Sensorimotor self-learning model based on operant conditioning for two-wheeled robot

Traditional control methods of two-wheeled robot are usually model-based and require the robot’s precise mathematic model which is hard to get. A sensorimotor self-learning model named SMM TWR is presented in this paper to handle these problems. The model consists of seven elements: the discrete learning time set, the sensory state set, the motion set, the sensorimotor mapping, the state orientation unit, the learning mechanism and the model’s entropy. The learning mechanism for SMM TWR is designed based on the theory of operant conditioning (OC), and it adjusts the sensorimotor mapping at every learning step. This helps the robot to choose motions. The leaning direction of the mechanism is decided by the state orientation unit. Simulation results show that with the sensorimotor model designed, the robot is endowed the abilities of self-learning and self-organizing, and it can learn the skills to keep itself balance through interacting with the environment.     

Compensation of pressure enthalpy effects on temperature fields for throttling of high-pressure real gas

For the pressure enthalpy of high pressure pneumatics, the computational fluid dynamics (CFD) simulation based on ideal gas assumption fails to obtain the real temperature information. Therefore, we propose a method to compensate the pressure enthalpy of throttling for CFD simulation based on ideal gas assumption. Firstly, the pressure enthalpy is calculated for the pressure range of 0.101 to 30 MPa and the temperature range of 190 to 298 K based on Soave-Redlich-Kwong (S-R-K) equation. Then, a polynomial fitting equation is applied to practical application in the above mentioned range. The basic idea of the compensation method is to convert the pressure enthalpy difference between inlet air and nodes into the compensation temperature. In the above temperature and pressure range, the compensated temperature is close to the real one, and the relative temperature drop error is below 10%. This error is mainly caused by the velocity difference of the orifice between the real and ideal gas models. Finally, this compensation method performs an icing analysis for practical high pressure slide pilot valve.     

Approximate method for reliability assessment of complex phased mission systems

Phased-mission systems (PMSs) have wide applications in engineering practices, such as manmade satellites. Certain critical parts in the system, such as cold standby, hot standby and functional standby, are designed in redundancy architecture to achieve high reliability performance. State-space models such as Markov process have been used extensively in previous studies for reliability evaluation of PMSs with dynamic behaviors. The most popular way to deal with the dynamic behaviors is Markov process, but it is well known that Markov process is limited to exponential distribution. In practice, however, the lifetime of most machinery products can follow non-exponential distributions like the Weibull distribution which cannot be handled by the Markov process. In order to solve this kind of problem, we present a semi-Markov model combined with an approximation algorithm to analyze PMS reliability subjected to non-exponential failures. Furthermore, the accuracy of the approximation algorithm is investigated by comparing to an accurate solution, and a typical PMS (attitude and orbit control system) is analyzed to demonstrate the implementation of the method.     

Design of car battery protection device based on torsion spring

In recent years, electric vehicles are developing rapidly in automotive industry. When involved in accidents, if the batteries of electric cars break, it is likely to cause a short circuit and start a fire. Aimed at this issue, a car battery protection device based on torsion spring has been designed. The car battery protection device can deform in a particular pattern in a collision accident. Impact energy of the accident is absorbed by the deformation, which can significantly reduce impact force on the batteries. Meanwhile, based on the principle of maximum energy absorption, some crucial parameters of the device can be determined. Furthermore, an impact simulation conducted on ANSYS software shows that maximum safety factors can be obtained when the material of car battery protection device is carbon steel. The analysis of “safe space” in the car battery protection device shows that the device can prevent battery damage effectively in general circumstances, which means the reliability of the device has been verified. Therefore, when applied to electric vehicles, the car battery protection device, which can prevent secondary accidents, significantly improves the vehicle security in accidents.     

Calculation of strain amplification matrix for strain invariant failure theory based on representative volume element models with periodical boundary condition

Strain invariant failure theory (SIFT) is a micro-mechanics-based failure theory for multi-scale failure analysis of composite materials originally proposed by Gosse and Christensen. In this paper, the approach for obtaining strain amplification matrix which is a key step for the execution of SIFT is improved by adopting representative volume element (RVE) finite element models considering periodical boundary condition, based on which more actual deformation mode is reflected. The deformation modes and strain data at the characteristic points of the centroid cell of multi-cell RVE model are analyzed and taken as a reference. It can be concluded that more reasonable deformation mode and relationship between the micro-mechanical and macro-mechanical strain states are obtained by employing the new model. Finally, numerical examples are provided to illustrate the determination of strain amplification factors within the RVEs considering periodical boundary condition at the characteristic points.     

Fault diagnosis for wind turbine based on improved extreme learning machine

A fault diagnosis method based on improved extreme learning machine (IELM) is proposed to solve the weakness (weak generalization ability, low diagnostic rate) of traditional fault diagnosis with feedforward neural network algorithm. This method fuses signal feature vectors, extracts six parameters as the principal component analysis (PCA) variables, and calculates correlation coefficient matrix among the variables. The weight values of control parameters in the extreme learning model are dynamically adjusted according to the test samples’ constantly changing. Consequently, the weight fixed drawback in the original model can be remedied. A fault simulation experiment platform for wind turbine drive system is built, eight kinds of fault modes are diagnosed by the improved extreme learning model, and the result is compared with that of other machine learning methods. The experiment indicates that the method can enhance the accuracy and generalization ability of diagnosis, and increase the computing speed. It is convenient for engineering application.     

Gain and noise figure analysis of Er<Superscript>3+</Superscript>-doped YAG transparent ceramic microchip amplifier

The rate equations and the power evolution equations based on excited state absorption (ESA) and cooperative upconversion (CUC) of high concentration erbium-doped yttrium aluminum garnet (YAG) transparent ceramic waveguide amplifier are set up to analyze the effects of the pump power, active ion concentration and waveguide length on the amplifier gain and noise figure (NF). The numerical analysis predicts that with a pump power of 100mW, an active ion concentration of 1.0×10²⁶ ion/m³ and a waveguide length of 3 cm, a small-signal gain of 30 dB and an NF of 5 dB can be achieved in the micro-chip amplifier.     

大客车车身骨架结构强度分析及其改进设计

在Un igraph ics软件中建立车身骨架的线框模型后,用自行编制的接口程序生成命令流文件将模型导入到ANSYS环境中,建立了车身骨架有限元模型。用有限元理论分析了静态工况下客车车身骨架的强度特性,探讨了承载式车身骨架不同部位的受力特性。提出了通过对骨架结构进行局部改进来提高整体结构强度的方法,提出了对原结构进行改进设计的方案,并对改进前后的客车进行了强度试验,验证了改进后结构的合理性和可靠性。     

交通分配的粒子群优化算法

为了方便合理地分配交通量,提出了交通量多路径分配的粒子群优化算法。算法的求解方法是在粒子群算法中构造了路径条数维的粒子空间,每维对应一条可行性路线,其值为对应路径所分配的交通量;对粒子进行归一化处理,使交通量守恒,并进行交通量的多路径分配;根据目标函数评价与筛选粒子,直到满足终止条件。实例计算结果表明:利用粒子群算法得到的目标函数值最小,各路段分配的交通量没有超容量现象,模型求解过程具有方向性,对交通分配的网络规模无限制,因此,粒子群优化算法可行、合理。     

Study on dynamic characteristics of vehicle gearbox under multi-boundary conditions

With the development of vehicle gearbox to high-power-density and high-speed, how to predict and optimize the dynamic characteristics of vehicle gearbox becomes increasingly prominent. Aiming at the vehicle gearbox, this paper comprehensively and deeply studies the dynamic characteristics under the multi-boundary conditions. The generation mechanism of the multi-source excitations triggering the gearbox vibration is analyzed firstly. The vibration transfer path of the gearbox is explored. Secondly, the engine excitation, the gear meshing excitation and the bearing support load are numerically calculated. According to the finite element method, a fluid-solid coupling finite element model of the gearbox body is established to predict the gearbox dynamic responses based on the Galerkin method and the Hamiltonian variational principle. Finally, the effects of the excitation condition, oil height and reinforcement forms on the vibration responses of the gearbox body are thoroughly studied by simulation. The analysis indicates that it not only helps to modify and improve the method of forecasting the gearbox dynamic response, and also provides the theoretical and technical guidance for the gearbox design and optimization.