Research On The Quality Acceptance Content And The Image Recognition Of The Impact Echo Detection Of The Prefabricated Concrete Bridge Pier

In recent years,the increasing rise of prefabricated bridges effectively solves the problems that the construction in some areas leads to the reduction of the scope of people’s living activities and the long construction time of bridges.A large number of cast-in-place construction has a great impact on the surrounding environment,causing a lot of problems for people’s daily travel.The construction quality of prefabricated bridges determines the safety and service life of bridges Limit.At present,the quality control of assembled piers in our country is lack of corresponding specifications.Some local specifications that have been issued are also in the preliminary development stage,and the application scope is also very small.Through investigation and analysis,this paper understands various problems that may occur in the construction process of prefabricated piers,analyzes the causes of defects comprehensively,and gives corresponding solutions.At the same time,the results of detecting the grouting quality of prefabricated concrete bridge joints are identified intelligently.Based on the study of the characteristics and construction process of the prefabricated pier construction technology,this paper summarizes the existing local standards and industry specifications,combined with the current research status and engineering application of the grouting sleeve,and analyzes the common defects and causes of the design and construction of the connection nodes of the prefabricated pier,so as to effectively control the possible problems in the construction of the prefabricated pier Defects,and gives effective solutions and control methods.It includes the quality of materials,the manufacturing quality of components,the standard operation to be followed in transportation,the quality of installation and construction,and the content of construction acceptance.In the construction of the assembly bridge,the quality of the joint determines the integrity and safety of the assembly bridge.In the detection of the filling degree of the joint,most of the detection results are identified and classified through the experience of the detection personnel,and there are some errors in the image recognition.For this reason,this paper will process the data and image detected by the impact echo methodso that the information of the image can be easily and quickly read;then use Canny operator,Sobel operator and LOG operator to read the image Edge detection is used to remove the background noise,and the impact echo signal is extracted based on the image morphology;and the convolutional neural network is used to extract the impact echo signal Network,CNN)defect recognition research,designed CNN to achieve defect image recognition,over fitting problem through the use of dropout technology to solve,the use of convolutional neural network deep learning theory for image defect recognition learning after the recognition accuracy of the image can reach 80%.Finally,the quality control content of the prefabricated bridge is studied,which provides a reference for the quality control of the prefabricated concrete pier project.