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The inaccurate force and position control of tendon sheath system (TSS) due to nonlinear friction during surgery seriously hinders its development in the field of precision surgical robots. To this end, this paper proposes a time-varying bending angle estimation method under the state of sensorless offline identification combined with robot kinematics by analyzing the friction of the TSS and the deformation of the robot during the movement, and establishes a force and position transfer model with time-varying path trajectory (SJM model). The model uses B-spline curve to fit tendon-sheath trajectory. In order to further improve the control accuracy of force and position, a new intelligent feedforward control strategy that integrates the SJM model and a neural network algorithm is proposed. In order to gain an in-depth understanding of the transmission process of force and position and to demonstrate the validity of the SJM model, an experimental platform for the TSS was built. A feedforward control system under the MATLAB environment was built with the aim of verifying the accuracy of the intelligent feedforward control strategy. The system innovatively combines the SJM model with BP and RBF neural networks, respectively. The experimental results showed that the correlation coefficients (R2) of force and position transfer are above 99.10% and 99.48%, respectively. Ultimately, we compared the intelligent feedforward and intelligent control strategy under a single neural network, and observed that the intelligent feedforward control strategy has a better effect.

Surgical skill assessment can quantify the quality of the surgical operation via the motion state of the surgical instrument tip (SIT), which is considered one of the effective primary means by which to improve the accuracy of surgical operation. Traditional methods have displayed promising results in skill assessment. However, this success is predicated on the SIT sensors, making these approaches impractical when employing the minimally invasive surgical robot with such a tiny end size. To address the assessment issue regarding the operation quality of robot-assisted minimally invasive surgery (RAMIS), this paper proposes a new automatic framework for assessing surgical skills based on visual motion tracking and deep learning. The new method innovatively combines vision and kinematics. The kernel correlation filter (KCF) is introduced in order to obtain the key motion signals of the SIT and classify them by using the residual neural network (ResNet), realizing automated skill assessment in RAMIS. To verify its effectiveness and accuracy, the proposed method is applied to the public minimally invasive surgical robot dataset, the JIGSAWS. The results show that the method based on visual motion tracking technology and a deep neural network model can effectively and accurately assess the skill of robot-assisted surgery in near real-time. In a fairly short computational processing time of 3 to 5 s, the average accuracy of the assessment method is 92.04% and 84.80% in distinguishing two and three skill levels. This study makes an important contribution to the safe and high-quality development of RAMIS.

Robot-assisted pelvic fracture closed reduction (RPFCR) positively contributes to patient treatment. However, the current path planning suffers from incomplete obstacle avoidance and long paths.A collision detection method is proposed for applications in the pelvic environment to improve the safety of RPFCR surgery. Meanwhile, a defined orientation planning strategy (OPS) and linear sampling search (LSS) are coupled into the A* algorithm to optimise the reduction path. Subsequently, pelvic in vitro experimental platform is built to verify the augmented A*algorithm's feasibility.The augmented A* algorithm planned the shortest path for the same fracture model, and the paths planned by the A* algorithm and experience-based increased by 56.12% and 89.02%, respectively.The augmented A* algorithm effectively improves surgical safety and shortens the path length, which can be adopted as an effective model for developing RPFCR path planning.

Waste-to-energy is considered as an effective way to simultaneously digest the municipal waste and generate useful power. Steam Rankine cycle is conventionally adopted for solid-waste incineration ...

Ti-6Al-4V alloy has low thermal conductivity, poor machinability, and active chemical activity. However, it is easily bonded to tool surface in the cutting process, resulting in drastic tool wear. The friction contact state and friction behavior between the tool and machined surface can be significantly improved when adopting tool with micro texture on the surface. The tools with line texture, regular hexagonal texture, and without texture on the rake face were adopted in this study. The cutting force, tool wear morphology, and friction coefficient of different type of tools are analyzed based on dry cutting test, friction, and wear test of cemented carbide and titanium alloy. The result shows that the cutting force caused by the line-textured tool is the smallest, following by hexagonal-textured tool and no-textured tool. However, large damage would happen at the cutting edge of line-textured tool as the cutting continues, while the damage of hexagonal-textured tool is relatively light. The main cutting force and feed force of the three kinds of tools increase as cutting depth increased, while decrease with the increase of cutting speed. The wear morphology of textured tool is smoother than that of no-textured tool, due to the micro texture can contain debris and reduce friction coefficient. A cutting force equation is established by ridge regression method based on actual cutting data, which provides a new idea for monitoring the tool during cutting process.

In the dry and hard cutting process of hardened steel, the white layer of the machined surface has a great influence on the service performance and life of the part. The cutting force and cutting heat produced in the process are among the important factors affecting the white layer characteristics. In the process of machining, in addition to the cutting parameters, the characteristics of cutting tools can also lead to significant changes in both service performance and part lifetime. Therefore, it is necessary to further study the changes in the cutting force, cutting heat, and white layer characteristics under the influence of the tool characteristics. In this paper, hard cutting tests of hardened steel were carried out by cutting tools (including PCBN tools and ceramic tools) with different thermal conductivities and flank wear under different cutting speeds. The influence of the cutting speed and tool characteristics on the cutting force, flank temperature and white layer characteristics was analyzed, and a prediction model for the white layer thickness was established. It was found that the cutting speed, tool wear degree, and tool thermal conductivity all have a significant influence on the cutting force, cutting temperature, and white layer thickness. Among the results, the thickness of the white layer first increases and then decreases with increasing flank temperature, and the critical temperature at the maximum thickness of the white layer is the actual final temperature of austenite transformation. Changes in the cutting force indirectly affect the temperatures of the austenite and martensite phase transitions, thus affecting the thickness of the white layer. The prediction results show that a fuzzy neural network based on particle swarm optimization can effectively predict the thickness of the white layer.

Pre-ignition is an undesirable ignition event that affects chemical kinetic measurements in chemical reactors. Meanwhile, it appears randomly in engineering systems and is highly relevant to the soft knock or much stronger and detrimental super-knock in modern downsized engines. Currently its origins are still not fully understood. In this study, the role of turbulence in pre-ignition phenomena was experimentally investigated using a novel rapid compression machine. Different turbulent flow fields were achieved through calibrated orifice plates. Stoichiometric isooctane/air mixtures were tested under engine-relevant conditions in a target pressure range of 15–50 bar and a temperature range of 720–860 K. Useful insights into pre-ignition mechanism were obtained by combining instantaneous pressure acquisition with simultaneously recorded high-speed imaging. The experimental results demonstrate that owning to turbulent mixing with colder boundary layers, ignition timing is delayed when compared to ideal homogeneous compression ignition scenarios. However, pre-ignition phenomena can still be observed and become pronounced at lower target pressures with longer ignition delays. Moreover, pre-ignition formation can be characterized by single or multiple spherical flame kernels, distributed discretely inside core mixture or at near-wall regions. Different from the auto-ignition scenarios dominated by the chemical reactivity of test mixture, these pre-ignition flame kernels feature standard deflagration propagation. Finally, a dimensionless scaling analysis shows that pre-ignition formation is closely associated with turbulent length scale and laminar flame thickness.

In proton exchange membrane fuel cells (PEMFC), the design of the cathode flow field is very important, because an excellent flow channel design can not only accelerate the transmission rate of liquid water, but also affect the distribution of electrode reactants and electrode products which influence the electrochemical performance of the fuel cell. This study presents three new channels (models 1,2 and 3), which were created using two unilateral slopes and a bilateral slope structure with tapered tube lengths of 0.4, 1.2 and 0.8 mm, respectively. The dynamic behavior of liquid water under the three design schemes is numerically studied based on the volume of fluid method. And the influence on the performance of fuel cell was analyzed synthetically. The results indicate that the introduction of a tapered and sloping structure can improve the transmission efficiency of the droplets in the flow channel, and the maximum droplet removal time of the new channel can be reduced by 24.4%compare with standard conventional flow channel. The slope structure guides the flow path of water droplet and reduces the occurrence of droplet spatter. Influenced by the slope and tapered structures, the turbulence of airflow near the bottom surface (gas diffusion layer)of the flow channel is enhanced and Oxygen concentration in the cathode is raised, which improves the mass transfer capacity and average current density of reactive surface. In conclusion, the new type of channel with a tapered and sloping structure has a potential to improve the performance of water management in the cathode channel of PEMFC.

In this study, a proton exchange membrane (PEM) fuel cell stack composed of five cells in series is numerically investigated to study the impact of the nonuniform reactant flow rate on the performa...

The high-pressure injection strategy for di-n-butyl ether (DBE)-diesel fuel blends reduces particulate matter emissions. Exhaust gas recirculation (EGR) technology was used to decrease NOx ...

In this paper, a Pareto front (PF)-based sampling algorithm, PF-Voronoi sampling method, is proposed to solve the problem of computationally intensive multi-objectives of medium size. The Voronoi diagram is introduced to classify the region containing PF prediction points into Pareto front cells (PFCs). Valid PFCs are screened according to the maximum crowding criterion (MCC), maximum LOO error criterion (MLEC), and maximum mean MSE criterion (MMMSEC). Sampling points are selected among the valid PFCs based on the Euclidean distance. The PF-Voronoi sampling method is applied to the coupled Kringing and NASG-II models and its validity is verified on the ZDT mathematical cases. The results show that the MCC criterion helps to improve the distribution diversity of PF. The MLEC criterion and the MMMSEC criterion reduce the number of training samples by 38.9% and 21.7%, respectively. The computational cost of the algorithm is reduced by more than 44.2%, compared to EHVIMOPSO and SAO-MOEA algorithms. The algorithm can be applied to multidisciplinary, multi-objective, and computationally intensive complex systems.

This study investigated the effects of cooperative-control of the start of injection (SOI), excess air ratio (λ), internal exhaust gas recirculation (I-EGR), and intake air temperature (IAT) on the combustion and emission characteristics of gasoline compression ignition (GCI) engines, especially regards to the combustion stability and knock characteristics. And optimizing the GCI engine combustion and emissions through the cooperative control of multiple parameters is the innovation of this research. The results showed that advancing the SOI and increasing the I-EGR ratio can significantly expand the low-load limit, but the heating effect of 20% I-EGR only worked when the SOI was earlier. An appropriate increase of λ could increase the maximum brake thermal efficiency (BTE) to 40.06%, but resulted in high-knock probability and high NOx emissions. Rising the IAT was more effective than advancing the SOI in improving combustion fluctuations, but the knock probability and knock intensity were more sensitive to the early SOI. When the SOI varied from 26 °CA BTDC to 30 °CA BTDC, λ was 1–1.5, the I-EGR ratio was 5%–20%, and the IAT was 40–50 °C; the GCI engine can obtain the balance among high thermal efficiency, high combustion stability, low knock probability, and low emissions.

As a highly nonlinear system, the performance of proton exchange membrane fuel cell (PEMFC) is controlled by various parameters. If the effects of all parameters are considered during the performance optimization, low working efficiency and waste of resources will be caused. The development of sensitivity analysis for parameters can not only exclude the parameters which have slight effects on the system, but also provide the reasonable setting ranges of boundary values for simulation of performance optimization. Therefore, sensitivity analysis of parameters is considered as one of the methods to optimize the fuel cell performance. According to the actual operating conditions of PEMFC, the fluctuation ranges of seven sets of parameters affecting the output performance of PEMFC are determined, namely cell operating temperature, anode/cathode temperature, anode/cathode pressure, and anode/cathode mass flow rate. Then, the control variable method is used to qualitatively analyze the sensitivity of main parameters and combines with the Monte Carlo method to obtain the sensitivity indexes of the insensitive parameters under the specified current density. The results indicate that among these parameters, the working temperature of the fuel cell is the most sensitive to the output performance under all working conditions, whereas the inlet temperature is the least sensitive within the range of deviation. Moreover, the cloud maps of water content distribution under the fluctuation of three more sensitive parameters are compared; the results verify the simulated data and further reveal the reasons for performance changes. The workload of PEMFC performance optimization will be reduced based on the obtained results.

The combination dimethyl carbonate (DMC)/diesel-blended fuels and the exhaust gas recirculation (EGR) can decrease nitrogen oxide (NOX) and soot emissions simultaneously emitted from the compressio...

n-Pentanol exhibits some advantageous fuel properties, such as a higher energy density, lubricity, viscosity, and low hygroscopicity, when compared to short-chain alcohols. It is miscible with pure diesel in large proportions and burns directly on diesel engines. Therefore, n-pentanol is considered to be a promising diesel fuel additive. However, the differences between the chemical and physical properties of n-pentanol and commercial diesel affect the spray, combustion, and emissions performance of commercial diesel engines. In this study, visualization and engine experimental test methods were used to study the spray, combustion, and emissions performance of diesel/n-pentanol mixtures. The results showed that the atomization characteristics of diesel/n-pentanol mixtures were better than those of diesel. As the engine load increased, the maximum in-cylinder pressure and heat release rate increased. The brake specific fuel consumption (BSFC), nitrogen oxide (NOX), hydrocarbons (HC), and carbon monoxide (CO) emissions decreased, but soot emissions increased. Compared to diesel fuel, adding n-pentanol to pure diesel resulted in a decrease in soot emissions, while the BSFC, HC, and NOX emissions increased. Upon adding 50% n-pentanol to pure diesel (P50), the soot emissions decreased by up to 77.15% and the brake thermal efficiency (BTE) decreased by 1.86%. In summary, P50 could be burned directly on the diesel engine without any modifications, which can significantly reduce soot emissions; in this case, the BTE experienced only a slight decrease.

Strong knocking combustion has become the greatest challenge for advanced internal combustion engines to pursue thermal efficiency limits at high power density conditions. Arising from enclosed space and extreme combustion situations, the fundamental mechanism for strong knocking combustion has still not been fully understood. In this study, synchronization measurement was performed through simultaneous pressure acquisition and high-speed direct photography, and knocking experiments were comparatively conducted under spark-ignition (SI) and compression-ignition (CI) conditions in a high-strength optical rapid compression machine (RCM) with flat piston design. Strong knocking phenomena were reproduced through varying initial thermodynamic conditions, and localized autoignition (AI) initiation and reaction wave evolutions were visualized, companied by synchronous pressure and temperature trajectories. The results show that compared with initial temperature, initial pressure and equivalence ratio exhibit greater influence on the variations of knocking severity. The weighting of different contributors can be further quantified by an effective energy density that shows positive but nonlinear correlations with knocking severity. However, the distinctions between CI and SI knocking characteristics at identical effective energy density also reflect the essential role of the interplay between primary flame propagation and end-gas AI progress. Visualized combustion images show that through improving end-gas thermodynamic state and reactivity sensitivity, the primary flame propagation can enhance localized AI initiation and secondary intensive AI evolutions, facilitating combustion mode transitions into developing detonation. The significant influence of primary flame propagation is diminished until ignition delay time becomes sufficiently short. Finally, with estimated thermal heterogeneities in flat-piston RCM configurations, the ignition modes of strong knocking cycles are quantified by a non-dimensional ignition regime diagram, and favorable scaling agreements with strong and mixed ignition regimes are observed.

Particulate matter (PM) emitted from conventional diesel engines has significant deteriorating effects on natural environment and human health. Among alternative oxygenated fuels, polyoxymethylene dimethyl ether (PODE) is a novel renewable fuel with high cetane number, oxygen content and volatility, and has prominent potential for reducing the PM emissions. In this study, the influences of fuel injection parameters, including injection pressure and injection timing on the reduction of PM emissions were explored for a four-cylinder diesel engine fueled with PODE/diesel blends at various engine loads. The three blends were the pure diesel (denoted as P0), a mixture of 80% diesel and 20% PODE (denoted as PD20), and the mixture of 70% diesel and 30% PODE (denoted as PD30). The results showed that adding PODE to diesel resulted in a reduction in both the total particle number concentration (PNC) and the particle mass concentration (PMC) at all loads. For the PODE/diesel blends, at low load and higher injection pressures, the PMC further decreased, although the value of PNC drastically increased. For the PODE/diesel blends, at medium load and higher injection pressures, both the PNC and PMC values decreased. When the injection pressure was higher than 120 MPa, it could not continuously reduce PNC. Furthermore, for the PODE/diesel blends, at high load and high injection pressures, both the PNC and PMC values greatly decreased. The PODE/diesel blends coupled with the retarded injection timing could reduce the PNC and PMC values, but when the injection timing occurred too close to the top dead center (TDC), the PNC value increased. In addition, as the injection timing was closer to TDC, the effect of the addition of PODE in diesel fuel on reducing PNC and PMC became more significant.

A diesel/natural gas (NG) dual-fuel engine is regarded as an appealing option to reduce emissions while maintaining high thermal efficiency. In this study, a reduced n-heptane–n-butylbenzene–NG–polycyclic aromatic hydrocarbon (PAH) mechanism with 746 reactions and 143 species was developed for predicting the combustion characteristics and emission in dual-fuel engines. A mixture of methane, ethane, and propane was used to model the NG, and a mixture of n-heptane and n-butylbenzene was used to model the diesel. This mechanism was based on a reduced n-heptane–PAH mechanism, and the detailed mechanisms of n-butylbenzene and NG were reduced using the methods of directed relation graph with error propagation (DRGEP), rate of production (ROP), and sensitivity analysis. The key kinetic parameters of the model were optimized and adjusted according to the results of sensitivity analysis. The final optimized dual-fuel mechanism was verified against ignition delay, laminar flame speed, and homogenous charge compression ignition (HCCI) engine combustion, and a good prediction was obtained. Finally, the present mechanism was coupled into the CFD software to simulate the combustion characteristics and emission of a dual-fuel engine under four different NG substitution rates. The simulation results are consistent with the experimental data of emissions and combustion characteristics, indicating that the current mechanism can be applied to simulate practical diesel/NG dual-fuel engines.

Physicochemical properties of soot, such as graphitization degree and surface functional groups of dimethoxymethane (DMM)–diesel blends, have been conducted with Raman spectrum, FT-IR (Fourier transform infrared spectroscopy), and XPS (X-ray photoelectron spectroscopy), respectively. The experimental samples are collected in a four-cylinder, turbocharged engine at two different speeds (2200 and 1400 rpm), different loads (1.2 and 0.6 MPa), and different fuels (D100, DMM6.4, and DMM13). The results show that with the increase in loads, the difference of graphitization degree is gradually disappeared with different fuels, and a higher graphitization degree can be obtained. Moreover, the use of DMM reduces the proportion of unsaturated fuels, thereby leading to lower amounts of C H groups. In terms of oxygenated surface functional groups’ content of particulate matter (PM), the C O functional group accounts for 4%-12%, the COO functional group accounts for 1%-4%, and the C O functional group accounts for 3%-8%. Sensitivity analysis of the microscopic properties of soot found that the O/C ratio and sp3/sp2 ratio have the lowest effect on the apparent activation energy (Ea) of soot. And AD1/AG, AD2/AG, and AD4/AG significantly affect Ea.

Dimethyl carbonate (DMC) is a promising alternative fuel for diesel engines. Comparing with the traditional diesel fuel, the DMC application can lead to a different combustion process where the soot is synthesized, yielding variation in chemistry of engine-out soot particles. Soot chemistry is highly related to the concentration and accessibility of radical sites for the reactions regarding to soot oxidation on the exhaust systems or during DPF regeneration. Therefore, the study on the chemical feature of soot emissions is of great necessity. Nevertheless, comprehensive determination on the soot chemical property for DMC-contained fuel and its instinctive explanation is not well understood in the previous studies. In this study, to reveal the effect of DMC addition on the chemical feature of soot emissions, the surface functional groups and their bonding states of soot particles from various DMC-diesel blends were characterized using FT-IR and XPS technologies. Results showed that the DMC addition exerts different influences on the surface oxygen content, oxygenated groups and their bonding states with various DMC content. Therein, DMC addition in large amount can significantly increase the C sp3/sp2 ratio and the concentration of C-O epoxies on soot surfaces. At relatively low engine speed and load conditions, the low-content addition of DMC leads to slight increase in the aromatic C–H/aromatic C C ratio in soot bulk structure. However, the large-content DMC addition distinctly reduces the aromatic C–H/aromatic C C and aliphatic C–H/aromatic C C ratios. The results are useful for the prediction of the subsequent soot oxidation behavior during DPF regeneration on diesel engines.

The anti-knock quality of fuels are of vital importance for improving spark ignition (SI) engine efficiency. 2-pheylethanol (2-PE) is one of potential high-octane booster, which can be derived from lignin as a biomass component. To ascertain the possibility of 2-PE as a bio-additive in SI engines, combustion characteristics and emission performance of 2-PE addition were investigated in a downsized gasoline engine. Blending 2-PE in gasoline resulted to a decrease in cylinder pressure and heat release rate. As increase of 2-PE addition, ignition delay and combustion duration of 2-PE-gasoline become postponed, combustion phasing is retarded， and COVIMEP increased significantly. The reason is thought to be correlated with its relatively lower gas-phase reactivity and higher heat of vaporization. At elevated intake pressure, the number of knock cycles and MAPO significantly increased of SI engine，addition of 2-PE exhibits good knocking resistance because of its high octane number and physicochemical properties. For regulated gas emissions, 2-PE addition produces more unburned hydrocarbon, carbon oxide and less nitrogen oxides. The blending of 2-PE in gasoline tends to increase particle matter emissions and enlarge the particle size.

The n-pentanol/diesel dual-fuel coupled with EGR (exhaust gas recirculation) technology could simultaneously reduce soot and nitrogen oxide (NOX) emissions discharged from the compression ignition engine. However, under high EGR rates, the low cetane number of the n-pentanol/diesel dual fuel resulted to combustion deceleration behavior. Because the combustion rate has a significant influence on the thermal efficiency of the engine, it was necessary to add 2-ethylhexyl nitrate (EHN) as a cetane improver to fuel mixtures to ensure that the n-pentanol/diesel fuel has appropriate combustion characteristics. In this study, it was attempted to investigate the performance and emission of a four-cylinder, turbocharged diesel engine with EHN fueled with n-pentanol/diesel blends at varying EGR rates. The five tested fuels included pure diesel (P0), and a mixture of 50% n-pentanol and 50% diesel (P50). Moreover, EHN was added to P50 at ratios of 0.5, 1, and 2%. The results showed that P50 could reduce soot emission, nucleation and accumulation mode particles. However, the burning speed and brake thermal efficiency (BTE) were notably reduced, and emissions of hydrocarbon (HC) and carbon monoxide (CO) significantly increased. With the EGR technology, NOX emission was significantly reduced. When EHN was added to P50, engine ignition delay was shortened, BTE increased, and HC and CO emissions were substantially reduced. The use EGR technology combined with n-pentanol and EHN simultaneously reduced soot and NOX emissions, and only slightly reduced BTE.

Polyoxymethylene dimethyl ethers (PODE n ) are an excellent biofuel with no C C bond and substantial soot-reduction potential. The effects of BMEPs on the characteristics of combustion performance and emissions in a four-cylinder direct injection diesel engine with n -butanol/diesel/PODE 3–4 blends were investigated. Mechanism of the PODE blends on soot reduction is discussed. The experimental results indicate that upon adding PODE 3–4 to the blend of n -butanol with diesel can improve the thermal efficiency and combustion efficiency with an increment in the brake specific fuel consumption (BSFC). As the BMEP increased, a decreasing trend was observed in the emissions of soot, CO, and THC, while increasing NO x formation. Under a BMEP of 1.2 MPa, the soot emissions from the combustion of BD20, BDP10, and BDP20 reduced by 61.5%, 80.7, and 91.1%, respectively, compared to that from pure diesel. Under equal BMEP value, adding PODE 3–4 to n -butanol/diesel blend reduced the soot, CO and THC emissions, and the lowest soot and THC emissions were found for BDP20, followed by BDP10, BD20, and D100. The number concentration of the accumulated particulate matter as well as the mass concentration of total particulate matters can be decreased by adding PODE 3–4 . The chemical kinetics simulation results reveal that C O bonds break and CH 2 O is first produced in the pyrolysis of PODE n ; as the value of n increases, more CH 2 O is produced and further oxidized to form HCO, which is finally transformed into CO and CO 2 , avoiding the production of soot precursors.

In recent years, n-pentanol has attracted much attention because it can reduce the dependence on fossil fuels and the pollution emissions of engines. As important components of diesel, aromatic hydrocarbons play a significant role in soot generation. In this work, a new reduced chemical kinetic mechanism of n-heptane–n-butylbenzene–n-pentanol–polycyclic aromatic hydrocarbon (PAH) was established, containing 178 species and 746 reactions for diesel engine applications. On the basis of the reduced mechanism of n-heptane–PAH, the proposed mechanism was developed by adding the reduced mechanisms of n-butylbenzene and n-pentanol. Direct relation graph with error propagation (DRGEP), sensitivity analysis, and rate of production (ROP) methods were employed to reduce the detailed mechanisms of n-butylbenzene and n-pentanol, respectively; then, the sensitivity analysis method was employed to optimize the simplified model. In order to verify the reliability of the current mechanism, it was used to extensively verif...

Dynamics and tribology are vital to gear transmission device mainly because of relating to noise, vibration, lubricating performance and durability. A novel method for predicting dynamic characteristics and lubricating property in spur gear of ink vibrator is proposed in this paper by means of integration technology. Unlike the ordinary spur gears, the spur gears of ink vibrator used in offset press not only have rotatory movement, but also possess axial motion. Consequently, a unified tribo-dynamic model bridged the two branches of spur gear, a multiple degrees of freedom (DOFs) discrete dynamic model and a finite line contact elastohydrodynamic lubrication (EHL) model with axial velocity, is built up to investigate the interactive mechanism and the influence of axial velocity on pressure distribution. To this end, an iterative calculation program integrated the Runge-Kutta method and the multigrid method is utilized to solve the governing equations. Obvious differences of simulation results between the tribo-dynamic and quasi-static conditions are found by making a comparison, demonstrating the necessity of establishing the proposed model. Numerical results indicate that the proposed model can be utilized as a useful tool for gear design and performance analysis.