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With the development of highway transportation and automobile industry technology, highway truck overload phenomenon occurs frequently, which poses a danger to road safety and personnel life safety. So it is very important to identify the overload phenomenon. Traditionally, static detection is adopted for overload identification, which has low efficiency. Aiming at this phenomenon, a dynamic overload identification method is proposed. Firstly, the coupled road excitation model of vehicle speed and speed bump is established, and then the 4-DOF vehicle model of half car is established. At the same time, considering that the double input vibration of the front and rear wheels will be coupled when vehicle passes through the speed bump, the model is decoupled. Then, the vertical trajectory of the body in the front axle position is obtained by Carsim software simulation.

Intelligent sweeper vehicle is gradually applied to human life, in which the accuracy of garbage identification and classification can improve cleaning efficiency and save labor cost. Although Deep Learning has made significant progress in computer vision and the application of semantic network segmentation can improve waste identification rate and classification accuracy. Due to the loss of some spatial information during the convolution process, coupled with the lack of specific datasets for garbage identification, the training of the network and the improvement of recognition and classification accuracy are affected. Based on the Unet algorithm, in this paper we adjust the number of input and output channels in the convolutional layer to improve the speed during the feature extraction part. In addition, manually generated datasets are used to greatly improve the robustness of the model.

The turbine blade is a key component in the operation of the steam turbine hence the design and manufacturing level of the blade will directly affect the performance and efficiency of the turbine. CAD/CAM has been the foundation and important part of advanced manufacturing technology. It is important to study the steam turbine blade integrated CAD/CAM system to improve the design and manufacture of the blade. In this paper, the structure of CAD/CAM system for steam turbine blade is studied and the extensible framework structure including user layer, functional layer and system layer is proposed. Based on the control points of the turbine blade profile design method, and based on the expression between the three-dimensional parametric vector modeling method in UG-based platform, the use of UG/Open development tools and Visual C # developed a turbine blade CAD system.

The acquisition of vehicle dimensions in a vehicle’s moving process has a wide application in road monitoring, transportation, vehicle model recognition and non-contact overload recognition. At present, the detection of the vehicle dimensions mostly adopts the methods of human visual inspection and tool detection, which has a low detection efficiency and difficult to replicate on a large scale. Based on the image background subtraction method, this paper proposes a vehicle dimensions detection method, which can realize real-time detection of road vehicle dimensions. This method uses an adaptive Gaussian Mixture Model (GMM) to establish a background model based on the video stream. Initially, the moving target image is obtained by the background subtraction method, and then the edge detection under the Canny operator and Hough transform circle detection are performed on the image to obtain the pixel dimension of the vehicle's outline.

The non-contact overload recognition method refers to the method of detecting the vibration state of the vehicle through visual recognition without touching the vehicle, and then calculating the vehicle load in combination with the vehicle dynamics model to determine whether the passing vehicle is overloaded. Due to the convenience of detection, low cost of infrastructure and informatization, this method has great advantages in the field of overload identification. However, the model used in this recognition method is the single mass vibration model at present, which will have a large error due to the interaction between the front and rear suspension, and the position of the center of mass needs to be acquired in the recognition process, which is difficult in the actual identification process. In this paper, a vehicle vibration model containing two modes of vibration is proposed, and uses Sobol algorithm to analyze the parameter sensitivity of the model.

Lane detection is an important component in automatic pilot system and advanced driving assistance system (ADAS). The stability and precision of lane detection will directly determine precision of control and lane plan of vehicles. Traditional mechanical vision lane detection approaches in complicated environment have the deficiencies of low precision and feature semantic description disabilities. But the lane detection depending on deep learning, e.g. SCNN network, LaneNet network, ENet-SAD network have imbalance problems of splitting precision and storage usage. This paper proposes an approach of high-efficiency deep learning Segnet-LSTM semantic segmentation network. This network structure is composed with encoding network and corresponding decoding networks. First, convolution and maximum pooling. The proposal extracts texture details of five images and stores searching position of maximum pooling. Meanwhile, it will implement interpolate processing to the lost points.

The vehicle overload seriously jeopardizes traffic safety and affects traffic efficiency. At present, the static weighing station and weigh-in-motion station are both relatively fixed, so the detection efficiency is not high and the traffic efficiency is affected; the on-board dynamic weighing equipment is difficult to be popularized because of the problem of being deliberately damaged or not accepted by the purchaser. This paper proposes an efficient, accurate, non-contact vehicle overload identification method which can keep the road unimpeded. The method can detect the vehicle overload by the relative distance (as the characteristic distance) between the dynamic vehicle's marking line and the road surface. First, the dynamics model of the vehicle suspension is set up. Then, the dynamic characteristic distance of the traffic vehicle is detected from the image acquired by the calibrated camera based on computer vision and image recognition technology.

It’s not easy to start the engine in winter, especially in frigid highlands, because the low temperature increases the fuel’s viscosity, decreasing the lubricating oil flow ability and the storage performance of battery. Current electrical heating method can improve the engine starting performance in low temperature condition, but this method adds an external power to the engine, leading to the engine cannot maintain an efficient energy utilization. A warming device using the solar energy is designed to conserve the energy during the daytime, and directly warm up the engine at the time when the engine turns off for a long time, especially during the night. A solar collector installed on the top of the vehicle is used to convert the solar energy to the thermal energy, which is then transferred to the heat accumulator that contain the phase-change medium which can increase the heat storage performance.

Eddy current retarder (ECR) shares a large market of auxiliary brakes in China, but shortcomings of the short continuous braking time and the high additional energy consumption are also obvious. The propose of combined braking partakes the braking torque of ECR. However, the existed serial-parallel braking strategy could hardly balance well the relationship between the braking stability and the energy recovery efficiency. This research puts forward an energy management strategy of combined braking system which aims to maximize energy recovery while ensure the brake stability. The motor speed, the braking request and the state of charge (SoC) of the storage module are analyzed synthetically to calculate the reasonable braking torque distribution proportion. And the recovered energy is priority for using in the braking unit to reduce the additional energy consumption in this strategy.