Roll Angle Research Articles

Fatigue Driving Detection Based on Facial Multi-Information Feature Fusion

Abstract Driver fatigue driving risk detection is one of the important areas of road traffic safety research in China. According to statistics, more than 40% of China’s traffic accidents every year are related to driver fatigue. In order to reduce this risk, this paper proposes a new method based on facial multi-information feature fusion to realize real-time fatigue driving detection. The method includes using the camera to capture the driver’s face image in real time, combining the face recognition in Dlib library and the detection of 68 key points, and implementing the face detection through OpenCV. Further, the opening and closing states of eyes and mouth were analyzed based on EAR and MAR algorithms, and a reasonable threshold was set to judge fatigue behavior. The HPE head pose estimation method is used to judge the fatigue state by considering the pitch Angle and roll Angle information. Finally, the improved rough set theory comprehensive evaluation method is used to carry out decision fusion processing on the feature results, and intuitively display the system detection results, which is convenient to evaluate the fatigue state of the current driver. The experimental results show that the multi-feature fusion detection method has good real-time performance, the accuracy rate is 94.55%, and the fatigue state can be detected quickly and accurately under various driving attitudes.

Research on assisted recovery algorithm of stall state based on signal guidance

Abstract Given the lack of quantitative guidance in the current stall recovery process, which leads to the pilot’s misoperation or untimely recovery, referring to the energy control theory of complex state recovery, a stall state-assisted recovery algorithm based on pitch angle, engine thrust, and roll angle signal guidance was determined. The structure pilot model and the kinematics simulation model of aircraft at a high angle of attack were established. The effectiveness of the algorithm has been verified by simulation analysis. The man-machine closed-loop simulation analysis results show that the algorithm can guide the pilot in effectively recovering from stall conditions under different stall scenarios and engine failure conditions.

Synchronization of coupled quadcopters using contraction theory

In this paper, the synchronization of coupled quadcopters using contraction theory principles is presented. In order to synchronize the roll and pitch angles of the quadcopter models, contraction theory application is a pivotal tool. Despite the fact that all of the quadcopters used in this study have identical characteristics, their behaviour greatly depends on their initial conditions. Because of the inherently nonlinear nature of quadcopters, slight variations in the initial conditions can have a significant impact on the trajectory of the quadcopters in the future. Contraction theory is a useful technique for addressing this problem. By using the contraction theory, synchronization has been done for two quadcopters as well as for three quadcopters. Finally, a generalized method for synchronizing any number of quadcopters using contraction theory is presented. For the synchronization of two quadcopters, roll angles and pitch angles were synchronized in 3.2 and 3.6 seconds, respectively whereas for the synchronization of three quadcopters, roll angles and pitch angles were synchronized in 3.2 and 3.4 seconds, respectively. MATLAB® is used to carry out the mathematical modelling of the quadcopters and the synchronization procedure.

Computer modeling and validation testing for glenoid component rotation and optimal glenoid screw angles for reverse shoulder arthroplasty in an Asian population.

Good initial fixation of glenoid component for reverse total shoulder arthroplasty (RTSA) relies on component placement and screw purchase in the scapula bone. This is especially difficult in an Asian population with small glenoid geometry. Optimal glenoid component roll angle and screw angulation to achieve the longest screws for best fixation has not been defined in the current literature. Computer 3D modelling of 133 scapulas with RTSA performed were analyzed to determine patient specific optimal glenoid roll angle (GRA) for the longest bi-cortical screws attainable. The cranial-caudal angle (CCA), anterior-posterior angle (APA) and lengths for the superior and inferior screws were measured. Validation testing using calculated average (CA) angles and rounded average (RA) angles to the nearest 5 degree were recomputed for each case to determine the bi-cortical screw lengths achievable. The CA and RA screw lengths were compared against patient specific modelling using paired-sample t-tests. Average GRA was - 1.6°, almost perpendicular to the long axis of the glenoid and achieves an average bi-cortical screw length of 51.3mm and 45.5mm for the superior and inferior screws respectively. The CCA and APA were 9.1° cranial and 6.5° posterior for the superior screw and screw angulation of 11.2° caudal and 0.7° anterior for the inferior screw. Validation testing shows statistically shorter screw lengths in the CA and RA models compared to patient specific modelling (p < 0.01). Validation testing with average angles for GRA, CCA and APA demonstrates strong patient heterogeneity and anatomical variation. Despite this, screw lengths attainable in the RA group were > 38mm with good safety profile. Surgeons may consider the additional use of navigation-assisted, or 3D printed patient specific instrumentation to optimize baseplate and screw configuration for RTSA.

Fabrication of versatile and durable superhydrophobic cotton fabrics using PTA-Ala adhesive

In recent years, the preparation of functional textiles based on polyphenols adhesion has received extensive attention and research. However, polyphenols are prone to peroxidation during oxidative polymerization, which can compromise the interfacial adhesion of their monomers. Reintroducing reactive functional groups after oxidative polymerization of polyphenols may potentially compensate for the lost interfacial adhesion while increasing cohesion. In this paper, L-alanine (Ala) is introduced into poly (tannic acid) (PTA) solution to generate the PTA-Ala via Michael addition and Schiff base reaction. Original cotton fabrics are modified with PTA-Ala solution to enhance adhesion strength between the fabrics and subsequent functional modifiers. A silver nanowire network is then incorporated to increase the surface roughness through tannic acid reduction. Finally, polydimethylsiloxane is applied to reduce fabric surface energy, resulting in superhydrophobic multifunctional OH-PDMS/Ag/PTA-Ala/cotton fabrics. The finished cotton fabric exhibits a water contact angle of 166.7 ± 1.9° and a rolling angle of 5 ± 0.5°. Moreover, the fabric features diverse functionalities such as oil-water separation, photothermal conversion, antimicrobial properties, water collection, and anti-icing capabilities, alongside excellent durability and self-healing properties that extend its service life. This finished cotton fabric demonstrates promising applications in oil pollution control, outdoor clothing and medical protection, highlighting its broad across various industries.

Intelligent control of the Magnus anti-rolling device: A co-simulation approach

In this study, we present an artificial intelligence control method specifically designed for the Magnus anti-rolling device. The core of our approach is the development of a co-simulation framework that integrates an intelligent algorithm with a three-dimensional numerical computational programme within a complex hydrodynamic environment. This integration is achieved through the use of a deep reinforcement learning algorithm, which allows for intelligent adaptation of the anti-rolling device's rotating speed in real time. Our research focuses on evaluating the performance of the intelligent anti-rolling control algorithm under a variety of conditions, including different ship-model roll angles, column geometry models, and varying swinging or slewing speeds. Through numerical studies, we compare the effects of these variables on the effectiveness of the control method. The co-simulation technology provides a platform for testing the intelligent control method. It allows a detailed examination of how the intelligent algorithm interacts with the hydrodynamic responses of the Magnus anti-rolling device, ensuring that the control method can adapt to a wide range of operational scenarios. This adaptability is crucial for maintaining stability and improving the performance of the anti-rolling device in real maritime environments. This study highlights the potential for integrating artificial intelligence with traditional maritime engineering solutions.

Efficient and Controllable Preparation of Super-Hydrophobic Alumina-Based Ceramics Coating on Aviation Al-Li Alloy Surface for Corrosion Resistance and Anti-Icing Behavior

Al-Li alloys have been widely applied in aircraft structural component and shell material. However, Al-Li alloys are prone to corrosion failure, which leads to a considerable safety risk in the aerospace field and greatly limits their industrial application. Herein, a simple, low-cost, and large-scale air-spraying technique is developed for the preparation of an alumina-based ceramics coating with enhanced corrosion resistance and anti-icing behavior. The results show that the static contact angle of the as-prepared coating is 157.2 ± 0.4°, and the rolling angle is only 9.8°, suggesting a super-hydrophobic surface. Meanwhile, the electrochemical corrosion potential of the coating is 70 mV higher than that of the substrate, and the corrosion current density of the coating also decreases by 1 order of magnitude, indicating a significantly improved corrosion resistance. In addition, the fabricated super-hydrophobic coating also shows excellent anti-pollution and anti-icing characteristics. This work provides positive guidance for expanding the application of hydrophobic coating in the aerospace industry, especially in some complex corrosion, icing, and pollution environments.

A new dual-zone position sensitive detector for roll angle Measurement: Design and validation

The measurement of roll angle is widely acknowledged as the most challenging task in 6-degree-of-freedom pose measurement. Until now, a photodetector dedicated to roll angle measurement has not been developed. Here, we present a new dual-zone position sensitive detector, which enables straightforward roll angle measurement based on the relative positions of two spots. In the proposed device, two photosensitive areas share the same coordinate origin and are separated by a quasi-invisible ring. The quasi-invisible ring serves as photocurrent isolation and ensures the normal photocurrent distribution. For spot position measurement, the device shows an excellent spatial resolution of 0.75 μm, low nonlinearities of 0.90 %, and a fast response of 5.8 μs. For roll angle measurement, the device exhibits high accuracy of 0.2° and high resolution of 0.018° in the measurement range of 360°. This work offers an innovative solution for high-performance roll angle measurement in 6-DOF pose measurement systems.

Multi-Position Inertial Alignment Method for Underground Pipelines Using Data Backtracking Based on Single-Axis FOG/MIMU.

The inertial measurement method of pipelines utilizes a Micro-Electro-Mechanical Systems Inertial Measurement Unit (MIMU) to get the three-dimensional trajectory of underground pipelines. The initial attitude is significant for the inertial measurement method of pipelines. The traditional method to obtain the initial attitude uses three-axis magnetometers to measure the Earth's magnetic field. However, the magnetic field in urban underground pipelines is intricate, which leads to the initial attitude being inaccurate. To overcome this challenge, a novel multi-position initial alignment method based on data backtracking for a single-axis FOG and a three-axis Micro-Electro-Mechanical Inertial Measurement Unit (MIMU) is proposed. Firstly, the configuration of the sensors is determined. Secondly, according to the three-point support structure of the pipeline measuring instrument, a three-position alignment scheme is designed. Additionally, an initial alignment algorithm using the data backtracking method is developed. In this algorithm, a rough initial alignment is conducted by the data from single-axis FOG, and a fine initial alignment is conducted by the data from FOG/MIMU. Finally, an experiment was conducted to validate this method. The experiment results indicate that the pitch and roll angle errors are less than 0.05°, and the azimuth angle errors are less than 0.2°. This improved the precision of the 3-D trajectory of underground pipelines.

The Optimal Strategies of Maneuver Decision in Air Combat of UCAV Based on the Improved TD3 Algorithm

Nowadays, unmanned aerial vehicles (UAVs) pose a significant challenge to air defense systems. Unmanned combat aerial vehicles (UCAVs) have been proven to be an effective method to counter the threat of UAVs in application. Therefore, maneuver decision-making has become the crucial technology to achieve autonomous air combat for UCAVs. In order to solve the problem of maneuver decision-making, an autonomous model of UCAVs based on the deep reinforcement learning method was proposed in this paper. Firstly, the six-degree-of-freedom (DoF) dynamic model was built in three-dimensional space, and the continuous actions of tangential overload, normal overload, and roll angle were selected as the maneuver inputs. Secondly, to improve the convergence speed for the deep reinforcement learning method, the idea of “scenario-transfer training” was introduced into the twin delayed deep deterministic (TD3) policy gradient algorithm, the results showing that the improved algorithm could cut off about 60% of the training time. Thirdly, for the “nose-to-nose turns”, which is one of the classical maneuvers for experienced pilots, the optimal maneuver generated by the proposed method was analyzed. The results showed that the maneuver strategy obtained by the proposed method was highly consistent with that made by experienced fighter pilots. This is also the first time in a public article that compared the maneuver decisions made by the deep reinforcement learning method with experienced fighter pilots. This research can provide some meaningful references to generate autonomous decision-making strategies for UCAVs.

Temperature-irrelevant superhydrophobic polyimide–SiO2 aerogels with a confined shrinkage strategy for high-temperature thermal protection (>400 °C)

Polyimide (PI) aerogels often experience substantial volume shrinkage when exposed to temperatures above 200 °C. Furthermore, research regarding the hydrophobic characteristics of PI aerogels under high-temperature conditions is limited. Herein, a confined shrinkage strategy was proposed, and the PI–SiO2 aerogels were prepared with ultralow thermal shrinkage and high-temperature superhydrophobic properties. Micrometer-sized silica aerogel powders were used in this strategy as shrinkage inhibitors during the production of PI aerogels. The silica aerogel powders were then pulled together using the PI chain and braced to each other, limiting the shrinkage of the PI aerogel matrix attached to the powders. Results indicated that the prepared aerogel experienced a shrinkage of only 6.2 % after heat treatment at 400 °C for 1 h in a muffle furnace. The surface area of the sample decreased from 669 m2/g to 649 m2/g after heat treatment, revealing a reduction of only 2.7 %. Previous studies have never reported this remarkable thermal stability. Furthermore, the aerogel exhibited superhydrophobic properties with a water contact angle of 157.4° and a water rolling angle of approximately 0° at 300 °C due to its high surface roughness.

Correlation between Muscular Activity and Vehicle Motion during Double Lane Change Driving.

The aim of this study was to compare the correlation between electromyography (EMG) activity and vehicle motion during double lane change driving. This study measured five vehicle motions: the steering wheel angle, steering wheel torque, lateral acceleration, roll angle, and yaw velocity. The EMG activity for 19 muscles and vehicle motions was applied for envelope detection. There was a significantly high positive correlation between muscles (mean correlation coefficient) for sternocleidomastoid (0.62) and biceps brachii (0.71) and vehicle motions for steering wheel angle, steering wheel torque, lateral acceleration, and yaw velocity, but a negative correlation between the muscles for middle deltoid (-0.75) and triceps brachii long head (-0.78) and these vehicle motions. The ANOVA test was used to analyze statistically significant differences in the main and interaction effects of muscle and vehicle speed. The mean absolute correlation coefficient exhibited an increasing trend with the increasing vehicle speed for the muscles (increasing rate%): upper trapezius (30.5%), pectoralis major sternal (38.7%), serratus anterior (13.3%), and biceps brachii (11.0%). The mean absolute correlation coefficient showed a decreasing trend with increasing vehicle speed for the masseter (-9.6%), sternocleidomastoid (-12.9%), middle deltoid (-5.5%), posterior deltoid (-20.0%), pectoralis major clavicular (-13.4%), and triceps brachii long head (-6.3%). The sternocleidomastoid muscle may decrease with increasing vehicle speed as the neck rotation decreases. As shoulder stabilizers, the upper trapezius, pectoralis major sternal, and serratus anterior muscles are considered to play a primary role in maintaining body balance. This study suggests that the primary muscles reflecting vehicle motions include the sternocleidomastoid, deltoid, upper trapezius, pectoralis major sternal, serratus anterior, biceps, and triceps muscles under real driving conditions.

A durable superhydrophobic surface with bud-particle structure prepared by one-step spray method

Superhydrophobic surfaces play an essential role in numerous applications such as anti-fouling, waterproofing, and drag reduction due to their water-repellent. However, for most fabrication methods, there are high requirements for the preparation process and conditions. Meanwhile, the superhydrophobic surfaces generally have the problem of insufficient durability. In this study, a one-step method to fabricate a stable superhydrophobic surface by spraying is proposed. A new bud-particle structure is obtained by modifying micron and nano Aluminium hydroxide(Al(OH)3) particles, which helps the coated surface to demonstrate excellent superhydrophobicity with the water contact angle ∼157.0° and rolling angle ∼2.0°, and it shows great repellency to water droplet impact. Due to the compatibility of Al(OH)3with the pretreatment substrate and the reinforcing effect of nanoparticles, the coating maintained the superhydrophobicity well in the sandpaper wear and the ultrasonic damage test, which reflects the outstanding robustness of the coating.Moreover,benefiting from the control of the wetting state by micronand nanoparticles doping,the coating showed an excellent underwater drag reduction effect in the rheometer experiment, with a drag reduction rate of ∼67.7 %. The one-step spraying method proposed is a simple and convenient way to create the surface with excellent superhydrophobicity and durability, which has great potential applications in improving metal surface oxidation resistance and underwater reducing drag.

Modeling and control strategy of small unmanned helicopter rotation based on deep learning

Unmanned Aerial Vehicle (UAV) can serve as a substitute for workers in some hazardous environments, but the presence of ground effects makes UAVs prone to hardware damage during the recycling process. To study the rotation phenomenon of small UAV landing process and propose control strategy, the study completes the rotation modeling of small unmanned helicopter based on deep learning algorithm and proposes the control strategy. The results show that the CNN with ReLU function has the best performance, and the model converges in the 5th iteration with this function, while the model with Sigmoid function converges in the 36th iteration, and the fitting effect of the rotation model constructed by the study is higher than that of the traditional rotation model. The actual trajectory of the research-constructed rotation model starts to coincide with the expected trajectory at the 5th s of the landing process, while the actual trajectory of the Cheeseman-Bennett model starts to coincide with the expected trajectory only at the 26th s of the landing process. Under the control strategy model proposed in the study, the roll angle and pitch angle of UAV are stabilized at 46s, and the fluctuation of yaw angle is also minimal. The rotation model constructed in the study can completely reflect the rotation process of the small UAV, and the designed control system can help the UAV recover stability faster.

Gait planning and adjustment for a hexapod walking robot with one leg failure

ABSTRACT Gait adjusting is an effective way to solve leg failure problems and is also the foundation of intelligent self-adjustment. This paper takes a hexagonal type of robot as a prototype and proposes a ‘2-2-1’ gait grouping and gait sequence for the one leg failure case based on the ‘4 + 2’ gait. The longitudinal stability margin is used to evaluate the FLF-A and FLF-B gaits with left front leg failure and FLM-A and FLM-B gait with left middle leg failure. The foothold positions are adjusted by changing the median angle of the stance phase of the body-coxa joint in each leg in order to make sure the centre of gravity is in a stable support polygon. The experiments of the robot walking show that the FLF-A gait and the FLM-B gait are more stable than the FLF-B and FLM-A after adjustment. The pitch and roll angles are maintained within − 3° to 3°, which verify the effectiveness of the stance phase leg median position adjustment strategy. This study could be used to do forward pre-adjustment in the case of one leg failure.

Degradable polyvinyl alcohol/chitosan@carnauba wax superhydrophobic composite membrane for water-in-oil emulsion separation and heavy metal adsorption

At present, many oil-water separation membranes are being developed to purify oily wastewater. However, oily wastewater often contains heavy metal, which are often difficult to dispose during separation. Furthermore, most of the oil-water separation membranes cannot be degraded after scrap, producing pollution to environment. Herein, the polyvinyl alcohol/chitosan@carnauba wax (PCGCW) membrane with heavy metal adsorption and biodegradation performance was acquired by electrospinning and spraying process. The acquired PCGCW membrane had excellent mechanical properties after crosslinking glutaraldehyde (GA). Furthermore, the composite membrane had excellent superhydrophobic property (WCA = 154°) with a rolling angle of 2°, due to the introduction of carnauba wax. Exhilaratingly, for emulsions with surfactant, it had a high separation flux with 19,217 L·m−2·h−1·bar−1 and splendid an oil purity over 99.9 %. Besides, the efficiency of oil purity and separation flux remained stable even after 10 separations. In addition, the PCGCW membrane had the ability to adsorb heavy metals with adsorption capacity of 51–106 mg/g for Cu2+, Fe3+, Co2+ ions. Foremost, the superhydrophobic PCGCW membrane was biodegradable, with degrading 29.76 % within 40 days. The prepared composite membrane had the advantages of low cost, high separation flux, great repeatability, adsorbable heavy metals and degradability, which had a vast application prospect.

Neuroadaptive high-order fully-actuated system approach for roll autopilot with unknown uncertainties

In this paper, a neuroadaptive high-order fully-actuated system approach control scheme incorporating the disturbance observer technique is proposed for the missile roll autopilot, subject to model uncertainties generated by the induced roll moment, along with actuator control efficiency deterioration and external disturbance. To address model uncertainties, the radial basis function neural network is implemented. The external disturbance and approximation error are treated as compound disturbances and estimated by a nonlinear disturbance. To avoid the “differential explosion” inherent in the backstepping technique, the high-order fully-actuated system approach is invoked to track the desired roll angle command. The semi-globally uniformly bounded of the closed-loop system is demonstrated via the Lyapunov method. Numerous simulations under various conditions have been conducted to verify the effectiveness of the proposed roll autopilot.

Research on the Control Method of a 2DOF Parallel Platform Based on Electromagnetic Drive

In this paper, a spatial two-degree-of-freedom (2DOF) parallel platform based on electromagnetic redundant drive and its control method are investigated. The platform is redundantly driven by three electromagnetic-spring conforming branched chains, and the design provides better flexibility and responsiveness than conventional parallel structures. The introduction of the electromagnetic drive alleviates the stresses within the conventional rigid redundant drive structure and reduces the detrimental effects associated with rigid redundancy. In this paper, the structure and equivalent SPU model of the platform are first introduced, with S referring to the kinematic sub, P to the spherical sub, and U to the universal joint. The degrees of freedom of the platform are analyzed, and the inverse kinematic model and velocity Jacobi matrix are derived, so as to derive the relationship between the pitch, roll angles, and length of the gimbal chain, and the relational equation between the angle and the current is further established to realize the electromagnetic control of the parallel redundant platform. The control part is realized as follows. Firstly, the angle information of the platform is obtained from the gyroscope to the microcontroller, the filtered angle is derived through the Untraceable Kalman Filter (UKF), and the angle value can be fused with data by both the mathematical model and PID algorithm to introduce the current value required to achieve the balance and realize the balance. In the simulation part, this paper uses Simulink and Simscape in MATLAB for joint simulation, and by giving the simulated trajectory and the desired trajectory of the joints, the driving force diagrams of the three branched chains based on the Least-Second Paradigm method are derived, and the trajectory error and driving force error are given to validate the reliability of the method of this paper.

Design and Experiment of an Independent Leg-Type Chassis Vehicle Attitude Adjustment System

In response to the current low work efficiency of soil ridge-working machinery, as well as its poor stability, passability, and adaptability, this paper designs an independent leg-type working platform that can autonomously adjust its vehicle attitude through LiDAR scanning in a soil ridge-working environment. The platform, in terms of its mechanism and structural design, adopts dual parallelogram mechanisms, dual lead screw mechanisms, and independent column leg mechanisms, with a maximum adjustable ground clearance of 107 mm and a maximum wheelbase adjustment of 150 mm. A gyroscope is mounted at the center of the platform for attitude adjustment, ensuring the accurate data collection of the ultrasonic ranging module. Moreover, the platform adopts an adaptive adjustment method based on vehicle attitude and soil ridge shape parameters, obtaining soil ridge parameters through LiDAR and combining ultrasonic ranging module data with stepper motor pulse signals to obtain the absolute vehicle attitude parameters, using first and second linear regression methods to adjust the vehicle attitude and other working parameters. A prototype was also created, and the test data from the soil obtained through experiments show that, after leveling with the gyroscope leveling algorithm, the average value of the pitch angle is up to 0.6154°, and the average value of the roll angle is up to 0.9989°, with the maximum variance of the pitch angle being 0.0474° and the maximum variance of the tilt angle being 0.1320°. After the ultrasonic ranging module data are filtered by the Kalman filter, the maximum variance is 0.0304, and after applying the final fusion algorithm, the maximum variance is only 0.0085. The LiDAR measurement width value deviates from the actual width value by no more than 1.0 cm, and the LiDAR measurement height value deviates from the actual height value by no more than 1.0 cm. The platform’s actual adjusted width deviates from the actual soil ridge width by no more than 2.0 cm, and the platform’s actual adjusted height deviates from the actual soil ridge height by no more than 1.2 cm. This platform can improve the passability, adaptability, and stability of agricultural machinery in soil ridge work and provide technical references for subsequent related research.

Fabrication of a Hydrophilic Al2O3/AlN EP Coating with Self‐Cleaning and High‐Efficiency Anti‐Corrosion Properties

AbstractCurrently, with the gradual development of anticorrosive coatings, the pursuit of simple preparation methods and the improvement of anticorrosive coatings’ properties have become the major research trends. This study successfully prepared a hydrophilic super anticorrosive coating through a simple mixing method. The coating has a contact Angle of 67.8° and a rolling Angle greater than 20°. This coating can withstand 180 days of salt spray test with no bubble or rust formation when placed on a Q 235 substrate in a 3.5 wt % NaCl solution, demonstrating the excellent corrosion resistance of the AO0.4AN0.6EP coating. Furthermore, after being immersed in a 3.5 wt % NaCl solution for 3 days, the AO0.4AN0.6EP coating exhibited the largest impedance diameter (2.07×108 Ω⋅cm2), almost three times larger than other coatings, and possessed the highest Bode modulus value, one order of magnitude higher than other coatings. After immersion in a 3.5 wt % NaCl solution for 7 days, the AO0.4AN0.6EP coating had the largest Ecorr and the smallest icorr, indicating its superior corrosion resistance. In addition to corrosion resistance, the AO0.4AN0.6EP coating showed no signs of cracking, discoloration, or decomposition after being exposed to ultraviolet aging lights for 30 days, demonstrating its excellent UV resistance. Moreover, neither dry soil particles nor muddy water could adhere to the coating surface, proving its good self‐cleaning ability. Therefore, this coating holds promising applications in the field of super corrosion‐resistant coatings.