Spurred by fall in passenger numbers following the COVID-19 pandemic, railways today have made rapid progress in improving operational efficiency and labor saving measures. DX (digital transformation) technology, which has been applied to automatic train operation, inter alia, is therefore attracting attention. Another focal point for railways is the realization of global decarbonization, illustrated by "2050 Carbon Neutral" goal declared by the Suga Cabinet and "COP26." This paper introduces the outlines of three technologies related to these topics, namely, a "Method for evaluating wheel slide protection (WSP) performance by hybrid simulator," a "Method applying neural networks to detect abnormal noise during train operation," and "High efficiency of diesel electric railcars."
From the viewpoint of safe train operation, railway tracks must be kept in a satisfactory condition by appropriate track inspection and maintenance activities. On the other hand, from the viewpoint of good management, it is necessary to develop track technologies for cost reduction of both track inspection and maintenance. In the development of these technologies, research needs to focus on automation and labor-saving advances by applying ICT and AI techniques, which have progressed significantly in recent years. This paper describes RTRIʼs recent R&D for these track technologies.
The Human Science Division of the Railway Technical Research Institute in Japan, has been conducting research on prevention of human error and safety management as well as measures against transport disruptions and to improve user environments in order to ensure better railway safety, convenience and comfort. This paper outlines recent outcomes from representative research on prevention of human error accidents and improvement of user environments.
In recent years, some railway vehicles have been equipped with condition monitoring devices, which constantly record the operating condition of railway vehicle equipment. For more effective use of condition monitoring devices, we propose an anomaly detection method for railway vehicle equipment using Long Short-Term Memory (LSTM), which is a deep learning method suitable for learning time-series data. In this paper, we apply the proposed method to data on engines and air-conditioning units recorded on vehicles in operations. Results confirmed that the anomaly score for anomalous data increases by using the proposed method, and that anomalies are detected in railway vehicle equipment before faults appear.
Ultrasonic inspection of axles to detect flaws, in which shear waves are emitted into an axle at certain angles, is widely applied. However, when shear waves are obliquely incident on a boundary surface, sound beam displacement may shift the geometric reflection point parallel to the boundary surface. In this study, two types of boundary surface, that is, an axle body and a wheel seat, are targeted. The relationship between a shear-wave incident angle and sound beam displacement is derived theoretically and then confirmed using finite element calculations. The propagation behavior of ultrasonic waves while inspecting surface flaws on an axle is discussed from the viewpoint of sound beam displacement.
We are developing high-damping elastic support of under-floor equipment as one method for reducing vertical car-body vibrations. In this study, two types of excitation test were performed using an actual vehicle. Firstly, we conducted excitation tests in the rolling stock testing plant to verify the effect of the elastically supported mass on the reduction of the elastic vibration of car-body. Secondly, to examine the vibration isolation performance of the developed rubber mount, we conducted stationary excitation tests using a vibration exciter.
We developed a thermal deformation analysis model using numerical calculation in order to quantitatively understand the deformation behavior of rail gas pressure welding. We found that the degree of deformation at the center of the rail base and the jaw part of the rail head are smaller to that of other parts. Furthermore, we also identified that hot cracks occur in these parts in crack simulation tests. This paper describes the developed thermal deformation analysis model for rail gas pressure welding and presents test results validating this method.
In this study, the remaining life of PC sleepers is evaluated from the viewpoint of the fatigue life of PC-steels of PC sleepers. Specifically, a method of acquiring the stress waveform of PC-steels during train running is developed. Furthermore, using this waveform, we calculate the fatigue strength of PC-steels in consideration of the occurrence probability of wheel loads in actual measurement, and quantitatively evaluate the fatigue life of PC-steels. The result of this study shows that PC-steels for a post-tension type have a longer fatigue life than those for a pre-tension type, and PC-steels for both types have a fatigue life of over 300 years.
In order to reduce the cost of track maintenance, grouted ballastless tracks for existing lines where ballast voids are filled with cement grout have been developed and put into practical use. However, there is a problem that some constructed grouted ballastless tracks laid on soft roadbeds are in need of repair within only a few years after operations restart. Therefore, we have developed a method for improving grouted ballastless tracks laid on soft roadbeds and carried out construction work to verify the developed method on existing lines. The roadbed improvement thickness for construction was determined according to design flow proposed in this paper. This paper also describes the improvement method developed for grouted ballastless tracks for existing lines and its verification results.
Using physiological data from a basic experiment simulating railroad driving in general participants, we studied a method for detecting mental and physical states that may interfere with driving. As a result, characteristic changes in brain activity are observed in the group that experienced a psychological upset. In addition, we selected heart rate and respiration as physiological indices that can be easily measured during driving and proposed a method for selecting effective indices for estimating mental and physical states for each individual. We examine the relationship between brain activity associated with psychological agitation and a questionnaire score on resilience (ability to adapt well) and found a weak correlation between them.
To evaluate environmental hygiene, we introduce a microbiome analysis that comprehensively and qualitatively grasps types and proportions of microbial genes on surfaces and airborne samples in railway vehicles. We monitored commuter vehicles using this analysis technology and confirmed that it was possible to grasp the difference in microbiome for each type of equipment. The result of the microbial diversity on each type of equipment showed that floors have different microbiomes, and that equipment touched directly by passengers, such as handrails and straps, have similar microbiomes. The result of estimation analysis of origin of microorganisms indicates that the proportion of human-derived microbiomes tends to be high on handrails and straps.
To increase overall passenger satisfaction, the comfort of railways was reconsidered from a passenger perspective. We twice conducted a web-based survey (February and November 2020) on passenger comfort during several representative travel phases (from planning to destination) and developed a draft evaluation index to estimate the overall comfort from the comfort of each travel phase. We confirm that this draft evaluation index created in the first survey shows 70 to 80% estimation accuracy against the second survey data affected by COVID-19, and that the overall comfort can be stably estimated from the comfort of each travel phase.