A Rapid Search Method for Scheduling Delivery of Multiple Automated Guided Vehicles

In this study, a method was developed to address the automated guided vehicle (AGV) transportation scheduling problem. For deliveries in factories and warehouses, it is necessary to quickly plan a feasible transportation schedule without delay within a specified time. This study focused on obtaining a transport schedule without delay from the specified time while maintaining the search for a better solution during the execution of the transport task. Accordingly, a method was developed for constructing a solution with a two-dimensional array of delivery tasks for each AGV, arranged in the order in which they are executed, as well as for searching for a schedule by performing exchange and insertion operations. For the exchange and insertion, a method that considers the connectivity between the end point of a task and the start point of the next task was adopted. To verify the effectiveness of the proposed method, numerical simulations were performed assuming an actual transportation task.

Layered Lossless Compression Method of Massive Fault Recording Data

In order to overcome the problems of large error and low precision in traditional power fault record data compression, a new layered lossless compression method for massive fault record data is proposed in this paper. The algorithm applies LZW (Lempel Ziv Welch) algorithm, analyzes the LZW algorithm and existing problems, and improves the LZW algorithm. Use the index value of the dictionary to replace the input string sequence, and dynamically add unknown strings to the dictionary. The parallel search method is to divide the dictionary into several small dictionaries with different bit widths to realize the parallel search of the dictionary. According to the compression and decompression of LZW, the optimal compression effect of LZW algorithm hardware is obtained. The multi tree structure of the improved LZW algorithm is used to construct the dictionary, and the multi character parallel search method is used to query the dictionary. The multi character parallel search method is used to query the dictionary globally. At the same time, the dictionary size and update strategy of LZW algorithm are analyzed, and the optimization parameters are designed to construct and update the dictionary. Through the calculation of lossless dictionary compression, the hierarchical lossless compression of large-scale fault record data is completed. Select the optimal parameters, design the dictionary size and update strategy, and complete the lossless compression of recorded data. The experimental results show that compared with the traditional compression method, under this compression method, the mean square error percentage is effectively reduced, and the compression error and compression rate are eliminated, so as to ensure the integrity of fault record data, achieve the compression effect in a short time, and achieve the expected goal.

Estimating the Aerodynamic Coefficients of a Savonius Rotor Blade Profile Developed Through the Simplex Search Method

The Savonius rotor, a type of vertical-axis wind turbine, seems to be promising for small-scale power generation. Most of the studies conducted so far have focused on the evaluation of torque and power coefficients (CT, CP) of the rotor. This paper aims at analyzing the aerodynamic drag and lift coefficients (CD, CL) of a Savonius rotor blade profile that is generated by the simplex search method to maximize its CP. The optimization is carried out by coupling the numerical simulations with the simplex search method. The optimized blade profile thus obtained is symmetric about its axis, where one half is created through a natural cubic spline curve using three points. Two-dimensional (2D) unsteady numerical simulations have been conducted by adopting ANSYS FLUENT solver to examine the CD and CL of the optimized blade profile at an inlet air velocity of 7.30 m/s. The shear stress transport (SST) k-ω turbulence model is used to solve the transient Reynolds-averaged Navier-Stokes (RANS) equations. The aerodynamic analysis is performed over a range of tip speed ratios (TSRs). The total pressure, velocity magnitudes, and the turbulent intensity contours of the optimized blade profile are generated and studied at different angles of rotation. The CD and CL of the blade profile are investigated for a complete rotation with an increment of 1°. At TSR = 0.8, the optimized profile shows a CDmax of 1.91 at an angle of rotation of 54°, while CDmin is found to be 0.45 at an angle 147°.

Live Human Detection Robot in Earthquake Conditions

This report outlines a human searching device that takes the form of a robotic car and serves as a backup mechanism for saving lives in the event of a disaster. The temperature sensor, in general, detects the thermal image of the human body, and there has been extensive research into human searching with the gas and humidity sensor. In the intelligent robot device’s study, achieving accurate and reliable human detection and tracking is a difficult challenge. The architecture of human detection and tracking mechanisms over non-overlapping field of views is examined in this paper. To compensate for their respective flaws, a search method is proposed. The proposed method’s rate and accuracy of human detection was tested in an experimental setting. We may guide the robot’s movement by commanding it to move left, right, forward, or backward. We plan to equip the robot with sensors that will enable us to track and detect humans behind the wall.