Flight Parameters Research Articles

Winging it: hummingbirds alter flying kinematics during molt.

Hummingbirds are well known for their hovering flight, one of the most energetically expensive modes of locomotion among animals. Molt is a costly event in the annual cycle, in which birds replace their feathers, including all their primary feathers, which, in hummingbirds, comprise most of the area of the wing. Despite this, the effects of molt on hovering flight are not well known. Here, we examined high-speed videos (14 individuals of three species from the Colombian Andes recorded at 1200 frames per second) comparing molting and non-molting hummingbirds' wing kinematics and wingtip trajectories. We found that molting hummingbirds rotated their wings in more acute angles during both downstroke and upstroke compared to non-molting individuals (10° versus 20°, and 15° versus 29°, respectively), while other flight parameters remained unchanged. Our findings show that hummingbirds are capable of sustaining hovering flight and thereby maintaining their weight support even under impressive wing area reductions by adjusting their stroke amplitudes.

Crack Propagation Tests for Load Sequences Developed Using Different Flight Parameters of a Trainer Aircraft

Abstract Military aircraft are subjected to highly variable and unpredictable loads due to diverse mission profiles, armament configurations, and individual piloting styles. This variability complicates the definition of precise load spectra, particularly in cases where data loss occurs due to Flight Data Recorder (FDR) malfunctions or data mishandling. This paper investigates the use of different flight parameters, such as load factor (nz ), barometric height (Hb ), and horizontal velocity (Vp ), to define load sequences for the PZL-130 “Orlik” TC-II military trainer aircraft. These sequences were then used to evaluate crack propagation using Compact Tension (CT) specimens. The results show that the incorporation of additional flight parameters improves the accuracy of crack propagation predictions when compared to direct strain measurements. This study highlights the potential of using available flight data to develop reliable load spectra for fatigue life estimation in military aircraft, even when direct load measurements are not financially feasible.

Marking Helicoverpa zea (Lepidoptera: Noctuidae) with fluorophores for use in mark-release-recapture research

Abstract Knowledge of insect dispersal and long-distance migratory flight capacity and patterns represent key factors needed for risk assessment of invasive pest species, insecticide resistance management, and more effective pest control. Having operative tools to both mark and track insect pest movement is therefore critical to achieving such goals. Here, we describe a new procedure for marking Helicoverpa zea (Boddie) (Lepidoptera: Noctuidae), one of the most economically important crop pests in the United States. Adult H. zea moths were effectively marked using the liquid fluorophore cartax green, a persistent UV-fluorescent pigment, both directly by topical application and indirectly by briefly submerging pupae in the marking solution prior to adult emergence. Regardless of the application method, the cartax mark was retained on the moths throughout their entire adult lifespan. No mortality differences were observed between cartax green-marked and water-marked (control) moths. Additionally, using rotary flight mills, we found no significant differences in several flight parameters, including total number of flights, flight speeds, flight distances, or flight durations between unmarked and cartax-marked moths. Under laboratory conditions, we did observe the lateral transfer of different colored fluorophores between moths, indicating that undesirable marking could potentially occur. Moreover, we found that not all fluorophores were equally retained on H. zea moths, with cartax green remaining intact on moths longer than did a corresponding magenta fluorophore. The results show that cartax green fluorophore could be a practical marker for H. zea and other holometabolous species targeted for large-scale mark-release-recapture research.

Redundancy Design of FADS System for Complex Leading- Edge Aircraft Based on Neural Network

The flush airdata sensing system (FADS) calculates flight parameters such as angle of attack, sideslip angle, Mach number, incoming flow pressure and static pressure based on the pressure measurement of the aircraft surface. It can effectively solve the problem that the leading edge of the pitot tube protruding from the fuselage cannot adapt to the severe aerodynamic heating faced by hypersonic aircraft during the cruise phase, and at the same time meet the aircraft's demand for stealth performance. At present, there is little analysis and research on the use of neural network methods and FADS systems for complex leading edge aircraft. In view of the subsonic/transonic conditions of hypersonic aircraft returning autonomously during the landing phase, the redundancy design and verification of the head FADS system of complex leading edge aircraft are carried out considering the influence of thin leading edge and inlet components. 15 pressure measuring holes are opened in the head of the complex leading edge aircraft. Through a large number of refined numerical simulations, the pressure database of the aircraft under different incoming flow conditions is established, and the typical working conditions are verified by wind tunnel tests. For the complex leading edge aircraft, 4 sets of neural network algorithms are established based on pressure data and redundant design research is carried out, including 1 set of 9-hole algorithm and 3 sets of redundant algorithms. Among them, the 9-hole algorithm has a higher accuracy, with the solution error of the angle of attack within 0.07∘, the solution error of the sideslip angle within 0.3∘, the solution error of the Mach number within 0.0012, and the relative error of the solution of the incoming flow pressure and static pressure within 1.5%. In addition, a system solution process with a certain fault tolerance was established, which can continue to maintain the effective output of the incoming flow parameters in the event of failure of any single pressure measuring hole.

Adaptive hierarchical energy management strategy for fuel cell mobile robot hybrid power system based on working condition recognition

Energy management of hybrid power is critical to maintain the economical and efficient operation of fuel cell mobile robots. To improve the energy distribution between the proton exchange membrane fuel cell (PEMFC) and battery under different working conditions, this paper proposes an adaptive hierarchical energy management strategy (AHEMS) based on the recognition and management levels. Firstly, the recognition level realizes the identification of different working conditions based on the machine learning (ML) methods including the K-means and KNN. Secondly, the fuel cell hydrogen consumption and efficiency are both optimized by adaptive multi-objective particle swarm optimization (AMOPSO) at the management level. Specifically, an adaptive flight parameter strategy based on the particle dispersity (PD) information is proposed to balance the convergence and diversity of Pareto solutions. Besides, to overcome the parameter uncertainty caused by different working states and improve the system performance, an interval optimization scheme is proposed based on the Pareto solutions. Finally, the fuzzy decision combined with the recognition results and state of charge (SOC) of the battery is performed to find the most appropriate power distribution of the PEMFC and battery. The proposed AHEMS algorithm is compared with different algorithms in the numerical simulation and hardware-in-loop (HIL) experiments. These results demonstrate that the hybrid power system with the proposed optimization scheme performs better than the base model and classical optimization algorithms in terms of the hydrogen consumption and efficiency indexes, revealing the success of this AHEMS approach in solving the energy distribution problem in different working conditions.

Acquisition of Flight Data from Mini Unmanned Aerial Systems

Swift progress in unmanned aerial vehicle (UAV) system technology mandates effective real-time monitoring and accurate flight data capture for building an optimum target-based cutting-edge UAVs. In the current epoch of modern-UAV era, small size and mission-oriented UAV prototypes are increasingly pervasive. This study highlights the design of a data acquisition target-based mini-UAV and introduces a novel telemetry software solution to safe and reliable communication between mini-UAV and ground control station (GCS). The primary aim is to demystify the proposed wireless communication software solution on mini-UAV capability in obtaining and managing comprehensive flight data. While creating the appropriate target-based mini-UAV prototype architecture, the features that we aim to realize for the UAV components are addressed with a system approach and the component selection is presented in detail. The integration point of the selected components is conveyed in general terms. Thus, a guiding resource for future UAV studies will be presented. Then, the processes of obtaining the flight data of mini-UAVs will be addressed. At this point, the design logic of the required commands and background software will be conveyed. Obtaining the flight data of mini-UAVs will provide important scientific contributions to the literature in terms of aviation research and safety analysis. Obtaining the flight data of mini-UAVs will meet the data set needs for flight safety improvements and air traffic management optimization studies. A general analysis of the flight parameters obtained as a result of obtaining the flight data will be performed, the predictability of the parameters will be evaluated, and the analysis of the flight phases will be performed by presenting the relationships of the parameters according to the flight scenarios and the sections taken from the parameter set in the study. This study can be considered as a concrete example of situational monitoring of UAVs.

The Behavioral Responses of Geoffroy’s Spider Monkeys to Drone Flights

Drones are increasingly used for monitoring wildlife, and it is therefore necessary to evaluate their impact on animal behavior. According to the landscape of fear framework, animals assess and respond to perceived risks in their environment by adjusting their behavior and space use to avoid potential threats. Understanding how drones influence risk perception is thus crucial to avoid generating stress and altering the animal’s natural behavior. Geoffroy’s spider monkeys (Ateles geoffroyi) are endangered arboreal primates, but information on their distribution and abundance is scarce throughout their geographical distribution. Drones can aid to rapidly obtain such information, but data of their impact on the monkeys are needed to design surveys that minimize disturbance (i.e., any interference or modification of the natural behavior of the monkeys caused by the presence and operation of drones). Here, we evaluated whether drone flights influenced the following spider monkey behaviors: agonistic displays, self-scratching, whinny vocalizations, feeding, resting, social interactions, and moving. We also evaluated the effect of three flight parameters, flight height (35, 50 m above ground level), speed (2, 4 m/s), and distance to the drone (“close”, “medium”, and “far”) on spider monkey behavior and examined whether repeated exposure to drones resulted in tolerance (i.e., lack of a behavioral response). We found that drone flights influenced only agonistic displays and resting and that the only flight parameter affecting behaviors was the distance between the monkeys and the drone. We found that spider monkeys developed a tolerance to drone flights only for agonistic displays. Based on our results, we suggest that spider monkeys do not perceive drone flights as major sources of disturbance (such as predators) in the short term, and that drone monitoring can be a viable option to study this species if adequate flight protocols are implemented.

Density-guided and Adaptive Update Strategy for Multi-objective Particle Swarm Optimization

Abstract As a powerful optimization technique, multi-objective particle swarm optimization (MOPSO) has been paid more and more attention by scientists. However, in more complex problems, MOPSO faces the challenges of weak global search ability and easy to fall into local optimality. To address these challenges and obtain better solutions, people have proposed many variants. In this study, a density-guided and adaptive update strategy for multi-objective particle swarm optimization (DAMOPSO) is proposed. First, an adaptive grid is used to determine the mutation particles and guides. Then the Cauchy mutation operator is performed for the poorly distributed particles to expand the search space of the population. Additionally, the strategy of non-dominated sorting and hyper-region density are devised for maintaining external archives, which contribute to the uniform distribution of optimal solutions. Finally, an adaptive detection strategy based on the adjustment coefficient and conversion efficiency is designed to update the flight parameters. These approaches not only speed up the convergence of algorithms, but also balance exploitation and exploration more effectively. The proposed algorithm is compared with several representative multi-objective optimization algorithms on 22 benchmark functions; meanwhile, statistical tests, ablation experiments, analysis of stability and complexity are also performed. The experimental results demonstrate DAMOPSO is more competitive than other comparison algorithms.

Design and Development of a Side Spray Device for UAVs to Improve Spray Coverage in Obstacle Neighborhoods

Electric multirotor plant protection unmanned aerial vehicles (UAVs) are widely used in China for efficient and precise plant protection at low altitude for low volumes. Unstructured farmland in China has various types of obstacles, and UAVs usually use a detour path to avoid obstacles due to flight altitude limitations. However, existing UAV spray systems do not spray when in obstacle neighborhoods during obstacle avoidance, resulting in insufficient droplet coverage and reduced plant protection quality in the area. To improve the droplet coverage in obstacle neighborhoods, this article carries out a study of side spray technology with an electric quadrotor UAV, and proposes the design and development of a side spray device. The relationship between the obstacle avoidance path of the UAV and the spray pattern of the side spray device and their effect on droplet coverage in obstacle neighborhoods was explored. An accurate measurement method of the relative position between the UAV and obstacles was proposed. Spray angle calculations and nozzle selection for the side spray device were carried out in conjunction with the relative position. A rotor wind field simulation model was designed based on the lattice Boltzmann method (LBM), and the spatial layout of the side spray device on the UAV was designed based on the simulation results. To explore suitable spray patterns for the side spray device, comparative experiments of droplet coverage in obstacle neighborhoods were carried out under different environments, spray patterns, and flight parameter combinations. The relationship between the flight parameter combinations and the distribution uniformity of droplets and the effective swath width of the side spray device was explored. The experimental results were analyzed by an analysis of variance (ANOVA) and a relationship model was obtained. The results showed that the side spray device can effectively improve droplet coverage in obstacle neighborhoods compared to a device without side spray using the same flight parameter combinations. The effective swath width in obstacle neighborhoods can be increased by a minimum of 6.35%, maximum of 35.32%, and average of 15.25% using the side spray device. The error between the predicted values of the relational model and the field experiment results was less than 15%. The results verify the effectiveness and rationality of the method proposed in this article. This study can provide technical and theoretical references for improving the plant protection quality of UAVs in obstacle environments.

Evaluating Thermal Infrared Drone Flight Parameters on Spider Monkey Detection in Tropical Forests.

Geoffroy's spider monkeys, an endangered, fast-moving arboreal primate species with a large home range and a high degree of fission-fusion dynamics, are challenging to survey in their natural habitats. Our objective was to evaluate how different flight parameters affect the detectability of spider monkeys in videos recorded by a drone equipped with a thermal infrared camera and examine the level of agreement between coders. We used generalized linear mixed models to evaluate the impact of flight speed (2, 4, 6 m/s), flight height (40, 50 m above ground level), and camera angle (-45°, -90°) on spider monkey counts in a closed-canopy forest in the Yucatan Peninsula, Mexico. Our results indicate that none of the three flight parameters affected the number of detected spider monkeys. Agreement between coders was "substantial" (Fleiss' kappa coefficient = 0.61-0.80) in most cases for high thermal-contrast zones. Our study contributes to the development of standardized flight protocols, which are essential to obtain accurate data on the presence and abundance of wild populations. Based on our results, we recommend performing drone surveys for spider monkeys and other medium-sized arboreal mammals with a small commercial drone at a 4 m/s speed, 15 m above canopy height, and with a -90° camera angle. However, these recommendations may vary depending on the size and noise level produced by the drone model.

Risk Assessment of Bird Collisions with a Wind Turbine Based on Flight Parameters

The study addresses the challenge of bird collisions with wind turbines by developing an autonomous risk assessment method. The research uses data from the stereoscopic Bird Protection System (BPS) to anticipate potential collision threats by analysing flight parameters and distance from turbines. The danger factor depends on the flight characteristics of the identified bird species and the parameters of the wind turbine control system. The paper proposes an online quantitative risk assessment model that operates in real time, with the aim of minimising unnecessary turbine shutdowns while improving bird conservation. The model is validated through field data from bird flights. The findings suggest that adaptive management of turbine operations based on real-time bird flight data can significantly reduce collision risks without compromising energy production efficiency. The research underscores the balance between ecological considerations and the economic viability of wind energy, proposing an adaptive strategy that reduces unnecessary turbine stoppages while ensuring the safety of avian species.

Stability of Single-Channel Homing Rolling Aerospace Vehicle

This paper aims to analyze the stability of a special class of single-channel slow-rotating homing missiles using the Frank–Wall stability criterion. To achieve this, starting from the model of a slow-rolling missile with six degrees of freedom (6 DOFs) in the body frame, a 6-DOFs model in the Resal frame is obtained, which is used to linearize the coupled commanded motion. Based on the linearized model, we obtain the structural scheme of the commanded object and define the flight quality parameters. The obtained linear model has a complex representation (with real and imaginary parts) due to the coupling between longitudinal channels for the rolling missile. Then, the kinematic guidance equations, the seeker equations and the actuator relations using a switching function, specific to the slow-rolling single-channel missile, are defined. The guidance kinematic equations, the seeker equations and the actuator model are linearized in the Resal frame, and the structural diagram of the homing missile is constructed. Starting from this, the characteristic polynomial having complex coefficients is determined and then analyzed with the Frank–Wall stability criterion. Based on the analysis, a stability range is determined for the navigation constant (k), and a minimum and possibly a maximum limit for the time to hit the target tgo is obtained. The stability range defined for the navigation constant in the linear model is finally validated in the nonlinear model in the body frame.

Angle-of-attack and angle-of-sideslip estimation and complementary filter design for civil aircraft

Angle-of-Attack (AOA) and angle-of-sideslip (AOS) are critical flight parameters affecting the flight safety, and their accuracy and reliability directly impact the operating status and performance of some significant airborne systems. To enhance the redundancy and accuracy of AOA and AOS, this article investigates the problem of the airflow angles estimation and complementary filter design for civil aircraft. Specifically, an extended Kalman filter based AOA and AOS estimation method considering acceleration correction is developed to increase the redundancy. Subsequently, a novel inertial AOA and inertial AOS calculation method using attitude angles, azimuth angle, and flight path angle is introduced, and two schemes for designing the discrete complementary filter based on Tustin transform are presented to improve the accuracy. Through simulations, the developed algorithms are verified, and the results illustrate that the AOA estimation error is within ± 0.6°, and the AOS estimation error is within ± 0.3°.

Flight behaviour of Red Kites within their breeding area in relation to local weather variables: Conclusions with regard to wind turbine collision mitigation

Abstract Birds and bats are prone to collisions with wind turbines. To reduce the number of bat collisions, weather variables are commonly used to shut down wind turbines when a certain constellation of weather variables occurs. Such a general approach might also be interesting to mitigate raptor collisions. Studies on the relationship between flight behaviour and weather variables are needed. To investigate the flight behaviour of raptors within their breeding area in relation to local weather variables, we used high resolution data of flight tracks of Red Kites collected on a wind energy test site (Germany). Birds were tracked with a laser range finder (LRF) or with Global Positioning System (GPS) transmitters. Weather variables were continuously registered on site. We used generalised linear mixed models to analyse the influence of weather variables and of the measurement method on different flight parameters. Furthermore, we investigated the probability of flying within a virtual rotor height range defined by three hub heights (84, 94 and 140 m; diameter: 112 m). The median flight altitude measured by LRF (52.5 m, 95% CI: 44.9–61.0, N = 2511) was on average 25 m higher than the corrected one resulting from GPS (27.8 m, 95% CI: 24.7–31.2, N = 6792). Flight speed also differed between methods (GPS: 29.2 km/h, 95% CI: 28.2–30.3 km/h; LRF: 25.1 km/h, 95% CI: 24.0–26.3 km/h). The effects of the weather variables were weak. Birds tended to fly less and lower during wet (humid, rainy or foggy) than dry weather, and lower during strong than weak winds. Probabilities of flying within a height range of virtual rotors increased with decreasing hub height, and hence ground clearance. Synthesis and applications: Flight behaviour was highly variable. Flights occurred during all weather conditions at different altitudes throughout the day over the entire season. Further research into the relationship between flight behaviour, weather variables, collisions and other factors is needed as a basis for developing shutdown regimes generally suitable for raptors. The mean flight altitude and speed differed between the measurement methods. Any values resulting from studies should be interpreted in the context of the method.

Customised Octacopter Drone-based Magnetic Survey for Exploration of Mn-Fe ores in Sidhan Area, Jabalpur District, Madhya Pradesh, India

Encouraged by Digital Initiatives of the Government of India and NMDC’s Version 2.0 plans, we have carried out Magnetic Survey and Hyperspectral Remote Sensing using Unmanned Aerial System (UAS) for the first time in India for Mineral Exploration. This paper briefly presents the findings of the Unmanned Aerial Vehicle (UAV; Customised Octacopter Drone) magnetic survey to explore Mn-Fe ores in Sidhan Block, Jabalpur District, Madhya Pradesh, India. The specifications of the UAV, flight parameters and magnetometer used for mineral exploration are also discussed in this paper.

Optimization of flight conditions based on performance sensitivity analysis for jet transport aircraft

PurposeThis study aims to enhance the fuel efficiency of jet transport aircraft based on mathematical models and flight crew operating manual (FCOM) for the purpose to assist the civil aviation industry in improving flight safety and operational efficiency.Design/methodology/approachThe research applies flight data mining and fuzzy logic modeling technologies to set up lift-to-drag ratio (L/D) models and nine models of thrust, Mach number, engine pressure ratio and fuel flow rate to estimate the deviation of each flight parameter. All performance deviations are calculated based on the values of flight data recorded in the quick access recorder and FCOM at the observed flight conditions. The L/D model can obtain the influence of each flight parameter and estimate the insufficient amount of each parameter by averaging it with the least square method. In the estimation of optimal altitude, nine models are built based on data from FCOM to estimate the optimal altitude and complete comparative analysis of the airspeed, Mach number and fuel flow rate at the optimal altitude.FindingsAnalyze 11 relevant parameters from the sensitivity derivative of L/D model to obtain how each parameter affected fuel consumption and explore the causes of additional fuel consumption. Complete the estimation of the optimal cruise altitude of the aircraft, and calculate the comparative analysis of the altitude, speed, Mach number and other parameters with the sensitivity derivative of the L/D. The estimation of the optimal cruise altitude of the aircraft can meet the analysis of the sensitivity derivative.Research limitations/implicationsThis study is to enhance the fuel efficiency of jet commercial transport based on mathematical model and FCOM. FCOM is required to conduct this study. The estimation of the optimal cruise altitude through the nine models of the aircraft could meet the analysis of the sensitivity derivative.Practical implicationsThe object of present research is to demonstrate the effectiveness of optimization of flight conditions through model analysis to get knowledge of the effects of each influencing flight variable to L/D for future flight operations’ reference.Social implicationsThe model-based derivative analysis had the ability to perform derivative prediction analysis on any input parameters, more flight parameters could be optimized in future research to help airlines improve flight safety and operational efficiency.Originality/valueThe present enhancement method of fuel efficiency is an innovation to examine the abnormal aircraft performance and its flight operations, thereby to explore the causes of additional fuel consumption. The present method can become an auxiliary tool for flight operations quality assurance to improve fuel efficiency for the airlines.

Evaluating the transferability of airborne laser scanning derived stem size prediction models for Pinus taeda L. stem size estimation to two different locations and acquisition specifications

ABSTRACT Airborne laser scanning (ALS) datasets are used widely for estimating forest biometrics. The transferability of predictive models among ALS acquisitions is a topic of research due to differences in timing, flight parameters, equipment specifications, environmental conditions, and processing methods. The transferability of predictive models therefore is subject to uncertainty. This paper presents an evaluation of the transferability of models for the estimation of stem volume and diameter at breast height (DBH) based on individual tree crown size and competitive neighbourhood metrics derived for managed loblolly pine (Pinus taeda) and slash pine (Pinus elliottii) forest in the Southern USA. Two predictive models types were tested: multiple linear regression (MLR) and Rand Forest (RF). We also evaluated the inclusion of additional training data to model development. Models were able to be transferred to other locations with similar structural and management conditions as the original training dataset with little decrease in accuracy, specifically unthinned stands, despite different ALS acquisitions (Plot stem volume: R2 0.7–0.8; NRMSE 10–12%; mean DBH: R2 0.4–0.7; NRMSE 10–17%; plot basal area: R2 0.7–0.8; NRMSE 12%). Increases in structural differences between the training and test data, driven by age or thinning status, introduced unacceptable levels of uncertainty (Stem volume: R2 0.4–0.7; NRMSE 12–16%; mean DBH: R2 0.4–0.5; NRMSE 18–20%; plot basal area: R2 0.5–0.6; NRMSE 22–40%). Generally, RF models most accuracy estimated DBH, and MLR for stem volume. Improvements to estimate accuracy can be achieved through the addition of relatively small datasets, representing features which were not present in the original data. ALS’s ability to provide accurate and near-complete inventories of forests hold a great deal of potential for forest management. The existence of a transferable model that can be used across different acquisitions represents a saving in terms of cost and time, we would argue that future research is therefore warranted.

Optimizing UAV spray parameters to improve precise control of tobacco pests at different growth stages.

Unmanned aerial vehicles (UAVs) for pesticide application show promising potential in tobacco pest management. However, the impact of flight parameters on spray efficacy requires further investigation. Three field experiments were conducted from the rosette to the maturation stage of tobacco to systematically assess spray efficacy under varying flight heights, speeds, and application volumes. Using a multi-index weight analysis method, optimal operational parameter combinations for different tobacco growth stages were evaluated and compared with backpack electric sprayers. For the rosette stage, the recommended parameter is a flight speed of 5 m s-1, a flight height of 2 m, and a liquid application volume of 30 L hm-2; during the vigorous growth stage, the suggested parameter includes a flight speed of 3 m s-1, a flight height of 2 m, and a liquid application volume of 22.5 L hm-2. In the maturing stage, optimal parameter consists of a flight speed of 3 m s-1, a flight height of 3.5 m, and a liquid application volume of 30 L hm-2. Furthermore, UAV spraying achieves higher droplet deposition on both sides of tobacco leaves compared to traditional electric backpack sprayers. Adjusting UAV spraying parameters for different tobacco growth stages is crucial. These results can provide the methods for the precise control technology of tobacco pests at different growth stages. © 2024 Society of Chemical Industry.

Autonomous UAV Safety Oriented Situation Monitoring and Evaluation System

In this paper, a LabVIEW-based online monitoring and safety evaluation system for UAVs is designed to address the deficiencies in UAV flight state parameter monitoring and safety evaluation. The system consists of a lower unit for UAV recording and an upper unit on the ground. The lower unit collects and detects flight data and connects to the upper unit through a wireless digital transmission module via a serial port. The upper unit receives the data and carries out the monitoring and safety situation evaluation of the UAV. The lower unit of the system adopts multi-sensors to collect UAV navigation information in real time to achieve flight detection, while the upper unit adopts LabVIEW to design the UAV online monitoring and safety situation prediction system, enabling monitoring and safety situation prediction during UAV navigation. The test results show that the system can detect and comprehensively display the navigation information of the UAV in real time, and realize the safety evaluation and warning function of the UAV.

Reliability and validity of "My Jump 2" application for countermovement jump free arm and interlimb jump symmetry in different sports of professional athletes.

Vertical jumping is an important evaluation tool to measure muscle strength and power as well as lower limb symmetry. It is of practical importance and value to develop and utilize a portable and low-cost mobile application (APP) to evaluate jumping. The "My Jump 2" app is an iPhone camera-based application for measuring jumping movements, which is applied to the countermovement jump (CMJ) vertical jumps of the lower limbs of athletes in different sports. The validity of this application and previous versions applied to different forms of vertical jump tests has been preliminarily demonstrated in different population, which has an obvious progress in research. Therefore, the reliability and validity of the jump height, time of flight parameters and symmetry of the CMJ vertical jump of athletes in different sports are needed to be verified by more experiments. The purpose of this study is to verify whether "My Jump 2" can effectively and reliably assess jump height, flight practice and lower limb symmetry in CMJAM (countermovement jump free arm) tests in fencing, swimming and diving athletes. Seventy-nine fencers, swimmers and divers with training experience participated in this study. They completed a total of three CMJAM vertical jump and lower limb symmetry tests in 1 day, while being assessed by using the "My Jump 2" application and a force platform. The intra-group correlation coefficient (ICC) was used to verify reliability, while the Cronbach's alpha and coefficient of variation (CV%) was used to analyze the stability of the CMJAM vertical jump test over three jumps. The Pearson correlation coefficient was used to verify the strength of the relationship between methods (i.e., concurrent validity), and the Bland-Altman plot was used to represent consistency, meanwhile, the t-test was used to determine the systematic bias between methods. Compared with the force platform, the cumulative height values of the total number of jumps (r = 0.999; p = 0.000), the cumulative time to vacate (r = 0.999; p = 0.000) for the CMJAM test obtained by the "My Jump 2" application, the height (ICC = 0.999-1, p = 0.000), the time to vacate flight (ICC = 0.999-1, p = 0.000), contact time symmetry (ICC = 0.976-0.994, p = 0.000), and flight time symmetry (ICC = 0.921-0.982, p = 0.000), respectively. Showed high correlation between the results of "my jump 2" app and the force platform. The "My Jump 2" application is a valid tool to assess CMJAM vertical jump and lower limb symmetry in fencing, swimming and diving athletes with training experience.