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The safe operation of the metro power transformer directly relates to the safety and efficiency of the entire metro system. Through voiceprint technology, the sounds emitted by the transformer can be monitored in real-time, thereby achieving real-time monitoring of the transformer’s operational status. However, the environment surrounding power transformers is filled with various interfering sounds that intertwine with both the normal operational voiceprints and faulty voiceprints of the transformer, severely impacting the accuracy and reliability of voiceprint identification. Therefore, effective preprocessing steps are required to identify and separate the sound signals of transformer operation, which is a prerequisite for subsequent analysis.

This paper proposes an Adaptive Threshold Repeating Pattern Extraction Technique (REPET) algorithm to separate and denoise the transformer operation sound signals. By analyzing the Short-Time Fourier Transform (STFT) amplitude spectrum, the algorithm identifies and utilizes the repeating periodic structures within the signal to automatically adjust the threshold, effectively distinguishing and extracting stable background signals from transient foreground events. The REPET algorithm first calculates the autocorrelation matrix of the signal to determine the repeating period, then constructs a repeating segment model. Through comparison with the amplitude spectrum of the original signal, repeating patterns are extracted and a soft time-frequency mask is generated.

After adaptive thresholding processing, the target signal is separated. Experiments conducted on mixed sounds to separate background sounds from foreground sounds using this algorithm and comparing the results with those obtained using the FastICA algorithm demonstrate that the Adaptive Threshold REPET method achieves good separation effects.

A REPET method with adaptive threshold is proposed, which adopts the dynamic threshold adjustment mechanism, adaptively calculates the threshold for blind source separation and improves the adaptability and robustness of the algorithm to the statistical characteristics of the signal. It also lays the foundation for transformer fault detection based on acoustic fingerprinting.

Adolescents being in a stage of growth need good sleep, but, today, they suffer from sleep deprivation due to such extrinsic factor as a smartphone which they enjoy spending time using the device. However, the effects of smartphone output power (SOP) on the duration of good sleep remains unclear. The purpose of this paper is to investigate the correlation of the SOP and sleep loss in high school students.

The time-series study was conducted among 145 high school students in Chiang Mai Province who completed a sleep diary which applied by the Pittsburg Sleep Quality Index. The SOP was corrected by a smartphone application and transmitted by e-mail to a researcher every day. The completed data set contains 12,969 entries. Headache, anxiety and depression were also assessed. Data were analyzed using the generalized estimating equation adjusted for demographic data, smartphone use and other factors.

Most of the study subjects are female, 17.4 years old on average. The prevalence of sleep loss (<8 h) was 52.9 percent with averagely 7.4 ±1.7 h of sleep duration and poor sleep at 32.1 percent. Anxiety, depression, headache had relationships with sleep loss. The daily dose, evening and nocturnal SOP in the range of ≥ 2.00 × 10^‒5 mW had stronger relationships with sleep loss than their effects in the range of ≤ 1.79 × 10^‒5 mW (OR_adj1.32; 95% CI: 1.26–1.76, OR_adj1.34; 95% CI: 1.07–1.17 and OR_adj1.41; 95% CI: 1.07–1.17, respectively). Meanwhile, morning Lag_2 and daytime Lag_1 in the range of ≥ 2.00 × 10^‒5 mW appeared to have a strong relationship with sleep loss (OR_adj1.60; 95% CI: 1.26–1.76, OR_adj1.36; 95% CI: 1.07–1.17). The relationship between Lag_4 daily dose and sleep loss took the form of a reverse dose-response.

Sleep loss in adolescents has an increasing trend of prevalence and has been found to be correlated with the highest SOP group (≥ 2.00 × 10^‒5 mW range). These results confirmed that increased and longer smartphone use result in reduced sleep time. This causes them to be exposed to smartphone electromagnetic radiation and smartphone screen lighting. This disturbs brain waves and nervous system controlling sleep balance mechanisms. The findings recommended parents setting time and boundaries around technology use at home to reduce contact with electromagnetic radiation and smartphone screen lighting, thereby increasing sleeping time in order to create good sleep quality.

Nocturnal headaches among adolescents were reported to be increased with the development of modern technology. The purpose of this paper is to investigate the smartphone electromagnetic radiation related to nocturnal headaches among high school students.

The time series study of all 12,969 records from 145 high school students Chiang Mai Province was selected from the population in the first phase by setting criteria. The samples completed a headache diary utilizing a smartphone application. The smartphone output power (SOP) was measured and recorded by the smartphone application and transmitted by e-mail to a researcher. The smartphone use, sleep quality, anxiety and depression also were assessed. Data were analyzed using Generalized Estimating Equation adjusting for demographic data, smartphone use, and sleep quality and otherwise.

The resulted showed the prevalence of repeated headaches to be 13.4 percent, nocturnal headache only 5.3 percent and the strongest effect of day time SOP at a 1.80–1.99×10⁻⁵ mW range on nocturnal headaches (OR_adj5.18; 95% CI: 3.44–7.81). Meanwhile, Lag_6 of daily SOP exposure produced a nocturnal headache effect in a reverse dose-response manner. Furthermore, the nocturnal headache also had the strongest association with age, internet use and device brand (OR_adj2.33; 95% CI: 1.08–5.05, OR_adj2.14; 95% CI: 1.07–4.2 and OR_adj1.68; 95% CI: 1.1–2.4).

The electromagnetic radiation from a smartphone is the environmental variables influences on headache. The results suggested that there should be limited times for smartphone use and older age to start using a smartphone to prevent headache attacks at night.

This paper aims to design an active shock absorber scheme for use in conjunction with a passive shock absorber to suppress the horizontal vibration of elevator cars in a smaller range and shorter time. The developed active shock absorber will also improve the safety and comfort of passengers driving in ultra-high-speed elevators.

A six-degree of freedom dynamic model is established according to the position and condition of the car. Then the active shock absorber and disturbance compensation-based adaptive control scheme are designed and simulated in MATLAB/Simulink. The results are analysed and compared with the traditional shock absorber.

The results show that, compared with traditional spring-based passive damping systems, the designed active shock absorber can reduce vibration displacement by 60%, peak acceleration by 50% and oscillation time by 2/3 and is more robust to different spring stiffness, damping coefficient and load.

The developed active shock absorber and its control algorithm can significantly reduce vibration amplitude and converged time. It can also adjust the damping strength according to the actual load of the elevator car, which is more suitable for high-speed elevators.

Electromagnetic interference (EMI) on communication systems of unban rail transit can hardly be clarified because of complicated factors around railways. This paper aims to target this issue and extend experimental and theoretical analysis.

This paper take the Nanjing Dashengguan Bridge as an example, because it carries the most tracks in the world and bears three kinds of trains running through, providing a perfect complex environment. First, it investigates the three communication systems, terrestrial trunked radio, communications-based train control (CBTC) and passenger information system (PIS) that Nanjing Metro uses, and select appropriate devices accordingly. Second, it establishes a system level platform and conduct three tests to analyze their respective operating principles and performance difference under common electromagnetic environments. Third, it adopts theoretical formula to verify test results.

The experiment results and theoretical analysis mutually corroborate each other and present practical recommendations: an 8 m or more distance between two tracks will ensure no obvious EMI created by a passing train on communication systems; two certain communication systems should not share the same frequency band; interference level is more related to field strength than weathers and building materials; and CBTC DSSS waveguide mode as well as PIS LTE mode are preferred.

This research also provides a practical method of investigating EMI for other complex situations.

Modern meat processing requires automation and robotisation to remain sustainable and adapt to future challenges, including those brought by global infection events. Automation of all or many processes is seen as the way forward, with robots performing various tasks instead of people. Meat cutting is one of these tasks. Smart novel solutions, including smart knives, are required, with the smart knife being able to analyse and predict the meat it cuts. This paper aims to review technologies with the potential to be used as a so-called “smart knife” The criteria for a smart knife are also defined.

This paper reviews various technologies that can be used, either alone or in combination, for developing a future smart knife for robotic meat cutting, with possibilities for their integration into automatic meat processing. Optical methods, Near Infra-Red spectroscopy, electrical impedance spectroscopy, force sensing and electromagnetic wave-based sensing approaches are assessed against the defined criteria for a smart knife.

Optical methods are well established for meat quality and composition characterisation but lack speed and robustness for real-time use as part of a cutting tool. Combining these methods with artificial intelligence (AI) could improve the performance. Methods, such as electrical impedance measurements and rapid evaporative ionisation mass spectrometry, are invasive and not suitable in meat processing since they damage the meat. One attractive option is using athermal electromagnetic waves, although no commercially developed solutions exist that are readily adaptable to produce a smart knife with proven functionality, robustness or reliability.

This paper critically reviews and assesses a range of sensing technologies with very specific requirements: to be compatible with robotic assisted cutting in the meat industry. The concept of a smart knife that can benefit from these technologies to provide a real-time “feeling feedback” to the robot is at the centre of the discussion.

The purpose of this paper is to exploit a database of pre-existing designs to accelerate parametric optimization of antenna structures is investigated.

The usefulness of pre-existing designs for rapid design of antennas is investigated. The proposed approach exploits the database existing antenna base designs to determine a good starting point for structure optimization and its response sensitivities. The considered method is suitable for handling computationally expensive models, which are evaluated using full-wave electromagnetic (EM) simulations. Numerical case studies are provided demonstrating the feasibility of the framework for the design of real-world structures.

The use of pre-existing designs enables rapid identification of a good starting point for antenna optimization and speeds-up estimation of the structure response sensitivities. The base designs can be arranged into subsets (simplexes) in the objective space and used to represent the target vector, i.e. the starting point for structure design. The base closest base point w.r.t. the initial design can be used to initialize Jacobian for local optimization. Moreover, local optimization costs can be reduced through the use of Broyden formula for Jacobian updates in consecutive iterations.

The study investigates the possibility of reusing pre-existing designs for the acceleration of antenna optimization. The proposed technique enables the identification of a good starting point and reduces the number of expensive EM simulations required to obtain the final design.

The proposed design framework proved to be useful for the identification of good initial design and rapid optimization of modern antennas. Identification of the starting point for the design of such structures is extremely challenging when using conventional methods involving parametric studies or repetitive local optimizations. The presented methodology proved to be a useful design and geometry scaling tool when previously obtained designs are available for the same antenna structure.

The rostrum of a paddlefish provides hydrodynamic stability during feeding process in addition to detect the food using receptors that are randomly distributed in the rostrum. The exterior tissue of the rostrum covers the cartilage that surrounds the bones forming interlocking star shaped bones.

The aim of this work is to assess the mechanical behavior of four finite element models varying the type of formulation as follows: linear-reduced integration, linear-full integration, quadratic-reduced integration and quadratic-full integration. The paper also presents the load transfer mechanisms of the bone structure of the rostrum. The base material used in the study was steel with elastic–plastic behavior as a homogeneous material before applying materials properties that represents the behavior of bones, cartilages and tissues.

Conclusions are based on comparison among the four models. There is no significant difference between integration orders for similar type of elements. Quadratic-reduced integration formulation resulted in lower structural stiffness compared with linear formulation as seen by higher displacements and stresses than using linearly formulated elements. It is concluded that second-order elements with reduced integration are the alternative to analyze biological structures as they can better adapt to the complex natural contours and can model accurately stress concentrations and distributions without over stiffening their general response.

The use of advanced computational mechanics techniques to analyze the complex geometry and components of the paddlefish rostrum provides a viable avenue to gain fundamental understanding of the proper finite element formulation needed to successfully obtain the system behavior and hot spot locations.

Small highly saturated interior permanent magnet- synchronous machines (IPMSMs) show a very nonlinear behaviour. Such machines are mostly controlled with a closed-loop cascade control, which is based on a d-q two-axis dynamic model with constant concentrated parameters to calculate the control parameters. This paper aims to present the identification of a complete current- and rotor position-dependent d-q dynamic model, which is derived by using a finite element method (FEM) simulation. The machine’s constant parameters are determined for an operation on the maximum torque per ampere (MTPA) curve. The obtained MTPA control performance was evaluated on the complete FEM-based nonlinear d-q model.

A FEM model was used to determine the nonlinear properties of the complete d-q dynamic model of the IPMSM. Furthermore, a fitting procedure based on the nonlinear MTPA curve is proposed to determine adequate constant parameters for MTPA operation of the IPMSM.

The current-dependent d-q dynamic model of the machine models the relevant dynamic behaviour of the complete current- and rotor position-dependent FEM-based d-q dynamic model. The most adequate control response was achieved while using the constant parameters fitted to the nonlinear MTPA curve by using the proposed method.

The effect on the motor’s steady-state and dynamic behaviour of differently complex d-q dynamic models was evaluated. A workflow to obtain constant set of parameters for the decoupled operation in the MTPA region was developed and their effect on the control response was analysed.

A novel framework for expedited antenna optimization with an iterative prediction-correction scheme is proposed. The methodology is comprehensively validated using three real-world antenna structures: narrow-band, dual-band and wideband, optimized under various design scenarios.

The keystone of the proposed approach is to reuse designs pre-optimized for various sets of performance specifications and to encode them into metamodels that render good initial designs, as well as an initial estimate of the antenna response sensitivities. Subsequent design refinement is realized using an iterative prediction-correction loop accommodating the discrepancies between the actual and target design specifications.

The presented framework is capable of yielding optimized antenna designs at the cost of just a few full-wave electromagnetic simulations. The practical importance of the iterative correction procedure has been corroborated by benchmarking against gradient-only refinement. It has been found that the incorporation of problem-specific knowledge into the optimization framework greatly facilitates parameter adjustment and improves its reliability.

The proposed approach can be a viable tool for antenna optimization whenever a certain number of previously obtained designs are available or the designer finds the initial effort of their gathering justifiable by intended re-use of the procedure. The future work will incorporate response features technology for improving the accuracy of the initial approximation of antenna response sensitivities.

The proposed optimization framework has been proved to be a viable tool for cost-efficient and reliable antenna optimization. To the knowledge, this approach to antenna optimization goes beyond the capabilities of available methods, especially in terms of efficient utilization of the existing knowledge, thus enabling reliable parameter tuning over broad ranges of both operating conditions and material parameters of the structure of interest.