图像辅助汽车制动主缸补偿孔法线测量

随着道路上汽车的增多,汽车制动系统的可靠性受到越来越多的关注,基于机器视觉的汽车制动主缸补偿孔参数检测精度,是决定汽车安全性和停车可靠性的关键技术,补偿孔作为汽车制动主缸的重要组成部分,可以起到调节汽车制动主缸储液罐与压力室中制动液的重要作用,其尺寸精度和加工质量受到严格的控制,因此如何准确的获取补偿孔的图像是补偿孔参数检测的首要问题。通过将飞机钻铆孔法线找正的方法引入到图像获取中,将四点微平面法线检测方法与图像处理相结合,实现高效高精度的法线找正。实验表明,本文算法法线找正精度高于0.05°,优于传统检测精度的0.5°,检测时间小于1 s。本文提出的算法在满足精度要求的情况下,算法简单,实时性高,同时具有较好的鲁棒性,满足制动主缸生产工业现场对于检测速度和精度的要求。

基于多激光传感器装配的自由曲面法线找正方法研究

在国产化、技术自主化的大型飞机项目上,对孔位精度的标准正逐步升高,钻头的垂直度又是这一标准中最受关注的条件。机器人自动钻铆系统工作时,所产生的装配误差、磕碰、偏移等状况,不仅降低了制造及检测的准确度,还影响了整个结构件的疲劳性能。针对这一问题,提出了基于多激光传感器装配的自适应自由曲面法线检测技术,搭建了以该方法进行姿态找正的数学模型,并研究了检测装置的标定方法及流程。同时,着重讨论了在自适应方法检测时,利用电子经纬仪等装置进行误差补偿的相关技术。该方法的验证实验结果显示,多组实验数据均达到了法向精度<±0.5°的关键技术指标要求,找正后的法线平均偏差值为0.0667°。该方法能有效补偿在制孔工作中所产生的相关误差,进一步提高机器人的定位精度及法线方向检测精度。

基于工业机器人的飞机柔性装配技术

研究了基于工业机器人的飞机柔性装配技术,着重讨论了机器人精度补偿、末端执行器设计、法线检测与找正、系统控制、离线编程等关键技术。通过在小翼部件加工中的应用,达到了孔位精度<±0.5mm、法向精度<±0.5°等关键技术指标。结果表明,对于特定应用对象采用机器人技术进行飞机部件自动装配为一个理想、低成本的解决方案,随着当今工业机器人性能不断增强,配以末端执行器和相关的补偿系统,在航空工业作为装配平台是可行的。

塔式太阳能定日镜子镜面形精度和聚光性能评价的新方法

应用自行研制的基于法线测量原理的定日镜子镜面形检测系统,检测了用于100 m2定日镜的1.562 5 m2的正方形子镜,并基于能流分布仿真分析方法对子镜面形精度和聚光性能进行了评价。这种评价方法是采用激光束偏转测角法获取被测子镜的法线数据,用计算机仿真方法,对入射阳光进行光线追击,可以分析出子镜在任意时空位置的聚光性能。经与实际聚光光斑能流测量数据比对,检测分析数据与对实际日光跟踪聚光数据实测数据一致,可应用于子镜面形的在线调整。

Quantitative analysis of magnetic anomaly of reinforcements in bored in-situ concrete piles

We quantitatively study magnetic anomalies of reinforcement rods in bored insitu concrete piles for the first time and summarized their magnetic anomaly character. Key factors such as measuring borehole orientation, borehole-reinforcement distance, and multiple-section reinforcement rods are discussed which contributes valid and quantitative reference for using the magnetic method to detect reinforcement rods. Through tests with model piles, we confirm the accuracy of theoretical computations and then utilize the law discovered in theoretical computations to explain the characteristics of the actual testing curves. The results show that the Za curves of the reinforcement rod reflect important factors regarding the reinforcement rods, such as rod length, change of reinforcement ratio, length of overlap, and etc. This research perfects the magnetic method for detecting reinforcement rods in bored in-situ concrete piles and the method has great importance for preventing building contractor fraud.

^(18)F-DG PET/CT in detection of recurrence and metastasis ofcolorectal cancer

AIM: To evaluate the value of 18F-DG PET/CT in detecting recurrence and/or metastasis of colorectal cancer (CRC). METHODS: Combined visual analysis with semiquantitative analysis, the 18F-DG PET/CT whole- body imaging results and the corresponding clinical data of 68 postoperative CRC patients including 48 male and 20 female with average age of 58.1 were analyzed retrospectively. RESULTS: Recurrence and/or metastasis were confirmed in 56 patients in the clinical follow-up after the PET/CT imaging. The sensitivity of PET/CT diagnosis of CRC recurrence and/or metastasis was 94.6%, and the specificity was 83.3%. The positive predictive value (PPV) was 96.4% and the negative predictive value (NPV) was 76.9%. PET/CT imaging detected one or more occult malignant lesions in 8 cases where abdominal/pelvic CT and/or ultrasonography showed negative findings, and also detected more lesions than CT or ultrasonography did in 30.4% (17/56) cases. Recurrence and/or metastasis was detected in 91.7% (22/24) cases with elevated serum CEA levels by 18F-DG PET/CT imaging. CONCLUSION: 18F-DG PET/CT could detect the recurrence and/or metastasis of CRC with high sensitivity and specificity.

PROJECTION BASED STATISTICAL FEATURE EXTRACTION WITH MULTISPECTRAL IMAGES AND ITS APPLICATIONS ON THE YELLOW RIVER MAINSTREAM LINE DETECTION

Mainstream line is significant for the Yellow River situation forecasting and flood control.An effective statistical feature extraction method is proposed in this paper.In this method, a between-class scattering matrix based projection algorithm is performed to maximize between-class differences, obtaining effective component for classification;then high-order statistics are utilized as the features to describe the mainstream line in the principal component obtained.Experiments are performed to verify the applicability of the algorithm.The results both on synthesized and real scenes indicate that this approach could extract the mainstream line of the Yellow River automatically, and has a high precision in mainstream line detection.

Sparse Kernel Locality Preserving Projection and Its Application in Nonlinear Process Fault Detection

Locality preserving projection (LPP) is a newly emerging fault detection method which can discover local manifold structure of a data set to be analyzed, but its linear assumption may lead to monitoring performance degradation for complicated nonlinear industrial processes. In this paper, an improved LPP method, referred to as sparse kernel locality preserving projection (SKLPP) is proposed for nonlinear process fault detection. Based on the LPP model, kernel trick is applied to construct nonlinear kernel model. Furthermore, for reducing the computational complexity of kernel model, feature samples selection technique is adopted to make the kernel LPP model sparse. Lastly, two monitoring statistics of SKLPP model are built to detect process faults. Simulations on a continuous stirred tank reactor (CSTR) system show that SKLPP is more effective than LPP in terms of fault detection performance.

Improved Kernel PLS-based Fault Detection Approach for Nonlinear Chemical Processes

In this paper, an improved nonlinear process fault detection method is proposed based on modified kernel partial least squares(KPLS). By integrating the statistical local approach(SLA) into the KPLS framework, two new statistics are established to monitor changes in the underlying model. The new modeling strategy can avoid the Gaussian distribution assumption of KPLS. Besides, advantage of the proposed method is that the kernel latent variables can be obtained directly through the eigen value decomposition instead of the iterative calculation, which can improve the computing speed. The new method is applied to fault detection in the simulation benchmark of the Tennessee Eastman process. The simulation results show superiority on detection sensitivity and accuracy in comparison to KPLS monitoring.

AN EFFICIENT APPROXIMATE MAXIMUM LIKELIHOOD SIGNAL DETECTION FOR MIMO SYSTEMS

This paper proposes an efficient approximate Maximum Likelihood (ML) detection method for Multiple-Input Multiple-Output (MIMO) systems,which searches local area instead of exhaustive search and selects valid search points in each transmit antenna signal constellation instead of all hy-perplane. Both of the selection and search complexity can be reduced significantly. The method per-forms the tradeoff between computational complexity and system performance by adjusting the neighborhood size to select the valid search points. Simulation results show that the performance is comparable to that of the ML detection while the complexity is only as the small fraction of ML.

Pro-apoptotic effects of tectorigenin on human hepatocellular carcinoma HepG2 cells

AIM:To investigate the effects of tectorigenin on human hepatocellular carcinoma(HCC)HepG2 cells.METHODS:Tectorigenin,one of the main components of rhizome of Iris tectorum,was prepared by simple methods,such as extraction,filtration,concentration,precipitation and recrystallization.HepG2 cells were incubated with tectorigenin at different concentrations,and their viability was assessed by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay.Apoptosis was detected by morphological observation of nuclear change,agarose gel electrophoresis of DNA ladder,and flow cytometry with Hoechst 33342,Annexin V-EGFP and propidium iodide staining.Generation of reactive oxygen species was quantified using DCFH-DA.Intracellular Ca2+was monitored by Fura 2-AM.Mitochondrial membrane potential was monitored using Rhodamine 123.Release of cytochrome c from mitochondria to cytosol was detected by Western blotting.Activities of caspase-3,-8 and-9 were investigated by Caspase Activity Assay Kit.RESULTS:The viability of HepG2 cells treated by tectorigenin decreased in a concentration-and timedependent manner.The concentration that reduced the number of viable HepG2 cells by 50%(IC50)after 12,24 and 48 h of incubation was 35.72 mg/L,21.19 mg/L and 11.06 mg/L,respectively.However,treatment with tectorigenin at 20 mg/L resulted in a very slight cytotoxicity to L02 cells after incubation for 12,24 or 48 h.Tectorigenin at a concentration of 20 mg/L greatly inhibited the viability of HepG2 cells and induced the condensation of chromatin and fragmentation of nuclei.Tectorigenin induced apoptosis of HepG2 cells in a time-and dose-dependent manner.Compared with the viability rate,induction of apoptosis was the main mechanism of the anti-proliferation effect of tectorigenin in HepG2 cells.Furthermore,tectorigenininduced apoptosis of HepG2 cells was associated with the generation of reactive oxygen species,increased intracellular[Ca2+]i,loss of mitochondrial membrane potential,translocation of cytochrome c,and activation of caspase-9 and-3.CONCLUSION:Tectorigenin induces apoptosis of HepG2 cells mainly via mitochondrial-mediated pathway,and produces a slight cytotoxicity to L02 cells.

A NEW RECURSIVE ALGORITHM FOR MULTIUSER DETECTION

Based on the synthesis and analysis of recursive receivers, a new algorithm, namely partial grouping maximization likelihood algorithm, is proposed to achieve satisfactory performance with moderate computational complexity.During the analysis, some interesting properties shared by the proposed procedures are described.Finally, the performance assessment shows that the new scheme is superior to the linear detector and ordinary grouping algorithm, and achieves a bit-error rate close to that of the optimum receiver.

Reduced Popdc3 expression correlates with high risk and poor survival in patients with gastric cancer

AIM： To investigate the expression of Popeye domain containing 3 （Popdc3） and its correlation with clinicopathological features and prognosis of gastric cancer.METHODS： The method of immunohistochemistry was used to investigate the expression of Popdc3 in 306 cases of human gastric cancer and 84 noncancerous gastric tissues. Simultaneously, the relationship between Popdc3 expression and the survival of the patients was retrospectively analyzed.RESULTS： Popdc3 was detected in 72 （85.71%） of 84 human nontumor mucosa. High expression of Popdc3protein was detected in 78 （25.49%） of 306 human gastric cancer cases, and low expression was detected in 228 （74.51%）. Low expression of Popdc3 correlated with depth of invasion （P 〈 0.0001）, regional lymph nodes （P 〈 0.0001） and distant metastasis （P =0.02）, and tumor, nodes, metastasis （TNM） stages （P 〈 0.0001）. On multivariate analysis, only the patient＇s gender, regional lymph node metastasis, distant metastasis, TNM stages, and the expression of Popdc3 were independent prognostic factors in patients with gastric cancer. The Kaplan-Meier plot showed that low Popdc3 expression had a much more significant effect on the survival of those patients with early-stage tumors X^2 = 104.741, P 〈 0.0001）, with a 〉 51.9% reduction in the three-year survival compared with high Popdc3 expression. In late stages, the difference was also significant X^2 = 5.930, P = 0.015）, with a 32.6% reduction in the three-year survival.CONCLUSION： Reduced expression of Popdc3 may play a significant role in the carcinogenesis and progression of gastric cancer. Popdc3 may be an independent prognostic factor.

Vehicle Detection Method with Sub-stretching Based on Light Contrast in Fog Road Image

In this paper, detection of a vehicle from a road image with fog is focused to detect an vehicle from a foggy image. Because of the fog in the image, a shape of an object is vague. Therefore an obstacle may occur on the vehicle detection. Thus, features from a foggy road image are surveyed through experinmlts, and a histogram is caloalated with the bright value. The stretching method is then applied with the specific weight as the centre to detect a vehicle smoothly. If the high density area, from the view point of histogram, is applied with the stretching method, the definition of the image can be increased. On this fact, this paper proposed a method to divide the histogram and to determine applicable range of the stretching method. The improved results by the proposed methods are proved with the camparison tests between the proposed and previous methods.

Efficient Algorithm for K-Barrier Coverage Based on Integer Linear Programming

Barrier coverage of wireless sensor networks is an important issue in the detection of intruders who are attempting to cross a region of interest.However,in certain applications,barrier coverage cannot be satisfied after random deployment.In this paper,we study how mobile sensors can be efficiently relocated to achieve k-barrier coverage.In particular,two problems are studied:relocation of sensors with minimum number of mobile sensors and formation of k-barrier coverage with minimum energy cost.These two problems were formulated as 0–1 integer linear programming(ILP).The formulation is computationally intractable because of integrality and complicated constraints.Therefore,we relax the integrality and complicated constraints of the formulation and construct a special model known as RELAX-RSMN with a totally unimodular constraint coefficient matrix to solve the relaxed 0–1 ILP rapidly through linear programming.Theoretical analysis and simulation were performed to verify the effectiveness of our approach.

Fault detection of large-scale process control system with higher-order statistical and interpretative structural model

Nonlinear characteristic fault detection and diagnosis method based on higher-order statistical(HOS) is an effective data-driven method, but the calculation costs much for a large-scale process control system. An HOS-ISM fault diagnosis framework combining interpretative structural model(ISM) and HOS is proposed:(1) the adjacency matrix is determined by partial correlation coefficient;(2) the modified adjacency matrix is defined by directed graph with prior knowledge of process piping and instrument diagram;(3) interpretative structural for large-scale process control system is built by this ISM method; and(4) non-Gaussianity index, nonlinearity index, and total nonlinearity index are calculated dynamically based on interpretative structural to effectively eliminate uncertainty of the nonlinear characteristic diagnostic method with reasonable sampling period and data window. The proposed HOS-ISM fault diagnosis framework is verified by the Tennessee Eastman process and presents improvement for highly non-linear characteristic for selected fault cases.

LMMSE-based SAGE channel estimation and data detection joint algorithm for MIMO-OFDM system

A new channel estimation and data detection joint algorithm is proposed for multi-input multi-output （MIMO） - orthogonal frequency division multiplexing （OFDM） system using linear minimum mean square error （LMMSE）- based space-alternating generalized expectation-maximization （SAGE） algorithm. In the proposed algorithm, every sub-frame of the MIMO-OFDM system is divided into some OFDM sub-blocks and the LMMSE-based SAGE algorithm in each sub-block is used. At the head of each sub-flame, we insert training symbols which are used in the initial estimation at the beginning. Channel estimation of the previous sub-block is applied to the initial estimation in the current sub-block by the maximum-likelihood （ML） detection to update channel estimatjon and data detection by iteration until converge. Then all the sub-blocks can be finished in turn. Simulation results show that the proposed algorithm can improve the bit error rate （BER） performance.

A Method for Node Fault Detection in Wireless Sensor Networks

To reduce excessive computing and communication loads of traditional fault detection methods,a neighbor-data analysis based node fault detection method is proposed.First,historical data is analyzed to confirm the confidence level of sensor nodes.Then a node's reading data is compared with neighbor nodes' which are of good confidence level.Decision can be made whether this node is a failure or not.Simulation shows this method has good effect on fault detection accuracy and transient fault tolerance,and never transfers communication and computing overloading to sensor nodes.

Cooperative detection algorithm of spectrum holes in cognitive radio

To improve the detection performance of sensing users for primary users in the cognitive radio, an optimal cooperative detection algorithm for many sensing users is proposed. In this paper, optimal decision thresholds of each sensing user are discussed. Theoretical analysis and simulation results indicate that the detection probability of optimal decision threshold rules is better than that of determined threshold rules when the false alarm of the fusion center is constant. The proposed optimal cooperative detection algorithm improves the detection performance of primary users as the attendees grow. The 2 dB gain of detection probability can be obtained when a new sensing user joins in, and there is a 17 dB improvement when the accumulation number increases from 1 to 50.

Motion cue based pedestrian detection with two-frame-filtering

This study proposes a motion cue based pedestrian detection method with two-trame-filtering （Tff） for video surveillance. The novel motion cue is exploited by the gray value variation between two frames. Then Tff processing filters the gradient magnitude image by the variation map. Summa- tions of the Tff gradient magnitudes in cells are applied to train a pre-deteetor to exclude most of the background regions. Histogram of Tff oriented gradient （HTffOG） feature is proposed for pedestrian detection. Experimental results show that this method is effective and suitable for real-time surveil- lance applications.