Comprehensive Management Strategy for Tunnel Construction Quality Inspection and Monitoring

With the increase in the number and scale of tunnel projects in China in recent years,the comprehensive management for quality inspection and monitoring measurement in the tunnel construction process is receiving more and more attention.Based on this,this paper analyzes the comprehensive management of quality inspection and monitoring during tunnel construction to ensure the quality of tunnel construction.

Application of Non-Destructive Testing Technology in Quality Testing and Control of Water Conservancy Projects

In view of social development,the demand for water conservancy engineering applications continues to increase.The number and scale of water conservancy projects in China have been in a state of continuous expansion in recent years.As a result,how to achieve efficient testing and effective control of the quality of water conservancy projects has always been a topic of discussion in the field of water conservancy engineering in our country.This paper summarizes the application of non-destructive testing technology in the quality testing and control of water conservancy projects.On the basis of explaining the connotation and application advantages of non-destructive testing technology,the non-destructive testing application strategies for concrete strength,steel corrosion and shallow cracks in water conservancy projects were studied.

Integrated Inspection of QoM, QoP, and QoS for AOI Industries in Metaverses

With the rapid development of information technologies such as digital twin, extended reality, and blockchain,the hype around "metaverse" is increasing at astronomical speed. However, much attention has been paid to its entertainment and social functions. Considering the openness and interoperability of metaverses, the market of quality inspection promises explosive growth. In this paper, taking advantage of metaverses, we first propose the concept of Automated Quality Inspection(Auto QI), which performs integrated inspection covering the entire manufacturing process, including Quality of Materials, Quality of Manufacturing(Qo M), Quality of Products, Quality of Processes(Qo P), Quality of Systems, and Quality of Services(Qo S). Based on the scenarios engineering theory, we discuss how to perform interactions between metaverses and the physical world for virtual design instruction and physical validation feedback. Then we introduce a bottomup inspection device development workflow with productivity tools offered by metaverses, making development more effective and efficient than ever. As the core of quality inspection,we propose Quality Transformers to complete detection task,while federated learning is integrated to regulate data sharing.In summary, we point out the development directions of quality inspection under metaverse tide.

Statistical Analysis and Countermeasures for Specimen Rejection in the Emergency Department

The rejected specimens from the Emergency Department of the Center of Clinical Laboratory from January 1,2022 to January 1,2023 were analyzed to reduce the specimen rejection rates and to improve the quality of inspection.The results showed that there were 1488 samples of rejected specimens and the non-conforming rate was 0.58%.The departments involved were mainly the Emergency Department,the Hematology Department,the Cardiology Department,the Intensive Care Department,and the Brain Surgery Department.Among the reasons for rejection,blood hemolysis accounted for 43.15%,blood coagulation accounted for 26.61%,and the rate of insufficient specimens was 17.14%.Among them,the sample rejection rate for arterial blood gas analysis was the highest,which accounted for 1.74%;followed by specimens for coagulation test,which was 1.18%.These results indicate the main reason for producing rejected specimens is mainly due to not following the standard operating procedure.Specimen rejection can largely be avoided if the standards for specimen collection are strictly followed.

Technological Analysis on Motor Stall and Its Perspective

The brush lock is due to assembly tightly during assembling three gripper so that it curls after some time in motor and bare motors.The motor happen to have current decreasing and cause rotary too slowly is an important technique problem.At last the motor hasn’t worked due to disconnection.It give company to bring assembly issue for customers.So the motor stall is main issue in motor working.We shall pay more attention to it necessarily and shall be strict quality inspection and we shall monitor the flow line for the sake of decreasing it.We shall solve the problem as soon as possible and communicate with the customer engineers.Unloaded rotation is radical in the base inspection.The engineer need to negotiate with supplying engineers for the qualified material of brush.Increasing inspection into more times is a method to decrease unqualified brushes.Some experiment method is explained to analyze for customer engineers.Two kinds of motors ie.stepping and asynchronous motor and motors used in future in car is explained to further knowledge to motor’s application.Such as the experiment with torque,voice and electric voltage converter.The pseudo soldering results the slow rotary.The reverse voltage is a reason for a motor to slow rotary even stall.

Tianjin Automotive Test Center & National Passenger Car Quality Supervision and Inspection Center——A State Testing and Universality Techniques Research Base in China

Tianiin Automotive Test Center has a test capability as well as a capability of conducting universality techniques research. With fixed assets of around RMB 76.44 million yuan and an architectural area of 11,200 sqm, test labs mainly include: auto emission test lab, full-scale vehicle crash test lab, auto safety test lab, auto lighting and view field test lab, engine test lab,

A novel approach to identifying the ultrasonic echoes for inspecting well cementing quality

In this paper, it is presented that an approach based on Continuous Wavelet Thansform(CWT) and Fourier Transform(FT) for identifying ultrasonic echoes in inspecting oil well cementing quality. First, CWT is used to process echo signals. Then spectra of the processing results in some specilic scale-time segments are calculated as pattern features. The research results show that theoretical calculations basically agree with experimental results. Compared with the aPproach based on the spectra or Discrete Wavlet Transform, our approach has advantages of fine analyzing scales, stable features and high recognizing rate. It is very suitable to identify echo signals whose spectra vary with time.

Bridging the gap:Neuro-Symbolic Computing for advanced AI applications in construction

Deep Learning(DL)has revolutionized the field of Artificial Intelligence(Al)in various domains such as computer vision(CV)and natural language processing.However,DL models have limitations including the need for large labeled datasets,lack of interpretability and explainability,potential bias and fairness issues,and limitations in common sense reasoning and contextual understanding.On the other side,DL has shown significant potential in construction for safety and quality inspection tasks using CV models.However,current CV approaches may lack spatial context and measurement capabilities,and struggle with complex safety and quality requirements.The integration of Neuro-Symbolic Computing(NSC),an emerging field that combines DL and symbolic reasoning,has been proposed as a potential solution to address these limitations.NSC has the potential to enable more robust,interpretable,and accurate AI systems in construction by harnessing the strengths of DL and symbolic reasoning.The combination of symbolism and connectionism in NSC can lead to more efficient data usage,improved generalization ability,and enhanced interpretability.Further research and experimentation are needed to effectively integrate NSC with large models and advance CV technologies for precise reporting of safety and quality inspection results in construction.

Corn kernel classification from few training samples

This article presents an efficient approach to classify a set of corn kernels in contact,which may contain good,or defective kernels along with impurities.The proposed approach consists of two stages,the first one is a next-generation segmentation network,trained by using a set of synthesized images that is applied to divide the given image into a set of individual instances.An ad-hoc lightweight CNN architecture is then proposed to classify each instance into one of three categories(ie good,defective,and impurities).The segmentation network is trained using a strategy that avoids the time-consuming and human-error-prone task of manual data annotation.Regarding the classification stage,the proposed ad-hoc network is designed with only a few sets of layers to result in a lightweight architecture capable of being used in integrated solutions.Experimental results and comparisons with previous approaches showing both the improvement in accuracy and the reduction in time are provided.Finally,the segmentation and classification approach proposed can be easily adapted for use with other cereal types.

Thresholding-based detection of fine and sparse details

Fine and sparse details appear in many quality inspection applications requiring machine vision.Especially on flat surfaces,such as paper or board,the details can be made detectable by oblique illumination.In this study,a general definition of such details is given by defining sufficient statistical properties from histograms.The statistical model allows simulation of data and comparison of methods designed for detail detection.Based on the definition,utilization of the existing thresholding methods is shown to be well motivated.The comparison shows that minimum error thresholding outperforms the other standard methods.Finally,the results are successfully applied to a paper printability inspection application,and the IGT picking assessment,in which small surface defects must be detected.The provided method and measurement system prototype provide automated assessment with results comparable to manual expert evaluations in this laborious task.