Induction motors are essential in industrial production, and their fault diagnosis is vital for ensuring continuous efficient equipment operation. Minimizing downtime losses optimizing maintenance costs key to maintaining smooth production enhancing economic efficiency. This paper presents a novel diagnostic approach diverse motor faults, integrating time series analysis, Transformer-based networks, multi-modal data fusion. Firstly, multiple signals such as three-phase current, vibration,...

In the fields of industrial production or safety monitoring, wireless sensor networks are often content with unreliable and time-varying channels that susceptible to interference. Consequently, ensuring both transmission reliability data accuracy has garnered substantial attention in recent years. Although multipath routing-based schemes can provide for networks, achieving high simultaneously remains challenging. To address this issue, an Energy-efficient Multipath Routing algorithm...

Abstract Background The accuracy of digital impressions for fully edentulous cases is currently insufficient routinely clinical application. To overcome the challenge, a modified scan body was introduced, which demonstrated satisfactory in vitro. aim this study to evaluate using bodies with extensional structure versus without mandible two implants beagle dogs. Methods unilateral mandibular second premolar molar were extracted four Twelve weeks later, placed. Five repeated performed an...

1. Rolling element bearings are the critical parts of every rotating machinery and their failure is one main reasons machine downtime even breakdown. The significance early detection cannot be overstated, as it plays a crucial role in maintaining proper functioning equipment, enhancing production efficiency, ensuring safety. Among them, envelope analysis most effective widely used approach, working according to principle linear filtering process signals remove undesirable components....

Abstract In addressing the problem of low prediction accuracy in remaining useful life (RUL) rolling bearings, caused by noise interference and insufficient extraction sensitive features deep learning models, this paper presents a method based on signal reconstruction dual-channel network fusion. First, issue extracting weak from bearing vibration signals, an optimized combination variational mode decomposition (VMD) Teager–Kaiser energy operator (TKEO) for is proposed. TKEO used to track...

The working condition of mechanical equipment can be reflected by vibration signals collected from it. Accurate classification these is helpful for the machinery fault diagnosis. In recent years, L1-norm regularization based sparse representation (SRC) has obtained huge success in image recognition, especially face recognition. However, investigation SRC shows that accuracy and sparsity concentration index are not high enough. this paper, a new method proposed, which L1L2-norm...

Abstract This paper presents an adaptive compensation scheme for reducing the force ripple effects in permanent magnet synchronous linear motor (PMSLM). Firstly, when velocity of a is close to zero, based on fast Fourier transform (FFT) analysis, dominant displacement periodicity can be obtained simplifying model. Next, enhance identification accuracy and guarantee real‐time performance servo system simultaneously, improved just‐in‐time learning (JITL) algorithm proposed estimate model...

Under normal circumstances, bearings generally run under variable loading conditions. such conditions, the vibration signals of bearing malfunctions are often nonstationary signals, which difficult to process effectively. In order accurately and effectively diagnose failure types damage degree load an intelligent diagnostic model based on variational mode decomposition (VMD) quantum chaotic fruit fly optimization algorithm (QCFOA) a multiclassification relevance vector machine (VRVM) is...

Efficient data dissemination protocols play a crucial role in transmitting messages among vehicles Vehicular Ad Hoc Networks (VANETs). In scenarios where the destination nodes VANETs are unknown, it becomes imperative to disseminate across as many locations possible, thereby enhancing likelihood of reaching potential destinations. While multi-hop broadcasting facilitates rapid coverage networks, often results challenges such broadcast storms, redundancy, and transmission delays. This work...

Aiming at non-stationary signals with complex components, the performance of a variational mode decomposition (VMD) algorithm is seriously affected by key parameters such as number modes K, quadratic penalty parameter α and update step τ. In order to solve this problem, an adaptive empirical (EVMD) method based on binary tree model proposed in paper, which can not only effectively problem VMD selection, but also reduce computational complexity searching optimal using intelligent optimization...

Aiming at the problems of early weak fault feature extraction bearings in rotating machinery, an improved stochastic resonance (SR) is proposed combined with advantage SR to enhance characteristic signals noise energy. Firstly, according characteristics large parameters actual signal, amplitude transform coefficient and frequency are introduced convert parameter signal into small which can be processed by SR, relationship second-order introduced. Secondly, a comprehensive evaluation index...

Abstract Fault diagnosis of asynchronous motors has become a pressing need in the metallurgical industry. Due to complex structure motors, fault types and characteristics are diverse, with strong nonlinear relationships between them, which leads difficulty diagnosis. To efficiently accurately diagnose various motor faults, we propose method based on an optimal deep bidirectional long short-term memory neural network. First, three-phase current, multidimensional vibrational signal, acoustic...

In the incipient fault vibration signals of rolling bearings, weak features are easily submerged in strong background noise and difficult to be extracted. The sparse decomposition method can perform well extraction features, but low signal-to-noise ratio (SNR) would cause excessive decomposition. To enhance maintain time–frequency structure impulses, a novel feature bearing based on signal reconstruction is proposed. Firstly, Teager energy operator (TEO) used obtain envelope impulse...

This study investigates the direct torque control strategy of permanent magnet synchronous motor with space vector modulation, on account large fluctuation and varied switching frequency classic strategy. The relationship among terminal voltages stator flux is derived through dynamic model motor. Accordingly, closed-loop feedback structure are established, where error signals regulated by proportional integral controllers to generate output voltages. Furthermore, parameters designed...

In order to extract fault impulse feature of large-scale rotating machinery from strong background noise, a sparse extraction method based on decomposition combined multiresolution generalized S transform is proposed in this paper. method, employed find the optimal atom for every iteration, which firstly takes account with discretized adjustment factors, then builds an corresponding maximum energy. The has better accuracy compared and faster searching speed orthogonal matching pursuit...

As the Vehicle to or Infrastructure communication in Vehicular Ad Hoc Network (VANET) is usually based on opportunity network, transmission delay will be high with low vehicle density far distance. result, Quality of Service requirements safety message dissemination cannot satisfied. The paper proposed a broadcast strategy VANET-cellular architecture, and it does not rely too much traffic additional deployment Road Side Unit. Meanwhile, only relay node selected from candidate subset via...

To address the problem of uneven anchor node path coverage in underwater wireless sensor networks, which leads to low localization rate and large error, a dual planning model is established. Based on model, algorithm based mobile for network proposed. The collects information by utilizing communication between nodes collaborate with each other, uses RSSI ranging multilateral complete localization. trajectory this paper overcomes collinearity localization, then uniform. Performance analysis...

As one of the key issues users' mobility management in next generation heterogeneous wireless network, vertical handover has received extensive attention academic and industrial circles. With development mobile terminals, users can simultaneously run different types applications, which have requirements on network properties. Therefore, this article proposes an adaptive weight algorithm, select most suitable as target according to type working application calculating vector user's...

The working state of machinery can be reflected by vibration signals. Accurate classification these signals is helpful for the fault diagnosis. A novel method signals, named Transform Domain Sparse Representation-based Classification (TDSRC), proposed. achieves high accuracy three steps. Firstly, time-domain including training samples and test samples, are transformed to another domain, e.g. frequency-domain, wavelet-domain etc. Then, transform coefficients combined as a dictionary sparsely...

When bearing faults occur in induction motor fed with variable frequency power, some fault related characteristic components appear the stator current. But these are often submerged by strong fundamental component of power supply during dynamic speed regulation process. In this paper, an approach based on generalized demodulation rolling diagnosis is proposed, and used outer fault. For constant accelerating operation model motor, after measuring single-phase current signal, empirical mode...