存在障碍物影响的多AUV间距离量测识别与平滑算法

相互间距离量测信息是多AUV协同定位的基础。利用朗伯W函数求解AUV间的RSS距离估计,并通过TOA及RSS 2种距离量测结果的比较,引入一种障碍物引起的非视距(ONLOS)量测识别方法。在此识别基础上,建立了多AUV间距离量测动态变化模型,并利用Kalman滤波方法设计了ONLOS距离量测误差平滑算法。仿真结果表明,该算法可有效提高领航与跟随AUV间的相对距离量测估计精度,减轻ONLOS量测误差对多AUV协同定位性能的影响。

Quantitative prediction of channel sand bodies based on seismic peak attributes in the frequency domain and its application

The boundary identification and quantitative thickness prediction of channel sand bodies are always difficult in seismic exploration.We present a new method for boundary identification and quantitative thickness prediction of channel sand bodies based on seismic peak attributes in the frequency domain.Using seismic forward modeling of a typical thin channel sand body,a new seismic attribute-the ratio of peak frequency to amplitude was constructed.Theoretical study demonstrated that seismic peak frequency is sensitive to the thickness of the channel sand bodies,while the amplitude attribute is sensitive to the strata lithology.The ratio of the two attributes can highlight the boundaries of the channel sand body.Moreover,the thickness of the thin channel sand bodies can be determined using the relationship between seismic peak frequency and thin layer thickness.Practical applications have demonstrated that the seismic peak frequency attribute can depict the horizontal distribution characteristics of channels very well.The ratio of peak frequency to amplitude attribute can improve the identification ability of channel sand body boundaries.Quantitative prediction and boundary identification of channel sand bodies with seismic peak attributes in the frequency domain are feasible.

METHODS OF VISUAL RECOGNITION,POSITIONING AND ORIENTATING OF 3 D SIMPLE GEOMETRIC WORKPIECE

The methods of visual recognition,positioning and orienting with simple 3 D geometric workpieces are presented in this paper.The principle and operating process of multiple orientation run length coding based on general orientation run length coding and visual recognition method are described elaborately.The method of positioning and orientating based on the moment of inertia of the workpiece binary image is stated also.It has been applied in a research on flexible automatic coordinate measuring system formed by integrating computer aided design,computer vision and computer aided inspection planning,with a coordinate measuring machine.The results show that integrating computer vision with measurement system is a feasible and effective approach to improve their flexibility and automation.

Early-stage Internet traffic identification based on packet payload size

In order to classify the Intemet traffic of different Internet applications more quickly, two open Internet traffic traces, Auckland I1 and UNIBS traffic traces, are employed as study objects. Eight earliest packets with non-zero flow payload sizes are selected and their payload sizes are used as the early-stage flow features. Such features can be easily and rapidly extracted at the early flow stage, which makes them outstanding. The behavior patterns of different Intemet applications are analyzed by visualizing the early-stage packet size values. Analysis results show that most Internet applications can reflect their own early packet size behavior patterns. Early packet sizes are assumed to carry enough information for effective traffic identification. Three classical machine learning classifiers, classifier, naive Bayesian trees, i. e., the naive Bayesian and the radial basis function neural networks, are used to validate the effectiveness of the proposed assumption. The experimental results show that the early stage packet sizes can be used as features for traffic identification.

面向海洋渔业捕捞生产的深度学习方法应用研究进展

随着全球渔业资源不断衰退,各国渔业机构和区域渔业管理组织采用渔业观察员方式促进渔业可持续捕捞,但人类观察员方式成本高、覆盖率低,难以满足管理需要。近年来,深度学习新模型不断涌现和完善,其检测速度、精度均在不断增强,为其应用于海洋渔业捕捞生产监控提供了条件。本文从数据获取、数据预处理、算法设计、模型训练和精度评价等方面,总结了渔业捕捞生产监测模型的构建过程,以渔船与渔船行为、渔获物、渔场预报、船员和渔具为对象,综述了深度学习技术在海洋渔业捕捞中的应用,并提出利用迁移学习或强化学习等方法来拓展识别目标种类及增强检测模型、利用高精度的特征提取网络提高目标分类准确率、通过边缘计算技术解决电子监控数据实时解析及制定统一标准以规范电子监控在渔业管理中的应用等未来重点研究方向,以期为深度学习在海洋渔业捕捞生产中的推广应用提供科学参考。

Research on Radar Emitter Attribute Recognition Method

In order to solve emitter recognition problems in a practical reconnaissance environment, attribute mathematics is introduced. The basic concepts and theory of attribute set and attribute measure are described i n detail. A new attribute recognition method based on attribute measure is prese nted in this paper. Application example is given, which demonstrates this new me thod is accurate and effective. Moreover, computer simulation for recognizing th e emitter purpose is selected, and compared with classical statistical pattern r ecognition through simulation. The excellent experimental results demonstrate t hat this is a brand-new attribute recognition method as compared to existing st atistical pattern recognition techniques.

Measuring the Condition of Parking Lot by Image Processing

Aim To study the parking management in the condition of vehicles' increasing. Methods The methods of pattern recognition and image processing were used to analyze the eigenvalues of parking lot images. Results The automatic identification of every parking place in the parking plot was realized. The automatic measuring of parked vehicle count and parking lot utilization was completed. Conclusion It can complete the real time recognition, and has some practicabilities.

Automatic Recognition Method for Optical Measuring Instruments Based on Machine Vision

Based on a comprehensive study of various algorithms, the automatic recognition of traditional ocular optical measuring instruments is realized. Taking a universal tools microscope(UTM) lens view image as an example, a 2-layer automatic recognition model for data reading is established after adopting a series of pre-processing algorithms. This model is an optimal combination of the correlation-based template matching method and a concurrent back propagation(BP) neural network. Multiple complementary feature extraction is used in generating the eigenvectors of the concurrent network. In order to improve fault-tolerance capacity, rotation invariant features based on Zernike moments are extracted from digit characters and a 4-dimensional group of the outline features is also obtained. Moreover, the operating time and reading accuracy can be adjusted dy-namically by setting the threshold value. The experimental result indicates that the newly developed algorithm has optimal recognition precision and working speed. The average reading ratio can achieve 97.23%. The recognition method can automatically obtain the results of optical measuring instruments rapidly and stably without modifying their original structure, which meets the application requirements.

Gazing-detection of human eyes based on SVM

A method for gazing-detection of human eyes using Support Vector Machine （SVM） based on statistic leaming theory （SLT） is proposed. According to the criteria of structural risk minimization of SVM,the errors between sample-data and model-data are minimized and the upper bound of predicting error of the model is also reduced. As a result,the generalization ability of the model is much improved. The simulation results show that, when limited training samples are used, the correct recognition rate of the tested samples can be as high as 100% ,which is much better than some previous results obtained by other methods. The higher processing speed enables the system to distinguish gazing or not-gazing in real-time.

An outlier recognition approach in surveying data based on information entropy

A novel outlier recognition method in surveying data is presented based on Shannon information entropy. The probability distribution of surveying data does not need to be known or hypothesized in this method, and it is not only accurate but also convenient to calculate in this method compared with statistical recognition method.

A new method for PQ disturbance detection and identification

A new method based on phase-shift and N-1 Support Vector Machines(SVMs)is presented for power quality(PQ)disturbance detection and identification.Through phase-shift and simple algebra operation,the method detects out the PQ disturbances easily and effectively.Then a data dealing process is carried out to extract features from the detecting outputs.Then SVM theory is introduced into the identification of PQ disturbances.N kinds of PQ disturbances are classified with an N-1 SVMs classifier.The testing results show that the proposed method can detect and classify the PQ disturbances successfully.Moreover,the classifier has a good performance on training speed and correct ratio.

Robot Calibration Using Active Vision-based Measurement

This paper presents an efficient robot calibration method with non-contact vision metrology. Using the coplanar pattern to calibrate camera made the active-vision-based end-effector pose measurement be a feasible and costeffective way. Kinematic parameter errors were linearized and identified through two-step procedure, thus the singular and non-linear condition was overcome. These errors were then compensated using inverse model method. The whole calibration process is flexible, easy to implement and prevents the error propagation from the earlier stages to the later ones. Calibration was performed on MOTOMAN SV3industrial robot. Experiment results show that the proposed method is easy to setup and with satisfactory accuracy.

Damage Identification in Footbridges from Natural Frequency Measurements

The present study aims to develop a robust structural damage identification method that can be used for the evaluation of bridge structures. An approach for the structural damage identification based on the measurement of natural frequencies is presented. The structural damage model is assumed to be associated with a reduction of a contribution to the element stiffness matrix equivalent to a scalar reduction of the material modulus. A computational procedure for the direct iteration technique based on the non-linear perturbation theory is proposed to identify structural damage. The presented damage identification technique is applied to the footbridge over the Slunjcica River near Slunj to demonstrate the effectiveness of the proposed approach. Using a limited number of measured natural frequencies, reduction in the stiffness of up to 100% at multiple sites is detected. The results indicate that the proposed approach can be successful in not only predicting the location of damage but also in determining the extent of structural damage.

Statistics and Its Applications in Identification of Irregular Particles

Phase Doppler anemometry(PDA) is very sensitive to the shape of testing particles, which is based on sphericity assumption and Mie’s theory. In practice, there exists effectiveness of non sphericity and the response of PDA system deviates from the theoretical prediction. In this paper, the statistic characteristics of PDA signal are analyzed and a method of identifying and quantifying irregular particles is proposed. It is concluded that phase difference of PDA signal for irregular particles is an unbiased estimation for spherical particles.

Recognition of Multifunctional Coded Target in Single-camera Mobile 3D-vision Coordination Measurement

Single-camera mobile-vision coordinate measurement is one of the primary methods of 3D-coordinate vision measurement, and coded target plays an important role in this system. A multifunctional coded target and its recognition algorithm is developed, which can realize automatic match of feature points, calculation of camera initial exterior orientation and space scale factor constraint in measurement system. The uniqueness and scalability of coding are guaranteed by the rational arrangement of code bits. The recognition of coded targets is realized by cross-ratio invariance restriction, space coordinates transform of feature points based on spacial pose estimation algorithm, recognition of code bits and computation of coding values. The experiment results demonstrate the uniqueness of the coding form and the reliability of recognition.

Optimised Pattern Recognition for Robotic Weldment Geometry Measuring

Today, automated robot welding of components with low tolerances in series production is state-of-the-art. But turning to small batch production particularly of parts with high tolerances, engineering and construction of automated solutions is just at the beginning of providing economic efficiency. While weld seam tracking is well established for the described problem, geometric recognition of weldments is not yet solved satisfactorily. This paper will present an optimisation approach of a laser sensor guided and programmed robot welding system which was developed within the project ROPROF at the TU Dortmund. With this development, a working prototype of a robot weld system was built by a steel construction company as well as additional demonstration software showing the potential and transferability of adjusted geometric location of weldments for industrial applications.

Design of Low-power Inspection Instrument Based on RF Technology

A design for low power consumption inspection instrument, in which the ATMega32L is used as the control core, is presented. The reader with wireless identification based on RF technology is researched and the low-cost power is studied particularly. This instrument can be used in industry fields to measure temperature, humidity, gas concentration and other specifications, so it has wide applications and is worth to be extended.

Fuzzy finite element model updating of bridges by considering the uncertainty of the measured modal parameters

It is significant to consider the effect of uncertainty of the measured modal parameters on the updated finite element(FE) model,especially for updating the FE model of practical bridges,since the uncertainty of the measured modal parameters cannot be ignored owing to the application of output-only identification method and the existence of the measured noise.A reasonable method is to define the objective of the FE model updating as the statistical property of the measured modal parameters obtained by conducting couples of identical modal tests,however,it is usually impossible to implement repeated modal test due to the limit of practical situation and economic reason.In this study,a method based on fuzzy finite element(FFM) was proposed in order to consider the effect of the uncertainty of the measured modal parameters on the updated FE model by using the results of a single modal test.The updating parameters of bridges were deemed as fuzzy variables,and then the fuzzification of objective of the FE model updating was proposed to consider the uncertainty of the measured modal parameters.Finally,the effectiveness of the proposed method was verified by updating the FE model of a practical bridge with the measured modal parameters.

Daytime precipitation identification scheme based on multiple cloud parameters retrieved from visible and infrared measurements

Visible and infrared(VIR) measurements and the retrieved cloud parameters are commonly used in precipitation identification algorithms, since the VIR observations from satellites, especially geostationary satellites, have high spatial and temporal resolutions. Combined measurements from visible/infrared scanner(VIRS) and precipitation radar(PR) aboard the Tropical Rainfall Measuring Mission(TRMM) satellite are analyzed, and three cloud parameters, i.e., cloud optical thickness(COT), effective radius(Re), and brightness temperature of VIRS channel 4(BT4), are particularly considered to characterize the cloud status. By associating the information from VIRS-derived cloud parameters with those from precipitation detected by PR, we propose a new method for discriminating precipitation in daytime called Precipitation Identification Scheme from Cloud Parameters information(PISCP). It is essentially a lookup table(LUT) approach that is deduced from the optimal equitable threat score(ETS) statistics within 3-dimensional space of the chosen cloud parameters. South and East China is selected as a typical area representing land surface, and the East China Sea and Yellow Sea is selected as typical oceanic area to assess the performance of the new scheme. It is proved that PISCP performs well in discriminating precipitation over both land and oceanic areas. Especially, over ocean, precipitating clouds(PCs) and non-precipitating clouds(N-PCs) are well distinguished by PISCP, with the probability of detection(POD) near 0.80, the probability of false detection(POFD) about 0.07, and the ETS higher than 0.43. The overall spatial distribution of PCs fraction estimated by PISCP is consistent with that by PR, implying that the precipitation data produced by PISCP have great potentials in relevant applications where radar data are unavailable.

Identification of flexible buildings with bending deformation and the unmeasured earthquake ground motion

It is important to explore efficient algorithms for the identification of both structural parameters and unmeasured earthquake ground motion.Recently,the authors proposed an algorithm for the identification of shear-type buildings and unknown earthquake excitation.In this paper,it is extended to the investigation of the identification of flexible buildings with bending deformation and the unmeasured earthquake ground motion.In the absolute co-ordinate system,the unmeasured ground motion can be treated as an unknown translational force and a bending moment at the 1st floor level of a flexible building.Structural unknown parameters above the 1st story of the building can be identified by the extended Kalman estimator and the 1st story stiffness and the unmeasured ground motion are subsequently estimated based on the least-squares estimation.The proposed algorithm is further extended to the identification of tall bending-type buildings based on substructure approach.Inter-connection effect between sub-buildings is treated as‘additional unknown inputs’to sub-buildings,which are estimated by the extended Kalman estimator without the measurements of rotational responses.Numerical examples demonstrate the identification of a multi-story,tall bending-type building and its unmeasured earthquake ground motions using only partial measurements of structural absolute responses.