A novel method for estimating the track-soil parameters based on Kalman and improved strong tracking filters

A tracked vehicle has been widely used in exploring unknown environments and military fields. In current methods for suiting soil conditions, soil parameters need to be given and the traction performance cannot always be satisfied on soft soil. To solve the problem, it is essential to estimate track-soil parameters in real-time. Therefore, a detailed mathematical model is proposed for the first time. Furthermore, a novel algorithm which is composed of Kalman filter (KF) and improved strong tracking filter (STF) is developed for online track-soil estimation and named as KF–ISTF. By this method, the KF is used to estimate slip parameters, and the ISTF is used to estimate motion states. Then the key soil parameters can be estimated by using a suitable soil model. The experimental results show that equipped with the estimation algorithm, the proposed model can be used to estimate the track-soil parameters, and make the traction performance satisfied with soil conditions.     

Improving CNC contouring accuracy by robust digital integral sliding mode control

Integral sliding mode control (ISMC) has been employed and shown to improve contouring accuracy in the presence of external disturbances and model uncertainties. An ISMC controller directly reduces the tracking errors of each individual axis, thereby reducing the overall contour errors indirectly. An ISMC controller drives the system dynamics back onto the sliding surface if there exists a deviation from the predefined surface. In the design of an ISMC controller, it is crucial to choose an appropriate sliding surface as this has a great impact on system performance and on chattering. In current approaches, the sliding surface is chosen largely based on a rule of thumb which is only applicable for systems with open-loop poles having imaginary parts. In this paper, an approach is presented to design the sliding surface using principles of robust digital control so that both the regulation and robustness requirements can be satisfied. The natural frequency of the dominant closed-loop poles is chosen such that the modulus of the output sensitivity function lies within the robustness bounds. Resonant pole-zero filters are then used to reshape the output sensitivity function in specific frequency regions. Experiments showed that when the modulus of the output sensitivity function is kept within the robustness bounds, chattering can be avoided and the contour errors resulting from vibrations can be reduced. The introduction of a resonant pole-zero filter also allowed the attenuation band to be expanded so that the low frequency components of the contour errors are attenuated.     

A new numerical algorithm to check the observability and bad-data processing ability of the metering scheme

This paper provides a unified approach for the optimization of measurements placements employed for power system online monitoring through state estimation. The proposed methodology, which can be suitable for the mixed measure system, preserves state estimation observability and bad-data processing capability by employing numerical algorithms for observability checking, critical measurements and critical couple identification. First, node injection radix measurements and measurement categories are defined. According to the above definitions, the coefficient matrix can be solved. The analysis on the column vectors of the coefficient matrix can determine each measurement classification. Furthermore, the numbers of each measurement class contains can determine bad-data processing capability. The observability can be checked by the type number of measurements. The proposed method is illustrated with the IEEE39-bus system and the IEEE118-bus system. Results from the case studies are presented to demonstrate that the approach adequately fulfills the desired properties related to observability, bad-data processing, cost, and robustness.     

Interacting force estimation during blade/seal rubs

Abradable seals are used in aeronautical compressors to minimize the blade–casing clearance while ensuring the integrity of the mechanical parts in the invent of contact. Considering the tight clearance, in-flight blade–seal interactions may occur and have to be taken into account when designing abradable seals. The blade–seal interacting force is difficult to access but constitutes a key feature to understand the phenomena and to develop numerical models. The present paper aims to present an experimental methodology to estimate the blade–seal interacting force from indirect measurements. The methodology has been applied to a short interaction produced on a dedicated test rig in conditions representative of the full-scale configuration. The obtained force was correlated with the wear profile of the abradable seal.     

An improved adaptive unscented Kalman filter for estimating the states of in‐wheel‐motored electric vehicle

Vehicle state is essential for active safety stability control. However, the accurate measurement of some vehicle states is difficult to achieve without the use of expensive equipment. To improve estimation accuracy in real time, this paper proposes an estimator of vehicle velocity based on the adaptive unscented Kalman filter (AUKF) for an in‐wheel‐motored electric vehicle (IWMEV). Given the merits of an independent drive structure, the tire forces of the IWMEV can be directly calculated through a vehicle dynamic model. Additionally, by means of the normalized innovation square, the validity of vehicle velocity estimation can be detected, and the sliding window length can be adjusted adaptively; thus, the steady‐state error and the dynamic performance of the IWMEV are demonstrated to be simultaneously improved over an alternative approach in comparisons. Then, an adaptive adjustment strategy for the noise covariance matrices is introduced to overcome the impact of parameter uncertainties. The numerically simulated and experimental results prove that the proposed vehicle velocity estimator based on AUKF not only improves estimation accuracy but also possesses strong robustness against parameter uncertainties. The deployment of the estimation algorithm by using a single‐chip microcomputer verifies the strong real‐time performance and easy‐to‐implement characteristics of the proposed algorithm.     

基于广义二次互相关的低信噪比信号时延估计

针对时延估计精度受噪声影响,导致时延估计不准确的问题,在现有广义二次相关算法的基础上,提出了一种改进的广义二次相关算法,通过将二次相关函数先做指数运算,降低噪声干扰,再将傅里叶逆变换得到的相关函数做高次方运算,达到锐化峰值提高时延正确率的目的。仿真结果表明,信噪比(SNR)在0~10 dB时,改进算法的均方根误差明显优于广义二次相关算法,正确率相比于广义二次相关算法也显著提高,且在更低SNR的情况下仍然具有一定优势。     

基于卷积神经网络的单目深度估计

针对利用深度学习方法对街道图像进行深度估计，提出采用语义分割的方法解决深度图出现边界模糊等问题；估计深度通过左右视角图生成视差图进行无监督的训练。在网络模型中添加语义分割层，采取多个空洞卷积并行的结构增加感受野，同时减少了图像下采样的次数，降低了由于下采样带来的信息损失，使得的结果更加准确。这也是在深度估计中首次与空洞卷积相结合增加准确率。通过对KITTI街道数据集进行训练，与现有结果相比，除了增加检测准确性，降低错误率之外，使得效果图中的物体更加清晰，并且在效果图中还保留了一些原模型中被忽视掉的细节信息，将原始图像更加完整的表现出来。     

裂解态正癸烷点火延迟时间的理论研究（英）

在先进飞行器发动机中,吸热碳氢燃料在进入燃烧室之前会发生热裂解反应,生成未反应燃料和小分子裂解产物的混合物(称为裂解态燃料)。本工作研究了在1300~1800 K、0.1~3.0 MPa和当量比为1.0的条件下,不同的裂解转化率、裂解压力、点火压力和自由基对正癸烷裂解着火特性的影响。通过采用一种精确的组合机理,从理论上计算了流动反应器中3.0和5.0 MPa下正癸烷裂解组分,与文献中的实验结果吻合较好。结果表明,正癸烷在3 MPa和5 MPa下裂解的出口转化率分别为46.2%和58.8%,裂解产物分布一致,但乙烯的含量随着压力的升高明显的降低,而烷烃含量随着压力的增大而增加。尽管自由基总体含量很低,但在3 MPa条件下裂解产物中的自由基浓度依然高于5 MPa条件下。对于点火延迟时间的计算结果则表明,裂解态正癸烷的点火延迟时间随着转化率的增大而延长,且在5 MPa下随着转化率的变化更明显。相同转化率下,5 MPa下的裂解态正癸烷的点火延迟时间比3 MPa下更短。此外,与无自由基的裂解正癸烷相比,裂解正癸烷中自由基的存在可以加速着火过程,转化率小于40%时,着火延迟时间缩短15%以上。     

基于改进的最大似然法识别风力发电机转子的载荷参数

风机不对中故障是多载荷参数耦合而成,工程师难以凭经验了解载荷参数的大致范围。针对因转子结构参数和测试条件等不确定性参数的存在及载荷参数先验信息未知,最大似然法识别转子不对中故障的载荷参数时采用的搜索计算面临计算量大,且迭代过程中灵敏度会带来一些数值问题。引入搜索区间进退法到敏感矩阵法与最大似然法中,对最大似然法进行改进。改进后的最大似然法中的迭代适于处理复杂工程优化问题,避免传统迭代数值法对搜索空间的苛刻要求。以输入尺寸和输出测试响应具有随机性测量误差的风力发电机转子系统为例,在三种测量误差下的识别结果表明,改进的最大似然法提高了最大似然法的辨识效果,可以减少不确定性因素对识别结果的影响,鲁棒性好。     

双态组织高Nb-TiAl合金的缺口敏感性

通过对圆棒状缺口试样和无缺口光滑试样进行单向拉伸试验,研究了双态组织高Nb-TiAl合金的缺口敏感性。研究表明,缺口根半径R≥0. 5 mm的U型试样和缺口角度60°、R≥1 mm的V型试样的抗拉强度RmN都大于光滑试样的抗拉强度Rm,缺口敏感度NSR均大于1,合金对缺口不敏感。当缺口类型相同时,缺口敏感性随缺口根半径R的减小而增大; V型缺口敏感性大于U型缺口;对于V型缺口试样,当R=0. 5 mm时,其NSR在0. 98～1. 03之间,RmN在Rm附近波动,易出现缺口敏感。