scholarly journals Quality inspection method of layered compacted subgrade and engineering example analysis

2021 ◽  
Vol 248 ◽  
pp. 03068
Author(s):  
Binbin Xu
Keyword(s):  
Detection Method ◽  
Sampling Point ◽  
Quality Inspection ◽  
Road Engineering ◽  
Inspection Method ◽  
Quality Detection ◽  
Detection Technology ◽  
Filling Method ◽  
Point Detection ◽  
Compaction Method

The effective detection of layered roller compacted subgrade quality is the key of road engineering quality control. The traditional sand filling compaction method belongs to random sampling point detection method, and it is not easy to detect the subgrade compaction condition below the sand filling pit. Based on the summary of the current domestic and foreign subgrade detection technology, this paper innovatively combines the geological radar method with sand filling method, and through the fixed point detection method. The results show that the traditional sand filling method can directly and quantitatively reflect the compactness of sampling points, while the geological radar can realize the continuous detection, and can judge the compaction layer from the loose state to the interlaminar line after compaction through the geological radar image At the same time, the GPR can identify the under compacted area in the subgrade compaction layer and reflect the overall compaction effect of the subgrade. The detection method of combining the GPR method and sand filling method has obvious technical advantages in the subgrade quality detection.

scholarly journals Quality Inspection of Digital Archives of Application and Installation in Power Business Expanding based on Artificial Intelligence Technology

2021 ◽  
Vol 2079 (1) ◽  
pp. 012030
Author(s):  
Haihong Liang ◽  
Ling Zeng ◽  
Xiaozhou Shen ◽  
Weiwei Shi ◽  
Jiujiao Cang
Keyword(s):  
Artificial Intelligence ◽  
Classification Accuracy ◽  
Detection Method ◽  
Detection Methods ◽  
Digital Archive ◽  
Quality Inspection ◽  
Digital Archives ◽  
Evaluation Standard ◽  
Quality Detection ◽  
Artificial Intelligence Technology

Abstract The existing quality detection methods of business expansion digital archives have the problem of fuzzy evaluation standard, which leads to low classification accuracy. This paper designs a quality detection method of business expansion Digital Archives based on artificial intelligence technology. The business characteristics of business development are extracted, the minimum business data unit is described, the digital archive catalogue database is established, the digital archive evaluation standard is defined, the text similarity is calculated, the user model is established, and the quality inspection mode is established by using artificial intelligence technology. Experimental results: the average classification accuracy of the designed method based on artificial intelligence technology and the other two quality detection methods is 55.763, 43.560 and 42.605, which proves that the quality detection method based on artificial intelligence technology has higher use value.

Shape Analysis of the Raw Silk Defects

2011 ◽  
Vol 175-176 ◽  
pp. 429-433
Author(s):  
Kun Nan Xiao ◽  
Jia Li ◽  
Qing Guan Chen ◽  
Kai Meng
Keyword(s):  
Shape Analysis ◽  
High Speed ◽  
Detection Method ◽  
Quality Inspection ◽  
Inspection Method ◽  
Evaluation Standards ◽  
Popular Method ◽  
Testing Method ◽  
Actual Shape

The detection of raw silk defects is important in the quality inspection of raw silk. Electronic inspection is a popular method now for the reasons of high speed and objectivity. However, the traditional seriplane testing method is also applied in many countries for its advantages that the electronic inspection method haven’t. Due to the different evaluation standards, different results will be derived when the same raw silk defect is detected by the two different methods. In this study, various raw silk defects were detected according to the two different methods or standards. The cause of different results derived by different detection method was analyzed through observing the actual shape of the raw silk defects under the microscope. This is favorable to the development of electronic inspection method and standards for the raw silk defects.

Research Situation Analysis of On-line Detection Technology for Power Transformer Winding Deformation

2020 ◽  
Vol 13 (6) ◽  
pp. 823-832
Author(s):  
Zhenhua Li ◽  
Weihui Jiang ◽  
Li Qiu ◽  
Zhenxing Li ◽  
Yanchun Xu
Keyword(s):  
Detection Method ◽  
Theoretical Research ◽  
Line Detection ◽  
Response Analysis ◽  
Advantages And Disadvantages ◽  
Detection Technology ◽  
The Future ◽  
Transformer Winding ◽  
On Line ◽  
Winding Deformation

Background: Winding deformation is one of the most common faults in power transformers, which seriously threatens the safe operation of transformers. In order to discover the hidden trouble of transformer in time, it is of great significance to actively carry out the research of transformer winding deformation detection technology. Methods: In this paper, several methods of winding deformation detection with on-line detection prospects are summarized. The principles and characteristics of each method are analyzed, and the advantages and disadvantages of each method as well as the future research directions are expounded. Finally, aiming at the existing problems, the development direction of detection method for winding deformation in the future is prospected. Results: The on-line frequency response analysis method is still immature, and the vibration detection method is still in the theoretical research stage. Conclusion: The ΔV − I1 locus method provides a new direction for on-line detection of transformer winding deformation faults, which has certain application prospects and practical engineering value.

scholarly journals A Two-Phase Fashion Apparel Detection Method Based on YOLOv4

2021 ◽  
Vol 11 (9) ◽  
pp. 3782
Author(s):  
Chu-Hui Lee ◽  
Chen-Wei Lin
Keyword(s):  
Object Detection ◽  
Transfer Learning ◽  
Detection Method ◽  
Phase Transfer ◽  
Recognition Task ◽  
Phase Detection ◽  
Target Domain ◽  
Two Phase ◽  
Detection Technology ◽  
Fashion Apparel

Object detection is one of the important technologies in the field of computer vision. In the area of fashion apparel, object detection technology has various applications, such as apparel recognition, apparel detection, fashion recommendation, and online search. The recognition task is difficult for a computer because fashion apparel images have different characteristics of clothing appearance and material. Currently, fast and accurate object detection is the most important goal in this field. In this study, we proposed a two-phase fashion apparel detection method named YOLOv4-TPD (YOLOv4 Two-Phase Detection), based on the YOLOv4 algorithm, to address this challenge. The target categories for model detection were divided into the jacket, top, pants, skirt, and bag. According to the definition of inductive transfer learning, the purpose was to transfer the knowledge from the source domain to the target domain that could improve the effect of tasks in the target domain. Therefore, we used the two-phase training method to implement the transfer learning. Finally, the experimental results showed that the mAP of our model was better than the original YOLOv4 model through the two-phase transfer learning. The proposed model has multiple potential applications, such as an automatic labeling system, style retrieval, and similarity detection.

Design of Swimming Pool Temperature Dot Matrix Screen Display

2014 ◽  
Vol 556-562 ◽  
pp. 2208-2211
Author(s):  
Xue Feng Yang
Keyword(s):  
Water Temperature ◽  
Real Time ◽  
Room Temperature ◽  
Detection Method ◽  
Swimming Pool ◽  
Real Time Monitoring ◽  
Real Time Processing ◽  
The Core ◽  
Swimming Pool Water ◽  
Point Detection

According to the need of the real-time monitoring and displaying of the environment in many areas,to put forward a method of temperature monitoring and displaying, using STC11F32XE microcontroller as the core controller, DS18B20 as temperature acquisition chip, 32X64LED dot matrix screen as a display screen,using the mothod of multi point detection method,real-time monitoring of swimming pool water temperature and room temperature, real-time displaying of Multipoint collecting information, Real time processing the detected temperature, the page display to multipoint temperature display through the wireless remote control module,the system will alarm When the water temperature is too high or too low, to remind managers of real-time processing.To design a clear temperature display for the swimming pool,real time monitoring and controlling is very convenient,after the experimental verification, the system reaches the anticipative goal,the system is an ideal and effective.

Ultrasonic Attenuation Based Inspection Method for Scale-up Production of A206–Al2O3 Metal Matrix Nanocomposites

2015 ◽  
Vol 137 (1) ◽  
Author(s):  
Jianguo Wu ◽  
Shiyu Zhou ◽  
Xiaochun Li
Keyword(s):  
Metal Matrix ◽  
High Performance ◽  
Ultrasonic Attenuation ◽  
Hypothesis Test ◽  
Scale Up ◽  
Al2o3 Nanoparticles ◽  
Quality Inspection ◽  
Ultrasonic Dispersion ◽  
Inspection Method ◽  
Metal Matrix Nanocomposites

A206–Al2O3 metal matrix nanocomposite (MMNC) is a promising high performance material with potential applications in various industries, such as automotive, aerospace, and defense. Al2O3 nanoparticles dispersed into molten Al using ultrasonic cavitation technique can enhance the nucleation of primary Al phase to reduce its grain size and modify the secondary intermetallic phases. To enable a scale-up production, an effective yet easy-to-implement quality inspection technique is needed to effectively evaluate the resultant microstructure of the MMNCs. At present the standard inspection technique is based on the microscopic images, which are costly and time-consuming to obtain. This paper investigates the relationship between the ultrasonic attenuation and the microstructures of pure A206 and Al2O3 reinforced MMNCs with/without ultrasonic dispersion. A hypothesis test based on an estimated attenuation variance was developed and it could accurately differentiate poor samples from good ones. This study provides useful guidelines to establish a new quality inspection technique for A206–Al2O3 nanocomposites using ultrasonic nondestructive testing method.

Sign in / Sign up

Export Citation Format

Share Document