The article presents materials on the use of cable metro technology in a highly urbanized environment, as an improvement in urban mobility in the format of a smart city. The presented transport system is significantly different from the traditional cablecar, which is described in the comparative characteristics of each system. The article describes the principle of operation of the cable metro, based on the use of mechatronic motion modules.
Introduction. The safety problem and the situation with accidents during the operation of elevator installations are elucidated. The role of elevator rope defects as a factor of dangerous incidents is indicated from the point of view of statistics. The malfunctions of the elevator mechanical equipment related to the defective indices of the ropes are listed. There is a difference in the documentary fixation of defective indices and rejection rates of ropes of lifting structures. Materials and Methods. The well-known approaches to the control of ropes of lifting structures were described. It was emphasized that visual inspection control (VIC) was required to identify such rejection rates of steel elevator ropes as geometry change, corrosion and wear, wire breaks, temperature exposure, etc. The rejection rate was presented in the form of a mathematical system. The technical condition of elevator ropes during the operation was integrally assessed by the totality of identified defects at a fixed length. The decision to create a software and hardware complex (PAC) for the practical implementation of visual and measuring control was validated. Results. The developed PAC VIC laboratory sample consisted of a hardware part, a video stream processing module, communicator for the server connectivity, specially designed software, and a client mobile application. PAC VIC implemented the following functions: – automatic detection and classification of the major significant rope defects based on a deep convolutional artificial neural network; – demonstration of a three-dimensional image of a rope and an image scanning algorithm with distortion compensation, according to which the metric characteristics of defects were fixed; – integral assessment of the technical condition of the rope according to the totality of detected defects; – color interpretation of the actual technical condition of the rope with subsequent transmission to the user's mobile device. Preliminary tests have shown the suitability of the PAC VIC for identifying defects. The reliability of the results for the identification and qualification of defects exceeded 80%. Work on deep learning of the system continues. Discussion and Conclusions. PAC VIC of elevator ropes provides eliminating the risks of visual control caused by the psychophysical state of a person. It works remotely and contactless. The solution proposed by the authors automatically evaluates the rejection rates according to five criteria: external wire breaks, surface wear, rope diameter change, undulation, traces of temperature exposure. An important result of the VIC of steel ropes using computer vision and artificial intelligence is an increase in reliability and safety during the operation of elevator equipment.
Introduction. Currently, the technical condition of ropes of cable-working machines is evaluated periodically according to regulatory documentation. At the same time, methods of visual and instrumental control are used, which depend on the skills and physical capabilities (vision) of the personnel performing the work. There is no unified system of continuous assessment of the technical condition based on a set of factors that does not depend on the human factor. As a result, emergencies occur even when all routine maintenance is carried out on time. To correct this situation, it is proposed to use a computer vision system and neural networks, which allows determining its suitability for further operation by risk levels based on the totality of detected and identified defects, with the interpretation of their results in the color scheme: green — acceptable, yellow — increased, red — high. The work objective is to propose an integral method for risk assessment of operating machines with rope traction when defects and their combinations are detected in a steel rope using computer vision while excluding the influence of the human factor. Materials and Methods. Training of the neural network was carried out on the basis of statistical data of defects obtained from the results of technical inspections of machines with rope traction, on sections of the rope, multiples of its six and thirty nominal diameters according to GOST 33 718. Indexing of risks in the color scheme was carried out according to GOST 55 234.3 to develop a strategy for steel ropes maintenance. A certificate of registration of a computer program was obtained for the neural network program code. The neural network processes visual and measurement control data based on computer vision. Results. An integrated risk assessment system has been created for the diagnosis of steel ropes using computer vision, which allows you to detect defects in steel ropes timely, assess the existing risk of further operation and give recommendations to specialists of operating organizations in real time. This will dramatically reduce the risk of accidents, injury and death of people at facilities using steel ropes. Discussion and Conclusion. The proposed integrated risk assessment system can be applied in any facility that uses rope traction. These are elevators for various purposes, funiculars, cable cars, cranes and many other machines. It should be noted that the estimated commercial cost of the system is low; therefore, the system is available to a wide range of consumers.
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