## 4 Detection Process of Degraded Insulators Based on Time-Domain Waveform of Space Electric Field  
Based on the above simulation and test results, this paper improves the traditional insulator electric field detection method and puts forward the optimization strategy for spatial electric field detection under the actual operating conditions of insulators. Firstly, by analyzing the test results in Section 3, it can be seen that the deteriorated insulator will have an impact on the electric field distribution of the insulator string. For the 220 kV insulator string, the electric field distribution of the last three insulators is the most sensitive to the perception of insulator deterioration at any position in the string, so it is defined as a sensitive insulator set. The pre-inspection of the sensitive insulator set can effectively identify whether there is a deteriorated insulator in the insulator string. If the pre-inspection determines that there is a deteriorated insulator in the string, the next step is to inspect the insulator string piece by piece. If the pre-inspection determines that there is no deteriorated insulator in the string, the piece-by-piece inspection operation is not required. The degradation probability of insulators in actual lines is only 1% [29]. The vast majority of insulator strings in the operating line are good insulator strings without deteriorated insulators. If the electric field strength of all insulator strings is detected piece by piece, it will not only greatly affect the patrol efficiency of patrol inspectors, but also put forward strict requirements for the endurance ability of patrol UAVs. The pre-inspection based on the sensitive insulator criteria can avoid the redundant detection of good insulator strings and effectively improve the efficiency of non-contact electric field detection methods. The following Figure 13 is the pre-inspection flow chart. \(E_{av}\) in the figure is the average electric field of two insulator strings at the same position corresponding to two circuits of the same tower. When the degraded insulator is detected in the insulator string through pre-inspection, it is necessary to further detect the insulator string piece by piece to identify the position of the degraded insulator in the string. At this time, it is necessary to consider the impact of complex working conditions on the electric field distribution of the insulator string and put forward corresponding optimization strategies. Based on the simulation results in the second section, an optimization method of increasing path interest points is proposed for the actual working condition of insulator string sag. This method can reduce the measurement error from 4.8% to 0.4% and effectively improve the accuracy of measurement results. For the measurement error caused by UAV attitude disturbance, this paper proposes an optimization strategy combining hardware and software: in terms of hardware, it is recommended to use the UAV equipped with an RTK module as the carrying platform for an electric field detection device. At present, the mainstream UAV with an RTK function in the market can achieve centimeter-level positioning accuracy and meet the requirements of electric field detection; in terms of software, as shown in Figure 14, the electric field information obtained by the traditional detection method based on the UAV platform is only related to the time information and cannot perceive the path offset and attitude disturbance. The measured electric field data will have certain errors compared with the expected electric field data on the path, which will lead to false detection and the missed detection of degraded insulators.