No abstract

Traditional fault identification algorithms applied to catenary dropper suffer from various problems due to its small contact area. These problems include misidentification and lower recognition rate of the faulty dropper. Compared with the traditional convolutional neural network, the vector is utilized as the input of the capsule network (CapsNet) for the first time, which can well retain the feature information such as the direction and angle of the target, and is more suitable for identifying the dropper under complex background. Therefore, this paper proposes a dropper fault identification algorithm based on improved capsule network. The convolutional layer of traditional 9 × 9 capsule network is simplified through 1 × 1 reduction layer and 3 × 3 convolutional layer, and the optimization algorithm is adopted for parameter optimization to shorten the training weight time. At the same time, the output can retain more information such as direction and angle, which can accurately identify the breakage and falling of current carrying broken. Thus, in order to better improve the accuracy and real-time of detecting the fault dropper from a running train operation, a dropper fault identification algorithm based on an improved CapsNet is proposed in this paper. Experimental results show that the improved CapsNet is well-suited for fault identification of catenary dropper, as it can effectively remove the interference caused by the complex background on the dropper image, and identify the image containing the faulty dropper with a higher recognition rate.

Current research on quadrotor modeling mainly focuses on theoretical analysis methods and experimental methods, which have problems such as weak adaptability to the environment, high test costs, and long durations. Additionally, the PID controller, which is currently widely used in quadrotors, requires improvement in anti-interference. Therefore, the aforementioned research has considerable practical significance for the modeling and controller design of quadrotors with strong coupling and nonlinear characteristics. In the present research, an aerodynamic-parameter estimation method and an adaptive attitude control method based on the linear active disturbance rejection controller (LADRC) are designed separately. First, the motion model, dynamics model, and control allocation model of the quad-rotor are established according to the aerodynamic theory and Newton–Euler equations. Next, a more accurate attitude model of the quad-rotor is obtained by using a tool called CIFER to identify the aerodynamic parameters with large uncertainties in the frequency domain. Then, an adaptive attitude decoupling controller based on the LADRC is designed to solve the problem of the poor anti-interference ability of the quad-rotor and adjust the key control parameter b0 automatically according to the change in the moment of inertia in real time. Finally, the proposed approach is verified on a semi-physical simulation platform, and it increases the tracking speed and accuracy of the controller, as well as the anti-disturbance performance and robustness of the control system. This paper proposes an effective aerodynamic-parameter identification method using CIFER and an adaptive attitude decoupling controller with a sufficient anti-interference ability.

In accordance with problems such as difficulty in obtaining aerodynamic parameters of a quad-rotor model, the change of model parameters with external interference affects the control performances, an aerodynamic parameter estimation method and an adaptive attitude control method based on LADRC are designed. Firstly, the motion model, dynamics model and control distribution model of quad-rotor are established by using the aerodynamic and Newtonian Euler equations. Secondly, the identification tool CIFER is used to identify the aerodynamic parameters with large uncertainties in frequency domain and a more accurate attitude model of the quad-rotor is obtained. Then an adaptive attitude decoupling controller based on LADRC is designed to solve the problem of poor anti-interference ability of the quad-rotor, so that the control parameter b0 can be automatically adjusted to identify the change of the moment of inertia in real time. Finally, a semi-physical simulation platform is used for simulation verification. The results show that the adaptive LADRC attitude controller designed can effectively estimate and compensate the system's internal and external disturbances, and the tracking speed of the controller is faster and the precision is higher which can effectively improve system's anti-interference and robustness.