China Railway Corporation

From 2001 to 2005, a new railroad linking Beijing with Lhasa was built by more than 100,000 workers, of whom 80% traveled from their lowland habitat to altitudes up to 5000 m to work on the railroad. We report on the medical conditions of 14,050 of these altitude workers, specifically with regard to preexisting illness. All subjects were seen at low and high altitude. Average age was 29.5 +/- 7.4 (SD) yr, range 20 to 62 yr; 98.8% of the subjects were men and 1.2% were women. Overall incidence of AMS upon first-time exposure was 51%, that of HACE 0.28%, and that of HAPE 0.49%. About 1% of the subjects were hypertensive before altitude exposure. Those with blood pressure >or=160/95 were excluded from employment at altitude. Altitude exposure led to a greater increase of blood pressure in hypertensives compared to normotensives. On prealtitude screening prevalence of cardiac arrhythmias was 0.33%. Since the majority of these were rather benign and occurring in young and otherwise healthy subjects, we allowed altitude employment. Follow-up at altitude was uneventful. Subjects with coronary heart disease and diabetes were excluded from altitude employment. Obesity was a risk factor for acute mountain sickness and for reduced work performance at altitude. Overweight subjects lost more weight during their altitude stay than subjects with normal weight. Altitude exposure was a risk factor for upper gastrointestinal tract bleeding, especially in combination with alcohol, aspirin, and dexamethasone intake. Asthmatic subjects generally did better at altitude compared to low altitude, with the exception of one subject who experienced an asthma episode from pollen exposure. In conclusion, careful evaluation of preexisting chronic illness and risk factors allowed prevention of altitude deterioration of a preexisting health condition, all the while allowing subjects with some specific conditions to work and live at altitude without problems.

A series of laboratory experiments is carried out to replicate moisture accumulation in an unsaturated coarse-grained soil underneath an impervious cover. The results show that significant moisture accumulation occurs in relatively dry specimens when the temperature at the cover drops below the freezing point. The tested soil is a coarse-grained sand and is not expected to generate much moisture accumulation according to existing frost susceptibility criteria in the literature. The primary mechanism of moisture migration in the soil is observed to be vapour diffusion, and the primary mechanism of moisture accumulation is ice formation by way of vapour–ice desublimation. It is also observed that two peak values exist along the total water content profile of the 13·5 cm long specimen. For a non-freezing condition, water content gradually decreases from the warmer end to the colder end without any peak value, and the amount of moisture accumulation is less than occurs under freezing conditions. The test results are considered to be useful for understanding vapour diffusion in unsaturated freezing soils, and for validating theoretical and numerical models.

This paper proposes a novel scheme for the identification of the whole flux linkage map of permanent magnet synchronous machines, by which the map of dq-axis flux linkages at different load or saturation conditions can be identified by the minimization of a proposed estimation model. The proposed method works on a conventional three-phase inverter based vector control system and the immune clonal based quantum genetic algorithm is employed for the global searching of minimal point. Besides, it is also noteworthy that the influence of uncertain inverter nonlinearity and circuit resistance are cancelled during the modeling process. The proposed method is subsequently tested on two PMSMs and shows quite good performance compared with the finite element prediction results.

The condition monitoring of railway track line is one of the essential tasks to ensure the safety of the railway transportation system. Railway track line is mainly composed of tracks, fasteners, sleepers, and so on. Given the requirements for rapid and accurate inspection, innovative and intelligent methods for multi-target defect identification of the railway track line using image processing and deep learning methods are proposed in this paper. Firstly, the track and fastener positioning method based on variance projection and wavelet transform is introduced. After that, a bag-of-visual-word (BOVW) model combined with spatial pyramid decomposition is proposed for railway track line multi-target defect detection with a detection accuracy of 96.26%. Secondly, an improved YOLOv3 model named TLMDDNet (Track Line Multi-target Defect Detection Network), integrating scale reduction and feature concatenation, is proposed to enhance detection accuracy and efficiency. Finally, to reduce model complexity and further improve the detection speed, with the help of dense connection structure, a lightweight design strategy for the TLMDDNet model named DC-TLMDDNet (Dense Connection Based TLMDDNet) is proposed, in which the DenseNet is applied to optimize feature extraction layers in the backbone network of TLMDDNet. The effectiveness of the proposed methods is demonstrated by the experimental results.

Various samples of cooking oil fumes were analyzed to an effort to study the relationship between the high incidence of pulmonary adenocarcinoma in Chinese women and cooking oil fumes in the kitchen. Polycyclic aromatic hydrocarbons (PAHs) in samples of cooking oil fumes were extracted, chromatographed, and measured by fluorescence spectrophotometer. The samples included oil fumes from three commercial cooking oils and fumes from three catering shops. All samples contained benzo(a)pyrene (BaP) and dibenzo (a,h)anthracene (DBahA). In addition, the concentration of DBahA was 5.7 to 22.8 times higher than that of BaP in the fume samples. Concentrations of BaP and DBahA were, respectively, 0.463 and 5.736 micrograms/g in refined vegetable oil, 0.341 and 3.725 micrograms/g in soybean oil, and 0.305 and 4.565 micrograms/g in vegetable oil. Investigation of PAH concentrations at three catering shops showed that the level of BaP at a Youtiao (deep-fried twisted dough sticks) shop was 4.18 micrograms/100 m3, 2.28 micrograms/100 m3 at a Seqenma (candied fritters) workshop, and 0.49 micrograms/100 m3 at a kitchen of a restaurant; concentrations of DBahA were 33.80, 14.41, and 3.03 micrograms/100 m3, respectively. The high concentration of carcinogens, such as BaP and DBahA, in cooking oil fumes might help explain why Chinese women, who spend more time exposed to cooking oil fumes than men, have a high incidence of pulmonary adenocarcinoma.

The Harbin–Dalian high-speed railway in northeastern China has a significant portion of track foundation built on seasonally frozen ground. Wide-spread frost heave was observed during the first winter of its operation and the heave occurred mainly in coarse fills that were considered not susceptible to frost heave. This paper first presents the field data of frost heave and frost depth observed along the railway. It then analyses alternative mechanisms that have been considered to have caused the observed frost heave. The three most likely mechanisms are poor quality control of fine content in the coarse fill, the top-down water supply mechanism, and the bottom-up water supply mechanism. The likelihoods of these mechanisms are analysed against observed field data, using a one-dimensional frost heave model. The results indicate that the most likely explanation for the unexpected frost heave is a combined action of different mechanisms.

Single-phase pulse-width modulation (PWM) rectifier is commonly used in a high-speed railway electric traction system. Occurrence of unexpected failure in the sensors of the detection system may lead to feedback values deviation and system degradation, which can be extremely detrimental to the operation safety of the electric locomotive. This paper presents a fast and reliable fault diagnosis and fault resilient control strategy for catenary current and dc-link voltage sensor faults in the control system for an electric traction single-phase PWM rectifier. Sliding mode observers are designed to produce analytical redundancy. In order to avoid unobservable states and fluctuation introduced by discrete dynamics in observer design, a novel description for switching variables is presented in system modeling. Normalized residuals are generated using measured and observed values. The fault diagnosis unit proposed can detect and isolate three types of sensor faults online by comparing residuals with thresholds. System reconfiguration is realized by substituting the observed values for the information of faulty sensors. Simulation and experimental results are demonstrated to validate the effectiveness of the strategy.

Exploratory physical-model studies were made of the hydraulics of stormwater dropshafts in the city of Edmonton. Under certain conditions, it is necessary to provide a curved inlet at the top of the dropshaft to increase its carrying capacity. Except for very small discharges, the falling water in the dropshaft does not form a coherent central jet but takes the form of a complex jet with a spreading flow around the periphery of the dropshaft. Such a flow also forms a pool at the bottom of the shaft. The energy loss in the dropshaft is significant. For the case studied, with the diameter of the shaft (Ds) equal to about twice the diameter (D) of the inflow sewer and a fall of 6.6Ds, and over a wide range of flow rates, the relative energy loss in the dropshaft was about 80–95%. Further, the air flow Qa required by the falling water, relative to the water flow rate Q, decreased from about 1.4 to 0.5 as Q* increased from 0.1 to about 1.0. Q*=Q/(gD5).Q= water discharge and g= acceleration due to gravity.

The successful completion of the Zhengzhou–Xi’an high-speed railway project has greatly improved the construction level of China’s large-section loess tunnels, and has resulted in significant progress being made in both design theory and construction technology. This paper systematically summarizes the technical characteristics and main problems of the large-section loess tunnels on China’s high-speed railway, including classification of the surrounding rock, design of the supporting structure, surface settlement and cracking control, and safe and rapid construction methods. On this basis, the key construction techniques of loess tunnels with large sections for high-speed railway are expounded from the aspects of design and construction. The research results show that the classification of loess strata surrounding large tunnels should be based on the geological age of the loess, and be determined by combining the plastic index and the water content. In addition, the influence of the buried depth should be considered. During tunnel excavation disturbance, if the tensile stress exceeds the soil tensile or shear strength, the surface part of the sliding trend plane can be damaged, and visible cracks can form. The pressure of the surrounding rock of a large-section loess tunnel should be calculated according to the buried depth, using the corresponding formula. A three-bench seven-step excavation method of construction was used as the core technology system to ensure the safe and rapid construction of a large-section loess tunnel, following a field test to optimize the construction parameters and determine the engineering measures to stabilize the tunnel face. The conclusions and methods presented here are of great significance in revealing the strata and supporting mechanics of large-section loess tunnels, and in optimizing the supporting structure design and the technical parameters for construction.

The condition monitoring and fault detection of rolling bearing are of great significance to ensure the safe and reliable operation of rotating machinery system.In the past few years, deep neural network (DNN) has been recognized as an effective tool to detect rolling bearing faults. However, It is too complex to directly feed the original vibration signal to the DNN neural network, and the accuracy of fault identification is not high. By using the signal preprocessing technology, the original signal can be effectively removed and preprocessed without losing the key diagnosis information. In this paper, a new EEMD-LSTM bearing fault diagnosis method is proposed, which combines the signal preprocessing technology with the EEMD method that can get clear fault feature signals, and LSTM technology to extract fault features automatically that improves the efficiency of fault feature extraction. In the case of small sample size, this method can significantly improve the accuracy of fault diagnosis.

The three Barnett-Lothe tensors <bold>S, H, L</bold> , appear very often in the solutions to two-dimensional anisotropic elasticity problems. So do their associated tensors <inline-formula content-type="math/mathml"> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" alttext="ModifyingAbove upper S With caret left-parenthesis theta right-parenthesis comma ModifyingAbove upper H With caret left-parenthesis theta right-parenthesis comma ModifyingAbove upper L With caret left-parenthesis theta right-parenthesis"> <mml:semantics> <mml:mrow> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:mover> <mml:mi>S</mml:mi> <mml:mo stretchy="false"> ^ </mml:mo> </mml:mover> </mml:mrow> <mml:mrow> <mml:mo>(</mml:mo> <mml:mi> θ </mml:mi> <mml:mo>)</mml:mo> </mml:mrow> <mml:mo>,</mml:mo> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:mover> <mml:mi>H</mml:mi> <mml:mo stretchy="false"> ^ </mml:mo> </mml:mover> </mml:mrow> <mml:mrow> <mml:mo>(</mml:mo> <mml:mi> θ </mml:mi> <mml:mo>)</mml:mo> </mml:mrow> <mml:mo>,</mml:mo> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:mover> <mml:mi>L</mml:mi> <mml:mo stretchy="false"> ^ </mml:mo> </mml:mover> </mml:mrow> <mml:mrow> <mml:mo>(</mml:mo> <mml:mi> θ </mml:mi> <mml:mo>)</mml:mo> </mml:mrow> </mml:mrow> <mml:annotation encoding="application/x-tex">\hat S\left ( \theta \right ), \hat H\left ( \theta \right ), \hat L\left ( \theta \right )</mml:annotation> </mml:semantics> </mml:math> </inline-formula> for line forces and dislocations and <inline-formula content-type="math/mathml"> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" alttext="upper S left-parenthesis upsilon right-parenthesis comma upper H left-parenthesis upsilon right-parenthesis comma upper L left-parenthesis upsilon right-parenthesis"> <mml:semantics> <mml:mrow> <mml:mi>S</mml:mi> <mml:mrow> <mml:mo>(</mml:mo> <mml:mi> υ </mml:mi> <mml:mo>)</mml:mo> </mml:mrow> <mml:mo>,</mml:mo> <mml:mi>H</mml:mi> <mml:mrow> <mml:mo>(</mml:mo> <mml:mi> υ </mml:mi> <mml:mo>)</mml:mo> </mml:mrow> <mml:mo>,</mml:mo> <mml:mi>L</mml:mi> <mml:mrow> <mml:mo>(</mml:mo> <mml:mi> υ </mml:mi> <mml:mo>)</mml:mo> </mml:mrow> </mml:mrow> <mml:annotation encoding="application/x-tex">S\left ( \upsilon \right ), H\left ( \upsilon \right ), L\left ( \upsilon \right )</mml:annotation> </mml:semantics> </mml:math> </inline-formula> in the problem of surface waves. Explicit expressions of the components of these tensors are derived and presented for orthotropic materials in which the planes of material symmetry coincide with the coordinate planes. With minor modifications, the results for <bold>S, H, L</bold> and <inline-formula content-type="math/mathml"> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" alttext="ModifyingAbove upper S With caret left-parenthesis theta right-parenthesis comma ModifyingAbove upper H With caret left-parenthesis theta right-parenthesis comma ModifyingAbove upper L With caret left-parenthesis theta right-parenthesis"> <mml:semantics> <mml:mrow> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:mover> <mml:mi>S</mml:mi> <mml:mo stretchy="false"> ^ </mml:mo> </mml:mover> </mml:mrow> <mml:mrow> <mml:mo>(</mml:mo> <mml:mi> θ </mml:mi> <mml:mo>)</mml:mo> </mml:mrow> <mml:mo>,</mml:mo> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:mover> <mml:mi>H</mml:mi> <mml:mo stretchy="false"> ^ </mml:mo> </mml:mover> </mml:mrow> <mml:mrow> <mml:mo>(</mml:mo> <mml:mi> θ </mml:mi> <mml:mo>)</mml:mo> </mml:mrow> <mml:mo>,</mml:mo> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:mover> <mml:mi>L</mml:mi> <mml:mo stretchy="false"> ^ </mml:mo> </mml:mover> </mml:mrow> <mml:mrow> <mml:mo>(</mml:mo> <mml:mi> θ </mml:mi> <mml:mo>)</mml:mo> </mml:mrow> </mml:mrow> <mml:annotation encoding="application/x-tex">\hat S\left ( \theta \right ), \hat H\left ( \theta \right ), \hat L\left ( \theta \right )</mml:annotation> </mml:semantics> </mml:math> </inline-formula> can be applied to orthotropic materials in which only the <inline-formula content-type="math/mathml"> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" alttext="x 3 equals 0"> <mml:semantics> <mml:mrow> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:msub> <mml:mi>x</mml:mi> <mml:mn>3</mml:mn> </mml:msub> </mml:mrow> <mml:mo>=</mml:mo> <mml:mn>0</mml:mn> </mml:mrow> <mml:annotation encoding="application/x-tex">{x_3} = 0</mml:annotation> </mml:semantics> </mml:math> </inline-formula> plane coincides with one of the planes of material symmetry.

Summary In this paper, the resource allocation problems of multiagent systems are investigated. Different from the well‐studied resource allocation problems, the dynamics of agents are taken into account in our problem, which results that the problem could not be solved by most of existing resource allocation algorithms. Here, the agents are in the form of second‐order dynamics, which causes the difficulties in designing and analyzing distributed resource allocation algorithms. Based on gradient descent and state feedback, two distributed resource allocation algorithms are proposed to achieve the optimal allocation, and their convergence are analyzed by constructing suitable Lyapunov functions. One of the two algorithms can ensure that the decisions of all agents asymptotically converge to the exact optimal solution, and the other algorithm achieves the exponential convergence. Finally, numerical examples about the economic dispatch problems of power grids are given to verify the effectiveness of the obtained results.

The statistical characteristic of ocean ambient noise plays an important role in developing underwater signal processors. Considering that the noise in shallow water shows the impulsive nature, non‐Gaussian noise models are usually applied to model the ocean ambient noise. In this study, the ocean ambient noise is modelled by using the Middleton Class B model, which can be decomposed into Gaussian and non‐Gaussian models. Then, the parameters of Class B model are estimated based on the least‐square estimation method, which can be deduced by using the characteristic function of the Middleton Class B model. The processing results of simulated data and real data indicate that the presented method well estimates the parameters of Class B modelled noise. Besides, it further shows that the Middleton Class B model is suitable for modelling the impulsive noise in shallow water.

In the voltage source inverter applications, inverter nonlinearities would affect the parameter identification process in many ways. Hence, this article proposes an offline identification method for resistance and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dq</i> -axis inductance surface by considering the inverter nonlinearity characteristics. A variable amplitude square-wave injection (VASI) scheme is proposed for the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dq</i> -axis inductance identification. The VASI method achieves the inductance identification with a novel data sampling strategy. Meanwhile, it can also establish the inductance surfaces by only a few identified data points with a polynomial fitting algorithm, which greatly reduces the identification time compared with the existing methods. The resistance identification is realized by a slope signal injection method, in which the effect of IGBT voltage drop is analyzed. In order to improve the identification accuracy, the inverter nonlinearities are compensated by a self-learning method considering the zero-axis voltage at different rotor positions. At the same time, the sampling error in zero current zones of abc-phases is researched. In order to verify the effectiveness and generality, the proposed method is carried out on two different test machines and confirmed by finite element analysis.

The rolling bearing is an important part of the train's running gear, and its operating state determines the safety during the running of the train. Therefore, it is important to monitor and diagnose the health status of rolling bearings. A convolutional neural network is widely used in the field of fault diagnosis because it does not require feature extraction. Considering that the size of the network model is large and the requirements for monitoring equipment are high. This study proposes a novel bearing fault diagnosis method based on lightweight network ShuffleNet V2 with batch normalization and L2 regularization. In the experiment, the one-dimensional time-domain signal is converted into a two-dimensional Time-Frequency Graph (TFG) using a short-time Fourier transform, though the principle of graphics to enhance the TFG dataset. The model mainly consists of two units, one for extracting features and one for spatial down-sampling. The building units are repeatedly stacked to construct the whole model. By comparing the proposed method with the origin ShuffleNet V2, machine learning model and state-of-the-art fault diagnosis model, the generalization of the proposed method for bearing fault diagnosis is verified.

Summary In this paper, an aggregative game of multiagent systems over weight‐balanced digraphs is studied, where the decisions of all players are coupled by linear constraints. Different from the well‐known aggregative games, the dynamics of players are disturbed first‐order linear systems in our problem. In order to seek the variational generalized Nash equilibrium (GNE) of the game, a distributed algorithm is developed via gradient descent, internal model, and dynamic average consensus, where the gradient is for seeking the variational GNE, the internal model is for rejecting the exogenous disturbances, and the dynamic average consensus is for estimating the aggregate of the decisions of all players. The exponential convergence of the algorithm to the variational GNE is analyzed by constructing suitable Lyapunov functions. Finally, the effectiveness of our method is illustrated via two examples.

The pantograph-catenary system is used in modern electrified railways to power electric trains. Common sense is that the increase of train speed leads to a deterioration of the interaction performance. But recent studies indicate that a higher speed may result in a better performance in some local speed regions. This paper is the first attempt to provide a theoretical explanation for this phenomenon. A validated pantograph-catenary model is built to reproduce this phenomenon. Referring the definition of critical speed in moving load problems, the catenary's critical speed is defined. The wavelength components can be extracted through the Fourier transformation to the contact wire's vertical mode shape. The speed that satisfies the resonance condition can be regarded as the potential critical speed. The corresponding contact wire amplitude is further evaluated to determine the critical speeds at a given mode. The analysis indicates that a good interaction performance happens when the speed falls in the transition procedure between the critical two speeds. Based on this idea, a simple indicator that describes the overall contribution of all modes subjected to a moving pantograph at a given speed is proposed to facilitate the determination of the local optimal speed. The variation of the proposed indicator with respect to the speed shows good consistency with the trend of the simulation results. The main finding in this paper can be used in the design phase to determine the optimal speed of the pantograph-catenary system in a local speed range.

This paper reviews a number of engineering technologies and workmanships for addressing the challenging issues concerning possible landslides in large-scale slope reinforcement projects in China. It includes: (1) the multi-point anchored piles with a depth of 64 m in the Jietai Temple rehabilitation project, (2) soil nailing strengthened by driven pipe grouting technique covering an area of 530 m × 100 m (length × height) in the Xiluodu hydropower project, (3) the cantilever piles extending vertically from the slope toe to stabilize a 300 m high slope at the Xiaowan hydropower station, (4) a new and simple workmanship for building a pile with cross-sectional area of 20 m × 5 m in the Hongjiadu hydropower station, and (5) comprehensive reinforcement scheme proposed for excavation of a 530 m high slope in Jinping I hydropower station. These new technologies can provide valuable experiences for reinforcement of high slopes of similar projects in China and other regions and countries with similar geological conditions.

As a mass transit mode, the metro attracts passengers from a vast area around its stations through various feeding modes such as walking and cycling. This catchment area is important in interchange planning, transit integration and implementation, and demand forecasting, but the conventional airline buffer greatly overestimates the service area. Moreover, other access modes such as cycling and bus have seldom been considered. It is significant to delineate service areas for multiple modes using the network distance. To this end, an approach of determining the access distances and delineating the service coverage for metro stations was established for multiple feeding modes using a network approach. The proposed method was applied to the Beijing metro based on a large survey sample of trip origins. Data on more than four thousand metro trips were collected in a field survey, and the trip origins were retrieved and visualized in a geographic information system (GIS). Using the geocoded information of the metro, bus lines, and road networks of Beijing, the trip distances were calculated for the corresponding networks for all of the trips investigated. The shares of access modes and the distributions of access distances were analyzed. The service areas of all the metro stations were delineated for each mode and visualized in the downtown and suburban areas through a network analysis. The possible applications of the geocoded service areas drawn in this work, such as optimizing the location of the interchange facilities and boosting the cooperation of different transit modes, are discussed.

As the “first service station” for ships in the whole port logistics system, the tugboat operation system is one of the most important systems in port logistics. This paper formulated the tugboat scheduling problem as a multiprocessor task scheduling problem (MTSP) after analyzing the characteristics of tugboat operation. The model considers factors of multianchorage bases, different operation modes, and three stages of operations (berthing/shifting‐berth/unberthing). The objective is to minimize the total operation times for all tugboats in a port. A hybrid simulated annealing‐based ant colony algorithm is proposed to solve the addressed problem. By the numerical experiments without the shifting‐berth operation, the effectiveness was verified, and the fact that more effective sailing may be possible if tugboats return to the anchorage base timely was pointed out; by the experiments with the shifting‐berth operation, one can see that the objective is most sensitive to the proportion of the shifting‐berth operation, influenced slightly by the tugboat deployment scheme, and not sensitive to the handling operation times.