Design and Research on the Cigarette Paper Smoldering Rate of PRS-2 Tester

2013 ◽  
Vol 694-697 ◽  
pp. 1382-1386
Author(s):  
Wei Dong Huang ◽  
Yong Min Yu
Keyword(s):  
Image Processing ◽  
Image Resolution ◽  
Vision Sensor ◽  
Control Data ◽  
Timing Accuracy ◽  
Vision Sensors ◽  
Computer Image Processing ◽  
Scanning Frequency ◽  
Cigarette Paper ◽  
Advanced Computer

The measuring body of PRS-2 cigarette paper smoldering rate tester is industrial vision sensors P4E1.3, it could determine and identify the burning of the cigarette paper by using the advanced computer image processing techniques.The vision sensor can detection to 10,000 times per minute when the image resolution is 1.3 million pixels-accurate, it simultaneously monitors the 5 cigarette paper, and can ensure that the scanning frequency of each cigarette paper is not lower than 100 Hz. In the case of deducting the necessary analysis and calculation time, it can guarantee that the timing accuracy is no less than 0.1s. The instrument is able of detecting the serrated depth of the burned cigarette paper line and excludes the misjudgment which caused by human factors,so it could achieve control, data analysis, save and print independently.

scholarly journals Rotation Estimation: A Closed-Form Solution Using Spherical Moments

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 4958
Author(s):  
Hicham Hadj-Abdelkader ◽  
Omar Tahri ◽  
Houssem-Eddine Benseddik
Keyword(s):  
Image Processing ◽  
Closed Form ◽  
Synthetic Data ◽  
Closed Form Solution ◽  
Form Solution ◽  
Unified Model ◽  
Experimental Results ◽  
Motion Information ◽  
Vision Sensors ◽  
Spherical Projection

Photometric moments are global descriptors of an image that can be used to recover motion information. This paper uses spherical photometric moments for a closed form estimation of 3D rotations from images. Since the used descriptors are global and not of the geometrical kind, they allow to avoid image processing as features extraction, matching, and tracking. The proposed scheme based on spherical projection can be used for the different vision sensors obeying the central unified model: conventional, fisheye, and catadioptric. Experimental results using both synthetic data and real images in different scenarios are provided to show the efficiency of the proposed method.

scholarly journals Particle Morphology Analysis of Biomass Material Based on Improved Image Processing Method

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Zhaolin Lu ◽  
Xiaojuan Hu ◽  
Yao Lu
Keyword(s):  
Image Processing ◽  
Particle Size ◽  
Particle Morphology ◽  
Processing Method ◽  
Image Resolution ◽  
Ultrasonic Dispersion ◽  
Image Processing Method ◽  
Size And Shape ◽  
Nominal Size ◽  
Particle Size And Shape

Particle morphology, including size and shape, is an important factor that significantly influences the physical and chemical properties of biomass material. Based on image processing technology, a method was developed to process sample images, measure particle dimensions, and analyse the particle size and shape distributions of knife-milled wheat straw, which had been preclassified into five nominal size groups using mechanical sieving approach. Considering the great variation of particle size from micrometer to millimeter, the powders greater than 250 μm were photographed by a flatbed scanner without zoom function, and the others were photographed using a scanning electron microscopy (SEM) with high-image resolution. Actual imaging tests confirmed the excellent effect of backscattered electron (BSE) imaging mode of SEM. Particle aggregation is an important factor that affects the recognition accuracy of the image processing method. In sample preparation, the singulated arrangement and ultrasonic dispersion methods were used to separate powders into particles that were larger and smaller than the nominal size of 250 μm. In addition, an image segmentation algorithm based on particle geometrical information was proposed to recognise the finer clustered powders. Experimental results demonstrated that the improved image processing method was suitable to analyse the particle size and shape distributions of ground biomass materials and solve the size inconsistencies in sieving analysis.

Super-Resolution Analysis on Molten Pool Image of Metal Active-Gas Welding Based on Wavelet with Fractal

2011 ◽  
Vol 103 ◽  
pp. 152-157
Author(s):  
Guang Zhi Dai ◽  
Guo Qiang Han ◽  
Chao Yi Dong
Keyword(s):  
Image Processing ◽  
Super Resolution ◽  
Image Interpolation ◽  
Image Resolution ◽  
Mag Welding ◽  
Resolution Image ◽  
Fractal Image ◽  
Welding Image ◽  
Resolution Analysis ◽  
Wavelet Image

According to the unique advantages in image processing combining wavelet and fractal and the different ways of combination, a super-resolution image processing methods are proposed. The methods are characterized by combining the wavelet transform, Wavelet Image Interpolation and FBM Fractal Image interpolation in a certain way to achieve super-resolution image reconstruction. Through processing MAG welding pool images polluted by noises seriously, the results show that: the method proposed in this paper, compared with the method based on wavelet bilinear interpolation, not only effectively raises MAG welding image resolution, but also PSNR of reconstruction images are enhanced 21.1049 dB.

scholarly journals Computer image processing and neural network technology for boiler thermal energy diagnosis

2020 ◽  
Vol 24 (5 Part B) ◽  
pp. 3059-3068
Author(s):  
Qinghong Wu
Keyword(s):  
Neural Network ◽  
Image Processing ◽  
Thermal Energy ◽  
Processing System ◽  
Heat Energy ◽  
Image Feature ◽  
The Neural Network ◽  
Computer Image Processing ◽  
On Line ◽  
Parameter Values

The paper uses the flame image processing technology to diagnose the furnace flame combustion achieve the measurement of boiler heat energy. The paper obtains the combustion image of the flame image processing system, and extracts the flame image characteristics of the boiler thermal energy diagnosis, constructs the neural network model of the boiler thermal energy diagnosis, and trains and tests the extracted flame image feature parameter values as the input of the neural network. A rough diagnosis of the boiler?s thermal energy is obtained while predicting the state of combustion. According to the research results, a boiler thermal energy diagnosis system was designed and tested on the boiler of 200 MW unit. The experimental results confirmed the applicability of the system, which can realize on-line monitoring of boiler heat energy and evaluate the combustion situation.

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