| When the inspection robot is working on transmission line, its energy is provided by the built-in lithium battery, and it inspects the section (transmission line between adjacent towers) as a unit. After checking a section and stop at the head of tower, the robot needs to clarify the energy consumption of inspecting next section and current battery state (SOC), to avoid the incident that robot stops in the middle of the section for the lack of power; according to the instant state, to predict the remain miles of inspection, and to make reasonable plan which can complete the inspection task as much as possible. Therefore, it is of great significance to estimate accurately the required energy consumption for travel and SOC. Meanwhile, high voltage transmission line distributed in the wild, across the mountains and lakes, the robot spends lots of energy when inspecting, but there is no power supply for charging, and changing lithium battery frequently during inspection is inconvenient, this defect limits greatly the extensive use of the inspection robot. In order to improve the robot's endurance and avoid changing battery off the transmission line, get energy online is particularly important. This paper makes research of the inspection robot from four aspects, energy consumption modeling, SOC prediction, power induction technology, and key technology of solar power.1) Energy consumption modeling of the inspection robot. The electrical structure of the inspection robot is introduced, and the energy consumption for running is analyzed; then according to the feature of inclined parabolic ground line, the force of the robot while ascending or descending at a constant speed is analyzed. Combining the mathematic model of ground line and the dynamic model of the robot, the energy consumption model on the working condition parameters, such as tower section distance and height difference, is finished. By analyzing the factor which may cause errors of energy consumption prediction during running, an energy consumption model based on RBF neural network is built. Finally, the model is verified by experiment to be correct and feasible.2) The state of charge (SOC) estimation for power source based on Kalman filter. Using the SOC got from arriving adjacent towers as the state before and after, a state-space model is built, which includes a state equation describing the relationship among working condition parameters of the section (the horizontal distance of section, height difference and etc.), terminal voltage of lithium battery of arriving adjacent towers, and SOC; a measurement equation describing the relationship between discharge condition of power source (terminal voltage and discharge current) is also built. At last, the validity and feasibility of the adaptive Kalman filtering SOC estimation is verified through experiments.3) The research of online power supply technique based on solar power source. The online power supply method for the inspection robot is to build the solar charging station on transmission tower. Then charging monitoring system and a self-adaptive charging docking-separating mechanism are designed. At last, the estimation model of power source discharge state (terminal voltage and discharge current) based on RBF neural network is built and verified, and with Kalman filtering SOC, it realizes the accurate estimation of cruising distance, which achieves the reasonable distribution of the solar charging station.4) The research of online power supply technique based on power induction. The basic theory of getting power from induction using the robot's lithium battery as energy storage element is explained; then the influence on abstracting power given by the saturation magnetic flux density of iron core in the power supply mechanism is analyzed; through theoretical derivation, the best match relationship among each parameter of power induction mechanism comes out, which is, in the same environment of transmission line, maximum power can be got by the best match design of parameters in the mechanism. After that, simulation and experiment have verified the best match relationship of parameters to be correct. Finally, the power induction mechanism based on the best match design of each parameter is integrative exploited and applied with the inspection robot. |
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