In railway freight transport of over-size cargos, elastic deflection of overloaded structures is the main cause of train-line collision in running. Deflection monitoring remains a challenge for the non-uniform and opening beam on well-hole freight cars. This work presented a new approach by strain perception and Finite Element Analysis (FEA). In theoretical modeling, support locations and the geometry symmetry were taken into account, to identify the support loads with bottom strains in single loading. Deflection calculation was developed by mathematically correlating bottom deflections with support loads, and further extended to the concerning region of the non-uniform and opening beam. Validation underwent in loading simulation and tests. The identified deflection deviates from the read and measured within 5.98%. In application, intransit monitoring reveals that the most unfavorable vertical cargo movement, which is calculated with the identified support deflections and the measured suspension displacement, climbs up to 231.6 mm in synthetic evaluation, when the train runs on a 400-m radius line curve at the speed of 19.6 km/h. The detecting maximum is within but very close to the limit dimension between cargo bottom and rail top, 250 mm. Hence, it is recommended to measure the limit after the transformer is loaded. Research outcome indicates that the proposed approach enables the real-time deflection monitoring and safety evaluation in railway freight transport, which offers scientific evidence for its operation maintenance and structural optimization.INDEX TERMS Deflection monitoring, load identification, non-uniform beam, opening beam, well-hole freight train, strain measurement.
Wind measurement in confined spaces is a challenge due to the influence of the dimensions of anemometers in intrusive flow-field measurements where the anemometer probes directly contact and influence the near-probe flow field. In this work, a new wind speed detection methodology is proposed based on wind-induced motion of a stick via vision-based recognition. The target’s displacement in pixel coordinates is mapped to its angular displacement in world coordinates to derive wind speed and direction information by applying the calibration coefficients. Simulation experiments were carried out to validate the model, the error of which was within an angular displacement of 4.0° and 3.0° for wind speed and direction detections, respectively. When applied to the measurement of wind speed in the inner equipment cabin of a stationary high-speed train, the error was within ±1.1 m/s in terms of average RMSE. Thus, the proposed method provides an accurate and economic option for monitoring 2D wind in a confined space.
Tunnel passing in high speed produces aerodynamic load on railway train, which brings about fatigue failure on the car-body, and damages passenger comfort due to interior penetration of the alternating wave. Experimental simulation of the alternating load remains a challenge concerning its accuracy and reliability. In this work, experiment approaches in terms of air compression and air suction were developed, in an attempt to simulate the air pressure variation when the train runs through tunnels. Pros and cons of the introduced methods were analyzed by theoretical calculation and numerical simulation, and further validated in experimental tests. It is revealed that in air compression means of eccentric wheel and stepping motor propulsion, pressure
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