An intelligent dental robot

An intelligent dental robot (IDR) is reported for the purpose of artificial denture verification and test. Methods: The IDR is composed of power system, intelligent control and driving system, sensor system and supporting system. Five Maxon motors are adopted to provide the driving force for the IDR. Novel motor linear actuators are developed to mimic the movement of human’s masticatory muscles. Forward and inverse kinematics of the IDR are analyzed. Seven high-precision pressure sensors are utilized to detect the force on individual artificial tooth. Results: Motion and force experiments are conducted on the IDR. The maximum biting force provided by the IDR is 490?N. Hysteresis rate of the biting force loading and unloading is less than 3%. The largest displacement for the mandible movement test is found to be 60, 9 and 22?mm in the vertical, protrusive and lateral directions, respectively. Conclusion: IDR can complete simulated human masticatory movement and provide sufficient biting force. Significance: The IDR provides clinical guidance for the design and performance test of artificial denture.     

A Penalized Crouzeix–Raviart Element Method for Second Order Elliptic Eigenvalue Problems

In this paper we propose a penalized Crouzeix–Raviart element method for eigenvalue problems of second order elliptic operators. The key idea is to add a penalty term to tune the local approximation property and the global continuity property of discrete eigenfunctions. The feature of this method is that by adjusting the penalty parameter, some of the resulted discrete eigenvalues are upper bounds of exact ones, and the others are lower bounds, and consequently a large portion of them can be reliable and approximate eigenvalues with high accuracy. Furthermore, we design an algorithm to select a penalty parameter which meets the condition. Finally we provide numerical tests to demonstrate the performance of the proposed method.     

Real-Time Attitude Estimation by Using Parallax Observation System

With the development of the satellite spatial resolution, high-resolution and high-quality remote sensing images require high stability of the observation satellite platform. Therefore, real-time attitude information is essential to enhance the accuracy and the robustness of the attitude control system in observation satellites. Through the use of the parallax observation system, this paper designs a novel framework to estimate the on-orbit attitude, which includes a complete deconvolution process, a detailed camera motion model, and a support vector regression algorithm to detect the attitude and deal with the latency. The proposed framework is testified by realistically simulated data and remote sensing images from the JL-1 satellite. Simulation and experiment results demonstrate that the proposed framework can detect and predict the attitude in real-time while the error is lower than \(1.125\,\upmu \mathrm{rad}\).     

Ni-25Cr-20Co合金时效组织结构及性能研究

在Thermo-Calc热力学软件模拟计算基础上,采用光学显微镜、扫描电子显微镜、能谱检测和透射电子显微镜研究了Ni-25Cr-20Co合金在长期时效过程中析出相的变化情况及对性能的影响,理论分析了γ′相颗粒粗化对合金拉伸变形过程中第二相与位错交互作用机制的影响。结果表明:经750℃时效后合金中析出MC、M_(23)C_6和γ′相,γ′相的体积分数约为16%。长期时效后,γ′相颗粒的平均尺寸与时间t符合LSW理论,受溶质原子扩散及γ/γ′界面能的影响。时效后合金的拉伸强度明显增加,随时效时间的延长,拉伸强度逐渐降低。随γ′相的粗化,拉伸变形过程中第二相与位错交互作用的机制由位错热攀移机制→位错切割机制→Orowan绕越机制转变为位错热攀移机制→Orowan绕越机制→位错切割机制。     

银离子修饰的磺酸硅胶的制备研究

为了制备一种具有硫离子显色反应性的材料,先用氯磺酸对硅胶进行改性,制备磺酸硅胶(SSA),然后SSA的磺酸基通过离子键结合银离子,制备得到银离子修饰的磺酸硅胶(Ag-SSA)。利用傅里叶红外光谱仪(FTIR)、扫描电子显微镜(SEM)、X射线衍射仪(XRD)、等离子体光谱仪(ICP)等测试对实验材料以及产物进行表征。结果表明,磺酸基成功地接枝在硅胶表面,银离子结合在磺酸硅胶表面,Ag-SSA对含硫离子的溶液具有变色反应特征。     

Improved electrochemical hydrogen storage capacity of Ti45Zr38Ni17 quasicrystal by addition of ZrH2

Ti₄₅Zr₃₈Ni₁₇ + xZrH₂ (x = 5, 10, 15 and 20 wt%) composite materials are produced by ball milling for 20 min. The results of XRD measurement show that the composite materials contain icosahedral quasicrystal phase (I-phase), FCC phase with a Ti₂Ni type crystal and C14 Laves phase. After adding ZrH₂, the composite materials include not only the individual phases mentioned above, but also the ZrH phase. These composite materials are used as the negative electrode material of the nickel-metal hydride batteries. The electrochemical hydrogen storage characteristics of the material after adding ZrH is investigated. The Ti₄₅Zr₃₈Ni₁₇ + xZrH₂ (x = 5, 10, 15 and 20 wt%) composite material has reached the maximum discharge capacity (83.2 mA h/g) when x equals 10. This maximum discharge capacity is much higher than that of Ti₄₅Zr₃₈Ni₁₇ alloy without ZrH. After adding ZrH_2, the high-rate discharge ability and the cycling stability are enhanced simultaneously. The improvement of the electrochemical properties can be attributed to the synergistic effects of ZrH₂, and the synergistic effects in the composite electrodes are probably attributed to the entry of most of hydrogen atoms from weakly bond strength of the Zr-H to the I-phase structure in electrochemical reaction.     

新型架空线路防坠落装置用自锁器研制

针对架空线路防坠落装置T型导轨用自锁器现场使用需求,对自锁器机械结构及特性进行了研究。设计了自锁器的导向和拆卸结构方案,进行了仿真计算,生产了样机,通过了实验室力学试验验证,并在架空线路现场进行了应用试验。在保证自锁器安全性的基础上,使自锁器具备了拆卸功能,并提高了现场适用性能,解决了一线登塔人员的使用难题。     

Adoption of combined detection technology of tumor markers via deep learning algorithm in diagnosis and prognosis of gallbladder carcinoma

This study was to explore the application value of back propagation (BP) neural network (BPNN) and genetic algorithm (GA) in the combined detection and prognosis of tumor markers in patients with gallbladder cancer. 446 patients with gallbladder cancer were included in the experimental group, 279 patients with benign gallbladder disease were included in the control group, and 188 healthy people were selected and included in the blank group. Serum tumor markers (CA242, CA199, CEA, and CA125) of the three groups were detected by electrochemical luminescent immune analyzer, and follow-up data for 5 years after surgery were collected. Based on BPNN and GA, an optimization algorithm for multi-tumor markers was constructed and applied to the combined detection of tumor markers in patients. The artificial neural network (ANN), dynamic network biomarker (DNB), auxiliary diagnosis algorithm of the support vector machine (SVM) based on the particle swarm optimization (PSO) (PSO-SVM), matched-pairs feature selection (MPFS) based on the machine learning, and the BPNN were introduced to compare with the algorithm constructed. The diagnostic performances of the algorithms were evaluated with the fivefold cross-validation method. The results showed that the levels of CanAg (CA) 242, carcinoma embryonic antigen (CEA), CA199, and CA125 and positive rates in the experimental group were significantly higher than those in the control group and the blank group (P?<?0.05); but the differences between control group and blank group were not visible (P?>?0.05). The sensitivity (91.72%) and specificity (87.49%) in detecting CA242 and CA199 based on the proposed algorithm were the highest; the sensitivity (0.9186), specificity (0.8622), and accuracy (94.94%) of the proposed algorithm were higher than those of the conventional algorithms. The postoperative follow-up survival rate of patients in the experimental group was reduced from 41.72% in the first year to 4.28% in the fifth year; tumor node metastasis (TNM) stage IV, neck gallbladder cancer, and CA199 were significantly correlated with the survival rate of patients in the experimental group (P?<?0.05). In summary, the combined detection technology of multiple tumor markers based on deep learning algorithms showed excellent diagnostic and prognostic performance for gallbladder cancer. The occurrence of gallbladder cancer was related to the tumor markers CA242, CA199, CEA, and CA125, showing better detection effects by combination of CA242 and CA199. The TNM stage IV, neck gallbladder cancer, and CA199 were independent risk factors for the decrease in survival rate of patients with gallbladder cancer.

     

Underdetermined blind source extraction of early vehicle bearing faults based on EMD and kernelized correlation maximization

Journal of Intelligent Manufacturing - The incipient bearing fault diagnosis is crucial to the industrial machinery maintenance. Developed based on the blind source separation, blind source...