Search

In order to realize the rapid detection of three-dimensional defects of connectors, this paper proposes a method for detecting connector defects based on structured light. This method combines structured light with binocular stereo vision to obtain three-dimensional data for the connector. Point cloud registration is used to identify defects and decision trees are used to classify defects. The accuracy of the 3D reconstruction results in this paper is 0.01 mm, the registration accuracy of the point cloud reaches the sub-millimeter level, and the final defect classification accuracy is 94%. The experimental results prove the effectiveness of the proposed three-dimensional connector defect detection method in connector defect detection and classification.

Phase encoding and phase-shift profilometry are two commonly used 3D measurement techniques. However, the acquired phases in the techniques are subject to jump errors due to phase ambiguity and phase errors caused by multiple heterodyne. The phase-shifting profilometry also makes the selection of fringe period difficult. To overcome this problem and achieve high-precision measurement, a phase unwrapping method that combines dual-frequency heterodyne with double complementary phase encoding is proposed. First, two wrapped phases are obtained by two groups of sinusoidal fringes; the heterodyne phase is obtained after heterodyne processing, and the high-frequency phase is expanded by heterodyne phase. Second, the fringe levels are obtained using the complementary phase encoding fringes that are shifted by half an order, and then the absolute phase is obtained by selecting different phase coding levels according to different regions for the first phase unwrapping; Finally, the phase noise is removed by exploiting the difference between the phase slopes of adjacent pixels. Experimental results show that a system with the proposed method achieves an RMS error of 0.015 mm. In addition, the period of dual-frequency heterodyne synthesis does not need to cover the whole field of view, which breaks the limitation of frequency selection of the traditional dual-frequency heterodyne method and triple frequency heterodyne method, enabling high-precision measurement with higher frequency fringes. This method overcomes the limitations of the phase principal value error when using higher frequency fringes for high-precision measurement, improves the measurement effect of reflective objects, and effectively avoids the error caused by phase jump.

This work deals with quantitative analysis of multicomponent mud logging gas based on infrared spectra. An accurate analysis method is proposed by combining a genetic algorithm (GA) and a radial basis function neural network (RBFNN). The GA is used to screen the infrared spectrum of the mixed gas, while the selected spectral region is used as the input of the RBFNN to establish a calibration model to quantitatively analyze the components of logging gas. The analysis results demonstrate that the proposed GA-RBFNN performs better than FS-RBFNN and ES-RBFNN, and our proposed method is feasible.

Metal component surfaces are random textured and non-smooth. There are many stains on the surface of metal component that are similar to the gray scale of the scratches. The scratches have non-uniform gray distribution, various shapes, and low contrast in their background, posing challenges in accurate scratch detection. This paper presents a method for detecting weak scratches on metal component surfaces based on deep convolutional neural networks (DCNNs). First, a DCNN is trained using labeled scratch images. Then, the scratches and some faults are detected by the trained DCNN, and most of the faults can be removed through properly thresholding based on the size of connected regions. Finally, the scratch length united in the number of pixels is obtained by the skeleton extraction. The experimental results show that the proposed method can effectively deal with background noise, thereby achieving accurate scratch detection.

To quickly obtain accurate 3D data of dental cast model, this paper proposes a 3D reconstruction method for dental cast model based on structured light. This method combines the structured light with the motor turntable to obtain a group of 3D data for the dental cast model from multiple angles, and automatically registers the dental 3D data from multiple angles through the ball calibration of turntable. Compared with the real data of the dental cast model, the maximum error of the 3D reconstruction results in this paper is 0.115 mm. The reconstruction time of this process is about 130 s. The experimental results show that the method has high precision and high scanning speed for the 3D reconstruction of the dental cast model.

Rapid, accurate, and sensitive determination of hydrogen sulfide was provided by tunable distributed feedback diode laser absorption spectroscopy. The laser wavelength scanning range covere...

An optical hydrogen sulfide (H2S) sensor based on wavelength modulation spectroscopy with the second harmonic (2f) corrected by the first harmonic (1f) signal (WMS-2f/1f) is developed using a distributed feedback (DFB) laser emitting at 1.578 μm and a homemade gas cell with 1-m-long optical path length. The novel sensor is constructed by an electrical cabinet and an optical reflecting and receiving end. The DFB laser is employed for targeting a strong H2S line at 6 336.62 cm-1 in the fundamental absorption band of H2S. The sensor performance, including the minimum detection limit and the stability, can be improved by reducing the laser intensity drift and common mode noise by means of the WMS-2f/1f technique. The experimental results indicate that the linearity and response time of the sensor are 0.999 26 and 6 s (in concentration range of 15.2—45.6 mg/m3), respectively. The maximum relative deviation for continuous detection (60 min) of 30.4 mg/m3 H2S is 0.48% and the minimum detection limit obtained by Allan variance is 79 μg/m3 with optimal integration time of 32 s. The optical H2S sensor can be applied to environmental monitoring and industrial production, and it has significance for real-time online detection in many fields.

A new solution to the high-quality 3D reverse modeling problem of complex surfaces for fine workpieces is presented using a laser line-scanning sensor. Due to registration errors, measurement errors, deformations, etc., a fast and accurate method is important in machine vision measurement. This paper builds a convenient and economic multi-view stereo (MVS) measurement system based on a linear stage and a rotary stage to reconstruct the measured object surface completely and accurately. In the proposed technique, the linear stage is used to generate the trigger signal and synchronize the laser sensor scanning, the rotary stage is used to rotate the object and obtain multi-view point cloud data, and then the multi-view point cloud data are registered and integrated into a 3D model. The measurement results show a measurement accuracy of 0.075 mm for a 360&deg, reconstruction in 34 s, and some evaluation experiments were carried out to demonstrate the validity and practicability of the proposed technique.

This paper proposes a deep convolutional neural network (CNN) -based technique for the detection of micro defects on metal screw surfaces. The defects we consider include surface damage, surface dirt, and stripped screws. Images of metal screws with different types of defects are collected using industrial cameras, which are then employed to train the designed deep CNN. To enable efficient detection, we first locate screw surfaces in the pictures captured by the cameras, so that the images of screw surfaces can be extracted, which are then input to the CNN-based defect detector. Experiment results show that the proposed technique can achieve a detection accuracy of 98%, the average detection time per picture is 1.2 s. Comparisons with traditional machine vision techniques, e.g., template matching-based techniques, demonstrate the superiority of the proposed deep CNN-based one.

The non-contact three-dimensional measurement and reconstruction techniques have played a significant role in the packaging and transportation of precious cultural relics. This paper develops a structured light based three-dimensional measurement system, with a low-cost for cultural relics packaging. The structured light based system performs rapid measurements and generates 3D point cloud data, which is then denoised, registered and merged to achieve accurate 3D reconstruction for cultural relics. The multi-frequency heterodyne method and the method in this paper are compared. It is shown that the relative accuracy of the proposed low-cost system can reach a level of 1/1000. The high efficiency of the system is demonstrated through experimental results.

Infrared spectrum analysis technology can perform fast and nondestructive detection of gas and has been widely used in many fields. This work studies the quantitative analysis technology of the infrared spectrum based on deep learning. The experimental results show that the quantitative analysis model of logging gas established here can reach 100% recognition accuracy for elemental gas; further, the accuracy rate of spectral of mixed gas recognition reached 98%, indicating that the infrared spectrum logging gas detection model based on deep learning can quickly and accurately perform quantitative analysis of logging gas.

In order to classify the gears and achieve high precision measurement results, a non-contact gear measurement system based on the laser vision is developed in this paper. The laser vision precision measurement method (LVPMM) is proposed to ensure the accuracy. Experimental results indicate that the gear measuring uncertainty is 2.1 μm. The precision can satisfy the gear measurement requirements for two-grade or under two-grade standard gears in industry, and can classify the gears very well.

To deal with the three-dimensional (3-D) point cloud loss caused by object reflection in the active fringe projection 3-D measurement, an active reflection suppression method for 3-D measurement is proposed. The method employs high-dynamic range images obtained by multiple exposure image fusion and a three-wavelength phase-shift profilometry method to achieve high-precision 3-D measurement of reflective objects. Experimental results show that, compared to traditional 3-D measurement methods, the proposed one can more effectively handle reflections thereby avoiding 3-D point cloud loss in the measurement of reflective objects.

Large amount of carbon has emitted from the transport, and which growing faster. This paper summarized the theoretical system, technology, product, methods and demonstration projects of low carbon transport. The deficiencies of current research were pointed out, such as researches on low carbon transport network and low carbon transportation system are less involved; low-carbon technology of transport is also imperfect, and some low carbon indicators still remain in the defined stages. At last, the evaluation methods of low-carbon indicators, building methods of low-carbon indicator system and evaluation methods were prospected. The paper also put forward that researches about the concept of low-carbon road, screening and construction method of low-carbon index system, application feedback and model validation should be deepened in future.

A full-view three-dimensional (3-D) measurement method for complex surfaces is proposed, where 3-D data for standard balls with different angles are used to calibrate the rotation axes of a turntable and obtain transformation matrices of 3-D data of adjacent views. It can achieve accurate registration of 3-D data of views with different angles and obtains full-view 3-D data for complex surfaces in conjunction with the method for principal point calibration of cameras and modified triple-frequency six-step phase-shifting phase demodulation methods. Experiments show that the developed system based on the proposed method can achieve automatic registration of 3-D data of views with different angles, and good full-view 3-D measurement precision for complex surfaces.

Water injection was a widely used method for oil exploration in China. The defects of water injection process，inject water quality exceed standard, Unreasonable of injection-production ratio and ,invalid of well control measures, during the water flooding process，may lead to These factors may lead to the occurrence of geological oil spill accident. This paper introduced and discussed these key factors which may lead to oil spill accident, in oil field development processes, for risk prevention and environmental protection in water flooding process.

To examine the role of the forest in non-point source pollution control in the Taihu lake region, the soil profile nutrients including nitrate, hydrolyze nitrogen(HN), available phosphorus(AP), total nitrogen(TN), total phosphorus(TP) concentration of 26 forest sample plots along the Xitiaoxi River from upstream to downstream were measured through July to August 2009, the relationship between vegetation type and topographic factors and soil nutrients was analyzed. results show that: (1) All of five soil nutrients concentration decreased with increasing soil depth; (2) Soil nutrients of different soil depth is intermediate variability, the coefficient of variation of AP, TN, HN, TP were increased with the increasing of soil depth, and the coefficient of variation of nitrate was decreased with the increasing of soil depth. (3)Soil HN content under plots with an average tree height above 10m was significantly higher than plots with an average tree height less than 10m; (4) Soil AP, HN, TN, TP content was first decreased and then increased with the increasing of elevation. .In summary, the soil nutrients of different soil depth was found to be closely related to vegetation type, community age, structure, fertilization and topographic features in the upstream of Taihu lake basin.

Based on the analysis of the field and characteristics of environmental protection in highway and water transportation, the fields of the standardization of environmental protection in highway and water transportation were defined into the environmental protection supervision, environmental protection in traffic planning, infrastructure facility construction and maintenance, passenger and freight transport, and the standard system was positioned as the level of specific trade standards system, including basic and specific standards. By analyzing the intersection among existing standard systems in China and characteristic of highway and water transportation, part of standards of standard system for national environmental protection, engineering construction of highway and water transportation, inland river shipping were used relative standards of standard system for environmental protection in highway and water transportation, and standards for pollution control of shipping were included standards system for environmental protection in highway and water transportation.

The water conservation capacities of main forests in Beijing, China were estimated through the quantitative analysis. Various methods developed in published papers on forest hydrology were employed. The forests in Huairou, Yanqing, Miyun, Mentougou and Fangshan districts are the main contributors to water conservation (the cumulative ratio reaches 65%), and the forests in Tongzhou, Chaoyang, Shunyi and Daxing districts have the highest water conservation capacity (3000 m3/ha). Altitude and slope are the key factors to affect the water conservation capacity. The forests located in Plain Area, Hilly Area, Low Mountain, and Middle Mountain contributes 27%, 28%, 24% and 21% of the conserved water, respectively. The water conservation capacity of forests in Plain Area (2 948 m3/ha), is superior to the forests in other regions. And the forests situated on Flat Slope, Moderate Slope and Gentle Slope constitute the largest proportion (nearly 93%) of water conservation, while the forests on Flat Slope has the highest water conservation capacity (2 797 m3/ha), and the forest on Steep slope has the lowest water conservation capacity (948 m3/ha).

CdS nano-particulate films were prepared at the air/water interface under Langmuir monolayers of arachidic acid (AA) via interfacial reaction between Cd 2+ ions in the subphase and H 2 S molecules in the gaseous phase. The films were made up of fine CdS nanoparticles with hexagonal Wurtzite crystal structure after reaction. It was revealed that the formation of CdS nano-particulate films depends largely on the experimental conditions. When the films were ripened at room temperature or an increased temperature (60 °C) for one day, numerous holes were appeared due to the dissolution of smaller nanoparticles and the growth of bigger nanoparticles with an improved crystallinity. When the films were ripened further, CdS rodlike nanoparticles with cubic zinc blende crystal structure appeared due to the re-nucleation and growth of CdS nanoparticles at the stacking faults and defect structures of the hexagonal CdS grains. These structures were characterized by transmission electron microscopy (TEM), high-resolution TEM (HRTEM), and X-ray diffraction (XRD). These results declare that CdS semiconductor nanoparticles formed at the air/water interface change their morphologies and crystal structures during the ripening process due to dissolution and recrystallization of the particles.

Ordered two-dimensional (2D) arrays of β-HgS nanocrystal aggregates were prepared successfully at the air/water interface through the interfacial reaction between Hg(2+) ions in the subphase and H(2)S in the gaseous phase under the direction of liquid-expanded monolayers of arachidic acid (AA). These 2D arrays are composed of hexagonal or quasi-hexagonal aggregates with the size of several hundreds of nanometers that consist of several tens of HgS nanocrystals with the size of several nanometers. The formed HgS nanocrystals together with AA molecules self-assembled into round aggregates due to the interactions between the species, and the aggregates self-assembled into 2D arrays further due to the attractions between them. During the self-assembly process, the soft round aggregates transformed into hexagonal or quasi-hexagonal ones. The experimental conditions, especially the phase states of the AA monolayers and temperature, have great influences on the formation of the 2D arrays. To the best of our knowledge, this is the first case to get 2D ordered arrays at the air/water interface through a one-step synthesis and assembly process.

Triangular single-crystalline nanorings of PbS were prepared at the air/water interface and characterized by transmission electron microscopy (TEM), high-resolution TEM (HRTEM), scanning electron microscopy (SEM), atomic force microscopy (AFM), and UV−vis spectroscopy. The nanorings were transformed from triangular PbS nanopyramids that were formed under Langmuir monolayers of arachidic acid (AA) through interfacial reactions between Pb2+ ions in the subphases and H2S in the gaseous phase. The basal plane of the pyramids is a (111) face of PbS crystals with rock salt crystal structure, which is parallel to the air/water interface. The tips of the pyramids beneath the interface dissolved gradually due to selective etching of Pb2+ in the nanocrystals by Cl− ions in the subphase because of their higher surface energy, resulting in the formation of the rings. The size of the rings could be tuned by changing the experimental conditions, and the optical properties changed when the rings formed.

On the background of increasing request for stringent quality improvement and rising productivity, requirements for online measurement systems are growing as well. Among all the measurement tools, the vision system is considered as the most appropriate tool to provide proper accuracy, high speed, low cost, and 100% online inspection. Structure lighting sensor is the most popular method used in vision system. In this paper, the theory of vision system based on structure lighting is introduced. The measurement application to the seamless steel tube is introduced particularly. Another typical application, the online measurement on car body using structure lighting, is also illustrated.

The Stem Radial Growth (SRG) was measured by dendrometer from 6 sample trees of Picea meyeri at the tree-line of Luya Mountain, North China, combined with synchronized instrumental observation and measurement of habitat temperature, moisture, etc., from July the 15 th to August the 7 th (summer phase) and from September the 5 th to October the 9 th (autumn phase) in 2007. The preliminary analytic results were as follows: 1) the diameter of stems varied on sunny days with a daily fluctuation but steadily widened, while on rainy days it continuously increased during the rain but shrank rapidly after the rain. 2) The SRG pattern in both phases was fitted with a quadratic curve, showing a positive value in summer phase; whereas declining to a negative figure in the first stage of autumn phase --early September, and then kept as a constant zero from middle September on. 3) The distance analysis showed a relative warmer and moister environment was suitable for the growth of Picea meyeri in autumn phase, whereas an environment with a high relative humidity (RH) in the air and moisture in the soil was suitable in summer phase. Thus the water regime was the controlling factor for Picea meyeri growth on treeline of Luya Mountain.