device, and understanding its strengthening and toughening mechanism. Therefore, this paper studies and discusses the effects of stacking type and extreme service temperature with low and high levels on the contact mechanical properties (maximum load, hardness, Young modulus, contact stiffness), micro-structure evolution, contact mass, fold morphology, and total length of dislocation. The atomic-scale mechanism of enhanced mechanical properties of SiC material with multi-layer graphene is explained. The research shows that the damage to carbon-carbon bond at the maximum indentation depth will lead graphene to lose the excellent in-plane elastic deformation capability when the graphene stacking type is AB stacking, so that the maximum load-bearing capacity of the substrate covered by three layers of graphene will drop linearly. In addition, the mechanical property of SiC material coated with three graphene layers is twice that of pure SiC substrate, and the strengthening mechanism is mainly due to the increase of wrinkle caused by the increase of multilayer graphene loading, which causes the quality of contact between the SiC substrate and the virtual indenter to decrease, thus increasing the interface contact stiffness. The increase of the active temperature will trigger off the increase of the atomic vibration frequency, which will cause the number of interface contact atoms to increase greatly, and the interface contact stiffness will weaken, and finally lead the interface contact quality to improve, This is because the mechanical properties of SiC substrate coated with multilayer graphene will decrease approximately linearly with the extreme service from low temperature to high temperature. In addition, the stress concentration in the subsurface layer of SiC substrate can induce the evolution of its micro-structure, and the increase of the number of graphene layers on the substrate can effectively reduce the stress concentration distribution in the subsurface layer of the substrate.