可调谐半导体激光吸收光谱（TDLAS）技术具有很高的选择性和灵敏度,能够实现污染区域环境中痕量氨气（NH_3）的在线检测。影响TDLAS系统测量精度的因素有很多,温度和压力是最基本的两个影响条件。首先介绍了TDLAS原理和实验系统,然后研...可调谐半导体激光吸收光谱（TDLAS）技术具有很高的选择性和灵敏度,能够实现污染区域环境中痕量氨气（NH_3）的在线检测。影响TDLAS系统测量精度的因素有很多,温度和压力是最基本的两个影响条件。首先介绍了TDLAS原理和实验系统,然后研究了温度变化对检测结果的影响,温度在-10℃~50℃之间,使用空芯波导（Hollow Waveguide,HWG）气体池对浓度为50 ppm的NH3进行检测,得到其二次谐波光谱图,从图中可以得出在该温度范围内,NH_3二次谐波信号幅度随温度升高而减小。温度不变,气体池内压力从0 k Pa变化到100 k Pa时,二次谐波信号的幅度随着压力增加而减小。根据实验结果,给出了该系统的温度压力修正公式。修正后,50 ppm的NH_3在不同温度下的最大检测相对误差为-5.5%。对30 ppm的NH_3长时间监测结果表明,修正后系统能够适应现场监测需求。展开更多
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 turntab...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 130s. The experimental results show that the method has high precision and high scanning speed for the 3D reconstruction of the dental cast model.展开更多
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 n...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.展开更多
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 bi...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.展开更多
文摘可调谐半导体激光吸收光谱（TDLAS）技术具有很高的选择性和灵敏度,能够实现污染区域环境中痕量氨气（NH_3）的在线检测。影响TDLAS系统测量精度的因素有很多,温度和压力是最基本的两个影响条件。首先介绍了TDLAS原理和实验系统,然后研究了温度变化对检测结果的影响,温度在-10℃~50℃之间,使用空芯波导（Hollow Waveguide,HWG）气体池对浓度为50 ppm的NH3进行检测,得到其二次谐波光谱图,从图中可以得出在该温度范围内,NH_3二次谐波信号幅度随温度升高而减小。温度不变,气体池内压力从0 k Pa变化到100 k Pa时,二次谐波信号的幅度随着压力增加而减小。根据实验结果,给出了该系统的温度压力修正公式。修正后,50 ppm的NH_3在不同温度下的最大检测相对误差为-5.5%。对30 ppm的NH_3长时间监测结果表明,修正后系统能够适应现场监测需求。
基金supported by the National Natural Science Foundation of China(Nos.61078041 and 51806150)the Natural Science Foundation of Tianjin(Nos.16JCYBJC15400,15JCYBJC51700 and 18JCQNJC04400)+2 种基金the State Key Laboratory of Precision Measuring Technology and Instruments(Tianjin University)(PIL1603)the Program for Innovative Research Team in University of Tianjin(No.TD13-5036)Tianjin Enterprise Science and Technology Commissioner Project(No.18JCTPJC61700)
文摘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 130s. The experimental results show that the method has high precision and high scanning speed for the 3D reconstruction of the dental cast model.
基金supported by the Natural Science Foundation of Tianjin(Nos.16JCQNJC02100,15JCYBJC51700 and 16JCYBJC15400)the National Key Scientific Instrument and Equipment Development Project of China(No.2012YQ0901670602)+1 种基金the State Key Laboratory of Precision Measuring Technology and Instruments(Tianjin University,No.PIL1603)the Program for Innovative Research Team in University of Tianjin(No.TD13-5036)
文摘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.
基金This work has been supported by the National Natural Science Foundation of China(Nos.61078041 and 51806150)the Natural Science Foundation of Tianjin(Nos.16JCYBJC15400,15JCYBJC51700 and 18JCQNJC04400)+2 种基金the State Key Laboratory of Precision Measuring Technology and Instruments(Tianjin University)the Program for Innovative Research Team in University of Tianjin(No.TD13-5036)the Tianjin Enterprise Science and Technology Commissioner Project(No.18JCTPJC61700)。
文摘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.
