Engineering test data traceability method and system based on blockchain

Abstract

The present invention relates to the field of data processing technology, and in particular to a method and system for tracing the source of engineering test data based on blockchain. The method includes: obtaining engineering test data of each construction process in the construction phase of a target engineering project; determining the construction correlation coefficient between the current construction process and the other construction processes based on the engineering test data of the current construction process and the engineering test data of other construction processes; determining the authenticity coefficient of the engineering test data of the current construction process based on the construction correlation coefficient between the current construction process and other construction processes; using the authenticity coefficient to judge whether the engineering test data of the construction process are real data, and if they are real data, storing them in blockchain to trace the engineering test data of the construction process. In this way, the present invention improves the accuracy of data tracing results.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a blockchain-based engineering test data traceability method and system. Background Art

[0002] In modern engineering construction, the authenticity and integrity of engineering test and inspection data are fundamental to ensuring project quality. Data traceability can ensure the authenticity and integrity of engineering test and inspection data and quickly locate the source of any problems. The development of information technology, particularly blockchain technology, has provided new solutions for tackling the problem of engineering test and inspection data traceability. A blockchain-based engineering test and inspection data traceability method utilizes blockchain technology to track and verify the authenticity and integrity of engineering test and inspection data. Traceability is crucial for improving project quality, ensuring safety, and complying with regulatory requirements.

[0003] In some scenarios, blockchain-based engineering test and inspection data traceability methods ensure data transparency and traceability by recording and storing detailed test and inspection data for each engineering material at each stage. However, the large amount of engineering test and inspection data generated during the construction process may contain some errors or false data, which may affect the authenticity of the engineering test and inspection data and lead to lower accuracy of data traceability results. Summary of the Invention

[0004] In order to solve the technical problem of low accuracy of data traceability results, the purpose of the present invention is to provide a blockchain-based engineering test data traceability method and system. The technical solutions adopted are as follows:

[0005] In a first aspect, an embodiment of the present invention provides a blockchain-based engineering test data traceability method, comprising:

[0006] Obtain engineering test and inspection data for each construction process during the construction phase of the target project;

[0007] Determining, based on the engineering test and inspection data of the current construction process and the engineering test and inspection data of other construction processes, a construction correlation coefficient between the current construction process and the other construction processes, wherein the construction correlation coefficient represents the degree of correlation between the current construction process and the other construction processes;

[0008] Determining, based on the construction correlation coefficient between the current construction process and the other construction processes, a authenticity coefficient of the engineering test data of the current construction process, wherein the authenticity coefficient represents the authenticity of the engineering test data of the current construction process;

[0009] The authenticity coefficient is used to determine whether the engineering test and detection data of the construction process is real data. If it is real data, it is stored in the blockchain to trace the engineering test and detection data of the construction process. If it is not real data, the engineering test and detection data of the construction process is checked.

[0010] Furthermore, determining the construction correlation coefficient between the current construction process and the other construction processes based on the engineering test and detection data of the current construction process and the engineering test and detection data of the other construction processes includes:

[0011] Determining a quality degradation coefficient of the current construction process based on engineering test data of the current construction process and similar construction processes, wherein the quality degradation coefficient represents the data quality of the current construction process, wherein the similar construction process and the current construction process are construction processes of the same construction type but at different construction stages;

[0012] The construction correlation coefficient between the current construction process and the other construction processes is determined by using the quality degradation coefficient of the current construction process, the quality degradation coefficient of the other construction processes, and the first Pearson correlation coefficient between the current construction process and the other construction processes.

[0013] Furthermore, determining the quality degradation coefficient of the current construction process based on engineering test data of the current construction process and similar construction processes includes:

[0014] Obtaining average test data of engineering test data of the same type of construction process;

[0015] The ratio of the engineering test detection data of the current construction process to the average detection data is determined as the quality degradation coefficient of the current construction process.

[0016] Furthermore, the determining of the construction correlation coefficient between the current construction process and the other construction processes by using the quality degradation coefficient of the current construction process, the quality degradation coefficient of the other construction processes, and the first Pearson correlation coefficient between the current construction process and the other construction processes includes:

[0017] Acquiring engineering test and inspection data of the current construction process under different construction conditions and engineering test and inspection data of other construction processes under different construction conditions;

[0018] Determining a first Pearson correlation coefficient between the current construction process and the other construction processes based on the engineering test data of the current construction process under different construction conditions and the engineering test data of the other construction processes under different construction conditions;

[0019] Calculating the absolute value of the difference between the quality degradation coefficient of the current construction process and the quality degradation coefficient of the other construction processes;

[0020] The product of the absolute value and the first Pearson correlation coefficient is determined as the construction correlation coefficient.

[0021] Furthermore, the determining of the authenticity coefficient of the engineering test data of the current construction process based on the construction correlation coefficient between the current construction process and the other construction processes includes:

[0022] Determining a quality contribution factor of the current construction process based on the engineering test and detection data of the current construction process, wherein the quality contribution factor represents the degree of influence of the engineering test and detection data of the current construction process on the engineering quality of the target engineering project;

[0023] Selecting a first target construction process having a construction correlation coefficient greater than a first threshold from the other construction processes;

[0024] Determine, based on engineering test data of an intermediate construction process between the current construction process and the first target construction process, a quality contribution factor of the intermediate construction process, and an engineering quality indicator corresponding to the intermediate construction process, a correlation annoyance coefficient between the current construction process and the first target construction process, wherein the correlation annoyance coefficient represents the degree of influence of the intermediate construction process on the engineering quality of the target engineering project;

[0025] determining a data correlation factor between the current construction process and the first target construction process based on the construction correlation coefficient and the correlation nuisance coefficient between the current construction process and the first target construction process, wherein the data correlation factor represents a degree of data correlation between the engineering test detection data of the current construction process and the first target construction process;

[0026] The authenticity coefficient of the engineering test data of the current construction process is determined by using the data correlation factor, the engineering test data of the current construction process and the first target construction process under different construction conditions.

[0027] Furthermore, determining the quality contribution factor of the current construction process based on the engineering test data of the current construction process includes:

[0028] Fitting the engineering test data of the current construction process under different construction conditions to obtain a first fitting curve, and fitting the engineering quality indicators corresponding to the engineering test data of the current construction process under different construction conditions to obtain a second fitting curve;

[0029] Obtaining a variance of a data value at each data sampling point in the first fitting curve, a first curve slope at each data sampling point, and a second curve slope at each data sampling point in the second fitting curve;

[0030] A quality contribution factor of the current construction process is determined according to the variance, the first curve slope, and the second curve slope.

[0031] Furthermore, determining the correlation annoyance coefficient between the current construction process and the first target construction process based on engineering test data of an intermediate construction process between the current construction process and the first target construction process, a quality contribution factor of the intermediate construction process, and an engineering quality indicator corresponding to the intermediate construction process includes:

[0032] Obtaining engineering test and inspection data of the intermediate construction process under different construction conditions and engineering quality indicators corresponding to the engineering test and inspection data of the intermediate construction process under different construction conditions;

[0033] determining a second Pearson correlation coefficient between the current construction process and the first target construction process based on the engineering test data of the intermediate construction process under different construction conditions and the engineering quality indicators corresponding to the engineering test data of the intermediate construction process under different construction conditions;

[0034] The correlation annoyance coefficient between the current construction process and the first target construction process is determined by using the number of the intermediate construction processes, the quality contribution factor of the intermediate construction processes, and the second Pearson correlation coefficient.

[0035] Furthermore, determining the data correlation factor between the current construction process and the first target construction process based on the construction correlation coefficient and the correlation nuisance coefficient between the current construction process and the first target construction process includes:

[0036] Determining a superposition value of the relevant nuisance coefficient and a preset value;

[0037] The ratio of the construction correlation coefficient to the superposition value is determined as a data correlation factor between the current construction process and the first target construction process.

[0038] Furthermore, the determining of the authenticity coefficient of the engineering test data of the current construction process by using the data correlation factor, the engineering test data of the current construction process and the first target construction process under different construction conditions includes:

[0039] Selecting a second target construction process from the first target construction process, wherein the data correlation factor is greater than a second threshold;

[0040] Determining a first ratio of the engineering test data of the current construction process to the engineering test data of the second target construction process;

[0041] Determine a second ratio of a first average value to a second average value, where the first average value is an average value of engineering test data of a construction process of the same type as the current construction process under different construction conditions, and the second average value is an average value of engineering test data of a construction process of the same type as the second target construction process under different construction conditions;

[0042] The authenticity coefficient of the engineering test detection data of the current construction process is determined according to the number of the second target construction processes, the first ratio and the second ratio.

[0043] In the second aspect, an embodiment of the present invention provides a blockchain-based engineering test and detection data traceability system, which includes: a processor and a memory; wherein the memory is used to store computer programs that can be run on the processor; the processor is used to execute the program stored in the memory to implement the steps of the blockchain-based engineering test and detection data traceability method mentioned in the first aspect.

[0044] The present invention has the following beneficial effects: first, the engineering test and detection data of each construction process in the construction phase of the target engineering project is obtained; then, based on the engineering test and detection data of the current construction process and the engineering test and detection data of other construction processes, the construction correlation coefficient between the current construction process and the other construction processes is determined, and the construction correlation coefficient represents the degree of correlation between the current construction process and the other construction processes; then, based on the construction correlation coefficient between the current construction process and other construction processes, the authenticity coefficient of the engineering test and detection data of the current construction process is determined, and the authenticity coefficient represents the authenticity of the engineering test and detection data of the current construction process; finally, the authenticity coefficient is used to judge whether the engineering test and detection data of the construction process is real data. If it is real data, it is stored in the blockchain to trace the engineering test and detection data of the construction process. If it is not real data, the engineering test and detection data of the construction process is checked.

[0045] In this way, by analyzing the correlation between the current construction process and other construction processes within the target project, the authenticity of the engineering test and inspection data for the current construction process can be determined. Based on the authenticity of the engineering test and inspection data, it is then determined whether it is authentic. If it is authentic, it is stored in the blockchain. If it is not authentic, further inspection is performed. This prevents the storage of false data in the blockchain, ensures the authenticity of the data stored in the blockchain, and improves the accuracy of data traceability results. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0047] Figure 1 A flowchart of a blockchain-based engineering test data traceability method provided by one embodiment of the present invention;

[0048] Figure 2 A schematic diagram of the module composition of a blockchain-based engineering test data traceability system provided by one embodiment of the present invention;

[0049] Figure 3 A schematic structural diagram of a blockchain-based engineering test and detection data traceability system provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0050] To further illustrate the technical means and effects adopted by the present invention to achieve the predetermined purpose of the invention, the following, in conjunction with the accompanying drawings and preferred embodiments, describes in detail a blockchain-based engineering test data traceability method and system proposed by the present invention, including its specific implementation, structure, features, and effects. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable form.

[0051] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0052] The following describes in detail a blockchain-based engineering test data traceability method and system provided by the present invention in conjunction with the accompanying drawings.

[0053] Example 1:

[0054] See also Figure 1 , which shows a flowchart of a blockchain-based engineering test data traceability method provided by one embodiment of the present invention, including:

[0055] S101, obtaining engineering test and inspection data of each construction process during the construction phase of a target engineering project.

[0056] Specifically, a target project refers to a project developed for a certain engineering requirement, such as a residential building construction project, a public entertainment venue construction project, a wall construction project, and a nursing home construction project. The construction phase refers to the construction steps for completing the project. For example, for a wall construction project, the construction phase includes but is not limited to the preparatory work phase (such as surveying the ground flatness, wall structure, and soil quality testing at the construction site), the foundation construction phase (such as excavation, backfilling, and compaction based on the soil conditions at the construction site), the main construction phase (such as using selected materials for wall masonry work), and the finishing construction phase (such as wall surface treatment, such as plastering and polishing). Each construction phase includes multiple construction processes, and a construction process refers to the multiple construction steps for completing that construction phase. For example, the preparatory work phase in a wall construction project includes the construction process of surveying the ground flatness at the construction site, the construction process of surveying the wall structure at the construction site, and the construction process of testing the soil quality at the construction site. During each construction process, engineering test data is collected through sensors, measuring instruments, and other equipment. For example, in a wall construction project, engineering test data includes soil quality test data during the preparatory work phase, fill density data during the foundation construction phase, concrete strength data during the main construction phase, and plaster layer uniformity data during the finishing phase.

[0057] Furthermore, all engineering test and inspection data of each construction process under different construction conditions during the construction phase of the target engineering project are collected, and different construction conditions refer to different construction methods.

[0058] Furthermore, after obtaining the engineering test and inspection data for each construction process during the construction phase of the target project, it is input into the data layer of the traceability system. The data layer of the traceability system preprocesses the engineering test and inspection data. The preprocessing includes but is not limited to denoising, standardization, and normalization to ensure the feasibility and accuracy of subsequent analysis of engineering test and inspection data under different construction conditions. The data layer hashes the preprocessed data to generate a unique hash value. The hash value and timestamp information are packaged into a data block for further storage and management of the data block by the consensus layer and contract layer of the traceability system.

[0059] Furthermore, to improve the efficiency of subsequent data processing, a neural network model can be used to evaluate the data volume of the engineering test data. The evaluation result is a score between 1 and 10, which is regarded as the level parameter of the engineering test data. In the processing of subsequent embodiments, the level parameter of the engineering test data can be used for subsequent calculations, or the engineering test data can be used for calculations.

[0060] S102: Determine the construction correlation coefficient between the current construction process and other construction processes based on the engineering test and detection data of the current construction process and the engineering test and detection data of other construction processes.

[0061] The construction correlation coefficient represents the degree of correlation between the current construction process and the other construction processes.

[0062] Specifically, in the same target engineering project, there is a correlation between the engineering test and detection data generated by the construction processes of different construction stages. Therefore, the correlation between the engineering test and detection data generated by different construction processes can be used to verify the authenticity of the engineering test and detection data, thereby improving the accuracy of data traceability. Furthermore, in actual operations, certain construction processes in different construction stages may have the same construction direction. Taking wall construction as an example, the ground compaction process in the foundation construction stage and the masonry process in the main construction stage both directly affect the hardness of the final wall. These two stages have a high correlation because they jointly affect the same engineering quality indicator, namely the wall hardness. The quality of the engineering test and detection data of the early construction process will directly affect the data quality of the engineering test and detection data of the later construction process. Therefore, the construction correlation coefficient can be determined by the engineering test and detection data of the current construction process and the same type of construction process.

[0063] As an optional embodiment of the present invention, determining the construction correlation coefficient between the current construction process and other construction processes based on the engineering test and inspection data of the current construction process and the engineering test and inspection data of other construction processes includes: determining the quality degradation coefficient of the current construction process based on the engineering test and inspection data of the current construction process and the same type of construction processes, the quality degradation coefficient characterizing the data quality of the current construction process, the same type of construction process and the current construction process are construction processes of the same construction type in different construction stages; utilizing the quality degradation coefficient of the current construction process, the quality degradation coefficients of other construction processes and the first Pearson correlation coefficient between the current construction process and other construction processes to determine the construction correlation coefficient between the current construction process and other construction processes.

[0064] Specifically, the same type of construction process and the current construction process are construction processes of the same construction type in different construction stages. The construction process of the same construction type refers to the same engineering quality indicators corresponding to the construction process. For example, in the wall construction project, the ground compaction process in the foundation construction stage and the masonry process in the main construction stage both directly affect the hardness of the wall. The hardness of the wall is an engineering quality indicator. The ground compaction process and the masonry process jointly affect the same engineering quality indicator, namely the hardness of the wall. Therefore, the ground compaction process in the foundation construction stage and the masonry process in the main construction stage belong to the same construction type of construction process.

[0065] Furthermore, the first Pearson correlation coefficient represents the correlation between the current construction process and the other construction processes. When the first Pearson correlation coefficient is a positive number and the larger the value, the higher the positive correlation between the current construction process and the other construction processes.

[0066] As an optional embodiment of the present invention, when determining the quality degradation coefficient of the current construction process, the average detection data of the engineering test data of the same type of construction process can be obtained first; and then the ratio of the engineering test data of the current construction process to the average detection data is determined as the quality degradation coefficient of the current construction process.

[0067] Specifically, the quality degradation coefficient of the current construction process can be expressed as follows:

[0068]

[0069] In the above formula, h i Represents the engineering test data of the i-th construction process, H i represents the mean value (average test data) of the engineering test data of the same type of construction process of the i-th construction process, E i represents the quality degradation coefficient of the i-th construction process.

[0070] As an optional embodiment of the present invention, when determining the construction correlation coefficient between the current construction process and other construction processes, first obtain the engineering test and detection data of the current construction process under different construction conditions and the engineering test and detection data of other construction processes under different construction conditions; then, based on the engineering test and detection data of the current construction process under different construction conditions and the engineering test and detection data of other construction processes under different construction conditions, determine the first Pearson correlation coefficient between the current construction process and other construction processes; finally, calculate the absolute value of the difference between the quality degradation coefficient of the current construction process and the quality degradation coefficient of other construction processes; and determine the product of the absolute value and the first Pearson correlation coefficient as the construction correlation coefficient.

[0071] Specifically, the process for obtaining the first Pearson correlation coefficient is as follows: first, a set B of engineering test and detection data for the same type of construction process as the current construction process under different construction conditions, and a set A of engineering test and detection data for the current construction process under different construction conditions are obtained. Based on the engineering test and detection data in set A and the engineering test and detection data in set B, the first Pearson correlation coefficient between the current construction process and the other construction processes is calculated. It is worth noting that the specific calculation process of the Pearson correlation coefficient can refer to the existing technology and will not be repeated in this embodiment of the present invention.

[0072] Furthermore, the construction correlation coefficient can be calculated using the following formula:

[0073] K i，m =γ(A i , A m )×|E i -E m |;

[0074] In the above formula, K i，m represents the construction correlation coefficient between the i-th construction process and the m-th construction process, m represents the m-th construction process in the current target project except the i-th construction process, A i represents the set A of the i-th construction process, A m represents the set B of the mth construction process, γ(A i , A m ) represents the set A i With set A m The first Pearson correlation coefficient between i represents the quality degradation coefficient of the i-th construction process, E m Represents the quality degradation coefficient of the mth construction process.

[0075] Among them, when there is a strong correlation between the construction processes in different construction stages, the engineering test and inspection data of the construction process in the early construction stage will directly affect the engineering test and inspection data of the construction process in the later construction stage; and the degree of quality deterioration caused by the construction process in the early stage is far less than the degree of quality deterioration of the construction process in the later stage.

[0076] S103, determining the authenticity coefficient of the engineering test data of the current construction process based on the construction correlation coefficient between the current construction process and other construction processes.

[0077] Among them, the authenticity coefficient represents the authenticity of the engineering test data of the current construction process.

[0078] Specifically, the engineering test and inspection data involved in the construction process plays a vital role in the construction quality of each construction phase. However, due to differences in construction direction and project requirements, different construction processes contribute to varying degrees to the final quality of the target project. For example, the wall masonry construction process contributes significantly to the overall wall quality, as both its stability and sound insulation rely on the quality of the masonry. In contrast, the wall plastering construction process contributes relatively little to the wall quality. Therefore, the authenticity coefficient can be determined based on the contribution of the current construction process's engineering test and inspection data to the target project's quality, as well as the construction correlation coefficient.

[0079] Among them, as an optional embodiment of the present invention, determining the authenticity coefficient of the engineering test and detection data of the current construction process based on the construction correlation coefficient between the current construction process and other construction processes includes: determining the quality contribution factor of the current construction process based on the engineering test and detection data of the current construction process, the quality contribution factor representing the degree of influence of the engineering test and detection data of the current construction process on the engineering quality of the target engineering project; selecting a first target construction process with a construction correlation coefficient greater than a first threshold from other construction processes; determining the correlation interference coefficient between the current construction process and the first target construction process based on the engineering test and detection data of the intermediate construction processes between the current construction process and the first target construction process, the correlation interference coefficient representing the degree of influence of the intermediate construction process on the engineering quality of the target engineering project; determining the data correlation factor between the current construction process and the first target construction process based on the construction correlation coefficient and the correlation interference coefficient between the current construction process and the first target construction process, the data correlation factor representing the degree of data correlation between the engineering test and detection data of the current construction process and the first target construction process; and determining the authenticity coefficient of the engineering test and detection data of the current construction process and the first target construction process under different construction conditions.

[0080] Specifically, the first target construction process and the current construction process are strongly correlated. The first threshold can be determined based on actual conditions. For example, it can be set to 0.7. Construction processes with a construction correlation coefficient greater than 0.7 are considered strongly correlated, indicating a high degree of correlation between the two construction processes. Furthermore, between two strongly correlated construction processes, there may be multiple intermediate construction processes. These intermediate construction processes may affect the relationship between the originally strongly correlated construction processes. For example, between the ground compaction process in the foundation construction phase and the masonry process in the main construction phase, there may be intermediate construction processes such as waterproofing and structural reinforcement. The treatment quality of these intermediate construction processes may also affect the final quality indicator of the same project, such as wall hardness, thereby affecting the correlation between the two construction processes. Therefore, when considering the correlation between construction processes, the impact of intermediate construction processes must also be fully considered to ensure accurate evaluation and management of construction processes. Therefore, the authenticity of the engineering test data for the current construction process needs to be determined based on the degree of influence of the intermediate construction processes between the strongly correlated construction processes on the two strongly correlated construction processes.

[0081] As an optional embodiment of the present invention, when determining the quality contribution factor of the current construction process, the engineering test and detection data of the current construction process under different construction conditions are first fitted to obtain a first fitting curve, and the engineering quality indicators corresponding to the engineering test and detection data of the current construction process under different construction conditions are fitted to obtain a second fitting curve; then the variance of the data value of each data sampling point in the first fitting curve, the first curve slope at each data sampling point, and the second curve slope at each data sampling point in the second fitting curve are obtained; finally, the quality contribution factor of the current construction process is determined based on the variance, the first curve slope, and the second curve slope.

[0082] Specifically, the least squares method or polynomial fitting method can be used to fit the engineering test data of the current construction process under different construction conditions to obtain a first fitting curve f(x). Furthermore, the engineering quality indicators corresponding to the engineering test data of the current construction process under different construction conditions can be fitted to obtain a second fitting curve F(x). Engineering quality indicators refer to the quality indicators to be achieved by the construction process at each construction stage, such as fill density, concrete strength, and soil quality.

[0083] Furthermore, the quality contribution factor of the current construction process can be expressed as follows:

[0084]

[0085] In the above formula, G irepresents the quality contribution factor of the i-th construction process, i represents the i-th construction process in the current target project, S i represents the variance of the first fitting curve f(x) of the i-th construction process, K f(x) is the set of first curve slopes at each data sampling point in the first fitting curve f(x), K F(x) is a set of second curve slopes at each data sampling point in the second fitting curve F(x). Represents the set K f(x) With set K F(x) The +1 is to avoid the situation where the denominator of the fraction is zero. It is worth noting that the calculation of data fitting, variance and mean square error can be referred to the prior art, and the embodiments of the present invention will not be repeated here.

[0086] Furthermore, for the important construction processes in each construction stage of the target project, the engineering test and inspection data have a greater impact on the final engineering quality of the target project. By performing a differential analysis on the slope trend of each data point in the fitting curve f(x) of the engineering test and inspection data of the construction process and the slope trend of each data point in the fitting curve F(x) of the corresponding engineering quality index, the smaller the difference, the greater the impact of the engineering test and inspection data of the current construction process on the engineering quality, G i The larger the value is, the higher the contribution of the current construction process to the entire project.

[0087] As an optional embodiment of the present invention, when determining the correlation interference coefficient between the current construction process and the first target construction process, first obtain the engineering test and detection data of the intermediate construction process under different construction conditions and the engineering quality indicators corresponding to the engineering test and detection data of the intermediate construction process under different construction conditions; then, based on the engineering test and detection data of the intermediate construction process under different construction conditions and the engineering quality indicators corresponding to the engineering test and detection data of the intermediate construction process under different construction conditions, determine the second Pearson correlation coefficient between the current construction process and the first target construction process; finally, use the number of intermediate construction processes, the quality contribution factor of the intermediate construction process and the second Pearson correlation coefficient to determine the correlation interference coefficient between the current construction process and the first target construction process.

[0088] Specifically, the second Pearson correlation coefficient represents the correlation between the current construction process and the first target construction process. The process of calculating the second Pearson correlation coefficient is as follows: a set C of engineering test and inspection data for intermediate construction processes and similar construction processes under different construction conditions is obtained, and a set D of engineering quality indicators corresponding to the engineering test and inspection data for the intermediate construction processes and similar construction processes under different construction conditions is obtained, and then the Pearson correlation coefficient between set C and set D is calculated. The specific calculation process of the Pearson correlation coefficient can be referred to the prior art and will not be repeated in detail in the embodiments of the present invention.

[0089] Furthermore, the correlation annoyance coefficient between the two strongly correlated construction processes can be measured based on the engineering test data and corresponding engineering quality indicators of all intermediate construction processes between the current construction process and the first target construction process. Simultaneously, the quality contribution factor of the current construction process is introduced to correct the correlation annoyance coefficient, resulting in a more accurate correlation annoyance coefficient.

[0090] Furthermore, the correlation nuisance coefficient can be calculated using the following formula:

[0091]

[0092] In the above formula, N represents the number of intermediate construction processes between the current construction process and the first target construction process, n represents the nth intermediate construction process, C n represents the collection of engineering test data of the nth intermediate construction process and the same type of construction process under different construction conditions. D represents C n The set of engineering quality indicators corresponding to the engineering test data in the project, Y(C n , D) represents C n The second Pearson correlation coefficient of the set G and the set D, n represents the quality contribution factor of the nth intermediate construction process, and R represents the correlation annoyance coefficient between the current construction process and the first target construction process. The larger the value is, the greater the impact of the intermediate construction process on the correlation between the current construction process and the first target construction process.

[0093] As an optional embodiment of the present invention, determining the data correlation factor between the current construction process and the first target construction process based on the construction correlation coefficient and the related disturbance coefficient between the current construction process and the first target construction process includes: determining the superposition value of the related disturbance coefficient and the preset value; determining the ratio of the construction correlation coefficient to the superposition value as the data correlation factor between the current construction process and the first target construction process.

[0094] Specifically, the preset value can be determined according to actual conditions, and in the embodiment of the present invention, the value is 1.

[0095] Furthermore, the data-related factor can be expressed as follows:

[0096]

[0097] In the above formula, K represents the construction correlation coefficient between the current construction process and the first target construction process, R represents the correlation interference coefficient between the current construction process and the first target construction process, and U represents the data correlation factor of the engineering test data of the current construction process and the first target construction process. The larger the value is, the stronger the data correlation between the engineering test data of the current construction process and the first target construction process is.

[0098] As an optional embodiment of the present invention, determining the authenticity coefficient of the engineering test detection data of the current construction process using data correlation factors, the engineering test detection data of the current construction process and the first target construction process under different construction conditions includes: selecting a second target construction process with a data correlation factor greater than a second threshold from the first target construction process; determining a first ratio of the engineering test detection data of the current construction process to the engineering test detection data of the second target construction process; determining a second ratio of the first average value to the second average value, the first average value being the average value of the engineering test detection data of the construction process of the same type as the current construction process under different construction conditions, and the second average value being the average value of the engineering test detection data of the construction process of the same type as the second target construction process under different construction conditions; determining the authenticity coefficient of the engineering test detection data of the current construction process based on the number of second target construction processes, the first ratio, and the second ratio.

[0099] Specifically, the second threshold value can be determined based on actual conditions. In the embodiment of the present invention, the data correlation factor is first normalized using a norm function, and then the normalized data correlation factor is compared with the second threshold value. In the embodiment of the present invention, the second threshold value is set to 0.7. A second target construction process is selected from the first target construction process, and the normalized data correlation factor is greater than the second threshold value. The second target construction process has a strong correlation with the engineering test and detection data of the current construction process, that is, the engineering test and detection data of the second target construction process has a high degree of correlation with the engineering test and detection data of the current construction process.

[0100] Furthermore, after obtaining the second target construction process, the current construction process and all second target construction processes are sorted and connected according to construction progress to obtain several construction process curves with strong correlation. For each construction process curve with strong correlation, the changes in engineering test data for each construction process are consistent. Engineering test data for the same type of construction process under different construction conditions is obtained for each construction process curve, and the authenticity coefficient of the engineering test data for the current construction process is calculated based on this data.

[0101] Furthermore, the authenticity coefficient of the engineering test data of the current construction process can be expressed as follows:

[0102]

[0103] In the above formula, Z j represents the authenticity coefficient of the engineering test data of the j-th construction process, Q represents the set of construction processes other than the j-th construction process in the construction curve of the strongly correlated construction process (the second target construction process), q represents the q-th construction process in the Q set, and x j represents the engineering test data of the jth construction process, x q represents the engineering test data of the qth construction process, X j represents the mean (first average) of the engineering test data of the same type of construction process under different construction conditions for the jth construction process, X q It represents the mean (second average value) of the engineering test data of the same type of construction process under different construction conditions for the qth construction process.

[0104] Further, The smaller the difference, the greater the authenticity of the engineering test data of the current construction process; in addition, the engineering test data in this embodiment does not have a zero value.

[0105] S104, using the authenticity coefficient to determine whether the engineering test and detection data of the construction process is real data. If it is real data, it is stored in the blockchain to trace the engineering test and detection data of the construction process. If it is not real data, the engineering test and detection data of the construction process is checked.

[0106] Specifically, a third threshold can be set to treat engineering test data with a authenticity coefficient greater than the third threshold as true data, otherwise as false data. The third threshold can be determined based on actual conditions. In the embodiment of the present invention, the third threshold is set to 0.5.

[0107] Furthermore, if engineering test data is false, relevant personnel are promptly alerted so they can review the engineering test data for the construction process and re-enter the correct data. After data screening and correction, the traceability system conducts subsequent traceability management based on the actual engineering test data, ensuring the reliability and accuracy of the final traceability results.

[0108] The embodiment of the present invention determines the authenticity of the engineering test data for the current construction process by analyzing the correlation between the current construction process and other construction processes in the target project. Based on the authenticity of the engineering test data, it is then determined whether the engineering test data is authentic. If it is authentic, the engineering test data is stored in the blockchain. If it is not authentic, further inspection is performed. In this way, false data is prevented from being stored in the blockchain, the authenticity of the data stored in the blockchain is guaranteed, and the accuracy of the data traceability results is improved.

[0109] Example 2:

[0110] Corresponding to the blockchain-based engineering test data traceability method provided in the above embodiment, based on the same technical concept, the embodiment of the present invention also provides a blockchain-based engineering test data traceability system. Figure 2 Schematic diagram of the module composition of the blockchain-based engineering test data traceability system provided in an embodiment of the present invention, which is used to perform Figure 1 The engineering test data traceability method based on blockchain described in Figure 2 As shown, the blockchain-based engineering test and detection data traceability system 200 includes: an acquisition module 201, which is used to obtain the engineering test and detection data of each construction process in the construction phase of the target engineering project; a determination module 202, which is used to determine the construction correlation coefficient between the current construction process and the other construction processes based on the engineering test and detection data of the current construction process and the engineering test and detection data of other construction processes, and the construction correlation coefficient represents the degree of correlation between the current construction process and other construction processes; the determination module 202 is also used to determine the authenticity coefficient of the engineering test and detection data of the current construction process based on the construction correlation coefficient between the current construction process and other construction processes, and the authenticity coefficient represents the authenticity of the engineering test and detection data of the current construction process; the traceability module 203 is used to use the authenticity coefficient to determine whether the engineering test and detection data of the construction process are real data. If they are real data, they are stored in the blockchain to trace the engineering test and detection data of the construction process. If they are not real data, the engineering test and detection data of the construction process are checked.

[0111] The embodiment of the present invention determines the authenticity of the engineering test data for the current construction process by analyzing the correlation between the current construction process and other construction processes in the target project. Based on the authenticity of the engineering test data, it is then determined whether the engineering test data is authentic. If it is authentic, the engineering test data is stored in the blockchain. If it is not authentic, further inspection is performed. In this way, false data is prevented from being stored in the blockchain, the authenticity of the data stored in the blockchain is guaranteed, and the accuracy of the data traceability results is improved.

[0112] Optionally, the determination module 202 is also used to determine the quality degradation coefficient of the current construction process based on the engineering test data of the current construction process and the same type of construction process, where the quality degradation coefficient represents the data quality of the current construction process, and the same type of construction process and the current construction process are construction processes of the same construction type in different construction stages; and to determine the construction correlation coefficient between the current construction process and the other construction processes by utilizing the quality degradation coefficient of the current construction process, the quality degradation coefficient of the other construction processes, and the first Pearson correlation coefficient between the current construction process and the other construction processes.

[0113] Optionally, the determination module 202 is further used to obtain average test data of engineering test data of the same type of construction processes; and determine the ratio of the engineering test data of the current construction process to the average test data as the quality degradation coefficient of the current construction process.

[0114] Optionally, the determination module 202 is also used to obtain the engineering test and inspection data of the current construction process under different construction conditions and the engineering test and inspection data of other construction processes under different construction conditions; determine the first Pearson correlation coefficient between the current construction process and the other construction processes based on the engineering test and inspection data of the current construction process under different construction conditions and the engineering test and inspection data of other construction processes under different construction conditions; calculate the absolute value of the difference between the quality degradation coefficient of the current construction process and the quality degradation coefficient of other construction processes; and determine the product of the absolute value and the first Pearson correlation coefficient as the construction correlation coefficient.

[0115] Optionally, the determination module 202 is further used to determine the quality contribution factor of the current construction process based on the engineering test and detection data of the current construction process, the quality contribution factor characterizes the degree of influence of the engineering test and detection data of the current construction process on the engineering quality of the target engineering project; select a first target construction process with a construction correlation coefficient greater than a first threshold from other construction processes; determine the correlation interference coefficient between the current construction process and the first target construction process based on the engineering test and detection data of the intermediate construction process between the current construction process and the first target construction process, the correlation interference coefficient characterizes the degree of influence of the intermediate construction process on the engineering quality of the target engineering project; determine the data correlation factor between the current construction process and the first target construction process based on the construction correlation coefficient and the correlation interference coefficient between the current construction process and the first target construction process, the data correlation factor characterizes the degree of data correlation between the engineering test and detection data of the current construction process and the first target construction process; and determine the authenticity coefficient of the engineering test and detection data of the current construction process and the first target construction process under different construction conditions using the data correlation factor and the engineering test and detection data of the current construction process and the first target construction process.

[0116] Optionally, the determination module 202 is also used to fit the engineering test and detection data of the current construction process under different construction conditions to obtain a first fitting curve, and to fit the engineering quality indicators corresponding to the engineering test and detection data of the current construction process under different construction conditions to obtain a second fitting curve; obtain the variance of the data value of each data sampling point in the first fitting curve, the first curve slope at each data sampling point, and the second curve slope at each data sampling point in the second fitting curve; determine the quality contribution factor of the current construction process based on the variance, the first curve slope, and the second curve slope.

[0117] Optionally, the determination module 202 is also used to obtain the engineering test and inspection data of the intermediate construction process under different construction conditions and the engineering quality indicators corresponding to the engineering test and inspection data of the intermediate construction process under different construction conditions; determine the second Pearson correlation coefficient between the current construction process and the first target construction process based on the engineering test and inspection data of the intermediate construction process under different construction conditions and the engineering quality indicators corresponding to the engineering test and inspection data of the intermediate construction process under different construction conditions; and use the number of intermediate construction processes, the quality contribution factor of the intermediate construction process and the second Pearson correlation coefficient to determine the correlation annoyance coefficient between the current construction process and the first target construction process.

[0118] Optionally, the determination module 202 is further configured to determine a superposition value of the relevant nuisance coefficient and a preset value; and determine a ratio of the construction correlation coefficient to the superposition value as a data correlation factor between the current construction process and the first target construction process.

[0119] Optionally, the determination module 202 is also used to select a second target construction process whose data correlation factor is greater than a second threshold from the first target construction process; determine a first ratio of the engineering test and detection data of the current construction process to the engineering test and detection data of the second target construction process; determine a second ratio of the first average value to the second average value, the first average value being the average value of the engineering test and detection data of the construction process of the same type as the current construction process under different construction conditions, and the second average value being the average value of the engineering test and detection data of the construction process of the same type as the second target construction process under different construction conditions; determine the authenticity coefficient of the engineering test and detection data of the current construction process based on the number of second target construction processes, the first ratio, and the second ratio.

[0120] The blockchain-based engineering test and detection data traceability system provided by the embodiment of the present invention can realize the various processes in the embodiments corresponding to the above-mentioned blockchain-based engineering test and detection data traceability method, and has the same or similar beneficial effects. To avoid repetition, it will not be repeated here.

[0121] Example 3:

[0122] Corresponding to the blockchain-based engineering test and detection data traceability method provided in the above embodiment, based on the same technical concept, an embodiment of the present invention also provides a blockchain-based engineering test and detection data traceability system, which is used to execute the blockchain-based engineering test and detection data traceability method. Figure 3 A schematic diagram of a blockchain-based engineering test data traceability system for implementing various embodiments of the present invention is shown below. Figure 3 The blockchain-based engineering test data traceability system may have relatively large differences due to different configurations or performances, and may include one or more processors 301 and memory 302. The memory 302 is used to store computer programs that can be run on the processor 301. The processor 301 is used to execute the program stored in the memory 302 to achieve the above Figure 1 The various steps in the method embodiment are as follows. Memory 302 may be either transient or persistent storage. The application stored in memory 302 may include one or more modules (not shown), each of which may include a series of computer-executable instructions for a blockchain-based engineering test data traceability system.

[0123] Furthermore, the processor 301 can be configured to communicate with the memory 302 and execute a series of computer-executable instructions in the memory 302 on the blockchain-based engineering test and detection data traceability system. The blockchain-based engineering test and detection data traceability system can also include one or more power supplies 303, one or more wired or wireless network interfaces 304, one or more input and output interfaces 305, and one or more keyboards 306.

[0124] Specifically in this embodiment, the blockchain-based engineering test data traceability system includes a processor, a communication interface, a memory, and a communication bus; wherein the processor, the communication interface, and the memory communicate with each other through the bus; the memory is used to store computer programs; the processor is used to execute the programs stored in the memory to achieve the above Figure 1 The various steps in the method embodiment have the beneficial effects of the above method embodiments. To avoid repetition, the embodiments of the present invention will not be described again here.

[0125] It should be noted that the blockchain-based engineering test and detection data traceability system provided by the embodiment of the present invention and the blockchain-based engineering test and detection data traceability method provided by the embodiment of the present invention are based on the same inventive concept. Therefore, the specific implementation of this embodiment can refer to the implementation of the aforementioned blockchain-based engineering test and detection data traceability method, and has the same or similar beneficial effects, and the repetitions will not be repeated.

[0126] It should be noted that the order in which the embodiments of the present invention are described above is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0127] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

Claims

1. A blockchain-based engineering test data traceability method, characterized in that: The blockchain-based engineering test data traceability method includes: Obtain engineering test and inspection data for each construction process during the construction phase of the target project; Determining, based on the engineering test and inspection data of the current construction process and the engineering test and inspection data of other construction processes, a construction correlation coefficient between the current construction process and the other construction processes, wherein the construction correlation coefficient represents the degree of correlation between the current construction process and the other construction processes; Determining, based on the construction correlation coefficient between the current construction process and the other construction processes, a authenticity coefficient of the engineering test data of the current construction process, wherein the authenticity coefficient represents the authenticity of the engineering test data of the current construction process; The authenticity coefficient is used to determine whether the engineering test and detection data of the construction process is real data. If it is real data, it is stored in the blockchain to trace the engineering test and detection data of the construction process. If it is not real data, the engineering test and detection data of the construction process is checked.

2. The blockchain-based engineering test data traceability method according to claim 1 is characterized in that: Determining the construction correlation coefficient between the current construction process and the other construction processes based on the engineering test and detection data of the current construction process and the engineering test and detection data of the other construction processes includes: Determining a quality degradation coefficient of the current construction process based on engineering test data of the current construction process and similar construction processes, wherein the quality degradation coefficient represents the data quality of the current construction process, wherein the similar construction process and the current construction process are construction processes of the same construction type but at different construction stages; The construction correlation coefficient between the current construction process and the other construction processes is determined by using the quality degradation coefficient of the current construction process, the quality degradation coefficient of the other construction processes, and the first Pearson correlation coefficient between the current construction process and the other construction processes.

3. The blockchain-based engineering test data traceability method according to claim 2 is characterized in that: Determining the quality degradation coefficient of the current construction process based on engineering test data of the current construction process and similar construction processes includes: Obtaining average test data of engineering test data of the same type of construction process; The ratio of the engineering test detection data of the current construction process to the average detection data is determined as the quality degradation coefficient of the current construction process.

4. The blockchain-based engineering test data traceability method according to claim 2 is characterized in that: Determining the construction correlation coefficient between the current construction process and the other construction processes by using the quality degradation coefficient of the current construction process, the quality degradation coefficient of the other construction processes, and the first Pearson correlation coefficient between the current construction process and the other construction processes includes: Acquiring engineering test and inspection data of the current construction process under different construction conditions and engineering test and inspection data of other construction processes under different construction conditions; Determining a first Pearson correlation coefficient between the current construction process and the other construction processes based on the engineering test data of the current construction process under different construction conditions and the engineering test data of the other construction processes under different construction conditions; Calculating the absolute value of the difference between the quality degradation coefficient of the current construction process and the quality degradation coefficient of the other construction processes; The product of the absolute value and the first Pearson correlation coefficient is determined as the construction correlation coefficient.

5. The blockchain-based engineering test data traceability method according to any one of claims 1 to 4, characterized in that: Determining the authenticity coefficient of the engineering test data of the current construction process based on the construction correlation coefficient between the current construction process and the other construction processes includes: Determining a quality contribution factor of the current construction process based on the engineering test and detection data of the current construction process, wherein the quality contribution factor represents the degree of influence of the engineering test and detection data of the current construction process on the engineering quality of the target engineering project; Selecting a first target construction process having a construction correlation coefficient greater than a first threshold from the other construction processes; Determine, based on engineering test data of an intermediate construction process between the current construction process and the first target construction process, a quality contribution factor of the intermediate construction process, and an engineering quality indicator corresponding to the intermediate construction process, a correlation annoyance coefficient between the current construction process and the first target construction process, wherein the correlation annoyance coefficient represents the degree of influence of the intermediate construction process on the engineering quality of the target engineering project; determining a data correlation factor between the current construction process and the first target construction process based on a construction correlation coefficient and a correlation nuisance coefficient between the current construction process and the first target construction process, wherein the data correlation factor represents a degree of data correlation between engineering test data of the current construction process and the first target construction process; The authenticity coefficient of the engineering test data of the current construction process is determined by using the data correlation factor, the engineering test data of the current construction process and the first target construction process under different construction conditions.

6. The blockchain-based engineering test data traceability method according to claim 5 is characterized in that: Determining the quality contribution factor of the current construction process based on the engineering test data of the current construction process includes: Fitting the engineering test data of the current construction process under different construction conditions to obtain a first fitting curve, and fitting the engineering quality indicators corresponding to the engineering test data of the current construction process under different construction conditions to obtain a second fitting curve; Obtaining the variance of the data value of each data sampling point in the first fitting curve, the first curve slope at each data sampling point, and the second curve slope at each data sampling point in the second fitting curve; A quality contribution factor of the current construction process is determined according to the variance, the first curve slope, and the second curve slope.

7. The blockchain-based engineering test data traceability method according to claim 5 is characterized in that: Determining the correlation annoyance coefficient between the current construction process and the first target construction process based on engineering test data of an intermediate construction process between the current construction process and the first target construction process, a quality contribution factor of the intermediate construction process, and an engineering quality indicator corresponding to the intermediate construction process includes: Obtaining engineering test and inspection data of the intermediate construction process under different construction conditions and engineering quality indicators corresponding to the engineering test and inspection data of the intermediate construction process under different construction conditions; determining a second Pearson correlation coefficient between the current construction process and the first target construction process based on the engineering test data of the intermediate construction process under different construction conditions and the engineering quality indicators corresponding to the engineering test data of the intermediate construction process under different construction conditions; The correlation annoyance coefficient between the current construction process and the first target construction process is determined by using the number of the intermediate construction processes, the quality contribution factor of the intermediate construction processes, and the second Pearson correlation coefficient.

8. The blockchain-based engineering test data traceability method according to claim 5 is characterized in that: Determining the data correlation factor between the current construction process and the first target construction process based on the construction correlation coefficient and the correlation nuisance coefficient between the current construction process and the first target construction process includes: Determining a superposition value of the relevant nuisance coefficient and a preset value; The ratio of the construction correlation coefficient to the superposition value is determined as a data correlation factor between the current construction process and the first target construction process.

9. The blockchain-based engineering test data traceability method according to claim 5 is characterized in that: Determining the authenticity coefficient of the engineering test data of the current construction process by using the data correlation factor, the engineering test data of the current construction process and the first target construction process under different construction conditions includes: Selecting a second target construction process from the first target construction process, wherein the data correlation factor is greater than a second threshold; Determining a first ratio of the engineering test data of the current construction process to the engineering test data of the second target construction process; Determine a second ratio of a first average value to a second average value, where the first average value is an average value of engineering test data of a construction process of the same type as the current construction process under different construction conditions, and the second average value is an average value of engineering test data of a construction process of the same type as the second target construction process under different construction conditions; The authenticity coefficient of the engineering test detection data of the current construction process is determined according to the number of the second target construction processes, the first ratio and the second ratio.

10. A blockchain-based engineering test data traceability system, characterized by: The blockchain-based engineering test and detection data traceability system includes: a processor and a memory; wherein the memory is used to store computer programs that can be run on the processor; the processor is used to execute the program stored in the memory to implement the steps of the blockchain-based engineering test and detection data traceability method as described in any one of claims 1-9.

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