通过多转子防护装置提高潮汐水轮机性能的策略（英文）

Constructive interference between tidal stream turbines in multi-rotor fence configurations arrayed normally to the flow has been shown analytically, computationally, and experimentally to enhance turbine performance. The increased resistance to bypass flow due to the presence of neighbouring turbines allows a static pressure difference to develop in the channel and entrains a greater flow rate through the rotor swept area. Exploiting the potential improvement in turbine performance requires that turbines either be operated at higher tip speed ratios or that turbines are redesigned in order to increase thrust. Recent studies have demonstrated that multi-scale flow dynamics, in which a distinction is made between device-scale and fence-scale flow events, have an important role in the physics of flow past tidal turbine fences partially spanning larger channels. Although the reduction in flow rate through the fence as the turbine thrust level increases has been previously demonstrated, the within-fence variation in turbine performance, and the consequences for overall farm performance, is less well understood. The impact of turbine design and operating conditions, on the performance of a multi-rotor tidal fence is investigated using Reynolds-Averaged Navier-Stokes embedded blade element actuator disk simulations. Fences consisting of four, six, and eight turbines are simulated, and it is demonstrated that the combination of device-and fence-scale flow effects gives rise to cross-fence thrust and power variation. These cross-fence variations are also a function of turbine thrust, and hence design conditions,although it is shown simple turbine control strategies can be adopted in order to reduce the cross-fence variations and improve overall fence performance. As the number of turbines in the fence, and hence fence length, increases, it is shown that the turbines may be designed or operated to achieve higher thrust levels than if the turbines were not deployed in a fence configuration.     

Application of an improved EEMD method in bearing fault diagnosis of induction motors北大核心CSCD

[Objective]In order to overcome the disadvantages of the traditional ensemble empirical mode decomposition (EEMD) method in selecting parameters (integration time and white noise amplitude coefficient) based on experience, and reduce the cost of calculation time, a fast ensemble empirical mode decomposition (FEEMD) method is used to extract the characteristic frequency. [Method]By changing the distribution density of the added white noise, different signal envelopes can be obtained. Furthermore, we can identify the optimal envelope by finding the optimal search window width of the moving mean filter, thereby avoiding the defect of EEMD selecting parameters by experience. At the same time, after the abnormal component in the signal is decomposed, the residual component can be decomposed by EMD to further save the calculation time cost. Finally, the method is combined with Hilbert envelope demodulation technology and applied to the fault characteristic frequency diagnosis of the bearing inner ring of an asynchronous motor. [Results]As the results show, compared with the traditional EEMD method, FEEMD can extract the fault frequency more efficiently. [Conclusion]FEEMD overcomes the disadvantages of the traditional EEMD method in selecting parameters based on experience and shortens the calculation time. As such, it can be effectively applied in bearing fault frequency extraction experiments. © The Author(s) 2022.     

Fault diagnosis of steam power system based on convolutional neural network北大核心CSCD

[Objectives]In order to improve the fault diagnosis level of marine power systems, this paper studies the real-time fault diagnosis of a marine supercharged boiler based on a convolutional neural network (CNN).[Methods]First, the simulation program of the marine supercharged boiler is developed based on the GSE platform, and the simulation fault data is obtained. The fault diagnosis model of the boiler is then established using the CNN method. Next, through the change trends of temperature, flow and other parameters, combined with a priori knowledge and the machine learning method, fault identification is carried out. Lastly, the performance of the method is evaluated against criteria such as confusion matrix and accuracy. [Results]According to the comparison results between the feature extracted dataset and the original dataset, the stability of the model output results and the generalization ability of the model are optimized and improved, with an overall fault classification accuracy reaching 99.53%.[Conclusion]The results of this study can provide valuable references for the intelligent monitoring of marine power systems. © 2022 Chinese Medical Journals Publishing House Co.Ltd. All rights reserved.     

贵阳岩溶地层地铁盾构隧道工程中新型球状碳化钨刀具的研究与应用北大核心CSCD

在贵阳轨道交通3号线盾构隧道施工中,采用普通刀具易出现滚刀多边形磨损、偏磨、刀刃崩裂等异常磨损和刀圈脱落现象。为改进滚刀刀圈的耐磨、耐冲击性能,提高刀具的综合寿命,提出采用球状碳化钨刀具替换普通刀具,并介绍了激光熔覆焊工艺以及宏观磨损检测工艺。经过施工现场的实际应用,发现球状碳化钨刀具具有更好的耐磨性,新型球状碳化钨刀具平均磨损量为0.00255 mm/延米,相邻普通刀具平均磨损量为0.01655 mm/延米。在第338~736环掘进中,新型球状碳化钨刀具最大磨损量为0.015 mm/延米,刀具无崩刃现象,滚刀轴承、密封等均无异常,有效解决了普通刀具易磨损、磨损不均的问题,为喀斯特地质条件下盾构刀具的选型提供参考。     

Efficiency sensitivity analysis of a hydrostatic transmission for an off-road multiple axle vehicle

There is a large variety of multiple driven axle vehicles. Some of the most common are the 3-axle rigid vehicles and the 4-axle articulated vehicles, which can in some cases have different steering mechanisms, adaptive suspension, etc. This last kind of vehicles usually have very complex transmission configurations. Moreover, the required torques in each of the wheels can be very different, especially when the vehicle is working in rough terrains. The aim of this work is to study and model the driveline of this kind of vehicles, when using a hydrostatic transmission, from the performance and efficiency point of view, by analysing the influence of the operating conditions in the transmission efficiency. A global model is used to quantify the power flow in each of the transmission elements and the overall performance of the entire vehicle driveline, given the operating conditions thereof. A sensitivity analysis has also been done showing the influence of vehicle speed, rolling resistance, terrain slope and hydraulic motors displacement in the overall transmission efficiency. The interest of this work is also to make a contribution to the literature in the field of global modelling of drivelines under variable operating conditions and its application to ATVs. One important aspect is the influence of different actuation requirements that occur in different wheels at the same time. The results show that the overall performance of the transmission is highly dependent on operating conditions, on the selected transmission configuration and on the used components.     

Development and analysis of an air spring model

The analytical model of an air spring can be effectively used for the design of air spring equipped vehicles to provide better ride and handling characteristics along with various functions for passenger convenience. However, establishing a general model of an air spring poses particular difficulties due to the severe nonlinearities in the stiffness and the hysteresis effects, which are hardly observed in conventional coil springs. The purpose of this study is to develop a general analytic model of an air spring — one which represents the main characteristics of stiffness and hysteresis and which can be connected to a model of pneumatic systems desigined to control air spring height. To this end, the mathematical model was established on the basis of thermodynamics with the assumptions that the thermodynamic parameters do not vary with the position inside the air spring, that the air has the ideal gas property, and that the kinetic and potential energies of the air are negligible. The analysis of the model has revealed that the stiffness is affected by the volume variation, the heat transfer, and the variation of the air mass and the effective area. However, the hysteresis is mainly affected by the heat transfer and the variation of the effective area. In particular, it was revealed that the increase of the volume due to the cross-sectional area increases the stiffness, while the increase of the volume due to the other reason decreases it. In addition, the model was used to develop the sufficient stability condition, and the stability of the model was analyzed. The paper also presents the comparison between the simulation and experimental results to validate the established model and demonstrates the potential of the model to be usefully employed for the development of the air spring and its algorithm for use in a pneumatic system.     

Inclusion of latent variables in Mixed Logit models: Modelling and forecasting

Travel demand models typically use mainly objective modal attributes as explanatory variables. Nevertheless, it has been well known for many years that attitudes and perceptions also influence users’ behaviour. The use of hybrid discrete choice models constitutes a good alternative to incorporate the effect of subjective factors. We estimated hybrid models in a short-survey panel context for data among many alternatives. The paper analyses the results of applying these models to a real urban case study, and also proposes an approach to forecasting using these models. Our results show that hybrid models are clearly superior to even highly flexible traditional models that ignore the effect of subjective attitudes and perceptions.     

Effect of vehicle model on the estimation of lateral vehicle dynamics

A methodology is presented for estimating vehicle handling dynamics, which are important to control system design and safety measures. The methodology, which is based on an extended Kalman filter (EKF), makes it possible to estimate lateral vehicle states and tire forces on the basis of the results obtained from sinusoidal steering stroke tests that are widely used in the evaluation of vehicle and tire handling performances. This paper investigates the effect of vehicle-road system models on the estimation of lateral vehicle dynamics in the EKF. Various vehicle-road system models are considered in this study: vehicle models (2-DOF, 3-DOF, 4-DOF), tire models (linear, non-linear) and relaxation lengths. Handling tests are performed with a vehicle equipped with sensors that are widely used by vehicle and tire manufacturers for handling maneuvers. The test data are then used in the estimation of the EKF and identification of lateral tire model coefficients. The accuracy of the identified values is validated by comparing the RMS error between experimentally measured states and regenerated states simulated using the identified coefficients. The results show that the relaxation length of the tire model has a notable impact on the estimation of lateral vehicle dynamics.     

A robust,data-driven methodology for real-world driving cycle development

This paper develops a robust, data-driven Markov Chain method to capture real-world behaviour in a driving cycle without deconstructing the raw velocity–time sequence. The accuracy of the driving cycles developed using this method was assessed on nine metrics as a function of the number of velocity states, driving cycle length and number of Markov repetitions. The road grade was introduced using vehicle specific power and a velocity penalty. The method was demonstrated on a corpus of 1180 km from a trial of electric scooters. The accuracies of the candidate driving cycles depended most strongly on the number of Markov repetitions. The best driving cycle used 135 velocity modes, was 500 s and captured the corpus behaviour to within 5% after 1,000,000 Markov repetitions. In general, the best driving cycle reproduced the corpus behaviour better when road grade was included.     

A framework for robustness analysis of road networks for short term variations in supply

There is a growing awareness that road networks, are becoming more and more vulnerable to unforeseen disturbances like incidents and that measures need to be taken in order to make road networks more robust. In order to do this the following questions need to be addressed: How is robustness defined? Against which disturbances should the network be made robust? Which factors determine the robustness of a road network? What is the relationship between robustness, travel times and travel time reliability? Which indicators can be used to quantify robustness? How can these indicators be computed? This paper addresses these questions by developing a consistent framework for robustness in which a definition, terms related to robustness, indicators and an evaluation method are included. By doing this, policy makers and transportation analyst are offered a framework to discuss issues that are related to road network robustness and vulnerability which goes beyond the disconnected definitions, indicators and evaluation methods used so far in literature. Furthermore, the evaluation method that is presented for evaluating the robustness of the road network against short term variations in supply (like incidents) contributes to the problem of designing robust road networks because it has a relatively short computation time and it takes spillback effects and alternative routes into account.