Search Results (72)

Live stump-supported slopes are an environmentally friendly form of support that utilizes the powerful anchoring and reinforcing effects of deep-rooted plants to enhance slope stability. In order to ensure the safety and stability of embankment slopes during their service life, it is necessary to carry out research on the dynamic characteristics and stability of live stump slopes under train vibration loading. In this study, a large-scale indoor dynamic loading model test with a geometry of 1:7 was carried out on the live stump slope of a ballasted passenger railroad track to explore the attenuation characteristics of additional dynamic stresses, the dynamic displacement response law of the slope surface and the stress response characteristics of the live stumps, and to further investigate the influence of the live stumps on the stability of the slope under the dynamic loading. The results are as follows. (i) Additional dynamic stresses decayed at the bed surface and bed floor at a greater rate than the embankment body, and were significantly affected by dynamic loading when the vertical depth was less than 0.89 m. (ii) The dynamic displacement of the foundation bed is larger than that of the embankment body. The displacement response of the slope near the top and about 1/4 of the elevation of slope is the largest. (iii) The taproot of the living poles has many reverse bending points, and the bending moment of the taproot between the lateral roots shows the law of being larger on the top and smaller on the bottom. (iv) The slope facing has an amplifying effect on the vibration load of the train, and the farther away from the track, the smaller the amplifying effect. The research results have reference significance for the theoretical research and engineering application of living poles. Full article

Non-structural elements have been demonstrated to be essential for the dynamic performance of large-span structures. However, how to quantify their effect has not yet been fully understood. In this study, the contribution of non-structural elements to dynamic properties of large-span structures is systematically investigated via both field measurement and numerical simulation methods. Modal testing of an indoor stadium and an elevated highway bridge was conducted during different construction phases, and the corresponding modal characteristics were identified. Results show that the traditional capacity-based models are incapable of reflecting the actual dynamic characteristics of in-service structures since neglecting the effect of non-structural elements would result in remarkable discrepancies in modal properties. A general modeling framework incorporating the contribution of slab/deck pavement, infill walls (or crash barriers), and joints/connections for large-span structures is developed to quantitatively consider the effect of non-structural elements based on the principle of equivalence of stiffness and mass to the actual structure. The effectiveness of the method is validated by vibration measurement results. Full article

To address the limitations of traditional footstep vibration signal localization algorithms, such as limited accuracy, single feature extraction, and cumbersome parameter adjustment, a motion target localization method for step vibration signals based on deep learning is proposed. Velocity vectors are used to describe human motion and adapt it to the nonlinear motion and complex interactions of moving targets. In the feature extraction stage, a one-dimensional residual convolutional neural network is constructed to extract the time–frequency domain features of the signals, and a channel attention mechanism is introduced to enhance the model’s focus on different vibration sensor signal features. Furthermore, a bidirectional long short-term memory network is built to learn the temporal relationships between the extracted signal features of the convolution operation. Finally, regression operations are performed through fully connected layers to estimate the position and velocity vectors of the moving target. The dataset consists of footstep vibration signal data from six experimental subjects walking on four different paths and the actual motion trajectories of the moving targets obtained using a visual tracking system. Experimental results show that compared to WT-TDOA and SAE-BPNN, the positioning accuracy of our method has been improved by 37.9% and 24.8%, respectively, with a system average positioning error reduced to 0.376 m. Full article

Technical challenges associated with drainage and filling efficacy confront the Yellow River sediment filling reclamation, a novel approach to reclaiming coal-mined subsided lands. This study proposes an improved geotextile performance evaluation method to address the shortcomings of current geotextile screening methodologies in the drainage of the Yellow River sediment. This method comprehensively considers essential characteristics under working conditions, such as permeability, soil conservation, and blockage prevention properties, including indicators such as the permeability coefficient and sediment retention rate of geotextiles under pressure. Indoor flume filling and drainage experiments were implemented to verify the efficacy of geotextile drainage. The improved method identified thermal-bonded nonwoven geotextiles of 200 and 250 g·m⁻² as having the highest comprehensive evaluation scores. The experimental results showed that these geotextiles significantly improved their drainage efficiency and better met the specific requirements of the Yellow River sediment filling reclamation. Traditional screening methods may be unsuitable for sediment drainage conditions, necessitating sediment interception and rapid drainage due to the streaming water–sediment mixture. Therefore, the newly established performance evaluation method is more appropriate for the specific requirements. It is recommended that a simple vibrating device be installed to maintain 20 vibrations per minute to keep drainage channels clear and provide stable drainage performance in engineering applications. Full article

Urban land resources are scarce in China. To utilize land effectively and economically, many cities are developing over-track buildings above metro depots. The vibration from the entrance and exit lines of metro depots under an over-track platform would significantly impact over-track buildings. To study the influence of train vibration in the throat area of a metro depot on over-track buildings, a simulation model was established using a finite element method. The reasonability of the simulation method and parameter settings was verified through comparing the vibration simulation results with vibration test results in the throat area of a metro depot. Furthermore, the impact of parameters of over-track platform and building on indoor vibration induced by a train was quantitatively studied. According to simulation results, a prediction model was developed to predict the impact of train vibration on over-track buildings in metro depots. From the perspective of architectural planning and design, this study provides a theoretical and technical basis for the prevention and control of indoor vibrations in over-track buildings of urban metro depots. Full article

The advancement of urban rail transit is increasingly confronted with environmental challenges related to vibration and noise. To investigate the critical issues surrounding vibration propagation and the generation of structure-borne noise, a two-story frame building was selected for on-site measurements of both vibration and its induced structure-borne noise. The collected data were analyzed in both the time and frequency domains to explore the correlation between these phenomena, leading to the proposal of a hybrid prediction method for structural noise that was subsequently compared with measured results. The findings indicate that the excitation of structure-borne noise produces significant waveforms within sound signals. The characteristic frequency of the structure-borne noise is 25–80 Hz, as well as that of the train-induced vibration. Furthermore, there exists a positive correlation between structural vibration and structure-borne noise, whereby increased levels of vibration correspond to more pronounced structure-borne noise; additionally, indoor distribution patterns of structure-borne noise are non-uniform, with corner wall areas exhibiting greater intensity than central room locations. Finally, a hybrid prediction methodology that is both semi-analytical and semi-empirical is introduced. The approach derives dynamic response predictions of the structure through analytical solutions, subsequently estimating the secondary noise within the building’s interior using a newly formulated empirical equation to facilitate rapid predictions regarding indoor building vibrations and structure-borne noises induced by subway train operations. Full article

The impact of urban traffic on human health is significant. This research conducts field measurements in Guangzhou, China, focusing on a building situated near subgrade roads and viaducts to investigate the characteristics of airborne and structure-borne noise generated by these infrastructures. The analysis involves the use of both sound pressure level and overall sound pressure level, as well as an examination of the transfer function between outdoor and indoor noise levels. The findings indicate that traffic-related airborne noise demonstrates a characteristic frequency at 1000 Hz in this scenario, while viaduct- and building-generated structure-borne noise is predominantly distributed at lower frequencies. Additionally, it is worth noting that structural vibrations generate significantly less energy compared to airborne traffic noise sources. The variation in outdoor road noise across different floors over the entire frequency range demonstrates an initial increase followed by a decrease with rising floor height due to air damping effects as well as sound barriers’ attenuation properties. These results enhance engineers’ understanding of urban traffic-induced airborne or structure-borne noise while establishing foundational data for designing layouts integrating urban buildings with roads. Full article

The high-speed railway subgrade compaction quality is controlled by the compaction degree (K), with the maximum dry density (ρ_dmax) serving as a crucial indicator for its calculation. The current mechanisms and methods for determining the ρ_dmax still suffer from uncertainties, inefficiencies, and lack of intelligence. These deficiencies can lead to insufficient assessments for the high-speed railway subgrade compaction quality, further impacting the operational safety of high-speed railways. In this paper, a novel method for full-section assessment of high-speed railway subgrade compaction quality based on ML-interval prediction theory is proposed. Firstly, based on indoor vibration compaction tests, a method for determining the ρ_dmax based on the dynamic stiffness K_rb turning point is proposed. Secondly, the Pso-OptimalML-Adaboost (POA) model for predicting ρ_dmax is determined based on three typical machine learning (ML) algorithms, which are back propagation neural network (BPNN), support vector regression (SVR), and random forest (RF). Thirdly, the interval prediction theory is introduced to quantify the uncertainty in ρ_dmax prediction. Finally, based on the Bootstrap-POA-ANN interval prediction model and spatial interpolation algorithms, the interval distribution of ρ_dmax across the full-section can be determined, and a model for full-section assessment of compaction quality is developed based on the compaction standard (95%). Moreover, the proposed method is applied to determine the optimal compaction thicknesses (H₀), within the station subgrade test section in the southwest region. The results indicate that: (1) The PSO-BPNN-AdaBoost model performs better in the accuracy and error metrics, which is selected as the POA model for predicting ρ_dmax. (2) The Bootstrap-POA-ANN interval prediction model for ρ_dmax can construct clear and reliable prediction intervals. (3) The model for full-section assessment of compaction quality can provide the full-section distribution interval for K. Comparing the H₀ of 50~60 cm and 60~70 cm, the compaction quality is better with the H₀ of 40~50 cm. The research findings can provide effective techniques for assessing the compaction quality of high-speed railway subgrades. Full article

The wheeled chassis, which is the carrying device of the existing handling robot, is mostly only suitable for flat indoor environments and does not have the ability to work on outdoor rugged terrain, greatly limiting the development of chassis driven handling robots. On this basis, this paper innovatively designs a four-wheel-driving Ackerman chassis with strong vibration absorption and obstacle surmounting capabilities and conducts performance research and optimization on it through quantitative experiments and dynamic simulation. Firstly, based on the introduction of the working principle and structure of the four-wheel-driving Ackerman carrier chassis, a multi-sensor distributed dynamic performance test system is constructed through the analysis of the chassis performance evaluation index. Then, according to the quantitative operation experiment of the chassis, the vibration and acceleration characteristics of the chassis at different positions of the chassis, the amount of slip and straightness of the chassis under different running distance, and the operating characteristics of the chassis under different road conditions and different damping springs conditions were analyzed respectively, which verified the rationality of the chassis design. Finally, by constructing the chassis dynamics simulation model; the influence law of chassis structure; and performance parameters such as chassis wheelbase, guide rod structure, and parameters, wheel friction coefficient and assembly error on the dynamic characteristics of the chassis is studied, and the optimal structure of the four-wheel-driving Ackerman chassis is determined while it is verified based on the simulation results. The research shows that the four-wheel-driving Ackerman chassis has good vibration performance and stability and has strong adaptability to different roads. After optimization, the vibration performance, stability, amount of slip, and straightness of the chassis structure are significantly improved, and the straightness is reduced to 0.399%, which is suitable for precise carriage applications on the chassis. The research has important guiding significance for promoting the development and application of wheeled chassis. Full article

This research examines the application of periodic materials in wall–slab structures to mitigate impact noise and vibration propagation, a prevalent issue in multifamily housing. Traditional methods, such as floating floors, have proven insufficient in addressing low-frequency impact noises and in facilitating the identification of noise origins, leading to increased resident annoyance. Periodic materials, known for their effectiveness in controlling plane waves in civil engineering, were applied to the intermediate slab of a wall–slab experimental setup. The research involved assessing the attenuation of noise and vibration over distance before and after the application of periodic materials by measuring indoor sound pressure levels and the natural vibration amplitude of the structure’s members upon impact. The results showed that periodic materials not only facilitated distance attenuation but also significantly diminished noise and vibration throughout the structure, without the side effects of vibration amplification seen in prior civil engineering applications. This indicates a practical advancement in using these materials, offering a novel approach to sound insulation and enabling more precise impact source localization. Ultimately, this study contributes to improving urban living by suggesting a method to enhance acoustic comfort in multifamily housing, underlining the importance of further exploration in architectural applications of periodic materials. Full article

One of the important issues being explored in Industry 4.0 is collaborative mobile robots. This collaboration requires precise navigation systems, especially indoor navigation systems where GNSS (Global Navigation Satellite System) cannot be used. To enable the precise localization of robots, different variations of navigation systems are being developed, mainly based on trilateration and triangulation methods. Triangulation systems are distinguished by the fact that they allow for the precise determination of an object’s orientation, which is important for mobile robots. An important feature of positioning systems is the frequency of position updates based on measurements. For most systems, it is 10–20 Hz. In our work, we propose a high-speed 50 Hz positioning system based on the triangulation method with infrared transmitters and receivers. In addition, our system is completely static, i.e., it has no moving/rotating measurement sensors, which makes it more resistant to disturbances (caused by vibrations, wear and tear of components, etc.). In this paper, we describe the principle of the system as well as its design. Finally, we present tests of the built system, which show a beacon bearing accuracy of $\Delta \phi$ = 0.51$°$, which corresponds to a positioning accuracy of $\Delta R$ = 6.55 cm, with a position update frequency of $f_{update}$ = 50 Hz. Full article

Precision agriculture relies heavily on measuring grain production per unit plot, and a grain flow monitoring system performs this using a combine harvester. In response to the high cost, complex structure, and low stability of the yield monitoring system for grain combine harvesters, the objective of this research was to design a convex curved grain mass flow sensor to improve the accuracy and practicality of grain yield monitoring. In addition, it involves the development of a grain yield monitoring system based on a cut-and-flow combine harvester prototype. This research examined the real output signal of the convex curved grain mass flow sensor. Errors caused by variations in terrain were reduced by establishing the zero point of the sensor’s output. Measurement errors under different material characteristics, flow rates, and grain types were compared in indoor experiments, and the results were subsequently confirmed through field experiments. The results showed that a sensor with a cantilever beam-type elastic element and a well-constructed carrier plate may achieve a measurement error of less than 5%. After calibrating the sensor’s zero and factors, it demonstrated a measurement error of less than 5% during the operation of the combine harvester. These experimental results align with the expected results and can provide valuable technical support for the widespread adoption of impulse grain flow detection technology. In future work, the impact of factors such as vehicle vibration will be addressed, and system accuracy will be improved through structural design or adaptive filtering processing to promote the commercialization of the system. Full article

This paper presents an occupant localization technique that determines the location of individuals in indoor environments by analyzing the structural vibrations of the floor caused by their footsteps. Structural vibration waves are difficult to measure as they are influenced by various factors, including the complex nature of wave propagation in heterogeneous and dispersive media (such as the floor) as well as the inherent noise characteristics of sensors observing the vibration wavefronts. The proposed vibration-based occupant localization technique minimizes the errors that occur during the signal acquisition time. In this process, the likelihood function of each sensor—representing where the occupant likely resides in the environment—is fused to obtain a consensual localization result in a collective manner. In this work, it becomes evident that the above sources of uncertainties can render certain sensors deceptive, commonly referred to as “Byzantines.” Because the ratio of Byzantines among the set sensors defines the success of the collective localization results, this paper introduces a Byzantine sensor elimination (BSE) algorithm to prevent the unreliable information of Byzantine sensors from affecting the location estimations. This algorithm identifies and eliminates sensors that generate erroneous estimates, preventing the influence of these sensors on the overall consensus. To validate and benchmark the proposed technique, a set of previously conducted controlled experiments was employed. The empirical results demonstrate the proposed technique’s significant improvement ($\tilde{3}$0%) over the baseline approach in terms of both accuracy and precision. Full article

Flattened bamboo board is a new type of bamboo-based panel with various colors that maintains the natural texture of bamboo, and is gradually being used in indoor home decoration. Revealing the influence mechanism on the visual effect of flattened bamboo boards is the key to improving the processing of such boards for household materials. This study employed visual physical quantity measurement methods, field emission scanning electron microscopy, FTIR spectroscopy, and XPS to investigate the visual physical quantities, morphology, and chemical composition of flattened bamboo boards. The results showed that compared with the control samples, the bamboo outer layer boards were dark brown, with the largest ΔE* (38.55), while the outer boards were reddish-brown, with the largest a* (8.82). The inner boards were yellow-red and showed a lower ΔE* (6.55). Due to the elevated density, abundant inclusion, and wax, the bamboo outer layer board exhibited the highest glossiness and darkest color, followed by the outer board and the inner board. The FTIR spectroscopy revealed that hemicellulose decomposed, and the relative content of lignin increased, leading to color changes in the flattened bamboo boards. The bamboo outer layer board was the darkest due to changes in C=C bonds at 1600 cm⁻¹ and 1509 cm⁻¹. The surface color of the outer board was mainly red, which may be caused by C–O bonds at 1239 cm⁻¹. The surface of the inner board was mainly yellow, which may be caused by the C–H stretching vibration of lignin at 1108 cm⁻¹. XPS analysis showed that the proportion of C1 and O1 increased, while C2, C3, and O2 decreased, indicating that hemicellulose degraded at high temperatures, which increased the relative lignin content. Changes in the relative content of oxygen-containing functional groups and SiO₂ in the flattened bamboo board were important factors responsible for the change in visual physical quantities. Full article

Taking the expansive soil near Hefei Xinqiao International Airport as the research subject, indoor dynamic triaxial tests were conducted to investigate the influence of different loading methods on the dynamic pore pressure of saturated remolded expansive soil on the basis of maximally simulating the real characteristics of subway loading. Furthermore, the action laws of three factors, namely intermittent loading ratio, static deviator stress, and cyclic stress ratio, on the accumulated pore pressure of saturated remolded expansive soil under intermittent subway cyclic loading were analyzed. The research results indicate that the loading method significantly affects the development trend of the accumulated pore pressure. Under similar conditions, a larger intermittent loading ratio leads to smaller accumulated pore pressure values and a slower initial development rate of pore pressure under the same cycle vibration. Increasing static deviatoric stress promotes the accumulation of pore pressure. The influence of the cyclic stress ratio is dependent on the intermittent loading ratio and does not follow a consistent pattern. Full article