Engineering quality evaluation model design method

Abstract

The invention relates to the technical field of constructional engineering management, in particular to an engineering quality evaluation model design method, which comprises the following steps: acquiring related data in a construction site and a historical project, the data comprising material quality data, construction process data, environmental influence data and quality inspection record data; and constructing an initial quality evaluation model according to the acquired data. The engineering quality evaluation model can systematically evaluate the quality of the constructional engineering, and by combining real-time data and expert review, human errors are effectively reduced, the scientificity and efficiency of engineering management are improved, and the safety and compliance of the constructional engineering are ensured.

Description

Technical Field

[0001] The invention relates to the technical field of construction engineering management, and in particular to a method for designing an engineering quality assessment model. Background Art

[0002] Project quality assessment refers to the systematic inspection and evaluation of the structural safety, functional use, and appearance quality of a construction project during or after its completion, based on industry standards. This process involves multiple dimensions, including material quality, construction technology, environmental impact, and inspection records, and is intended to ensure that the project meets design requirements and expected performance, and to ensure the long-term stability and safety of the building, while providing a basis for the continuous improvement of project quality.

[0003] In construction projects, ensuring project quality is the key factor for project success. At present, construction project quality management mostly relies on manual inspection and experience judgment, which has problems such as strong subjectivity, information lag and low efficiency. With the development of information technology, a systematic and scientific project quality assessment model is urgently needed to improve the accuracy and efficiency of the assessment and ensure the safety and compliance of construction projects. Therefore, a project quality assessment model design method is proposed to address the above problems. Summary of the invention

[0004] The purpose of the present invention is to provide a method for designing a project quality assessment model to solve the problem that ensuring project quality is a key factor for project success in construction projects. Currently, construction project quality management mostly relies on manual inspection and experience judgment, which has the problems of strong subjectivity, information lag and low efficiency.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] A method for designing a project quality assessment model, comprising:

[0007] Obtain relevant data from construction sites and historical projects, including material quality data, construction process data, environmental impact data, and quality inspection record data;

[0008] An initial quality assessment model is constructed based on the acquired data. The model formula is:

[0009] Q=β0+β1·X1+β2·X2+β3·X3+β4·X4

[0010] Where Q is the project quality assessment value, X1 is the material quality score, X2 is the construction process score, X3 is the environmental impact score, X4 is the inspection record score, β0 is the intercept, β1, β2, β3, β4 are the regression coefficients of the features, indicating the degree of influence of each feature on the quality assessment, and satisfying β0+β1+β2+β3+β4=1;

[0011] Assess the weights of material quality, construction technology, environmental impact and quality inspection records affecting project quality. The obtained weight parameters will be used to calculate the evaluation results of given input features and conduct quantitative and qualitative analysis.

[0012] Real-time monitoring and dynamic updating: Use sensors and IoT technology to collect construction site data in real time; regularly update model parameters and adjust assessment results; generate real-time quality assessment reports and provide rectification suggestions.

[0013] As a further optimization of the present invention, the weights of material quality, construction technology, environmental impact and quality inspection records affecting project quality are calculated by a multiple linear regression model β j Parameter value,

[0014] S1: Model function f(X) definition: The model function f(X) is defined as:

[0015] Q=f(X)=y=β0+β1·X1+β2·X2+β3·X3+β4·X4

[0016] S2: Represent the collected historical engineering data in a matrix: Using historical engineering data to train the model, the data set is represented in matrix form, where X is the feature matrix and y is the target variable vector;

[0017] S3: Calculate weight parameter β j , the weight parameter is calculated by the least squares method, and the calculation formula of the weight parameter is:

[0018] β j =(X T X) -1 X T y

[0019] Where, X T is the transpose of the feature matrix, (X T X) -1 Yes X T The inverse matrix of X;

[0020] S4: Substitute the calculated weight parameters into the model function f(X) to calculate the evaluation result of the given input feature;

[0021] S5: Quantitative analysis: Use the calculated weight parameters to calculate the score of the quantitative analysis;

[0022] S6: Qualitative analysis: First, calculate (X T X) -1 ,(X T X) -1is the inverse operation of the 4×4 matrix, which is done using mathematical software. Then, (X T X) -1 Multiply by X T y gets the weight parameter β j .

[0023] As further optimized content of the present invention, the historical engineering data matrix includes material quality data, construction process data, environmental impact data and quality inspection record data of multiple engineering projects, and the data is preprocessed through standardized methods to ensure that data of different units and magnitudes can be analyzed with unified standards.

[0024] As a further optimization of the present invention, the real-time monitoring and dynamic update step further includes using Internet of Things technology to deploy sensor equipment to collect real-time environmental temperature, humidity, air pressure and vibration physical parameters of the construction site, and transmit the real-time data to the cloud for storage and analysis.

[0025] As a further optimization of the present invention, the quantitative analysis step further includes weighting the scoring results of each feature using a weighted average method to obtain a comprehensive quality score, the formula is:

[0026]

[0027] Where Qi is the score of each feature (material quality, construction technology, environmental impact, inspection record), wi is the weight of the corresponding feature, and satisfies

[0028] As further optimized content of the present invention, the updating process of the model adopts a rolling regression method, and newly collected historical data are regularly added to the training data set to ensure that the model can adapt to new changes that may occur during the construction process, and the regression coefficients in the evaluation model are regularly updated.

[0029] As a further optimization of the present invention, the model training process further includes cross-validation of input data to ensure the accuracy and robustness of the model, and adjusting the parameters of the model according to the validation results.

[0030] As a further optimization of the present invention, the qualitative analysis step includes calculating the inverse matrix of the feature matrix, using the NumPy library in the mathematical software Python for calculation, and judging the relative impact of each feature on the engineering quality by comparing with historical data.

[0031] As further optimized content of the present invention, the method further includes using virtual reality technology, combined with real-time quality assessment results, to display quality risk points and optimization suggestions in the construction process to project managers through a visual interface.

[0032] As further optimized content of the present invention, the relevant data in the construction site and historical projects, including material quality data, construction process data, environmental impact data and quality inspection record data, are obtained by relying on sensor equipment, Internet of Things technology, intelligent monitoring system, mobile devices and environmental monitoring equipment hardware equipment, combined with big data analysis platform and cloud computing technology to realize real-time data collection, storage and analysis.

[0033] Compared with the prior art, the present invention has the following beneficial effects:

[0034] In the present invention, the project quality assessment model provided can systematically evaluate the quality of construction projects, combine real-time data and expert review, effectively reduce human errors, improve the scientificity and efficiency of project management, and ensure the safety and compliance of construction projects. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 The present invention is a flowchart of a method for designing a project quality assessment model. DETAILED DESCRIPTION

[0036] The present invention will be further described below in conjunction with specific implementation methods, wherein the accompanying drawings are only used for exemplary descriptions and represent only schematic diagrams rather than actual drawings, and should not be understood as limiting the present invention. In order to better illustrate the specific implementation methods of the present invention, some parts of the accompanying drawings may be omitted, enlarged or reduced, and do not represent the size of the actual product.

[0037] The specific implementation process of the technical solution of the present invention includes the following steps:

[0038] Step 1: Data Collection: Collect relevant data from construction sites and historical projects, including:

[0039] Material quality data (strength, durability);

[0040] Construction process data (process, construction personnel skill level);

[0041] Environmental impact data (temperature, humidity);

[0042] Quality inspection records (unqualified items, rectification status);

[0043] Step 2: Initial evaluation model construction: The model formula is:

[0044] Q=β0+β1·X1+β2·X2+β3·X3+β4·X4

[0045] Where Q is the project quality assessment value, X1 is the material quality score, X2 is the construction process score, X3 is the environmental impact score, X4 is the inspection record score, β0 is the intercept, β1, β2, β3, β4 are the regression coefficients of the features, indicating the degree of influence of each feature on the quality assessment, and satisfying β0+β1+β2+β3+β4=1;

[0046] Step 3: Calculate β through the weights of material quality, construction technology, environmental impact and quality inspection records that affect project quality through a multivariate linear regression model j Parameter values, then, the model function f(X) is defined as:

[0047] Q=f(X)=y=β0+β1·X1+β2·X2+β3·X3+β4·X4

[0048] Use historical engineering data to train the model. The data set is:

[0049] <![CDATA[X1]]> <![CDATA[X2]]> <![CDATA[X3]]> <![CDATA[X4]]> y 9 8 5 6 7.8 7 9 3 6 6.9 2 3 9 3 8.1 5 6 1 9 5.8 6 8 4 2 9.8

[0050] Matrix representation:

[0051]

[0052] Calculate the weight parameter β j :

[0053] β j =(X T X) -1 X T y

[0054] Calculate X T X

[0055]

[0056] Calculate X T y

[0057]

[0058] Calculate (X T X) -1

[0059]

[0060] Substituting the above calculation results into β j The formula is:

[0061]

[0062] Run the code and substitute:

[0063] Q=f(X)=0.05+0.21X1+0.14X2+0.35X3+0.25X4

[0064] Assume that in a certain evaluation, the input features are as follows:

[0065] Material quality score X1 = 8

[0066] Construction technology score X2 = 7

[0067] Environmental impact score X3 = 5

[0068] Inspection record score X4 = 6

[0069] Then the evaluation result can be calculated:

[0070] Q=f(X)=0.15+0.21×8+0.14×7+0.35×5+0.25×6=6.06

[0071] Quantitative analysis: material quality score is 1.68; construction process score is 0.98, environmental impact score is 1.75, inspection record score is 1.5, and the final score is 6.06 (the qualification standard is set at 5);

[0072] Qualitative analysis: Organize experts to conduct on-site evaluation. The experts believe that the construction quality meets the standards, but the quality inspection and rectification process needs to be improved, as well as the construction process technology disclosure;

[0073] Step 4: Real-time monitoring and dynamic updates:

[0074] Use sensors and IoT technology to collect construction site data in real time;

[0075] The model parameters are updated regularly and Dongtai adjusts the assessment results;

[0076] Generate real-time quality assessment reports and provide correction suggestions;

[0077] In the above content, the historical engineering data matrix includes material quality data, construction process data, environmental impact data and quality inspection record data of multiple engineering projects, and the data is preprocessed through standardized methods to ensure that data of different units and magnitudes can be analyzed with unified standards. The historical data is preprocessed through standardized methods to ensure the uniformity of the data and avoid calculation errors caused by unit differences;

[0078] The real-time monitoring and dynamic update step further includes the use of IoT technology to deploy sensor equipment to collect the environmental temperature, humidity, air pressure and vibration physical parameters of the construction site in real time, and transmit the real-time data to the cloud for storage and analysis, which increases the application of IoT technology, collects environmental data in real time and transmits it to the cloud for analysis, and improves the timeliness and accuracy of the assessment;

[0079] The quantitative analysis step further includes using the weighted average method to weight the score results of each feature to obtain a comprehensive quality score, the formula is:

[0080]

[0081] Where Qi is the score of each feature (material quality, construction technology, environmental impact, inspection record), wi is the weight of the corresponding feature, and satisfies It provides a specific method for quantitative analysis, explaining how to weight different features to obtain a comprehensive quality score;

[0082] The model update process adopts the rolling regression method, regularly adding newly collected historical data to the training data set to ensure that the model can adapt to new changes that may occur during the construction process, and regularly updating the regression coefficients in the evaluation model to ensure that the model can dynamically adapt to changes in the construction process;

[0083] The model training process further includes cross-validation of input data to ensure the accuracy and robustness of the model, and adjusting the model parameters based on the validation results, which can ensure the accuracy of the model when training and improve the stability and reliability of the model;

[0084] The qualitative analysis step includes calculating the inverse matrix of the feature matrix, using the NumPy library in the mathematical software Python to perform the calculation, and by comparing with historical data, judging the relative impact of each feature on the engineering quality, thus improving the efficiency of the calculation;

[0085] The method further includes using virtual reality technology, combined with real-time quality assessment results, to display quality risk points and optimization suggestions in the construction process to project managers through a visual interface, presenting the quality assessment results to managers in an intuitive form, thereby improving the project managers' perception and response capabilities to quality issues, and making complex data easier to understand through visualization technology, thereby accelerating the decision-making process and problem-solving efficiency;

[0086] Relevant data from construction sites and historical projects, including material quality data, construction process data, environmental impact data, and quality inspection record data, are acquired by relying on sensor equipment, Internet of Things technology, intelligent monitoring systems, mobile devices, and environmental monitoring equipment hardware, combined with big data analysis platforms and cloud computing technologies to achieve real-time data collection, storage, and analysis, which can improve the accuracy of data collection.

[0087] This article uses specific examples to illustrate the principles and implementation methods of the present invention. The above examples are only used to help understand the method and core ideas of the present invention. The above is only a preferred implementation of the present invention. It should be pointed out that due to the limitations of textual expression and the objective existence of infinite specific structures, ordinary technicians in this technical field can make several improvements, modifications or changes without departing from the principles of the present invention, and can also combine the above technical features in an appropriate manner; these improvements, modifications, changes or combinations, or the direct application of the inventive concept and technical solution to other occasions without improvement, should be regarded as the protection scope of the present invention.

Claims

1. A method for designing a project quality assessment model, characterized in that: include: Obtain relevant data from construction sites and historical projects, including material quality data, construction process data, environmental impact data, and quality inspection record data; An initial quality assessment model is constructed based on the acquired data. The model formula is: Q=β0+β1·X1+β2·X2+β3·X3+β4·X4 Where Q is the project quality assessment value, X1 is the material quality score, X2 is the construction process score, X3 is the environmental impact score, X4 is the inspection record score, β0 is the intercept, β1, β2, β3, β4 are the regression coefficients of the features, indicating the degree of influence of each feature on the quality assessment, and satisfying β0+β1+β2+β3+β4=1; Assess the weights of material quality, construction technology, environmental impact and quality inspection records affecting project quality. The obtained weight parameters will be used to calculate the evaluation results of given input features and conduct quantitative and qualitative analysis. Real-time monitoring and dynamic updates: Use sensors and IoT technology to collect construction site data in real time; Regularly update model parameters and adjust evaluation results; Generate real-time quality assessment reports and provide corrective suggestions.

2. The method for designing a construction quality assessment model according to claim 1, characterized in that: The weights of material quality, construction technology, environmental impact and quality inspection records affecting project quality are calculated using a multiple linear regression model β j Parameter value, S1: Model function f(X) definition: The model function f(X) is defined as: Q=f(X)=y=β0+β1·X1+β2·X2+β3·X3+β4·X4 S2: Represent the collected historical engineering data in a matrix: Using historical engineering data to train the model, the data set is represented in matrix form, where X is the feature matrix and y is the target variable vector; S3: Calculate weight parameter β j , the weight parameter is calculated by the least squares method, and the calculation formula of the weight parameter is: β j =(X T X) -1 X T y Where, X T is the transpose of the feature matrix, (X T X) -1 Yes X T The inverse matrix of X; S4: Substitute the calculated weight parameters into the model function f(X) to calculate the evaluation result of the given input feature; S5: Quantitative analysis: Use the calculated weight parameters to calculate the score of the quantitative analysis; S6: Qualitative analysis: First, calculate (X T X) -1 ,(X T X) -1 is the inverse operation of the 4×4 matrix, which is done using mathematical software. Then, (X T X) -1 Multiply by X T y gets the weight parameter β j .

3. The method for designing a construction quality assessment model according to claim 1, characterized in that: The historical engineering data matrix includes material quality data, construction process data, environmental impact data and quality inspection record data of multiple engineering projects, and pre-processes the data through standardized methods to ensure that data of different units and magnitudes can be analyzed with unified standards.

4. The method for designing a construction quality assessment model according to claim 1, characterized in that: The real-time monitoring and dynamic update step further includes using Internet of Things technology to deploy sensor equipment to collect real-time environmental temperature, humidity, air pressure and vibration physical parameters at the construction site, and transmit the real-time data to the cloud for storage and analysis.

5. The method for designing a construction quality assessment model according to claim 1, characterized in that: The quantitative analysis step further includes weighting the scoring results of each feature using a weighted average method to obtain a comprehensive quality score, the formula is: Where Qi is the score of each feature (material quality, construction technology, environmental impact, inspection record), wi is the weight of the corresponding feature, and satisfies 6. The method for designing a construction quality assessment model according to claim 1, characterized in that: The updating process of the model adopts a rolling regression method, and newly collected historical data are regularly added to the training data set to ensure that the model can adapt to new changes that may occur during the construction process, and the regression coefficients in the evaluation model are regularly updated.

7. The method for designing a construction quality assessment model according to claim 1, characterized in that: The model training process further includes cross-validation of input data to ensure the accuracy and robustness of the model, and adjusting the parameters of the model based on the validation results.

8. The method for designing a construction quality assessment model according to claim 1, characterized in that: The qualitative analysis step includes calculating the inverse matrix of the feature matrix, using the NumPy library in the mathematical software Python for calculation, and judging the relative impact of each feature on the engineering quality by comparing with historical data.

9. The method for designing a construction quality assessment model according to claim 1, characterized in that: The method further includes using virtual reality technology, combined with real-time quality assessment results, to display quality risk points and optimization suggestions during the construction process to project managers through a visual interface.

10. The method for designing a construction quality assessment model according to claim 1, characterized in that: The relevant data of the construction sites and historical projects, including material quality data, construction process data, environmental impact data and quality inspection record data, are obtained by relying on sensor equipment, Internet of Things technology, intelligent monitoring systems, mobile devices and environmental monitoring equipment hardware equipment, combined with big data analysis platforms and cloud computing technologies to achieve real-time data collection, storage and analysis.

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