Search Results (14)

Traditional time-frequency diagnostics for high-speed bearings face an entrenched trade-off between resolution and real-time feasibility. We present a fast Dual-Phase Short-Time Root-MUSIC pipeline that exploits Hankel structure via FFT-accelerated Lanczos bidiagonalization and Sliding-window Singular Value Decomposition to deliver sub-Hz super-resolution under millisecond budgets. Validated on the Politecnico di Torino aerospace dataset (seven fault classes, three severities), fDSTrM detects 150 μm inner-race and rolling-element defects with 98% and 95% probability, respectively, at signal-to-noise ratio down to −3 dB (78% detection), while Short-Time Fourier Transform and Wavelet Packet Decomposition fail under identical settings. Against classical Root-MUSIC, the approach sustains approximately 200 times speedup with less than ${10}^{-11}$ relative frequency error in offline scaling, and achieves 1.85 milliseconds per 4096-sample frame on embedded-class hardware in streaming tests. Subspace order pre-estimation with adaptive correction preserves closely spaced components; Kalman tracking formalizes uncertainty and yields 95% confidence bands. The resulting early warning margin extends maintenance lead-time by 24–72 h under industrial interferences (Gaussian, impulsive, and Variable Frequency Drive harmonics), enabling field-deployable super-resolution previously constrained to offline analysis. Full article

To address the challenges of low diagnostic accuracy arising from the non-stationary and nonlinear time-varying characteristics of acoustic signals in rolling bearing fault diagnosis, as well as their susceptibility to noise interference, this paper proposes a fault diagnosis method based on a Weighted Average Algorithm–Feature Mode Decomposition (WAA-FMD) and a Local–Global Adaptive Multi-scale Attention Mechanism (LGAF)–Swin Transformer. First, the WAA is utilized to optimize the key parameters of FMD, thereby enhancing its signal decomposition performance while minimizing noise interference. Next, a bilateral expansion strategy is implemented to extend both the time window and frequency band of the signal, which improves the temporal locality and frequency globality of the time–frequency diagram, significantly enhancing the ability to capture signal features. Ultimately, the introduction of depthwise separable convolution optimizes the receptive field and improves the computational efficiency of shallow networks. When combined with the Swin Transformer, which incorporates LGAF and adaptive feature selection modules, the model further enhances its perceptual capabilities and feature extraction accuracy through dynamic kernel adjustment and deep feature aggregation strategies. The experimental results indicate that the signal denoising performance of WAA-FMD significantly outperforms traditional denoising techniques. In the KAIST dataset (NSK 6205: inner raceway fault and outer raceway fault) and the experimental dataset (FAG 30205: inner raceway fault, outer raceway fault, and rolling element fault), the accuracies of the proposed model reach 100% and 98.62%, respectively, both exceeding that of other deep learning models. In summary, the proposed method demonstrates substantial advantages in noise reduction performance and fault diagnosis accuracy, providing valuable theoretical insights for practical applications. Full article

In the context of green building development, the lighting design of campus living rooms in hot summer and cold winter areas faces the dual challenges of glare control in summer and insufficient daylight in winter. Based on BIM technology, this study uses Revit 2016 modeling and the HYBPA 2024 performance analysis platform to simulate and optimize the daylighting performance of the campus activity center of Hunan City College in multiple rounds of iterations. It is found that the traditional single large-area external window design leads to uneven lighting in 70% of the area, and the average value of the lighting coefficient is only 2.1%, which is lower than the national standard requirement of 3.3%. Through the introduction of the hybrid system of “side lighting + top light guide”, combined with adjustable inner louver shading, the optimized average value of the lighting coefficient is increased to 4.8%, the uniformity of indoor illuminance is increased from 0.35 to 0.68, the proportion of annual standard sunshine hours (≥300 lx) reaches 68.7%, and the energy consumption of the artificial lighting is reduced by 27.3%. Dynamic simulation shows that the uncomfortable glare index at noon on the summer solstice is reduced from 30.2 to 22.7, which meets the visual comfort requirements. The study confirms that the BIM-driven “static-dynamic” simulation coupling method can effectively address climate adaptability issues. However, it has limitations such as insufficient integration with international healthy building standards, insufficient accuracy of meteorological data, and simplification of indoor dynamic shading factors. Future research can focus on improving meteorological data accuracy, incorporating indoor dynamic factors, and exploring intelligent daylighting systems to deepen and expand the method, promote the integration of cross-standard evaluation systems, and provide a technical pathway for healthy lighting environment design in summer-hot and winter-cold regions. Full article

Weighted belief propagation (WBP) for the decoding of linear block codes is considered. In WBP, the Tanner graph of the code is unrolled with respect to the iterations of the belief propagation decoder. Then, weights are assigned to the edges of the resulting recurrent network and optimized offline using a training dataset. The main contribution of this paper is an adaptive WBP where the weights of the decoder are determined for each received word. Two variants of this decoder are investigated. In the parallel WBP decoders, the weights take values in a discrete set. A number of WBP decoders are run in parallel to search for the best sequence- of weights in real time. In the two-stage decoder, a small neural network is used to dynamically determine the weights of the WBP decoder for each received word. The proposed adaptive decoders demonstrate significant improvements over the static counterparts in two applications. In the first application, Bose–Chaudhuri–Hocquenghem, polar and quasi-cyclic low-density parity-check (QC-LDPC) codes are used over an additive white Gaussian noise channel. The results indicate that the adaptive WBP achieves bit error rates (BERs) up to an order of magnitude less than the BERs of the static WBP at about the same decoding complexity, depending on the code, its rate, and the signal-to-noise ratio. The second application is a concatenated code designed for a long-haul nonlinear optical fiber channel where the inner code is a QC-LDPC code and the outer code is a spatially coupled LDPC code. In this case, the inner code is decoded using an adaptive WBP, while the outer code is decoded using the sliding window decoder and static belief propagation. The results show that the adaptive WBP provides a coding gain of 0.8 dB compared to the neural normalized min-sum decoder, with about the same computational complexity and decoding latency. Full article

Building-integrated photovoltaic (BIPV) windows present a viable path towards carbon neutrality in the building sector. However, conventional BIPV windows, such as semi-transparent photovoltaic (STPV) glazings, still suffer from inadequate thermal insulation, which limits their effectiveness across different climate conditions. To address this issue, the cadmium telluride-based vacuum PV glazing has been developed to enhance the thermal performance of BIPV applications. To fully understand the complex thermal behaviour under real-world operational scenarios, this study introduces a one-dimensional transient heat transfer model that can efficiently capture the time-dependent thermal dynamics of this novel glazing system. Based on the numerical solutions using the explicit finite difference method (FDM), the temperature profile of the vacuum PV glazing can be obtained dynamically. Consequently, the heat gain of the semi-transparent vacuum PV glazing can be calculated under time-varying outdoor and indoor conditions. The validated heat transfer model was applied under four different scenarios, viz. summer daytime, summer nighttime, winter daytime, and winter nighttime, to provide a detailed analysis of the dynamic thermal behaviour, including the temperature variation and the energy flow. The dynamic thermal characteristics of the vacuum PV glazing calculated by the transient heat transfer model demonstrate its excellent thermal insulation and solar control capabilities. Moreover, the thermal performance of vacuum PV glazing was compared with a standard double-pane window under various weather conditions of a typical summer day and a typical winter day. The results indicate that the vacuum PV glazing can effectively minimise both heat gain and heat loss. The fluctuation of the inner surface temperature can be controlled within a limited range away from the set point of the indoor room temperature. Therefore, the vacuum PV glazing contributes to stabilising the temperature of the indoor environment despite the fluctuating solar radiation and periodic outdoor temperature. It is suggested that the vacuum PV glazing has the potential to enhance the climate adaptability of BIPV windows under different climate backgrounds. Full article

The study of high-pressure sound velocity is an important part of shock wave physics, and the study of ultra-high pressure sound velocity of iron is of great significance to many research fields such as geophysics, solid state physics, and crystallography. At present, the measurement of sound velocity is usually carried out by the catch-up sparse wave method and windowed VISAR technology, which is complex in structure and not highly adaptable. In particular, for the ultra-high pressure sonic velocity measurement of metals, it is limited by the loading platform and window materials and cannot realize the high temperature and high-pressure environment of the earth’s inner core. In this paper, the sound velocity measurement of iron under high temperature and high-pressure environment (78 GPa) is realized based on the two-stage light gas cannon experimental platform. The side-side sparse wave method was used to establish a coupling model of high-spatially resolved optical group and fiber bundle. A multiplexed all-fiber laser interferometry velocity measurement system (DISAR) was built, and the spatial resolution was better than 20 μm. In this paper, we will provide a feasible route for a method for measuring the high spatiotemporal resolution velocity. Full article

The cooling performance of the energy-saving water spray window cooling system under summer conditions in Nanning city in southern China, is experimentally examined in this study. By constructing two identical test rooms for comparison, in the experiment we analyzed the effects of water temperature (22 °C, 26 °C, 30 °C), spray frequency (8, 10, 12, 15 min intervals), glass structure (single-layer, double-layer, triple-layer), air conditioning temperature (26 °C, 27 °C, 28 °C, 29 °C), and outer lamination thickness (30, 50, 100, 200 mm) on the cooling effect of windows, aiming to determine the optimal operating conditions. The experimental outcomes demonstrate that the appropriate operating mode for the water spray window system involves using the coldest water source (22 °C), with a spray interval of 8 min, a three-layer air cavity sprayed glass construction, an air cavity thickness set at 100 mm, and the best air conditioning temperature (26 °C). The study found that the water spray system can reduce the outer glass surface temperature of the window by 6 °C and the inner surface temperature by 2 °C. Moreover, the more glass layers and the thicker the lamination, the higher the energy saving rate; with a maximum energy saving rate of 35.19%. The water spray window has good adaptability and significant energy-saving effects in Southeast Asia. By scientifically selecting energy-saving glass types and fine-tuning operating modes, it is expected that efficient building energy conservation in hot climates can be achieved. Full article

This study focused on the efficacy of employing a pulsed fiber laser in the curved cutting of thin, non-oriented electrical steel sheets. Experiments were conducted in paraffinic oil by adjusting the input process parameters, including laser power, pulse frequency, cutting speed, and curvature radius. The multiple output quality metrics included kerf width, inner and outer heat-affected zones, and re-welded portions. Analyses of the Random Forest Method and Response Surface Method indicated that laser pulse frequency was the most important variable affecting the cut quality, followed by laser power, curvature radius, and cutting speed. To improve cut quality, an innovative artificial intelligence (AI) approach incorporating a deep neural network (DNN) model and a modified equilibrium optimizer (M-EO) was proposed. Initially, the DNN model established correlations between input parameters and cut quality aspects, followed by M-EO pinpointing optimal cut qualities. Such an approach successfully identified an optimal set of laser process parameters, even beyond the specified process window from the initial experiments on curved cuts, resulting in significant enhancements confirmed by validation experiments. A comparative analysis showcased the developed models’ superior performance over prior studies. Notably, while the models were initially developed based on the results from curved cuts, they proved adaptable and capable of yielding comparable outcomes for straight cuts as well. Full article

This research presents a comparative study of different bio-sourced and recycled insulation materials and their impact on energy consumption of office buildings located in Ouagadougou, a city with a dry hot climate. A thorough assessment of the country’s meteorological and urban development data from 2004 to 2018 was conducted for climatic data. EnergyPlus was used for thermal comfort based on the American Society of Heating, Refrigerating, and Air-conditioning Engineers Standard (ASHRAE) 55 adaptive comfort model and energy analysis by calculating and comparing the yearly energy consumption, heat transfer through the building envelope, and discomfort degree hours. A four-story “H”-shaped office building made of cement blocks with a fixed north–south orientation and a 30% window-to-wall ratio served as the base case for this study to perform two rounds of multiple simulations and evaluate the most effective insulation material. First, exterior walls were insulated, and then the roof and inner floors were insulated using the best material from the first round. The findings confirmed hemp wool as the best performing bio-sourced insulation material, which reduces by 25.8% and 17.7% the annual cooling energy demand at 114,495 kWh and the annual energy consumption at 203,598 kWh, respectively, contributing to saving up to 43,852 kWh in annual energy consumption. Hemp wool impacted wall, roof, and internal floor heat transfer by reducing them by 90.86% at 12,583 kWh, 85.1% at 6666 kWh, and 88.1% at −2664 kWh, respectively, while the discomfort degree hours were reduced by 17.6% at 9720.12. The outcomes provide patterns, explanations, and inferences that may be generalized to other projects in Burkina Faso, especially, and sub-Saharan African countries, in general, where most buildings are not well insulated. The availability of these bio-based and recycled insulation materials may also serve as proof to foster a circular economy in the Burkina Faso construction industry. Full article

Saving energy while maintaining a high-quality internal environment is an increasingly important scientific and technological challenge in the building sector. This paper presents the results from a long-term study on thermal comfort in a passive house situated in the south of Poland. The building was constructed in 2010 with the use of prefabricated, lightweight technology. The main energy source is a ground source heat pump which powers the floor heating and DHW. The building is also equipped with a mechanical ventilation system with heat recovery and a ground source heat exchanger. A lightweight building structure which has active systems with limited capabilities (especially for cooling) is a combination which increases the difficulty of maintaining a proper inner environmental condition. Extensive experimental investigations on hygrothermal performance and energy use have been carried out in the building for several years. The measurement results, such as inner air temperature and humidity, as well as the inner surface temperature of partitions, could be directly used to determine basic thermal comfort indicators, including PMV and PPD. Any missing data that has not been directly measured, such as the surface temperature of the windows, floors, and some of the other elements of the building envelope, have been calculated using WUFI^®PLUS software and validated with the available measurements. These results are not final; the full measurement of thermal comfort as an applied methodology did not consider human adaptation and assumed constant clothing insulation. Nevertheless, in general, the results show good thermal comfort conditions inside the building under research conditions. This was also confirmed via a survey of the inhabitants: 2 adults and 3 children. Full article

Low rank and sparse representation (LRSR) with dual-dictionaries-based methods for detecting anomalies in hyperspectral images (HSIs) are proven to be effective. However, the potential anomaly dictionary is vulnerable to being contaminated by the background pixels in the above methods, and this limits the effect of hyperspectral anomaly detection (HAD). In this paper, a dual dictionaries construction method via two-stage complementary decision (DDC–TSCD) for HAD is proposed. In the first stage, an adaptive inner window–based saliency detection was proposed to yield a coarse binary map, acting as the indicator to select pure background pixels. For the second stage, a background estimation network was designed to generate a fine binary map. Finally, the coarse binary map and fine binary map worked together to construct a pure background dictionary and potential anomaly dictionary in the guidance of the superpixels derived from the first stage. The experiments conducted on public datasets (i.e., HYDICE, Pavia, Los Angeles, San Diego-I, San Diego-II and Texas Coast) demonstrate that DDC–TSCD achieves satisfactory AUC values, which are separately 0.9991, 0.9951, 0.9968, 0.9923, 0.9986 and 0.9969, as compared to four typical methods and three state-of-the-art methods. Full article

Directed by the feminist filmmaker Niki Caro, Disney’s 2020 live-action remake of Mulan (1998) strove to be a more gender progressive, culturally appropriate, and internationally successful adaptation of the Chinese legend of Mulan than the animated original. Contrary to the film’s intended effect, however, it was a critical and financial letdown. The film was criticized for a wide range of issues, including making unpopular changes to the animated original, misrepresenting Chinese culture and history, perpetuating Orientalist stereotypes, and demonizing Inner Asian steppe nomads. In addition, the film also faced boycott calls amid political controversies surrounding China. It received exceptionally low audience ratings in both the US and China, grossing a total well under its estimated budget. This article argues that Mulan (2020) is not, as many believe, just another Disney film suffering from simple artistic inability, cultural insensitivity, or political injustice, but a window into the tension-ridden intersectionality of the gender, sexual, racial, cultural, and political issues that shape the production and reception of today’s cross-cultural films. It discusses three major problems, the Disney problem, the gender problem, and the cultural problem, that Mulan (2020) tackled with respectful efforts in Caro’s feminist filmmaking pattern. The film made significant compromises between its goals of cultural appropriateness, progressive feminism, and monetary success. Although it eventually failed to satisfactorily resolve these at times conflicting missions, it still achieved important progress in addressing some serious gender and cultural problems in Mulan’s contemporary intertextual metamorphosis, especially those introduced by the Disney animation. By revealing Mulan (2020)’s value and defects, this article intends to flesh out some real-world challenges that feminist movements must overcome to effectively transmit messages and bring about changes at the transcultural level in the arts. Full article

Achromatopsia (ACHM) is an inherited autosomal recessive disease lacking cone photoreceptors functions. In this study, we characterize the time-frequency representation of the full-field electroretinogram (ffERG) component oscillatory potentials (OPs), to investigate the connections between photoreceptors and the inner retinal network using ACHM as a model. Time-frequency characterization of OPs was extracted from 52 controls and 41 achromat individuals. The stimulation via ffERG was delivered under dark-adaptation (DA, 3.0 and 10.0 cd·s·m⁻²) to assess mixed rod-cone responses. The ffERG signal was subsequently analyzed using a continuous complex Morlet transform. Time-frequency maps of both DA conditions show the characterization of OPs, disclosing in both groups two distinct time-frequency windows (~70–100 Hz and >100 Hz) within 50 ms. Our main result indicates a significant cluster (p < 0.05) in both conditions of reduced relative power (dB) in ACHM people compared to controls, mainly at the time-frequency window >100 Hz. These results suggest that the strongly reduced but not absent activity of OPs above 100 Hz is mostly driven by cones and only in small part by rods. Thus, the lack of cone modulation of OPs gives important insights into interactions between photoreceptors and the inner retinal network and can be used as a biomarker for monitoring cone connection to the inner retina. Full article

Health monitoring of wind turbine gearboxes has gained considerable attention as wind turbines become larger in size and move to more inaccessible locations. To improve the reliability, extend the lifetime of the turbines, and reduce the operation and maintenance cost caused by the gearbox faults, data-driven condition motoring techniques have been widely investigated, where various sensor monitoring data (such as power, temperature, and pressure, etc.) have been modeled and analyzed. However, wind turbines often work in complex and dynamic operating conditions, such as variable speeds and loads, thus the traditional static monitoring method relying on a certain fixed threshold will lead to unsatisfactory monitoring performance, typically high false alarms and missed detections. To address this issue, this paper proposes a reliable monitoring model for wind turbine gearboxes based on echo state network (ESN) modeling and the dynamic threshold scheme, with a focus on supervisory control and data acquisition (SCADA) vibration data. The aim of the proposed approach is to build the turbine normal behavior model only using normal SCADA vibration data, and then to analyze the unseen SCADA vibration data to detect potential faults based on the model residual evaluation and the dynamic threshold setting. To better capture temporal information inherent in monitored sensor data, the echo state network (ESN) is used to model the complex vibration data due to its simple and fast training ability and powerful learning capability. Additionally, a dynamic threshold monitoring scheme with a sliding window technique is designed to determine dynamic control limits to address the issue of the low detection accuracy and poor adaptability caused by the traditional static monitoring methods. The effectiveness of the proposed monitoring method is verified using the collected SCADA vibration data from a wind farm located at Inner Mongolia in China. The results demonstrated that the proposed method can achieve improved detection accuracy and reliability compared with the traditional static threshold monitoring method. Full article