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In the extreme power environment of flexible transmission line, wind load, high voltage and strong electromagnetic interference, the motion performance of the robot manipulator is strongly affected by the extreme environment. Therefore, this study aims to improve the manipulator motion control performance of power cable maintenance robot and effectively reduce the influence of specific operation environment on the robot manipulator motion posture.

The mathematical model under three typical operation conditions, namely, flexible line, wind load and strong electromagnetic field have been established, correspondingly the mapping relationship between different environment parameters and robot operation conditions are also given. Based on the nonlinear approximation feature of neural network, a back propagation (BP) neural network is adopted to solve the posture control problems. The power cable line sag, robot tile angle caused by wind load and spatial field strength are the input signals of the BP network in the robot motion posture control method.

Through the training and learning of the BP network, the output control variables are used to compensate the actual robot operation posture. The simulation experiment verifies the effectiveness of the proposed algorithm, and compared with the conventional proportional integral differential (PID) control, the method has high real-time performance and sound stability. Finally, field operation experiments further validate the engineering feasibility of the control method, and at the same time, the proposed control method has the remarkable characteristics of sound universality, adaptability and easy expansion.

A multi-layer control architecture which is suitable for smart grid platform maintenance is proposed and a robot system platform for network operation and maintenance management is constructed. The human–machine–environment coordination and integration mode and intelligent power system management platform can be realized which greatly improves the intelligence of power system management. Mathematical models of the robot under three typical operation conditions of flexible wire wind load and strong electromagnetic field are established and the mapping relationship between different environmental parameters and the robot operation conditions is given. Through the non-linear approximation characteristics of BP network, the control variables of the robot joints can be obtained and the influence of extreme environment on the robot posture can be compensated. The simulation results of MATLAB show that the control algorithm can effectively restrain the influence of uncertain factors such as flexible environment, wind load and strong electromagnetic field on the robot posture. It satisfied the design requirements of fast response, high tracking accuracy and good stability of the control system. Field operation tests further verify the engineering practicability of the algorithm.

This paper aims to develop a robot for tightening charged bolt to solve the shortcomings of high labor intensity, low efficiency, high risk and poor reliability in artificially tightening drainage board bolt of strain clamp for high voltage transmission line. Realizing bolt-nut capture and location by manipulator is a critical process to complete the whole working task. To solve such key technology, an autonomous location control method for N-joint robot manipulator based on kinematics was proposed.

Through D-H kinematics analysis under flexible working environment of transmission line, the autonomous location control of double manipulators can be abstracted as a nonlinear approximation problem based on joint inverse kinematics. In addition, regarding the complex coupling relationship among different joint angles and the complex decoupling process which leads to the non-uniqueness of inverse solution, an improved backpropagation (BP) network was proposed based on the combination of dynamic adaptive adjustment of learning rate and variable momentum factor, so that the inverse kinematics of manipulator can be solved and the optimization evaluation mechanism of inverse solution can be presented. The proposed autonomous location control method is of adaptability to flexible environment and structural parameters of different drainage boards. The simulation results verified the effectiveness of the proposed method. Compared with the other location control, this method can achieve faster location speed, higher precision and lower hardware cost. Finally, the field operation test further validated that such autonomous location control method was of strong engineering practicability.

The proposed autonomous location control method is adaptable to a flexible environment and to the structural parameters of different types of drainage board. Simulation results confirm the effectiveness of the proposed method, which, in comparison with other approaches to location control, can achieve faster location, higher precision and lower hardware cost. Finally, a field test further confirms the engineering practicability of the proposed autonomous location control method.

The proposed method can achieve faster location speed, higher precision which meet the requirement of real-time control relative to the standard BP algorithm. Moreover, it is of strong adaptability to flexible environment and structural parameters for different drainage board. Field operation experiment further validated the engineering practicability of the method.

To improve the operational efficiency and intelligence of live operation robots in dynamic-unstructured operation environments, this paper aims to propose a fuzzy logic-based method for the autonomous search and visual localization control of a manipulator end effector applied to a drainage plate bolt on a high-voltage transmission line. The proposed approach is based on a four-way video image information output from a dual-operation manipulator.

First, based on the structural characteristics of the drainage line, an autonomous search method for the drainage plate bolt and a mapping relationship between the autonomous search control parameters and the relative posture of the operation manipulator-drainage line are proposed. The posture control parameters of the dual manipulators can then be obtained, and a two-dimensional fuzzy controller is designed with the posture offset distance and the posture offset angle as its input signals. This enables the localization control of the bolt and nut alignment to be realized through a visual process.

The proposed fuzzy control algorithm is used for bolt location control, and its performance is compared with that of the conventional approach. The simulation results indicate that the fuzzy control algorithm greatly improves the localization accuracy and operational efficiency of live operation robots.

Field operation experiments on actual transmission lines verify that the fuzzy control-based visual localization control of the robot manipulator has great engineering practicality. Therefore, the proposed method further improves operational intelligence compared with conventional algorithms.

An accurate detection of overhead ground wire under open surroundings with varying illumination is the premise of reliable line grasping with the off-line arm when the inspection robot cross obstacle automatically. This paper aims to propose an improved approach which is called adaptive homomorphic filter and supervised learning (AHSL) for overhead ground wire detection.

First, to decrease the influence of the varying illumination caused by the open work environment of the inspection robot, the adaptive homomorphic filter is introduced to compensation the changing illumination. Second, to represent ground wire more effectively and to extract more powerful and discriminative information for building a binary classifier, the global and local features fusion method followed by supervised learning method support vector machine is proposed.

Experiment results on two self-built testing data sets A and B which contain relative older ground wires and relative newer ground wire and on the field ground wires show that the use of the adaptive homomorphic filter and global and local feature fusion method can improve the detection accuracy of the ground wire effectively. The result of the proposed method lays a solid foundation for inspection robot grasping the ground wire by visual servo.

This method AHSL has achieved 80.8 per cent detection accuracy on data set A which contains relative older ground wires and 85.3 per cent detection accuracy on data set B which contains relative newer ground wires, and the field experiment shows that the robot can detect the ground wire accurately. The performance achieved by proposed method is the state of the art under open environment with varying illumination.

In response to the poor reliability of live maintenance robots in semi-structured environments and the difficulty of monitoring their operation status, this paper aims to propose an online method for evaluating the operation status of high-voltage live maintenance robots based on fuzzy control.

The robot bolt tightening operation is taken as an example. During the whole operation process, the key technologies of bolt tightening are analyzed theoretically, a two-dimensional fuzzy control model of bolt tightening process control is established and the control parameters, which characterize the operation status, are obtained. Through dynamic adjustment of the fuzzy controller, real-time online monitoring of the robot operation status can be achieved.

The results of simulation experiments and 220 kV live operation experiments show that the reliability of robot bolt tightening is greatly enhanced by the proposed control method.

The results not only verify the engineering practicability of the fuzzy control-based method but also indicate that it can improve efficiency, safety and operability.

The purpose of this paper is to improve the operation and maintenance intelligence of power systems, and summarize the transmission line robots and their key technologies. High-voltage power cables are important channels for power transmission systems. Their special geographical environment and harsh natural environment can lead to many different faults. At present, such special operations in dangerous and harsh environments are performed manually, which have not only high labor intensity and low work efficiency but also great personal safety risks.

For maintenance works that are far away from the tower, power outages are required. With the increasing evaluation of transmission quality and operational safety, and the urgent need for automation and operation of modern power systems, the contradiction between this manual operation and modern high-quality power transmission has become increasingly prominent. An effective method to replace the manual maintenance work is to use the mobile robot to carry the operation manipulator and its end tool, that is, the live maintenance robot.

Some achievements have been made in the key technologies of live maintenance robots, the work to be done to meet the basic requirements of complex and changeable line environment and practical application. Based on the existing research results of live overhaul robot, the follow-up research will focus on the practical application needs and the frontier of scientific and technological development, and truly realize the human–machine integration between live overhaul robot–human working environment. Only in this way can the robot better serve the operation and maintenance of the power system.

This paper reviews the system platform, operation function, structural characteristics and key technologies involved in the power cable robot, and the combination of live maintenance robots and modern high-tech such as big data and cloud computing is also given, and finally, the future development direction of the special operation robot is pointed out.

This study aims to the three major problems of low cleaning efficiency, high labor intensity and difficult to evaluate the cleaning effect for manual insulators cleaning in ultra high voltage (UHV) converter station, the purpose of this paper is to propose a basic configuration of UHV vertical insulator cleaning robot with multi-freedom-degree mechanical arm system on mobile airborne platform and its innovation cleaning operation motion planning.

The main factors affecting the insulators cleaning effect in the operation process have been analyzed. Because of the complex coupling relationship between the influencing factors and the insulators cleaning effect, it is difficult to establish its analytical mathematical model. Combining the non-linear mapping and approximation characteristics of back propagation (BP) neural network, the insulator cleaning effect evaluation can be abstracted as a non-linear approximation process from actual cleaning effect to ideal cleaning effect. An evaluation method of robot insulator cleaning effect based on BP neural network has been proposed.

Through the BP neural network training, the robot cleaning control parameters can be obtained and used in the robot online operation control, so that the better cleaning effect can be also obtained. Finally, a physical prototype of UHV vertical insulator cleaning robot has been developed, and the effectiveness and engineering practicability of the proposed robot configuration, cleaning effect evaluation method are all verified by simulation experiments and field operation experiments. At the same time, this method has the remarkable characteristics of sound versatility, strong adaptability, easy expansion and popularization.

An UHV vertical insulator cleaning robot operation system platform with multi-arm system on airborne platform has been proposed. Through the coordinated movement of the manipulator each joint, the manipulator can be positioned to the insulator strings, and the insulator can be cleaned by two pairs high-pressure nozzles located at the double manipulator. The influence factors of robot insulator cleaning effect have been analyzed. The BP neural network model of insulator cleaning effect evaluation has been established. The evaluation method of robot insulator cleaning effect based on BP neural network has also been proposed, and the corresponding evaluation result can be obtained through the network training. Through the system integration design, the robot physical prototype has been developed. For the evaluation of other operation effects of power system, the validity and engineering practicability of the robot mechanism, motion planning and the method for evaluating the effect of robot insulator cleaning have been verified by simulation and field operation experiments.

The purpose of this paper is to examine the impact of the compensation amount as well as the mode through which compensations are paid on farmers’ satisfaction with the compensation received for farmland expropriation in China.

Using rural household survey data collected among 450 households in three provinces, located in eastern, central and western China, this paper estimates the impacts of compensation payments, compensation modes, household characteristics and other control variables on farmers’ satisfaction applying an ordinal probit model.

The major findings are: farmers’ satisfaction with the compensation depends not only on the size of the compensation but also on the gap between the compensation and the market value of the expropriated land; and the compensation amount positively affects farmers’ satisfaction when the social security compensation mode is used, but does not significantly affect farmers’ satisfaction when other modes are used.

First, it contributes to the literature on farmland expropriation by providing empirical evidence of the direct impact of the compensation amount and other factors on the degree of farmers’ satisfaction with farmland compensations. Second, potential interactions between compensation amount and compensation mode are taken into account in estimating factors affecting farmers’ satisfaction.

The purpose of this paper is to review the major systemic educational reforms that China has undertaken over the past three decades and analyze the reasons behind their different degrees of success.

Two running themes are identified among various reforms on the Chinese educational system: decentralization and marketization. The authors explore the driving forces behind these reforms and discuss whether the reforms were successful or not.

In conclusion, the authors highlight four takeaway lessons of Chinese educational reforms.

This is an original discussion of educational reforms in China in the contexts of decentralization and marketization.

The power cable maintenance robot is an important equipment to ensure the reliable operation of high-voltage transmission (HVT) lines and is a useful exploration to achieve high-quality power transmission. In respond to a series of technical problems in the operation process, such as robot shaking, terminal positioning error, camera image blurred and visual servo control difficulty which caused by the influence of high altitude random wind load on the motion control of power maintenance robot. The purpose of this study is to minimizing the impact of wind loads on robot motion control on the high voltage transmission line, so as to obtain the sound motion performance.

This paper presents a robust stabilization control method for flexible wire power maintenance robot under wind load action, the coupling mathematical model between the flexible wire with the robot has been established, and the robot rolling model under wind load has also been established. According to the tilt sensor, the robot pendulum angle value can be obtained and fitted through sinusoidal function; the robot swing period and frequency under wind load action can be also obtained; the feedforward- and feedback-based robot closed-loop control system is also designed.

Through the online detection of wind load dection, so as to dynamic control the clamping force of the robot's dual-arm jaws, therefore, the robot robust stabilization control with different grades of wind load can be realized. Finally, the effectiveness and engineering practicability of the proposed algorithm are verified by simulation experiments and field operation experiments. Compared with the conventional proportional integral differential (PID) algorithm, this method can effectively suppress the influence of wind load on the robot robust stabilization motion control, and the robot posture detection operation control has been further optimized.

A robust stabilization control method for power robot under wind load is proposed. The coupling motion model of flexible HVT and robot is established. The mathematical relationship between the robot wind rolling angle and the wind force has been deduced, and the corresponding closed-loop control system with feedforward and feedback has also been designed. Through the design of robust stabilization control algorithm based on mixed sensitivity function, the effectiveness of the mixed sensitivity robust stabilization control algorithm is verified by simulation experiments in MATLAB environment. Compared with the traditional PID algorithm, this method can effectively suppress the influence of large-scale disturbance information represented by wind load on the robot motion control. The engineering practicability of the robot robust stabilization control algorithm is further verified by the robot live damper replacement operation under the field wind load, which further improves the robot operation efficiency and intelligence.