基于悬架挠度的商用车车载测重传感器安装设计

为了增加商用车车载测重系统中霍尔式角度传感器的有效量程范围,提高系统的质量测量精度,该文对角度传感器的安装位置进行了研究。以某型商用车为实验平台,建立了传感器角度变化量与后悬架挠度之间的线性关系,确定了使角度变化量最大为设计目标。兼顾传感器摆臂连杆机构约束、车架和车轴约束、悬架挠度极限位置约束,确定了设计目标下的霍尔式角度传感器安装位置。仿真结果表明,在该安装位置下商用车车载测重系统的有效量程为17°,最小测量精度为158.5 kg。实车实验结果表明,在该安装位置下,系统质量测量较为准确,满足使用要求。

基于数字相敏检波算法的驼峰测重信号处理方法研究

在分析驼峰压磁测重传感器工作原理的基础上,提出了一种应用A/D转换器和计算机,采用DPSD算法对驼峰测重传感器输出信号进行处理的方法,并进行了静态和动态测量试验。试验结果表明,该方法能准确地测得钢轨外部压力与测重传感器信号输出电压的线性关系,可以应用于驼峰测重设备的设计和改进。

An Optical Disdrometer for Measuring Present Weather Parameters

A new present weather identifier(PWI) based on occlusion and scattering techniques is presented in the study. The present weather parameters are detectable by the meteorological optical range(MOR) approximately up to 50 km and by droplets with diameters ranging from 0.125 mm to 22 mm with velocities up to 16 m s-1. The MOR error is less than 8% for the MOR within 10 km and less than 15% for farther distances. Moreover, the size errors derived from various positions of the light sheet by the particles were checked within ± 0.1 mm ± 5%. The comparison shows that the MOR, in a sudden shower event, is surprisingly consistent with those of the sentry visibility sensors(SVS) with a correlation coefficient up to 98%. For the rain amounts derived from the size and velocity of the droplets, the daily sums by the PWI agree within 10% of those by the Total Rain Weighing Sensor(TRwS205) and the rain gauge. Combined with other sensors such as temperature, humidity, and wind, the PWI can serve as a present weather sensor to distinguish several weather types such as fog, haze, mist, rain, hail, and drizzle.

Characteristics from a hydrodynamic model of a trapezoidal artificial reef

Flume experiments and numerical simulation were conducted to characterize the hydrodynamics of a trapezoid artificial reef.Measurements in particle image velocimetry were conducted to observe the formation of upwelling and vortices;and forces for the reef model were measured by load cell.The results of flume experiments agree well with the numerical data.In addition,the flow structure around a reef combining trapezoidal and cubic blocks was simulated numerically under two deployment schemes,showing a more complicated flow structure than that of a stand-alone reef.Relationship between drag coefficient and Reynolds number suggest that the degree of turbulence can be assessed from the value of drag coefficient downstream from the reef.The role of the reef in water flow is to reduce flow velocity and generate turbulence.

Image Reconstruction for Invasive ERT in Vertical Oil Well Logging

An invasive electrical resistance tomographic sensor was proposed for production logging in vertical oil well.The sensor consists of 24 electrodes that are fixed to the logging tool,which can move in the pipeline to acquire data on the conductivity distribution of oil/water mixture flow at different depths.A sensitivity-based algorithm was introduced to reconstruct the cross-sectional images.Analysis on the sensitivity of the sensor to the distribution of oil/water mixture flow was carried out to optimize the position of the imaging cross-section.The imaging results obtained using various boundary conditions at the pipe wall and the logging tool were compared.Eight typical models with various conductivity distributions were created and the measurement data were obtained by solving the forward problem of the sensor system.Image reconstruction was then implemented by using the simulation data for each model.Comparisons between the models and the reconstructed images show that the number and spatial distribution of the oil bubbles can be clearly identified.

Two-stage prediction and update particle filtering algorithm based on particle weight optimization in multi-sensor observation

The reasonable measuring of particle weight and effective sampling of particle state are consid- ered as two important aspects to obtain better estimation precision in particle filter. Aiming at the comprehensive treatment of above problems, a novel two-stage prediction and update particle filte- ring algorithm based on particle weight optimization in multi-sensor observation is proposed. Firstly, combined with the construction of muhi-senor observation likelihood function and the weight fusion principle, a new particle weight optimization strategy in multi-sensor observation is presented, and the reliability and stability of particle weight are improved by decreasing weight variance. In addi- tion, according to the prediction and update mechanism of particle filter and unscented Kalman fil- ter, a new realization of particle filter with two-stage prediction and update is given. The filter gain containing the latest observation information is used to directly optimize state estimation in the frame- work, which avoids a large calculation amount and the lack of universality in proposal distribution optimization way. The theoretical analysis and experimental results show the feasibility and efficiency of the proposed algorithm.

Porous silicon biosensor for detection of variable domain of heavy-chain of HCAb antibody

In this paper, we produce porous silicon （PSi） by electrochemical etching, and it is the first time to evaluate the performance of label-free porous silicon biosensor for detection of variable domain of heavy chain of heavy-chain antibody （VHH）. The binding of hen egg white lysozyme （HEWL） and VHH causes a red shift in the reflection spectrum of the biosensor. The red shift is proportional to the VHH concenlration in the range from 14 gg.ml-I to 30 pg.ml~ with a detection limit of 0.648 ng.ml~. The research is useful for the development of label-free biosensor applied in the rapid and sensitive determination of small molecules.