A construction engineering detection method

Abstract

The present invention discloses a construction engineering detection method, which relates to the field of engineering detection technology, and aims to solve the problem that the final result also needs to be manually checked and explained, and the data result is inaccurate, and the layman cannot understand the specific situation. The main points of the technical solution are: comprising the following steps, step 1, establishing a standard database 1, a problem database 1, a standard database 2 and a problem database 2 through ultrasonic detection data of several wall types and walls of the same type and optical detection data; step 2, establishing a calibration model based on the standard database 2 and the problem database 2 as conditions and the standard database 1 and the problem database 1 as bases, and the calibration model adjusts the ultrasonic detection data when the optical detection data deviates; step 3, establishing a screening model for the standard data with the standard database 1. The present invention can output a drawing, and the wall strength is expressed by the depth of color on the drawing.

Description

Technical Field

[0001] The present invention relates to the technical field of engineering detection, and more specifically, to a construction engineering detection method. Background Art

[0002] The current domestic construction industry is developing rapidly. During the construction process of buildings in various places, construction engineering testing companies are required to issue test reports to prove that the various parameters of the existing buildings are in normal condition. The current tests are usually carried out manually with handheld testers. When the final report is issued, only local building walls can be tested and analyzed. The final results also need to be manually checked and explained. The data results are inaccurate and it is impossible for laymen to understand the specific situation.

[0003] Therefore, a new solution needs to be proposed to solve this problem. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention aims to provide a construction engineering detection method.

[0005] The above technical purpose of the present invention is achieved through the following technical solutions: a construction engineering detection method, comprising the following steps:

[0006] Step 1, establishing a standard database 1, a problem database 1, a standard database 2 and a problem database 2 through ultrasonic detection data and optical detection data of several wall types and walls of the same type;

[0007] Step 2, establishing a calibration model based on the standard database 2 and the problem database 2 and the standard database 1 and the problem database 1, and adjusting the ultrasonic detection data when the optical detection data deviates;

[0008] Step 3, establishing a screening model for screening standard data with standard database 1;

[0009] Step 4, establish the Y-axis coordinate in the wall height direction and the X-axis coordinate in the wall width direction, and place the ultrasonic data detected by the wall according to the wall coordinates to form a data matrix;

[0010] Step 5, substitute the data matrix into the screening model, remove the standard data, and form a data matrix of the problem data in the coordinate system;

[0011] Step 6, based on the problem database 1, the ultrasonic detection data range interval of the same type of wall, and the specific expression form of the ultrasonic detection data range interval of the same type of wall as conditions, a conversion model is established, and the conversion model is used to convert the data array into an ultrasonic detection data change graph;

[0012] Step 7: Combine the ultrasonic detection data change diagram with the wall photo and output the problem feedback drawing.

[0013] By adopting the above technical solution and according to the above steps, people can substitute the ultrasonic detection data obtained by ultrasonically detecting the wall into the above method, and then directly obtain the problem feedback drawing. At this time, people only need to understand the problem of the wall according to the marked parts on the problem feedback drawing, and can also judge how to repair it according to the feedback of the drawing. The drawing allows laymen to understand the location and severity of the wall problem in the drawing, and also reduces the burden of people checking data.

[0014] The present invention is further configured such that: the ultrasonic detection data includes a real-time concrete strength conversion value, and the optical detection data includes a real-time wall surface flatness.

[0015] By adopting the above technical solution, since the ultrasonic detection data corresponds to the real-time concrete strength conversion value, it can more directly and clearly reflect the concrete strength of the wall, making the data people obtain more intuitive. Since the optical detection data corresponds to the flatness of the wall, the data can more intuitively correspond to whether the wall is flat or whether there are bumps, which makes it more convenient for people to process the data.

[0016] The present invention is further configured as follows: the steps of establishing the calibration model are as follows:

[0017] The standard flatness interval α = average (X min , X max )±5, and calculate the standard concrete strength conversion value interval γ=average(fccu min ,fccu max )×(0.8or1.2), and establish a formula to calculate the coefficient interval β=α / γ of the standard flatness and standard concrete strength conversion value, the real-time wall flatness is Y, the real-time concrete strength conversion value is Z, when When Y>α or Y<α is determined, if Y>α, the adjusted real-time concrete strength conversion value Z1=Z-(Y-α) / β; if Y<α, the adjusted real-time concrete strength conversion value Z1=Z+(α-Y) / β.

[0018] The present invention is further configured as follows: the steps of establishing the screening model are as follows:

[0019] The real-time concrete strength conversion value Z1 is used as the filtering object.

[0020] To establish the filtering condition, def condition(Z1) = return Z1∈γ,

[0021] Filter the value filter(Z1,condition),

[0022] And output to the data matrix print(filtered_Z1),

[0023] The final output data array.

[0024] The present invention is further configured as follows: the steps of establishing the conversion model are as follows:

[0025] Set several problems Concrete strength conversion value range (Z n —Z n+1 , Z n+2 —Z n+3 …Z n+n —Z n+n+1 )

[0026] Color the range of concrete strength conversion values ​​for each problem

[0027] “Z n —Z n+1 ” = “#FFFFFF”

[0028] “Z n+2 —Z n+3 ” = “#9AFC7F”

[0029] …

[0030] “Z n+n —Z n+n+1 ” = “#219900”

[0031] Assigning colors to the data array

[0032] Map1<-read.table(text="Data Map")

[0033] Output ultrasonic detection data change graph

[0034] image(1:nrow(Map1),1:ncol(Map1),t(apply(Map1,2,rev)),col=cols,xaxt='n',yaxt='n',ann=FALSE,bty='n',asp=1).

[0035] The present invention is further configured as follows: in step 7, the ultrasonic detection data change graph is combined with the wall photo, the Y-axis coordinate is established in the wall height direction, and the X-axis coordinate is established in the wall width direction, and the ultrasonic detection data change graph is placed in the wall photo at the coordinate position.

[0036] In summary, the present invention has the following beneficial effects:

[0037] Through this method, people can see the concrete strength of the wall more intuitively and clearly, and more easily find the parts where the concrete strength has problems. It can also be understood by laymen, reducing the difficulty of feedback of the test results. DETAILED DESCRIPTION

[0038] The present invention is described in detail below in conjunction with embodiments.

[0039] A construction engineering detection method comprises the following steps:

[0040] Step 1, establish standard database 1, problem database 1, standard database 2 and problem database 2 through ultrasonic detection data of several wall types and walls of the same type and optical detection data, wherein the ultrasonic detection data includes real-time concrete strength conversion value, the optical detection data includes real-time wall flatness, the ultrasonic detection data is obtained by ultrasonic detection of the wall, and the optical detection data is obtained by optical detection of the wall.

[0041] The establishment of standard database 1, problem database 1, standard database 2 and problem database 2 enables people to collect statistics on different types of wall data, and to obtain the range of real-time concrete strength conversion values ​​of walls of the same type (X min , X max ).

[0042] Step 2: Establish a calibration model based on the standard database 2 and the problem database 2, and based on the standard database 1 and the problem database 1. When the optical detection data deviates, the calibration model adjusts the ultrasonic detection data. The steps for establishing the calibration model are as follows:

[0043] The standard flatness interval α = average (X min , X max )±5, and calculate the standard concrete strength conversion value interval γ=average(fccu min ,fccu max)×(0.8or1.2), and establish a formula to calculate the coefficient interval β=α / γ of the standard flatness and standard concrete strength conversion value, the real-time wall flatness is Y, the real-time concrete strength conversion value is Z, when When Y>α or Y<α, it is judged that if Y>α, the adjusted real-time concrete strength conversion value Z1=Z-(Y-α) / β; if Y<α, the adjusted real-time concrete strength conversion value Z1=Z+(α-Y) / β. After the real-time concrete strength conversion value is adjusted, the error of the concrete strength conversion value caused by the unevenness of the wall can be avoided, thereby ensuring that when the overall data does not consider whether the concrete wall is uneven, it is more objective to judge whether the real-time concrete strength conversion value is in a weak strength situation, thereby reducing the impact of the error.

[0044] Step 3: Establish a screening model for screening standard data with standard database 1. The steps for establishing the screening model are as follows:

[0045] The real-time concrete strength conversion value Z1 is taken as the filtering object to establish the filtering condition, defcondition(Z1)=return Z1∈γ, filter the value filter(Z1,condition), and output it to the data matrix print(filtered_Z1), and finally output the data array. By establishing the screening model, it is possible to filter the redundant normal data of the real-time concrete strength conversion value, thereby leaving the real-time concrete strength conversion value with problems to facilitate the detection personnel to perform data analysis, further improve the accuracy of data analysis, and reduce the errors generated during the analysis process. In addition, it can directly filter the data matrix, and the filtered data array can be directly matched with the corresponding position of the wall according to the coordinate system, so that people can more easily find and repair the parts of the wall with strength problems.

[0046] Step 4, establish the Y-axis coordinate in the wall height direction and the X-axis coordinate in the wall width direction, and place the ultrasonic data of the wall detection according to the wall coordinates to form a data matrix. By establishing the data matrix, the real-time concrete strength conversion value can be directly filled in according to the coordinate system established by the wall, so that people can find the real-time concrete strength conversion value for each area of ​​the wall.

[0047] Step 5, substitute the data matrix into the screening model, remove the standard data, and form a data map of the problem data in the coordinate system. After the data matrix is ​​brought into the screening model, only the problem data with problems in the real-time concrete strength conversion value are retained. The data map is still set in the coordinate system established by the wall. At this time, people can preliminarily judge the problem parts of the wall through the problem data retained in the coordinate system, and can analyze the renovation condition of the wall through the specific data.

[0048] Step 6, based on the problem database 1, the ultrasonic detection data range interval of the same type of wall, and the specific expression form of the ultrasonic detection data range interval of the same type of wall as conditions, a conversion model is established. The conversion model is used to convert the data array into an ultrasonic detection data change diagram. The steps for establishing the conversion model are as follows: set a number of problem concrete strength conversion value ranges (Z n —Z n+1 , Z n+2 —Z n+3 …Z n+n —Z n+n+1 ), assign color “Z” to the range of concrete strength conversion values ​​for each problem. n —Z n+1 ”=“#FFFFFF”,“Z n+2 —Z n+3 "="#9AFC7F",...,"Z n+n —Z n+n+1 ” = “#219900”, assign color to the data array Map1 <- read.table(text = "data array"), output the ultrasonic detection data change graph image(1:nrow(Map1), 1:ncol(Map1), t(apply(Map1,2,rev)), col = cols, xaxt = 'n', yaxt = 'n', ann = FALSE, bty = 'n', asp = 1), at this time, through the conversion model, the problem data in the data array is converted into the corresponding color pattern after distinguishing the interval, and then after outputting the ultrasonic detection data change graph, people only need to use the color card corresponding to the strength conversion value range of the problem concrete to simply judge the problem data situation with the naked eye, without having to analyze and check the detailed data one by one, and can understand the problem location and strength problem situation at the corresponding coordinate position of the wall.

[0049] Step 7, combining the ultrasonic detection data change graph with the wall photo, and outputting the problem feedback drawing. Specifically, the ultrasonic detection data change graph is combined with the wall photo, the Y-axis coordinate is established in the wall height direction, and the X-axis coordinate is established in the wall width direction, and the ultrasonic detection data change graph is placed in the wall photo at the coordinate position. After the ultrasonic detection data change graph is combined with the wall photo, people can directly and clearly find the problematic parts on it through the wall photo, so that people can more intuitively understand the problematic parts of the wall, which is convenient for people to carry out maintenance.

[0050] The above is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technicians in this technical field, some improvements and modifications without departing from the principle of the present invention should also be regarded as the protection scope of the present invention.

Claims

1. A construction engineering detection method, characterized in that: The following steps are included: Step 1, establishing a standard database 1, a problem database 1, a standard database 2 and a problem database 2 through ultrasonic detection data and optical detection data of several wall types and walls of the same type, wherein the ultrasonic detection data include real-time concrete strength conversion values, and the optical detection data include real-time wall surface flatness, wherein normal and abnormal standard concrete strength conversion values ​​and problem concrete strength conversion values ​​in ultrasonic detection data of several wall types and walls of the same type are stored in the standard database 1 and the problem database 1 respectively, and standard flatness and problem flatness that meet the flatness requirements and do not meet the flatness requirements in optical detection data of several wall types and walls of the same type are stored in the standard database 2 and the problem database 2 respectively; Step 2, establishing a calibration model based on the standard database 2 and the problem database 2 and the standard database 1 and the problem database 1, and adjusting the ultrasonic detection data when the optical detection data deviates; The steps for establishing the calibration model are as follows: The standard flatness interval α = average (X min , X max )±5, the X min , X max are the minimum and maximum values ​​of the real-time concrete strength conversion values ​​of the wall in the same category, and the standard concrete strength conversion value interval γ = average (fccu min ,fccu max )×(0.8or1.2), and establish a formula to calculate the coefficient interval β=α / γ of the standard flatness and standard concrete strength conversion value, the real-time wall flatness is Y, the real-time concrete strength conversion value is Z, when When Y>α or Y<α is determined, if Y>α, the adjusted real-time concrete strength conversion value Z1=Z-(Y-α) / β; if Y<α, the adjusted real-time concrete strength conversion value Z1=Z+(α-Y) / β. Step 3, establishing a screening model for screening standard data with standard database 1; Step 4, establish the Y-axis coordinate in the wall height direction and the X-axis coordinate in the wall width direction, and place the ultrasonic data detected by the wall according to the wall coordinates to form a data matrix; Step 5, substitute the data matrix into the screening model, remove the standard data, and form a data matrix of the problem data in the coordinate system; Step 6, based on the problem database 1, the ultrasonic detection data range interval of the same type of wall, and the specific expression form of the ultrasonic detection data range interval of the same type of wall as conditions, a conversion model is established, and the conversion model is used to convert the data array into an ultrasonic detection data change graph; Step 7: Combine the ultrasonic detection data change diagram with the wall photo and output the problem feedback drawing.

2. A construction engineering detection method according to claim 1, characterized in that: The steps for establishing the screening model are as follows: The real-time concrete strength conversion value Z1 is used as the filtering object. To establish the filtering condition, def condition(Z1) = return Z1∈γ, Filter the value filter(Z1,condition), And output to the data matrix print(filtered_Z1), The final output data array.

3. A construction engineering detection method according to claim 2, characterized in that: The steps for establishing the conversion model are as follows: Set several problems Concrete strength conversion value range (Z n —Z n+1 , Z n+2 —Z n+3 …Z n+n —Z n+n+1 ) Color the range of concrete strength conversion values ​​for each problem "WITH n -WITH n+1 ”="#FFFFFF” "WITH n+2 -WITH n+3 ”="#9AFC7F” … "WITH n+n -WITH n+n+1 ”="#219900” Assigning colors to the data array Map1<-read.table(text="Data Map") Output ultrasonic detection data change graph image(1:nrow(Map1),1:ncol(Map1),t(apply(Map1,2,rev)),col=cols,xaxt='n',yaxt='n',ann=FALSE,bty='n',asp=1).

4. A construction engineering detection method according to claim 1, characterized in that: In step 7, the ultrasonic detection data change graph is combined with the wall photo, the Y-axis coordinate is established in the wall height direction, and the X-axis coordinate is established in the wall width direction, and the ultrasonic detection data change graph is placed in the wall photo at the coordinate position.