基于协同优化算法的流速仪检定系统设计

提出了一种小型轻便的流速仪检定系统的设计方案,并运用改进的多学科协同优化方法求解各学科设计变量的最优解。首先介绍了算法思想及改进措施,并根据系统设计要求建立了各学科的设计变量、目标函数和约束条件；其次,运用遗传算法求解各学科设计变量的最优解,并根据优化结果完善了系统的设计方案,同时运用计算机仿真等方法验证了优化结果的可行性。结果表明,优化后的检定系统满足流体力学效应、匀速运动时间、系统重量等设计要求,同时证明了协同优化算法解决多学科设计优化问题的有效性。     

光致荧光剂量计β辐照器的研制及性能研究

本文针对空间辐射、核动力远洋、核应急等特殊环境下个人及环境剂量监测量值无法实时校准的问题，研制了一种便携式的β辐照器，可携带至现场对光致荧光剂量计（OSLD）进行校准，为特殊环境下剂量监测的准确性提供计量保障。β辐照器采用可替换的⁹⁰Sr-⁹⁰Y平面电镀源作为校准源，并可溯源至标准β辐射场，通过电磁阀控制辐照动作，其总质量小于3 kg。研究结果表明：β辐照器周围剂量当量率处于环境水平；参考点平均剂量率为0.060~0.083 mGy/s，其相对标准不确定度为6.9%；辐照剂量重复性为3.9%（n=10）。     

双离心机法线加速度计动态校准中三参数余弦算法实现及应用

在双离心机的线加速度计动态校准中,三参数余弦算法贯穿在幅频特性、相频特性以及幅值线性度的整个测试中。本文详细描述了三参数余弦算法的概念和推导过程,以及在双离心机线加速度计动态校准数据处理过程中三参数余弦算法的程序实现;介绍了在幅频特性和相频特性中关于采集点的选取方式,降低由于采集点选择方式不同对数据拟合精度造成的影响。选取某型线加速度计为例,利用双离心机进行动态校准,对采集得到的数据点进行曲线拟合并得到测试结果,验证了所编写的三参数余弦算法程序的可行性。     

新生儿经皮黄疸检测仪的校准

针对经皮黄疸检测仪在使用过程中测量结果无法溯源的问题,通过分析经皮黄疸检测仪的检测原理,研究其测量结果与血清法测胆红素的相关性,提出可尝试采用标准溶液法、标准板法和胆红素浓度模拟法对经皮黄疸检测仪进行校准,并探讨了校准方法的可行性。     

E6控制系统在天然气发动机上的应用

为了验证E6控制系统的配机效果,并使4020CT型天然气发动机的性能达到设计要求,使用E6控制系统对该发动机进行各工况运行条件的优化标定。E6控制系统使用空燃比闭环控制策略,能够使发动机保持运行在设定的各工况最佳运行条件下。通过E6控制系统的应用试验,完成了发动机性能参数的标定和优化,以及试验数据的采集和分析。试验结果表明,4020CT型天然气发动机的性能特性、排放指标等均达到设计要求。这说明E6控制系统标定效果较佳,同时,为E6控制系统的推广应用奠定了基础。     

A multilevel calibration technique for an industrial robot with parallelogram mechanism

This paper presents a multilevel calibration technique for improving the absolute accuracy of an industrial robot with a parallelogram mechanism (ABB IRB2400). The parallelogram structural error is firstly modeled based on the partial differential of the position function of a general four-bar linkage and the linearization of the position constraints of the parallelogram mechanism, the model coefficients are fitted from experimental data. Secondly, an absolute kinematic calibration model is established and resolved as a linear function of all the kinematic parameters, as well as the base frame parameters and tool parameters. Finally, contrary to most other similar works, the robot joint space (rather than Cartesian space) is divided into a sequence of fan-shaped cells in order to compensate the non-geometric errors, the positioning errors on the grid points are measured and stored for the error compensation on the target points. After the multilevel calibration, the maximum/mean point positioning errors on 284 tested configurations (evenly distributed in the robot common workspace) are reduced from 1.583/0.420 mm to 0.172/0.066 mm respectively, which is almost the same level as the robot bidirectional repeatability.     

Monocular-vision-based method for online measurement of pose parameters of weld stud

With the rapid development of stud welding technology, weld studs are extensively used in automobile industry. A weld stud differs from a regular stud in that it has special external features. This study develops a novel non-contact, fast, and high-precision method based on monocular vision for measuring the position and attitude parameters of a weld stud. Under this method, the measuring principle for the weld stud’s position and attitude parameters is derived and an accurate mathematical model is set up. Based on this mathematical model, a precise calibration method for the projective transformation’s corresponding relationship parameters is developed and an optimal observation condition is then introduced as the constraint into the measurement process so as to enhance the location precision. The experiment results show that the proposed method is fast and accurate, and it satisfies the requirement of online, flexible, fast, and high-precision measurement of weld studs’ pose parameters in automobile and other manufacturing industries.     

Statistical method‐based calibration and validation of a solid oxide fuel cell model

A 2‐stage model validation strategy for the previously developed solid oxide fuel cell model using the data from custom‐designed experiments is presented. The strategy is based on the identification of model structural and parametric errors. In the preliminary validation, the causes that can result in the voltage error during changing temperature and fuel flow rate conditions are analysed. It is identified that the convection heat transfer process contributes significantly towards the cell performance in a temperature controlled test environment. Rectification of this error results in the reduction of the maximum voltage error from 14% to 0.5%. Graphical methods for data visualisation are utilised to examine goodness of fit of the model. Input sensitivity analysis reveals that the air flow rate has negligible influence on the output quantities of current density, fuel utilisation, and cell temperature owing to temperature‐controlled conditions of the test. Parameter sensitivity analysis through the elementary effects method reveals that most of the electrochemical parameters in general and the activation energies in particular have dominant effects on the considered system outputs. Model validation is carried out through a classical statistical method of hypothesis testing by using the parameter uncertainty information obtained through nonlinear least squares fitting. The efficacy of the model validation strategy is demonstrated through the model acceptance with 8% maximum error in cell current.     

光学显微定位系统定位精度分析

为了提高光学显微定位系统对细胞微生物识别定位的精度：一方面，必须改进手眼标定方法；另一方面，需要提高全局图像识别的准确性，因此，提出一种两步法对系统进行手眼标定。首先，通过标定固定靶标来确定系统原点，并得到视觉模块相对于系统原点的转换关系；然后，根据每次拍照的起始点位置、拍照的数量和移动的步长求解出全局图像相对于系统原点的转换关系；最后，为了进一步提高全局转换关系的准确度，提出一种基于傅里叶变换的误差矫正方法，利用傅里叶变换求解出视觉模块在移动过程中的误差，并加入系统进行补偿。实验结果表明，误差补偿之后，系统X轴方向的误差均值从10.23 μm降为-0.002 μm，Y轴方向的误差均值从6.9 μm降为-0.50 μm，显微定位系统的平均定位精度达到了99%以上。结果表明，所提方法可很好地用于光学显微定位系统对细胞微生物进行高精度的自动化抓取。     

CBSC: A Crowdsensing System for Automatic Calibrating of Barometers

The mobile crowdsensing software systems can complete large-scale and complex sensing tasks with the help of the collective intelligence from large numbers of ordinary users. In this paper, we build a typical crowdsensing system, which can efficiently calibrate large numbers of smartphone barometer sensors. The barometer sensor now becomes a very common sensor on smartphones. It is very useful in many applications, such as positioning, environment sensing and activity detection. Unfortunately, most smartphone barometers today are not accurate enough, and it is rather challenging to efficiently calibrate a large number of smartphone barometers. Here, we try to achieve this goal by designing a crowdsensingbased smartphone calibration system, which is called CBSC. It makes use of low-power barometers on smartphones and needs few reference points and little human assistant. We propose a hidden Markov model for peer-to-peer calibration, and calibrate all the barometers by solving a minimum dominating set problem. The field studies show that CBSC can get an accuracy of within 0.1 hPa in 84% cases. Compared with the traditional solutions, CBSC is more practical and the accuracy is satisfying. The experience gained when building this system can also help the development of other crowdsensing-based systems.