Speed Load Research Articles

Research on Autonomous Navigation of Unmanned Aerial Vehicles Based on Correlation-Based Image Comparison Methods

Relevance. Autonomous navigation of unmanned aerial vehicles (UAVs) is one of the key challenges in the modern aerospace industry. Specifically, for small UAVs, the task of autonomous navigation becomes even more complex due to limitations in computational resources and sensor capabilities. Optimizing navigation methods under such conditions is a pressing issue that requires solutions capable of providing high performance with minimal resource consumption.Objective. Improving the efficiency of autonomous navigation for small UAVs by using correlation methods for image comparison. Achieving this objective is linked to the development and evaluation of algorithms that provide high-speed and accurate navigation with limited computational resources. The work uses methods such as the autocorrelation function, Pearson correlation, the structural similarity index, and a simple neural network for image comparison.Solution. The research showed that the autocorrelation-based approach demonstrates the best performance under low computational resources. It ensures high-speed processing of the entire image and shows optimal detection accuracy. Compared to other methods presented in the study, the autocorrelation approach is capable of working not only with noise in the "reference" map but also of using alternative areas with altered patterns as detected regions.The scientific novelty of the study is determined by the systematic comparison of various methods applied to the task of image comparison for small UAVs with limited computational resources. Unlike well-known works in the field of correlation-extreme systems, this research focuses on the use of a "reference map" and a search area, representing two different images of the same terrain taken from different sources. This is a key difference, as most methods are not highly efficient in processing such images where patterns may differ significantly.The practical significance of the developed algorithm lies in the fact that the proposed autocorrelation-based method can be used by developers of autonomous small UAV control systems to reduce computational load and increase data processing speed.

Mechanical characterization of large diameter UHMWPE ropes under quasi-static tensile loading: An experimental study

The Large diameter UHMWPEFR (Ultra High Molecular Weight Polyethylene Fiber Rope) are ideal for heavy lifting and slinging, with their mechanical properties and behaviour characterisation are key to the application.Therefore, this study conducts uniaxial tensile tests on a 115 mm diameter rope (FR-115) to investigate its mechanical properties under quasi-static tensile conditions. considering the anisotropic structural characteristics of UHMWPEFR, a method and criteria for eliminating inter-strand gaps and uneven force through pre-tensioning were proposed. Subsequently, tensile tests were carried out to examine the mechanical properties and constitutive relationship of the rope. The experimental results indicate that pre-tensioning can effectively eliminate the influence of non-elastic deformation of the rope, meeting the formal tensioning requirements based on the stability criteria of the rope structure constructed from mechanical and physical parameters. The stress-strain curve of FR-115 shows a linear bilinear shape without a yield segment during the tensioning process, presenting a typical brittle failure mode. The mechanical behavior is closely related to the historical load effects and loading speed, with the rope transitioning from soft and tough to hard and brittle, exhibiting hysteresis. Based on the above analysis, the graded load and time-varying modulus parameter are fixed, and the internal force is more sensitive to the quasi-static tensile velocity; a two-stage principal model is established based on the analysis of curve characteristics and time-dependent correlation, with 50 % MBS(Minimum Break Strength) as the characterization point, and the UHMWPEFR principal relationship in the pre-period is linear-elastic, and the strain-rate effect is taken into account for the dense section, and the rate correlation and nonlinear characteristics of the dense section of the rope can be accurately portrayed with the introduction of Cowper-Symonds.

Data-Driven Modelling and Regression Analysis on Ship Resistance of In-Service Performance

This study employs operational data to model ship resistance, aiming to bridge the gap between controlled experiments and real-world conditions. It comprehensively analyzes wind, waves, and currents, employing nonlinear regression and z-score filtering. The model is validated using data from three identically designed ships operating on the similar servicevoyages. Key findings reveal significant impacts of wind and waves on the added resistance, variability in resistance across different loading conditions, and discrepancies between in-service performance and model test results, especially at medium to low speeds. Calm water resistance results are reliable, varying within 5% to 10% of the average, though in-service performance is generally higher, indicating a need for further research. The added resistance due to wind is significant, with variations within 5% to 10%, and the transverse projected area does not always proportionally affect resistance. Head winds have a greater impact on resistance than following winds at the same speed. The analysis of added resistance due to waves shows significant, but sometimes inconsistent, transfer function coefficients, suggesting simpler model structures could be more effective. The added resistance due to current if found to typically fall within a 2-3% range, indicating that significant changes are rare and localized. For large ships, short waves dominate, with resistance increasing proportionally with the non-dimensionalized wave length. While head currents can increase resistance by up to 20% and following currents can reduce it by 5-10%, these larger changes are infrequent. Segmenting data by loading conditions, routes, and speeds improves regression analysis accuracy, though excessive segmentation reduces data diversity and reliability.

Construction of a ballistic model of the motion of uncontrolled cargo during its autonomous high-precision drop from a fixed-wing unmanned aerial vehicle

The object of this study is the process related to the fall of an uncontrolled cargo from a height of 400–600 meters relative to sea level in an air environment under the influence of gravity, air drag, and wind in the presence of an initial air speed of about 20 m/s. The study solves the task to build a ballistic model of the movement of an unguided cargo during autonomous high-precision dropping from an unmanned aerial vehicle of aircraft type. A system of equations was derived that explicitly describes the dependence of the cargo's travel speed and coordinates on time and takes into account the effect of gravity, air drag, and the influence of wind. The scope of application of the equations corresponds to drop heights of up to 400 m relative to the surface of the earth and the initial horizontal speed of the cargo up to 20 m/s. The resulting equations were analyzed using an example of a spherical load weighing 10 kg and the largest cross-sectional area of 7.1·10-2 m2 when it falls from heights of 200, 300, and 400 m relative to the earth's surface. In the absence of wind, the horizontal component of the load's speed at the moment of falling is ≈(13–15) m/s, and the vertical component is ≈(50–60) m/s. At the same time, the horizontal displacement of the load under the conditions of a weak crosswind can reach ≈(150–220) m. With a vertical wind speed profile, the equivalent constant wind speed can be determined, resulting in the same effect on the load as a variable speed wind. An algorithm for determining the point of unloading the cargo has been proposed. The cargo delivery error has been evaluated. The most important parameters are the flight time of the cargo and the drop height. In order to achieve a hit accuracy of ±5 m, an error in determining the time of the fall of the load is not more than ≈0.16 s, and an error in determining the height of the drop is not more than ±8 m

Research on Spatial Data Aggregation Based on Aggregation Degree Function

Abstract. Restricted by the development level of hardware and software technology, computers cannot load massive data at one time, coupled with the fact that the three-dimensional linear scene is characterized by complicated lines, irregular shapes of features and a large number of features. Therefore, it is necessary to seek a three-dimensional spatial data organization and scheduling method applicable to the railroad scene to realize the display and interaction of the scene. In this paper, we propose a data organization method based on the aggregation degree function for the 3D model of features. The feature model is projected to generate an orthographic projection map, the cluster division rule is designed to divide the subsets, the feature model after clustering is aggregated using the feature model aggregation rule, and the aggregated model is displayed according to the aggregation degree function and viewpoint factor. The results of the test applied to the railroad scene show that the 3D spatial data aggregation based on the aggregation degree function can improve the loading speed of the 3D scene, and can effectively support the application of interactive visualization of the railroad 3D scene.

Characterizing the Multiscale Knock Energy of the in-Cylinder Pressure of Compound Combustion Engines Fueled with Dimethyl Ether.

A two-cylinder, direct injection, and four-stroke naturally aspirated diesel engine is reformed to the compound combustion engine fueled with dimethyl ether. The wavelet energy spectra of the in-cylinder pressure with normal combustion and knocking combustion in a compound combustion engine are experimentally studied. The effects of the port fuel quantity, engine load, and engine speed on them are analyzed. The multiscale knock energy characteristics of the in-cylinder pressure are investigated based on wavelet energy and the Shannon entropy-energy ratio. The result shows that the in-cylinder pressure oscillation tends to be violent with the increase of port fuel quantity, the peak in-cylinder pressure increases, and its crank angle phase advances. With the increase in port fuel quantity, the wavelet energy of high-frequency detail signals d1, d2, and d3 obtained from wavelet decomposition all increases and the Shannon entropy-energy ratio decreases. The high-frequency detail signal d1 is more sensitive than the other detail signals. The frequency band of 5-10 kHz is the knock characteristic frequency band. The energy of the detail signal d1 increases significantly during knocking combustion, and the oscillation range enlarges and moves forward. The wavelet energy of detail signal d1 is the largest, and the Shannon entropy-energy ratio is the smallest at different brake mean effective pressures and different engine speeds. The effect of brake mean effective pressure and engine speed on the values is not obvious, and the port fuel quantity is the main factor.

Analysis of the degradation in transmission accuracy of RV reducers considering the wear clearance between cycloidal wheels and pinwheels

To accurately determine the transmission accuracy degradation pattern of Rotate Vector (RV) reducers due to wear, a predictive method is proposed that simultaneously considers the initial clearance and wear clearance between the cycloid wheel and the pinwheel. The initial clearance is derived from a comprehensive gear system analysis, considering assembly errors, manufacturing errors and modifications. Building on this, the wear depth of the cycloid wheel tooth profile is numerically simulated using Archard's wear theory, revealing the wear distribution pattern under various operating conditions. A Gaussian regression model is used to predict the maximum wear amount for different operational durations. Based on the predicted wear amount, a multi-body dynamic simulation model incorporating wear clearance was established to analyze the transmission error under varying clearance conditions. Results indicate that the wear depth along the tooth profile initially increases and then decreases. The depth and region of wear along the tooth profile gradually increase with load and output speed, with the impact of load on the wear region being greater than that of output speed. Under the initial clearance condition, the maximum transmission error is 22.91″. As the wear clearance increases, transmission accuracy declines sharply. When the cumulative wear clearance reaches 0.2 mm, the transmission error exceeds the allowable backlash limit. This study provides a theoretical reference for predicting accuracy degradation and guides the manufacturing design of RV reducers.

Prediction of the Resource of the Power Plant Hybrid Vehicle

This article substantiates the possibility of solving a difficult task to offer a reliable estimate of the residual resource of the power plant of a hybrid car, which is exposed during operation to the influence of a complex set of external factors. This task is solved by monitoring the time change of diagnostic parameters and controlling the load–speed mode of the hybrid power plant, as well as using physical and chemical processes that cause the degradation of the traction battery. Methodological principles for assessing the resource of a hybrid power plant of a car have been developed, which are based on the disclosure of cause-and-effect relationships between realized and nominal quality indicators, operating conditions, and indicators of technical condition. The choice of rational solutions for the operation of a hybrid car is given, and the external conditions are determined, under which the residual life of the hybrid power plant will change. The scientific result of the study is a theoretical generalization of the scientific provisions of forecasting the resource of the hybrid power plant of a car. This ensures the efficient use of hybrid vehicles and reduces maintenance costs.

Effects of Structure Parameters on Static Performance of Gas Foil Bearings Based on a New Fully Coupled Elastic–Aerodynamic Model

Abstract: Accurately predicting the performance of gas foil bearings (GFBs) is important. This paper presents a new fully coupled elastic–aerodynamic model for analyzing the static performance of gas foil journal bearings (GFJBs). The gas compressible lubrication model was solved in MATLAB to obtain the gas pressure. The foil structure deformation was solved in COMSOL by considering the Coulomb friction and allowing the contact surfaces to be separated from each other. Under given load and rotational speed conditions, the calculated minimum gas film thickness and attitude angle match well with the literature data, validating the accuracy of the developed model. Based on the model developed, a comprehensive and systematic analysis of the effects of the structural parameters on the static performance was performed. The results showed that as the bump height, top foil thickness, and bump foil thickness increased, the load capacity could be improved to different degrees. The bump foil thickness had the greatest effect on the load capacity. These results provide theoretical guidance for the structural design and practical applications of GFJBs.

Stiffness Hardening Effect of Wire Rope Isolators under Small Cyclic Loads for Vibration Isolation

Wire rope isolator (WRI) devices are widely used in vibration reduction industrial equipment, and stiffness is the key parameter that determines isolation effectiveness. WRI devices show slight nonlinearity under small loads, and the manufacturers generally only provide the initial parameters. To investigate the mechanical behavior changes in the WRI devices under repeated loads, five types of WRI specimens were tested under various amplitudes, loading speeds, and preloads. The test results of large symmetrical compression and tension loads showed that the WRI devices demonstrated stable hysteresis curves under repeated loads, while the hysteresis curves were independent of the loading speed. The test results of small cyclic loads with large preloads show that the stiffness of the WRI specimen follows the logarithmic law, with the cycle number under various loading conditions. Particularly, the stiffness of the specimen increases by about 10–30% after 50 cycles. The initial stiffness Ka decreases linearly with the preloads, while the decrease is quadratic in relation to the cyclic load. The hardening coefficient Ca shows a positive correlation with the loading capacity of the WRI devices, while it shows a negative correlation with the preload and cyclic load amplitudes. It is recommended to consider the stiffness increase in the WRI devices during the evaluation of isolation effectiveness.

Efficient tuning of active sound design in electric vehicles - An interactive validation approach

The implementation of active sound design models in a target vehicle requires careful tuning of all synthetic sound elements with respect to existent vehicle interior noise, current driving conditions and general driving styles. Besides the creative aspects in sound design, this tuning process is highly time-consuming. It must be ensured that load feedback, speed feedback and general interactivity with the synthetic sound meet the driver's expectations and match the intended emotional expressions of the sound concept. Testing the tuning parameters in real vehicles requires access to the vehicle prototype and all involved system components, which is often not granted in early development stages. A key approach to overcome this difficulty is the application of acoustic driving simulator technology, directly linked to the main tuning parameters. Combining this methodology with an efficient procedure for perceptive assessment of the sound design model, an interactive approach to active sound design is established. This paper discusses current progress in the field of efficient tuning of active sound design models, presenting a case study for a high-performance electric vehicle.

Modeling and Characterization of Li-Ion 18650 Nickel–Cobalt–Alumina Battery Jellyroll Subjected to Static and Dynamic Compression Loading

This study presents a comprehensive experimental investigation of the mechanical response of the jellyroll and complete Li-ion 18650 Nickel–Cobalt–Alumina (NCA) battery under axial compression, highlighting the effects of strain rate and state-of-charge (SOC). The jellyroll was subjected to both static (1 mm/min) and dynamic (10–30 m/s) axial compression using a Split-Hopkinson Pressure Bar (SHPB). A key innovation of this work is the investigation of the role of electrolytes under both static and dynamic conditions, revealing their significant impact on stress and strain behavior due to hydrostatic pressure. Additionally, the complete NCA battery was tested under various SOC levels (0–75%) using flat plate compression. The results demonstrate the jellyroll’s sensitivity to strain rate, with increased stress responses at higher loading speeds. Furthermore, the inclusion of electrolytes markedly amplified the stress and strain response. The Fu-Chang model was successfully employed to numerically replicate the observed static and dynamic behaviors. Critically, the full battery tests revealed a negative correlation between voltage cutoff and SOC, with the risk of fire and explosion increasing at higher SOC levels. This research provides novel insights into the safety and mechanical resilience of Li-ion batteries under compression.

Progressive degradation behavior and mechanism of lithium-ion batteries subjected to minor deformation damage

Minor deformation damage poses a concealed threat to battery performance and safety. This study delves into the progressive degradation behavior and mechanisms of lithium-ion batteries under minor deformation damage induced by out-of-plane compression. The effects of varying initial states of charge and loading speed on battery degradation are also analyzed. It has been observed that a deformation damage degree as low as 3.1 % can cause a significant transient capacity reduction up to 6.3 %. More transient capacity reduction can occur at higher initial state of charges and loading speed. Additionally, the investigation reveals that the capacity decay rate between the normal cell and cells experiencing deformation damage degree of <4.7 % is almost similar, with a maximum difference of merely 1.887 mAh/cycle and a minimum difference of 0.001 mAh/cycle, both observed over 3000 cycles. Non-destructive and destructive analysis methods are used to investigate degradation behaviors of the cells experiencing minor deformation dagame. It is found that such progressive degradation is primarily driven by the loss of active lithium ions, followed by the loss of cathode and anode active materials. It is anticipated that the findings will offer theoretical underpinnings for advancements in battery damage assessment, early failure prediction, and facilitation of loss adjustment and compensation by insurance agencies.

빅 히스토리를 활용한 AI 기반 융합질문 생성 교육용 서비스 ‘OASIS’ 개발

This study aims to design an AI-based educational service using Big History to enhance convergence competency in secondary school students and to evaluate the effectiveness and satisfaction of the designed service, OASIS(Online AI-based Service for Inquiry Studies). Through three stages of model improvement, the core model OASIS was developed. Convergence competency tests were conducted on 128 first-year high school students before and after using OASIS. Additionally, the effectiveness and user satisfaction were evaluated by a user satisfaction survey conducted with the same students and 15 educational experts. OASIS utilizes ChatGPT to provide multidisciplinary information on input keywords, thereby enhancing interdisciplinary understanding. The service is structured to foster convergence competency through the creation of convergence inquiries and interactive activities. The results of the convergence competency tendency test and user satisfaction survey indicated that the use of OASIS helped enhance students' convergence competency and showed high satisfaction regarding the usefulness of information. However, limitations such as the inaccuracy of information and slow loading speeds were noted. Addressing these limitations could improve the service’s applicability in secondary education for fostering convergence.

Full-scale experimental study on tribological performance of FPBs for highway bridges with various solid lubricants under fast loading

Friction pendulum bearings (FPBs) have proven to be effective for the seismic isolation of highway bridges. Previous studies often employed scaled model shaking table tests to investigate dynamic responses of the structures or quasi-static tests to assess the hysteretic performance of FPBs. However, it is noteworthy that the stress on the friction surface is reduced due to the size effect in scaled model in shaking table tests, while quasi-static tests of prototype bearings cannot simulate the sliding velocity experienced during seismic events, which is a sensitive parameter for the performance of FPBs with solid lubricant plates. Research on the performance of full-scale FPBs under fast frictional loading is very limited. This paper addresses this knowledge gap by studying the velocity demand for a highway bridge with FPBs and conducting fast sliding performance tests using full-scale FPBs. The results indicate that under a 0.2 g PGA earthquake, the velocity demand for FPBs can reach 0.5 m/s. Through testing full-scale FPBs at various loading speeds, it was found that solid lubricant plates by UHMWPE material exhibit poor thermal stability during wear tests, solid lubricant plates by PTFE material lack sufficient tangential tear strength under fast loading, and solid lubricant plates by PET material show good wear resistance but have a high breakaway force and levered maximum force during the running-in stage. Subsequently, this study developed ultra-high performance friction plate (UHPF) as the solid lubricant for FPBs, achieving ideal hysteretic performance under fast loading. The full-scale FPB specimens in this paper are the ones manufactured for the continuous beam bridges in the Shenzhen-Zhongshan Sea-crossing Link project in China. The dimensions of the bearing, axial load, and loading speed is much more stringent than those in previous FPB tests, providing results that are highly important for engineering applications.

Adaptation of Parallax Scrolling Effect Technique in LegitCheck Website Interface Development

This research focuses on developing LegitCheck's website interface by applying the Parallax Scrolling Effect technique, which is considered as a potential solution to support the startup's promotional strategy. LegitCheck, as a startup that needs an effective way to introduce its services and business concept to consumers and brands, requires a website that can serve as an attractive promotional medium as well as a comprehensive information center. The purpose of this research is to examine the effectiveness of the Parallax Scrolling Effect technique compared to a website without the effect in increasing the effectiveness of the LegitCheck website as a promotional tool. The research method used includes the design and implementation of the Parallax Scrolling Effect technique on the LegitCheck website, followed by evaluation using the A/B testing method. The results showed that the implementation of the Parallax Scrolling Effect technique provided significant benefits, including improved information accuracy, service quality, user satisfaction, and company net profit. Although there are constraints related to page loading speed, the majority of respondents prefer websites with Parallax Scrolling Effect because it provides a more interactive and engaging experience. The implication of this study is that the use of Parallax Scrolling Effect can be an effective strategy for startups such as LegitCheck to increase interaction with users, strengthen brand image, and increase the effectiveness of the website as a promotional tool, although it is necessary to pay attention to technical aspects such as page loading speed to minimize potential disruptions to the user experience.

Effects of temperature and loading rate on the shear performance of GFRP-steel single-lap joints

This research examines how the shear properties of glass fiber-reinforced polymer (GFRP) and steel single-lap joints react under various temperatures (−25, 0, 25, 50, and 100℃) and loading speeds (0.625, 1.25, 2.5, and 5.0 m/s). The GFRP sheets, aligned unidirectionally, were produced using vacuum-assisted resin transfer molding and were then adhesively attached to steel plates with epoxy resin. The assemblies were subjected to a high-speed servo-hydraulic testing apparatus for evaluation. The results indicate that the joint's performance is relatively unaffected by changes in the loading speed, but the overall toughness tends to decrease at higher speeds. However, the adhesive bond strength increases when temperatures are between −25 and 50℃ but diminishes as temperatures rise from 50 to 100℃. Most samples exhibited debonding at the steel-adhesive interface under varied speeds and colder temperatures, whereas debonding at the GFRP-adhesive interface was more prevalent at elevated temperatures. These insights are vital for both theoretical analyses and practical implementations of GFRP-steel single-lap joints in environments subject to extreme loading conditions and temperatures.

Modeling of an Adaptive HHO Gas Controller Based on Fuzzy Logic and Polynomial Function Controls to Improve Engine Torque of Gasoline Engine

Typical hydrogen-hydrogen-oxygen gas (HHO) usage to improve gasoline engine performance refers to the fixed HHO flow rate method, providing 0.25‒0.5 liters/minute of HHO for every 1000 cc engine size. However, the arising hypothesis expresses that the fixed HHO flow rate method does not optimally improve engine torque for various loads. The research objective is to propose an adaptive HHO gas controller that manages the HHO generator to produce an appropriate HHO flow rate for engine operation by adapting to load and engine speed variations. Hence, the engine torque improvement optimally occurs for various loads. The adaptive HHO controller combines fuzzy logic and polynomial function controls involving real-time engine data, such as mass airflow (MAF), air-fuel ratio (AFR), and the commanded AFR from the engine control unit (ECU), whose values vary with load and engine speed. A system simulation based on Matlab-Simulink investigates engine performance improvement due to the controller. The results show that the adaptive HHO flow rate due to the proposed adaptive HHO controller improves engine torque during small, medium, and big-loaded engine operations, respectively, by 1.5%‒4.7%, 6.8%‒26.8%, and 21.1%‒72.8% depending on engine speed 2500 rpm‒4000 rpm) and the commanded AFR (12.6‒15.4). Conversely, under the same condition, the fixed HHO flow rate with 0.75 liters/minute HHO for a 1500 cc engine, used for comparison, improves the engine torque by 0%‒0.6%, 0.3%‒14.2%, and 9.3%‒50.1%, respectively. The data show that the adaptive HHO controller provides better improvement. Moreover, the adaptive HHO controller improves engine thermal efficiency and reduces AFR error against the commanded AFR.

Enhancing Sports Injury Risk Assessment in Soccer Through Machine Learning and Training Load Analysis.

Sports injuries pose significant challenges in athlete welfare and team dynamics, particularly in high-intensity sports like soccer. This study used machine learning algorithms to assess non-contact injury risk in professional male soccer players from physiological and mechanical load variables. Twenty-five professional male soccer players with a first-time, non-contact muscle injury were included in this study. Recordings of external load (speed, distance, and acceleration/deceleration data) and internal load (heart rate) were obtained during all training sessions and official matches over a 4-year period. Machine learning model training and evaluation features were calculated for each of nine different metrics for a 28-day period prior to the injury and an equal-length baseline epoch. The acute surge in the values of each workload metric was quantified by the deviation of maximum values from the average, while the variations of cumulative workload over the last four weeks preceding injury were also calculated. Seven features were selected by the model as prominent estimators of injury incidence. Three of the features concerned acute load deviations (number of sprints, training load score-incorporating heart rate and muscle load- and time of heart rate at the 90-100% of maximum). The four cumulative load features were (total distance, high speed and sprint running distance and training load score). The accuracy of the muscle injury risk assessment model was 0.78, with a sensitivity of 0.73 and specificity of 0.85. Our model achieved high performance in injury risk detection using a limited number of training load variables. The inclusion, for the first time, of heart rate related variables in an injury risk assessment model highlights the importance of physiological overload as a contributor to muscle injuries in soccer. By identifying the important parameters, coaches may prevent muscle injuries by controlling surges of training load during training and competition.

Determination of eight neonicotinoid pesticides in wastewater by solid phase extraction combined with liquid chromatography-tandem mass spectrometry

Neonicotinoid pesticides are a relatively new class of pesticides that have garnered significant attention owing to their potential ecological risks to nontarget organisms. A method combining solid phase extraction with liquid chromatography-tandem mass spectrometry (SPE-LC-MS/MS) was developed for the rapid and accurate detection of eight neonicotinoid pesticides (dinotefuran, E-nitenpyram, thiamethoxam, clothianidin, imidacloprid, imidaclothiz, acetamiprid, and thiacloprid) in wastewater. The chromatographic mobile phase and MS parameters were selected, and a single-factor method was used to determine the optimal column type, extraction volume, sample loading speed, and pH for SPE. The optimal parameters were as follows: column type, HLB column (500 mg/6 mL); sample extraction volume, 500 mL; sample loading speed, 10 mL/min; and sample pH, 6-8. The matrix effects of the wastewater samples were reduced by optimizing the chromatographic gradient-elution program, examining the dilution factor of the samples, and using the isotope internal standard calibration method. Prior to analysis, the wastewater samples were diluted 5-fold with ultrapure water for pretreatment. Subsequently, 2 mmol/L ammonium acetate aqueous solution containing 0.1% (v/v) formic acid and methanol was used as mobile phases for gradient elution on a ZORBAX Eclipse Plus C18 column (100 mm×2.1 mm, 1.8 μm). The samples were quantified using positive-ion multiple reaction monitoring (MRM) mode for 10 min. Imidacloprid-d4 was used as the isotope internal standard. The SPE process was further optimized by applying response surface methodology to select the type and mass of rinsing and elution solvents. The optimal pretreatment of the SPE column included rinsing with 10% methanol aqueous solution and elution with methanol-acetonitrile (1∶1, v/v) mixture (7 mL). The eight neonicotinoid pesticides showed satisfactory linearity within the relevant range, with linear correlation coefficients (r) all greater than 0.9990. The method detection limits (MDLs) ranged from 0.2 to 1.2 ng/L, and the method quantification limits (MQLs) ranged from 0.8 to 4.8 ng/L. The average recoveries of the eight neonicotinoid pesticides were in the range of 82.6%-94.2% at three spiked levels, with relative standard deviations (RSDs) ranging from 3.9% to 9.4%. Finally, the optimized method was successfully applied to analyze wastewater samples collected from four sewage treatment plants. The results indicated that the eight neonicotinoid pesticides could be generally detected at concentrations ranging from not detected (ND) to 256 ng/L. The developed method has a low MDL and high accuracy, rendering it a suitable choice for the trace detection of the eight neonicotinoid pesticides in wastewater when compared with other similar methods. The proposed method can be utilized to monitor the environmental impact and assess the potential risks of neonicotinoid pesticides in wastewater, thus promoting the protection of nontarget organisms and the sustainable use of these pesticides in agriculture.