Dynamic Characteristics Research Articles

Study on the Effect of Cracks in Diaphragm Couplings on the Dynamic Characteristics of Shaft System

Diaphragm couplings are prone to developing diaphragm cracks under prolonged high-speed operating conditions, which can lead to degradation in the performance of the transmission system and affect the dynamics of the shafting system. To investigate the effects of diaphragm cracks on the dynamics of couplings and the shafting system, a finite element model of a diaphragm coupling with a crack failure is established using ANSYS finite element software to analyze the time-varying characteristics of the diaphragm coupling’s angular and radial stiffness. A shaft dynamics model of the diaphragm coupling with a crack is developed using Timoshenko beam elements to analyze the impact of different crack lengths and locations on the dynamics of the shafting system. The validity of the dynamic model for a diaphragm coupling with a crack is verified through a constant speed experiment conducted on a rotor test bench. The results indicate that diaphragm crack failure causes a change in the periodicity of the time-varying stiffness of the diaphragm coupling, leading to a distinct 2× component appearing in the frequency domain of the transmission shaft system.

Android Malware Detection Using Support Vector Regression for Dynamic Feature Analysis

Mobile devices face significant security challenges due to the increasing proliferation of Android malware. This study introduces an innovative approach to Android malware detection, combining Support Vector Regression (SVR) and dynamic feature analysis to address escalating mobile security challenges. Our research aimed to develop a more accurate and reliable malware detection system capable of identifying both known and novel malware variants. We implemented a comprehensive methodology encompassing dynamic feature extraction from Android applications, feature preprocessing and normalization, and the application of SVR with a Radial Basis Function (RBF) kernel for malware classification. Our results demonstrate the SVR-based model’s superior performance, achieving 95.74% accuracy, 94.76% precision, 98.06% recall, and a 96.38% F1-score, outperforming benchmark algorithms including SVM, Random Forest, and CNN. The model exhibited excellent discriminative ability with an Area Under the Curve (AUC) of 0.98 in ROC analysis. The proposed model’s capacity to capture complex, non-linear relationships in the feature space significantly enhanced its effectiveness in distinguishing between benign and malicious applications. This research provides a robust foundation for advancing Android malware detection systems, offering valuable insights for researchers and security practitioners in addressing evolving malware challenges.

Motor delay image recognition based on deep learning and human skeleton model

Children with developmental delays often exhibit gross motor delay during their early childhood. Identifying such delay typically requires standardized assessments, but these assessments are susceptible to subjective interpretation. To enhance objectivity and reliability in these assessments, this study proposes a novel method utilizing an AI model for identifying gross motor delay in children. The proposed method divides the assessment of gross motor skills into two components: static balance and dynamic balance. First, the Yolo target detection model and the Mediapipe human posture detection model are employed for preprocessing to determine skeletal joints and body positioning information. Subsequently, dimensionality reduction techniques are applied to extract key features. A sliding window method is then used to extract action features identifying static balance features of the human body (e.g., standing on one foot, standing on the left foot) and dynamic balance features (e.g., lifting the heels while walking, jumping on a mat). The machine learning classifier and LSTM-CNN are then used to categorize the static and dynamic balance feature data. Experimental results demonstrate that the proposed method achieved accuracy scores of 80 % and 87 % for static and dynamic balancing skills, respectively.

A fin-gate p-GaN HEMT with high threshold voltage and improved dynamic performance

A novel fin-gate p-GaN (FPG) HEMT is proposed to simultaneously increase threshold voltage (Vth) and improve dynamic performance of the p-GaN HEMT. The fin-gate structure works as a normally-on p-channel MESFET between gate and source by forming a Schottky-type contact on sidewall and a source-connected Ohmic-type contact on top of the fin. Thus, the Vth can change with the shutdown voltage of the p-channel MESFET, which can be modulated by the doping concentration and width of the fin-p-GaN. By optimizing the fin structure, a high positive Vth of 4V is achieved without transconductance and breakdown voltage degradation in this work. It breaks the restriction between Vth and on-resistance for conventional p-GaN HEMT. The dynamic characteristics of the FPG HEMT are investigated by SPICE simulations. Owing to the well-grounded p-GaN through the normally-on MESFET, the recovery process of the dynamic shift in Vth (ΔVth) after on/off-state stress can be accelerated by two orders of magnitude. It means an imperceptible dynamic degradation and a great potential in high frequency application for the FPG HEMT.

Quality-related fault detection for dynamic process based on quality-driven long short-term memory network and autoencoder

Fault detection consistently plays a crucial role in industrial dynamic processes as it enables timely prevention of production losses. However, since industrial dynamic processes become increasingly coupled and complex, they introduce uneven dynamics within the collected data, posing significant challenges in effectively extracting dynamic features. In addition, it is a tricky business to distinguish whether the fault that occurs is quality-related or not, resulting in unnecessary repairing and large losses. In order to deal with these issues, this paper comes up with a novel fault detection method based on quality-driven long short-term memory and autoencoder (QLSTM-AE). Specifically, an LSTM network is initially employed to extract dynamic features, while quality variables are simultaneously incorporated in parallel to capture quality-related features. Then, a fault detection strategy based on reconstruction error statistic squared prediction error (SPE) and the quality monitoring statistic Hotelling T2 (H2) is designed, which can distinguish various types of faults to realize accurate monitoring for dynamic processes. Finally, several experiments conducted on numerical simulations and the Tennessee Eastman (TE) benchmark process demonstrate the reliability and effectiveness of the proposed QLSTM-AE method, which indicates it has higher accuracy and can separate different faults efficiently compared to some state-of-the-art methods.

Dynamic behavior and transfer characteristics of CO2-enriched bubbles within Spirulina sp. suspension under various aeration conditions using the high-speed imaging technique

The biological CO2 fixation method through microalgae photosynthesis has received considerable attention to alleviate the trend of global warming. CO2-enriched gas is generally aerated into the microalgae suspension in the form of bubbles through the gas distributors. Dynamic behavior and transfer characteristics of CO2-enriched bubbles are crucial to microalgae cells growth and CO2 bio-fixation. A visual experimental system based on the high-speed camera was constructed in this work to obtain the dynamic behavior and transfer characteristics of CO2-enriched bubbles within Spirulina sp. suspension. CO2-enriched bubbles movement and dissolution characteristics were comprehensively investigated under various CO2 concentrations, gas distributor aperture size, aeration rates, and Spirulina sp. biomass densities. Experimental results indicate that the optimal CO2 dissolution mass transfer and absorption rate were attained under the CO2 concentration of 5 %, gas distributor aperture diameter of 10 μm, and aeration rate of 0.1–0.3 vvm. Moreover, as Spirulina sp. biomass density increased, the bubble average diameter decreased, and rising velocity slowed while the volumetric mass transfer coefficient and CO2 absorption rate elevated. To summarize, this work may guide future efforts to enhance the photobioreactors (PBRs) performance from the perspective of aeration conditions optimization.

Visual SLAM system based on dynamic semantic features

Aiming at the problem that dynamic objects (such as pedestrians, vehicles, and animals) in real scenes affect the positioning and mapping accuracy of visual SLAM (Simultaneous Localization and Mapping), a YOLOv3-ORB-SLAM3 algorithm is proposed based on ORB-SLAM3 (Oriented FAST and Rotated BRIEF-Simultaneous Localization and Mapping 3). The algorithm adds a semantic thread on the basis of ORB-SLAM3, and adopts a dual-thread mechanism for dynamic and static scene feature extraction: the semantic thread uses YOLOv3 to perform semantic recognition target detection on dynamic objects in the scene, and removes outliers from the extracted dynamic area feature points; the tracking thread extracts scene area features through ORB features, and obtains static scene features combined with semantic information and sends them to the backend, thereby eliminating the interference of dynamic scenes on the system and improving the positioning accuracy of the visual SLAM algorithm. Verified using the TUM (Technical University of Munich) dataset, the results show that the ATE (Average Treatment Effect) index of the YOLOv3-ORB-SLAM3 algorithm in the monocular mode is about 30% lower than that of the ORB-SLAM3 algorithm, and the ATE index of the dynamic sequence in the RGB-D (Red, Green and Blue-Depth) mode is reduced 10%, while the static sequence has no significant decrease.

Design and analysis of folding mechanism for automotive seats based on space maximization

To solve the problem of maximizing space utilization of car folding seats within limited spatial constraints, a design method for space-maximizing four-bar folding seat hinges is proposed. First, we will investigate the existing types of car folding seats, identify the mainstream configurations, and determine the optimal position of the four-bar linkage hinge point based on the constraints present within the car using theoretical analysis methods. Secondly, kinematic and dynamic models of the four-bar linkage mechanism are established, followed by the formulation of kinematic and dynamic equations. Finally, numerical methods are employed to solve these equations and obtain the kinematic and dynamic characteristics. The results indicate that the design method proposed in the article, which aims to maximize the space of the hinge four-bar folding seat, is efficient and feasible. This approach optimizes the utilization of interior space and enhances passenger comfort while accommodating the folding function of the seat within the existing vehicle environment. This method holds significant engineering implications for the design of folding seats in similar types of vehicles.

Time-varying displacement excitation and dynamic modeling of angular contact ball bearing with local defects

Angular contact ball bearings will produce fault damage when working for a long time, thus affecting the normal operation of the system. This paper takes angular contact ball bearings with local defects on the outer ring as the research object, proposes a method to distinguish different local defect profiles, establishes a generalized characterization model of time-varying displacement excitation of local defects in angular contact ball bearings, and studies the evolution process of local defects and their displacement excitation mechanism. On this basis, considering the influence of time-varying displacement caused by bearing defects on dynamic characteristics, based on Hertz contact theory, a fault dynamics model of angular contact ball bearings is established, and the correctness of the established model is verified by experiments. In addition, the analysis results show that rectangular local defects will eventually evolve into trapezoidal shapes; the displacement excitation change trends induced by different defect morphologies are different; compared with the length of local defects, the width has a greater impact on displacement excitation. The research results provide a theoretical basis for bearing optimization design and fault diagnosis.

Investigation on Asymmetric Dynamic Response Characteristics of Anchored Surrounding Rock under Blasting Excavation of Inclined Layered Rock Tunnel

The dynamic response stability analysis of the anchored surrounding rock during blasting construction is crucial to ensure the safety of construction. Taking the Wuwan Tunnel in Luoyang as the engineering background, combined with methods such as physical simulation experiments, numerical simulation experiments, and on-site experiments, the asymmetric effects of layered rock mass on the surrounding rock and support structure during blasting excavation were studied. The asymmetric effects of tunnel blasting excavation on the surrounding rock and support system under the condition of a bedding angle of 30° were analyzed and summarized. The results indicate that when the blasting stress wave passes through the bedding plane, the stress wave will undergo significant attenuation. The strain generated by the anchor rod passing through the bedding plane exhibits asymmetry due to the reflection and weakening of the blasting stress wave after passing through the bedding plane.

Modal analysis and seismic optimization of multi-storey gymnasium frame

In order to improve the seismic resistance capacity of the multi-storey gymnasium frame, based on the finite element analysis method, the dynamic response characteristics were analyzed, and the natural frequencies and vibration modes were obtained. Based on the results of the modal analysis, different reinforcement methods were proposed for verification. Under the excitation conditions of Borego waves, the vibration responses of different nodes in initial model were obtained. Modal verification was carried out by using two methods of shear strengthening and support rod strengthening respectively. The analysis results show that the bearing capacity of the single-span frame is insufficient, the lateral stiffness is small, and it is prone to cause severe torsional vibration damage. It can also be known that the seismic resistance capacity of the support rods reinforcement is more balanced in different directions. It can not only effectively improve the lateral stiffness and bearing capacity of the structure, but also improve the seismic performance of the main structure through the energy dissipation of component yield, which is more suitable for multi-story buildings.

An Efficient Attentive-GRU Structure for Uncertainty Modelling of Crowdsourced Human Trajectories Under Building-obscured Urban Scenes

Abstract. Uncertainty modelling is regarded as one of the core components in the field of human mobility analysis and urban navigation, that can affect the performance of human behaviour modelling and location information acquisition. Existing uncertainty modelling algorithms towards the human movement trajectory are subjected to random and highly dynamic human motion characteristics and sampling and observation errors of Global Navigation Satellite System (GNSS) signals caused by the occlusion of buildings in urban scenes, which lead to the insufficient spatiotemporal correlation and poor accuracy of uncertainty modelling. To fill in this gap, this paper proposes an efficient attentive-GRU structure for uncertainty modelling of crowdsourced human trajectories under building-obscured urban scenes, that takes into account both temporal correlation and spatial correlation of human-originated GNSS trajectories and related motion features. A period of human motion data is modelled instead of only one or adjacent location points to avoid interference factors caused by the obstruction of urban buildings, and time-varying measurement and sampling errors are further estimated and combined with comprehensive human motion features to improve the accuracy of final uncertainty modelling. Comprehensive experiments indicate that compared with existing uncertainty modelling methods including physical models and deep-learning models, the proposed attentive-GRU structure realizes much better performance under different accuracy indexes.

An Enhanced Seamless Localization Framework Using Spatial-temporal Uncertainty Predictor Under Obscured Indoor and Outdoor Scenes

Abstract. Uncertainty modelling is regarded as one of the core components in the field of urban navigation, that can affect the performance of indoor and outdoor location information acquisition, especially under obscured scenarios. Existing multi-source fusion-based seamless positioning algorithms are subjected to random and highly dynamic human motion characteristics and changeable observation errors caused by the dynamic occlusions of human and buildings under urban scenes, which lead to the insufficient spatiotemporal correlation and poor accuracy of final multi-source fusion structure. To fill in this gap, this paper proposes an enhanced seamless localization framework using spatial-temporal uncertainty predictor under obscured indoor and outdoor scenes (ESL-STUP), that takes into account both temporal correlation and spatial correlation of trajectories provided by Wi-Fi, GNSS, and sensor-originated motion information. An iPDR-based trajectory estimation structure is proposed, using the integration of INS/PDR mechanizations, magnetic observations, and deep-learning based speed estimation to enhance the performance of traditional PDR algorithm. A period of human motion features extracted from hybrid location sources are modelled instead of only one or adjacent location points to realize time-varying measured uncertainty errors prediction, and the predicted uncertainty errors of different indoor and outdoor location sources are integrated with iPDR to realize robust seamless positioning performance. Comprehensive experiments indicate that compared with existing multi-source fusion-based seamless positioning structure, the proposed ESL-STUP realizes much better performance under different scenes.

Dynamics analysis and collaborative optimization of vehicle steering mechanism

In order to improve the dynamic response characteristics of the steering mechanism, a research scheme for increasing the natural frequency based on lightweight design was proposed. Based on the finite element method and the collaborative optimization method, the modal characteristics and harmonic response characteristics of the model were studied and analyzed to verify the strength and stiffness performance of the optimized structure. The modal shapes between the free mode and the constrained mode were compared and analyzed. With the second-order natural frequency as the optimization objective, the response surface function of the equivalent stiffness was constructed. Through optimization calculation, the design variables that satisfy the constraint conditions can be obtained. The results show that the optimized structure can increase the second-order natural frequency by 14.4 % on the premise of reducing the mass by 5.2 %, effectively avoiding the excitation frequency of the engine.

Investigation of dynamic response characteristics of light fixed-wing aircraft

In order to ensure the stability of light fixed-wing aircraft during flight missions, considering the effects of relative airflow velocity and angle of attack, the distribution characteristics of velocity and pressure fields under different conditions, as well as the law of change of dynamic parameters, were derived by using aerodynamic methods. In the free modal condition, the modal truncation method was used to simulate and analyze the low-order modal shapes. Based on the modal analysis results, the sweep frequency range was set to 3-50 Hz, with a step size of 1.6 Hz, for a total of 30 substeps. A harmonic load of 1500 N was applied to the fuselage, and the displacement-frequency response curves and stress-frequency response curves of the fuselage structure and wing structure were extracted after the calculation. The results shows that the maximum lift-drag ratio occurs when the angle of attack is 6°, and the peak displacement deformation of the aircraft occurred around 24 Hz.

Analysis and optimization of the dynamic response characteristics of aircraft cargo rack

In order to effectively achieve the optimization design of the aircraft cargo rack, based on finite element modal simulation, the structure was redesigned and analyzed using two schemes of surrogate model size optimization and topology optimization, ensuring the strength requirements while improving the natural frequency and reducing the weight. According to the modal shape of vibration, additional bridge structures were added at the weak points to improve the dynamic stiffness of the structure. According to the optimization design requirements, the response surface function was constructed, and the particle swarm optimization algorithm was applied in the size optimization and surrogate model solution. A multi-objective optimization model was established for flexibility and low-order natural frequencies, and topology optimization was carried out in HyperWorks. The structural dynamic modification of the topology optimization model was performed using the modal strain energy analysis method. The research results show that both optimization methods can achieve good lightweight design. The static performance of the optimized structure is stable, and the overall modal frequency is improved.

The decoupled effect of oxidizer mass flux and combustion pressure on turbulent combustion characteristics of finite-length solid fuel

Combustion pressure and oxidizer mass flux are key factors influencing the performance of hybrid rocket motors. In the present work, the decoupled effects of oxidizer mass flux and combustion pressure on turbulent combustion characteristics were investigated. First, a finite-length combustion theory of fuel grains was developed to identify the main sensitive parameters, including flame structure and the recirculation zone, which affect the combustion of solid fuel. Then, a two-dimensional transient numerical model, based on the coupling characteristics of the heat transfer process in solid fuel grains and dynamic combustion flow, was developed and validated through fire experiments under a wide range of inflow conditions. A quantitative analysis was conducted to assess the impact of flame structure and the recirculation zone on the dynamic combustion characteristics of finite-length solid fuel. The results showed that the fuel characteristic temperatures of the front and central parts are negatively correlated with flame height, while the characteristic temperature of the rear part is positively correlated with the recirculation zone temperature. Both the mass flow rate and combustion pressure are negatively correlated with flame height and positively correlated with the temperature of the recirculation zone. Compared to combustion pressure, the influence of mass flow rate is more significant. The transient processes of the solid fuel regression rate under different inflow conditions exhibit a consistent tendency: an increase in mass flow flux and combustion pressure results in faster attainment of peak regression rate and stabilization.

Numerical analysis on the fate and transport of TiO2 nanoparticles in fractured porous media: Addressing intrinsic heterogeneities in sorptive mass transfer

The aggregation and slow migration of nanoparticles in aqueous media have caused serious concerns about their fate and impacts in the subsurface environment. Anthropogenic release and distribution of TiO2 nanoparticles (TNP) have immense potential for surface adsorption, occlusion, impregnation, bioaccumulation, and phase partition into various environmental compartments, and the actual risks in their interactions are still unknown. In an attempt to realize the extent of source zone migration of TNP in a fracture-skin-matrix (F-S-M) medium, a numerical model is developed and analyzed for sensitivity of certain features of the flow field. In addition, the sorptive mass transfer is simulated under four characteristic scenarios with varying assumptions pertaining to the intrinsic heterogeneities. The simulation results highlight the non-selective regulatory role of the skin in providing temporary interfacial space for reversible adsorption between the fracture and the matrix as well as in retarding the desorption rate. A preferential detachment of TNP is observed to be favored by the enhanced properties of skin due to the similarity in diffusion and dispersion coefficients. Out of the four scenarios, the two-site model and two-step model simulated the dynamic pore-filling features of adsorption pertaining to the heterogeneities in TNP and F-S-M characteristics. The results demonstrate that the proposed numerical could fairly detect the transition between local equilibrium and dynamic adsorption-desorption cycles that would eventually determine the mass transfer limitations and the extent of elution of TNP along the flow.

Dynamic model of arriving passengers based on dual value drive

In order to optimize the service process of integrated transportation hubs, the dynamic characteristics of the gathering behavior of arriving passengers were analyzed, and the transformation mechanism of the gathering behavior of arriving passengers in the time dimension of inverse gamma distribution, gamma distribution and chi-square distribution was studied. It was revealed that the gathering behavior was jointly affected by the flight operation time and the utility of the transfer mode, and was converted into the time value and utility value of the arriving passengers respectively. On this basis, a dual-value-driven dynamic model of arriving passengers was established based on the three distributions, and the output was the parameter-adjustable distribution of arriving passengers. The results show that the simulation output with adjustable parameters is consistent with the real distribution, which provides a method and basis for the accurate prediction of the distribution of arriving passengers at hub airports.

Dynamic characteristics analysis of shock absorber based on fluid simulation

Pneumatic spring dampers are extensively utilized within hydraulic systems, and the flow characteristics of the internal oil play a crucial role in determining noise and vibration levels. To validate the mechanical structure's reliability, the shock absorber was simplified and the fluid domain was extracted using a CFD method. The velocity field and pressure field under different conditions were then simulated and analyzed. A finite element model of the flow field was established, and its accuracy was verified by comparing simulation results of gas side pressure with experimental results. According to the working principle of the oil-gas spring, dynamic active surfaces in contact with the main piston and dynamic driven surfaces in contact with the floating piston were defined, determining moving conditions for dynamic grids. The results indicate that as the diameter of flow channels increases, there is a decrease in average pressure drop within the oil chamber (i.e., pressure loss within the flow field). Additionally, as bend angle increases, average pressure drop decreases. However, optimization effects become less significant beyond a certain bend angle.