Analysis of Assembly Error Effect on Stability Accuracy of Unmanned Aerial Vehicle Photoelectric Detection System

Abstract

A photoelectric detection system is a typical type of device widely used for detecting purposes based on unmanned aerial vehicles (UAV). Stability accuracy is the key performance index. Compared to traditional analysis methods aimed at unpredictable error-causing sources, assembly errors can be easily controlled during the manufacturing processes. In this research, an analysis method of assembly error effect on stability accuracy is proposed. First, by using kinematics analysis of homogeneous coordinate transformation, stability accuracy is comprehensively modeled and simulated. Then, by analyzing the manufacturing process, assembly errors of axis perpendicularities, run-outs and gyroscopes are defined and modeled. By simulating different carrier movements, the effects caused by assembly errors under various environments are studied. Finally, error sensitivity is proposed by using standard deviation analysis. Results show that the most sensitive assembly errors are identified, and ranked in order of sensitivity as follows: x-component of pitch axis perpendicularity, y-component of the azimuth gyroscope assembly, and z-component of the pitch gyroscope assembly. In conclusion, the results can be used as standards of manufacturing process improvements, and the proposed methods can be used to provide valuable references for real application scenarios.

Stability Precision Error Correction of Photoelectric Detection by Unmanned Aerial Vehicle

“…Based on our previous research of error modeling [31], the necessary predefinitions are shown as follows, and all modeling components are integrated together for the later analysis. Furthermore, because the device base is considered as being fixed to the UAV body, the dynamic modeling and related analysis of UAV can be simplified as that of the device base, which is presented as follows:…”

“…The values of Δθ si are the differences between the ideal pointing positions and the real ones, and they are also defined as the pointing errors. The specific method to calculate Δθ si and RMS can be seen in our previous work [31] by using a series of statistic indexes (ii) The angular velocity of the device base related to the ground is denoted as ω ! p = ½δ px , 0, δ pz T , which can be measured by using high precision instruments [32], run-outs [33], including γ !…”

“…a = ½γ ax , γ ay , 0 T and γ ! p = ½γ px , 0, γ pz T , and assembly deviations of gyroscope locations [34] including ε More details of those ECS and related kinematics analysis can be seen in our previous work [31]. By integrating all the above modules, the overall stability precision is modeled in Simulink, which is shown in Figure 3.…”

“…ib = ½ω ibx , ω iby , ω ibz T is set as the input. All of the modules of the kinematics, components, and ECS are embedded in the middle, and the details of those modules can also be seen in our previous work [31]. The final index of stability precision RMS is set as the output.…”

Optimization Method of High-Precision Control Device for Photoelectric Detection of Unmanned Aerial Vehicle Based on POS Data

“…Firstly, the UAV assembly accuracy was comprehensively modeled and simulated using kinematic analysis of homogeneous coordinate transformation. en, by analyzing the manufacturing process, the shaft perpendicularity, runout, and assembly errors of the gyroscope were defined and modeled, which improved the photoelectric detection accuracy of the UAV [1]. By using drones, Escobar and Sandoval obtained 8,000 images with a spatial resolution of 1.40 cm on a 30-kilometer beach.…”