Bendductor—Transformer Steel Magnetomechanical Force Sensor

In this paper, the design and investigation of an innovative force sensor, based on the Villari effect, is presented. The sensor was built from electrical steel, in a pressductor pattern, but working in bending load mode. The results of the experimental research allowed for the evaluation of transducer’s performance, mitigation of measurement hysteresis, and optimization of its functional parameters. Several issues have been examined, among them the selection of supply and measured signals, the measured values’ impact on measurement hysteresis, harmonic analysis, and the selection of proper current waveforms and frequencies. The proposed sensor is robust, made from inexpensive materials, and has high sensitivity, as compared to other magnetoelastic sensors. It has much higher stress sensitivity than other magnetoelastic sensors due to deformation mode. Based on the tests, its measuring range can be defined as 0.5–5 N with a near-linear characteristic, SNR of 46 dB, and 0.11 N uncertainty.

Multi-parametric Dynamic Analysis of a Rolling Bearings System

A method for calculating amplitudes and constructing frequency characteristics of forced and self-excited vibrations of a rotor-fluid-foundation system on rolling bearings with a non-linear characteristic based on the method of complex amplitudes and harmonic balance has been developed. Non-linear equations of motion of the rotor-fluid-foundation system are derived, and analytical methods of their solution are presented. Frequencies of fundamental and ultra-harmonic resonances are determined. The intervals between self-oscillation frequencies are estimated. The dependence of amplitudes on the amount of fluid in the rotor cavity, the mass of the foundation, linear imbalance, the value of the stiffness coefficient, and the damping coefficient is shown.

A discrete manufacturing SCOS framework based on functional interval parameters and fuzzy QoS attributes using moving window FPA

Manufacturing service composition and optimal selection (SCOS) is a key technology that improves resource utilization and reduces the cost in discrete manufacturing. However, the lack of evaluation of the service composition function and the unconformity of the actual composition vague characteristics, resulting in the incomplete evaluation of the service composition. Additionally, various optimization and selection algorithms have defects of premature convergence and low efficiency. At the same time, the fitness value distribution of the service composition has a non-linear characteristic. In this article, a framework called discrete manufacturing SCOS (DMSCOS) is proposed to overcome these issues. DMSCOS uses the functional interval parameter and fuzzy QoS attribute aware evaluation model (FIPFQA) to achieve composition evaluation and introduces a moving window flower pollination algorithm (MWFPA) to achieve optimization and selection for the non-linear characteristic population. Experiments show that DMSCOS has good performance for optimization and selection. The FIPFQA has a good effect on service composition evaluation. Furthermore, compared with two other extended algorithms, the proposed MWFPA performs better when addressing the optimal and selection problem.

Detecting and Evaluating Defects in Beams by Correlation Coefficients

This research proposes a correlation coefficient for detecting and evaluating defects in beams, which brings about a positive outcome in terms of accuracy and efficiency. This parameter surpasses other parameters, such as natural frequency and damping coefficient, thanks to its sensitivity to structural changes. Our results show that although the damping coefficient had more variation than the natural frequency value in the same experiment, its changes were insufficient and unstable at different levels of defects. In addition, the proposed correlation coefficient parameter has a linear characteristic and always changes significantly according to increasing levels of defects. The results outweigh damping coefficient and natural frequency values. Furthermore, this value is always sensitive to measurement channels, which could be an important factor in locating defects in beams. The testing index is statistically evaluated by a normal distribution of the amplitude value of vibration measurement signals. Changes and shifts in this distribution are the basis for evaluating beam defects. Thus, the suggested parameter is a reliable alternative for assessing the defects of a structure.

Detection of tower bolt looseness and its influence of wind level

Taking the wind turbine tower as the research object, based on the finite element software, a simplified beam-shell hybrid element model was first established; through the simulation, the phase difference between the loose position and the unloose position was compared to verify the feasibility of the phase difference detection method; Secondly, the influence of the number of loose bolts, the position of loosening, and the magnitude of the wind force on the phase of the flange bolt connection structure and the response characteristics of the system are analyzed. The research results show that the number of loose bolts, the position of loosening, and the magnitude of the wind have certain effects on the phase difference and response characteristics of the flange. With the increase in the number of loose bolts, the connection stiffness of the bolt connection continues to decrease. The linear characteristic is enhanced; the closer the loosening is to the excitation force loading position, the greater the detected phase difference; as the wind increases, the phase of the upper flange of the tower changes, and the phase of the lower flange remains unchanged, and the wind is on the flange The disc connection strength has little effect.

Sliding Bifurcations in the Memristive Murali–Lakshmanan–Chua Circuit and the Memristive Driven Chua Oscillator

In this paper, we report the occurrence of sliding bifurcations admitted by the memristive Murali–Lakshmanan–Chua circuit [Ishaq & Lakshmanan, 2013] and the memristive driven Chua oscillator [Ishaq et al., 2011]. Both of these circuits have a flux-controlled active memristor designed by the authors in 2011, as their nonlinear element. The three-segment piecewise-linear characteristic of this memristor bestows on the circuits two discontinuity boundaries, dividing their phase spaces into three subregions. For proper choice of parameters, these circuits take on a degree of smoothness equal to one at each of their two discontinuities, thereby causing them to behave as Filippov systems. Sliding bifurcations, which are characteristic of Filippov systems, arise when the periodic orbits in each of the subregions, interact with the discontinuity boundaries, giving rise to many interesting dynamical phenomena. The numerical simulations are carried out after incorporating proper zero time discontinuity mapping (ZDM) corrections. These are found to agree well with the experimental observations which we report here appropriately.

Modeling and Simulation of a Metal Oxide Lightning Surge Arrester for 132kV Overhead Transmission Lines

This paper demonstrated the design of a Metal Oxide Surge Arrester for a 132 kV system with a rated voltage of 120 kV according to specifications. The study model was chosen to be Pinceti model which is a derivation of the IEEE standard model of Lightning arrester design. The design specifications for the lab tests on 120kV rated arrester for ZnO material were obtained from the catalogue of Ohio Brass Pvt. Ltd. The parameters for the lumped components were derived from the manufacturer’s data sheet while the non-linear characteristic was derived from curve fitting based on the Pinceti provided curves in literature, using Matlab Curve Fitting Tool. The design was simulated on EMTP-RV commercial software and the results before optimization as well as after optimization are presented. A cross comparison with the manufacturers data results in 1.113% relative error, which is in competition with similar designs for different rated and system voltages in literature. The study presents an improved model of a metal oxide arrester for 132kV system, with its lumped and exponential parameters presented in detail.

A Non-Linear Temperature Compensation Model for Improving the Measurement Accuracy of an Inductive Proximity Sensor and Its Application-Specific Integrated Circuit Implementation

The non-linear characteristic of a non-contacting Inductive Proximity Sensor (IPS) with the temperature affects the computation accuracy when measuring the target distance in real time. The linear model based method for distance estimation shows a large deviation at a low temperature. Accordingly, this paper presents a non-linear measurement model, which computes the target distance accurately in real time within a wide temperature range from −55 °C to 125 °C. By revisiting the temperature effect on the IPS system, this paper considers the non-linear characteristic of the IPS measurement system due to the change of temperature. The proposed model adopts a non-linear polynomial algorithm rather than the simple linear Look-Up Table (LUT) method, which provides more accurate distance estimation compared to the previous work. The introduced model is fabricated in a 0.18 μm Complementary Metal Oxide Semiconductor (CMOS) process and packaged in a CQFN40. For the most commonly used sensing distance of 4 mm, the computed distance deviation of the Application-Specific Integrated Circuit (ASIC) chips falls within the range of [−0.2,0.2] mm. According to the test results of the ASIC chips, this non-linear temperature compensation model successfully achieves real-time and high-accuracy computation within a wide temperature range with low hardware resource consumption.