In Revit software, the bridge model is not accurate enough due to the need to manually pick the location of the bridge ’’double slope" components. In order to improve the accuracy of the bridge model, taking Huzhou inner ring Fenghe bridge as an example, the three-dimensional model of the bridge is accurately established by using the open source tool dynamo. In the process of building the model, the data transmission of Excel, Revit and dynamo is completed by calling and combining dynamo nodes. This updated "Data-Driven" method can quickly and accurately locate these components of the bridge, and effectively improve the quality of the bridge model.
The operation of high-speed trains in strong wind environment is a strong coupling and highly nonlinear process, and with the increase of wind speed, this characteristic gradually increases, which seriously affects the safety of high-speed trains. In order to overcome the time-varying parameters and nonlinear uncertainty of high-speed train operation process model under strong wind environment, an adaptive robust control algorithm is proposed in this paper, based on the Lyapunov stability theory, an ATO adaptive robust controller for high-speed trains is designed. The controller can overcome the adverse effects of parameter variations and wind disturbance, and ensure the robust global asymptotic stability and good tracking dynamic performance of the system. The simulation results verify the feasibility of the controller.
In order to improve the crawling efficiency of network crawler, make full use of CPU and realize the processing of high concurrency data, this paper proposes an asynchronous non-blocking network crawler design based on Node.js. It uses a single-threaded model to deal with concurrent data. When a client requests a connection, it triggers an internal event. Through the non-blocking I/O and event-driven mechanism, Node. js program can be parallelized macroscopically. At the same time, it constructs many asynchronous I/O APIs at the bottom, and there is no need to wait between each call. After the operation is completed, the data are processed through callback, so as to reduce the cost and complexity. It is used to write lightweight web crawlers. By acquiring the page, grasping the target content, storing it in JSON files and arrays, and then jumping to the next page, the crawling of web data is realized through several steps of obtaining detailed information. Through practical application test, it is very accurate and efficient to crawl nearly 1000 pieces of data from the webpage.
In order to take into account the randomness and intermittency of renewable energy, appropriate energy storage is usually configured in power systems to improve system flexibility. However, the differences between energy storage types and equipment are not fully considered in the traditional energy storage optimization allocation problem. Firstly, the generation of unbalanced power of power supply load in the power system is analyzed. Combined with the characteristics of pumped storage and battery energy storage, two kinds of energy storage are used to suppress the output fluctuation of low frequency and high frequency, respectively. Then, the discrete Fourier transform is studied first, and on this basis, the distribution power of the two kinds of energy storage is obtained. In this paper, the operation cost of energy storage investment, the loss cost of power shortage and the penalty cost of wind curtailment are comprehensively compared and analyzed. The optimal allocation model of hybrid energy storage system is constructed and solved by particle swarm optimization algorithm. The example shows that the cost of the model in this paper is better than that of some existing battery-pumping storage capacity allocation methods. The addition of photothermal energy can also save energy storage investment and reduce or even avoid the reversal characteristics of the tidal current in the region.
A conceptual medical robotic system applicable for the process of surgery aided diagnosis platform (SADP) is proposed in this paper. According to the requirement of SADP, the surgical navigation system is established. The navigation system proposed a set of image intensification algorithm, which can enhance the images visual effect and surgery precision. At last, the experimental results made for the prototype illustrate the system well. This research will lay a good foundation for the development of a medical robot to assist in SADP.
To realize mobile device location and real-time monitoring, this paper proposes an effective scheme of mobile device positioning management by integrating Internet of things(IoT) and wireless LAN technology. Taking the LAN of a large medical unit as the deployment environment, we designed the overall structure of the IoT based on RFID according to the actual needs of equipment management. Then it provides the specific implementation process of the key technologies such as the hardware composition of the system, the deployment of network AP and the positioning and identification of RFID. Finally, by tracking the quality control and location dynamic information of medical equipment, the trajectory is sent to the server in real time, to realize accurate positioning of medical equipment. The system test results show that our method effectively combines the IoT with mobile collection, location management and other technologies, and solves the problems of hospital fixed assets account, material correspondence management and overall equipment supervision to the maximum extent.
To improve the accuracy and efficiency of face recognition algorithm, a convolution neural network(CNN) face feature recognition scheme based on wavelet transform is proposed in this paper. Firstly, the face image is decomposed into four regions with different frequencies and scales by wavelet transform. Then, the compressed image is transformed by discrete cosine transform, and the weighted distance is used for classification and recognition. The improved lightweight CNN is adopted in face recognition algorithm to effectively eliminate the noise. Based on MATLAB platform, the feasibility of such method is tested in the collected face image database. The simulation results show it has higher recognition rate and robustness, and better comprehensive performance compared with the traditional algorithm.
The method of indoor positioning of terminal cluster based on time-frequency analysis is proposed, which uses time-frequency domain to characterize and analyze signals, and gets rid of the limitation of traditional single time-domain or frequency-domain description of signal characteristics. The time domain and frequency domain are combined to describe and observe the time-frequency characteristics of the signal, and how the spectrum content of the signal changes with time is analyzed through the time spectrum diagram. The hybrid precoding based on geometric mean decomposition is introduced to decompose the channel matrix into channels with the same diagonal element values. All diagonal element values are equal to the geometric mean of the eigenvalues of the channel matrix, so that the subchannel can obtain equal gain and avoid complex bit allocation. Finally, the weighted distance vector hop ranging method is adopted, and the signal intensity factor is introduced to weight the minimum hop number and average hop distance, so as to reduce the error caused by the minimum hop number and average hop distance in the conventional distance vector hop section.
In order to effectively reduce the cable amplitude, both EMID and TMD are used to reduce the vibration of the stay cable. In this study, the complex eigenvalue method is used to simulate and analyze the responses of the stay cable coupled with an electromagnetic inertial damper and a tuned mass damper. To maximize the modal damping ratio of the coupled system, the optimized parameters of the tuned mass damper and the electromagnetic inertial damper under different mass ratios and inertial mass ratios are obtained, respectively. Compared with the optimized parameters of a single tuned mass damper, the results show that the electromagnetic inertial damper and the tuned mass damper coupled system can provide more additional modal damping ratios for hybrid control of stay cables.
The fatigue durability of suspenders is the key problem in the operation and maintenance stage of the bridge. Based on the research background of a long-span tied arch bridge in China, the theoretical model of vehicle-bridge- interaction (VBI) is established. The numerical model of the bridge was established to carry out VBI analysis. Then, the influence of road roughness, speed, transverse lane and vehicle type are analyzed, the parameters that should be considered during the analysis of VIB were determined. Finally, the random traffic simulation program was adopted to simulate the traffic parameters to calculate the stress spectrum of suspenders under different driving parameters. In addition, the rain flow count method was utilized to count the fatigue stress amplitude and its cyclic number. By combination S–N curve with Palmgren-Miner cumulative damage criterion, the fatigue life of uncorroded suspenders and corroded suspenders was estimated. The results show that the fatigue life of suspenders considering corrosion or not are 100 years and 20 years, respectively and the difference of driving parameters of vehicles should be fully considered during the analysis.
The establishment of an accurate model for the risk assessment of stay cables can effectively avoid accidents and prolong the service life of stay cables. This paper proposes an improved risk assessment method based on ALARP criterion and cloud model theory. Firstly, the risk matrix is formed by using risk probability and risk loss. The inherent uncertainty is considered through the evaluation process, and the risk level is described by cloud model. Then, the cloud samples of evaluation indicators are generated according to the ranking of experts, and further transmitted to the forward cloud generator to obtain the certainty level. Finally, the effectiveness and rationality of the improved ALARP method are compared with the traditional method. The results show that the maximum error can be reduced by 54.18%. The improved ALARP principle proposed in this paper can be used as an effective basis for the management and maintenance of stay cables.
Current color enhancement methods will excessively eliminate noise in image processing, resulting in the loss of color information and details in the image, affecting the effect of color enhancement. In order to improve the defects of the above color enhancement methods, a brand image color enhancement method based on smooth filtering algorithm is studied. After the histogram is used to equalize the image, the color of the image is segmented to obtain the color information. Based on Gaussian filter, a joint bilateral filter is designed to smooth the image. Deep learning convolutional network is constructed to realize image color enhancement by encoding and decoding. The simulation results show that the CNI value of the enhanced image is closer to 1, the color quality of the image is better, and the color enhancement effect of the method is better.
Compared with the traditional experiment, the finite element (FE) simulation method is more cost-effective and more efficient. Hence, it is widely used to analyze the impact response of the structure. However, single structural analysis software is often only useful for some specific problems, and no one can be applied to solve all types of structural problems. A software that is widely used to analyze the impact response of structures, i.e., LS-DYNA, has been proved to be flawed in capturing the shear behavior of certain structures. Taking into account the shortcomings of the existing analysis software, this study has developed a hybrid simulation method based on OpenSees-MATLAB-VecTor2 to analyze the dynamic behavior of the bridge structure under rockfall impacts. The modeling details of the hybrid model are introduced in detail in this study. The single-machine model is built to compare the damage of the bridge column under the impact of rockfalls with the hybrid model. The results show that the impact point displacement of the impacted column simulated by the hybrid model is greater than that of the single-machine model because the hybrid model can capture the shear damage behavior of the bridge column.
Slam robot positioning system based on vision has good universality, but the depth information of the environment is lost due to low bandwidth, uncertainty of visual image change and poor real-time performance of motion mutation. In order to solve the above problems, a robot positioning system based on the integration of slam system and the inertial system is proposed. The hardware part designs inertial sensor modules such as accelerometer, odometer and gyroscope, and integrates the inertial sensor module with slam system. The IMU motion model is used to predict the attitude of the camera in the current frame and match the feature points of the current frame. The state of the robot is estimated by using the inertial sensor data of binocular vision, and the position and attitude of the robot are determined by slam according to the estimated value. The system test results show that the maximum positioning error rate of the system is only 1.8%, the positioning time is short and the performance is good.
Aiming at the problems of large error and long time-consuming in the traditional motion image attitude contour extraction results, a motion image attitude contour extraction method based on Bayesian classification is proposed. MEMS sensor is used to calibrate the real-time posture of human motion process, determine the posture of moving image, and Bayesian model is used for classification. The log operator is introduced to determine the edge indication function under the adaptive surface evolution extreme value, and combined with the reverse CRF transform to extract the pose contour of the moving image. The experimental results show that the iteration times and time-consuming, signal-to-noise ratio and SSE value of this method are better than those of the traditional method.
To solve the problem of differential human motion recognition of different users in human-computer interaction, SVM is used to classify and recognize the motion posture. We use Kinect sensor to capture human motion, generate depth image, and establish three-dimensional human model after processing. Then the target behavior recognition adopts a two-level SVM classifier to map various action signals to the feature space to form a feature vector with a certain dimension. During the process of outputting recognition results, corresponding confidence is output and the motion posture is determined by the change classification of motion features. The experimental results show that this research method uses the invariance and orthogonality of support vector machine to improve the recognition rate of vector optimization to more than 95%. Its the action recognition effect is good, which has better robustness with similar algorithms.
Regarding the problems of micro gas flow regulating valve, including micron assembly, precise trim of the valve spool and dynamic sealing of the valve port, if we do not master its working principle and simulation method, it is challenging to optimize better products just using a large number of experiments. Herein, the flow regulating valve is modeled theoretically by using the circuit model, magnetic circuit model, dynamic model, and nozzle model with the help of MATLAB software. The simulation and analysis includes the study of the dynamic characteristics, voltage displacement characteristics, and voltage flow characteristics of the valve spool, along with the effect of preload height, air gap height, stiffness coefficient, and temperature on the key characteristic of the flow regulating valve. The experimental results are consistent with the simulations, indicating that the model developed in this paper is accurate and the simulation results are reliable. It can be used for the iterative design and optimization of flow regulating valves, as well as in the assembly of flow regulating valves and the fine-tuning of their characteristics in the manufacturing process.
In order to effectively mine hidden research topics and potential evolution patterns from massive network public opinion data, this paper proposes a public opinion monitoring system based on LDA. The scheme mainly performs text crawling and topic extraction of network entities through self-programming by Python, and realizes fine-grained emotion analysis and topic mining combined with TF-IDF feature words and LDA model. Then, cluster analysis is made on the content and intensity of each stage of public opinion development, and the construction of topic model and topic confusion are extracted for further public opinion prediction. Finally, the LDA topic model is applied to the application of public opinion system, which realizes the intelligent monitoring, analysis and prediction function of public opinion, and it can quickly respond to the update and change of network public opinion.
As lightning strikes usually include multiple return strikes, the effect of multiple currents on grounding devices needs further research. In this paper, the dispersion characteristics of tower grounding devices with different materials based on the continuous impact test platform is analyzed. The results show that the impact grounding resistance of the grounding device is related to the time interval between impact pulses. When the time interval is small, the impact grounding resistance is less than the single impact grounding resistance. With the increase of time interval, the impact grounding resistance is restored to the primary impact grounding resistance. However, within a certain time interval, the grounding resistance of a grounding device in moist soil under a double pulse is greater than that of a single pulse.
