Blockchain-based consensus method for engineering test detection data

Abstract

The present application relates to the technical field of data consensus, in particular to a kind of engineering test detection data consensus method based on blockchain.The method comprises: obtaining the rebound value of different detection points of the road panel to be detected, the carbonation depth data of core drilling and the crystallinity of calcium carbonate;Carbonation intensity index and reliability of carbonation condition of detection point are analyzed and determined;Then, according to the carbonation intensity index and reliability of different detection points, the rebound value correction coefficient is determined, the rebound value correction coefficient is combined with the rebound value of the current detection point, and the carbonation intensity index of all detection points is determined to determine the corrected rebound value;The consensus test is carried out on the modified rebound value and reliability of the detection point, the data that passes the consensus is packaged as a structured data block and stored as a chain data.The present application can effectively solve the problem that the carbonation process of pavement concrete will have a virtual high impact on the rebound value of concrete strength data, and improve the authenticity and reliability of the chain data.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data consensus, in particular to an engineering test detection data consensus method based on a blockchain. BACKGROUND

[0002] With the large-scale application of engineering test detection data in quality control, safety evaluation and intelligent decision-making, its data consensus mechanism needs to be upgraded from "formal compliance" to "full-link trust". The full life cycle management of engineering test detection data based on a blockchain needs to go through the following key stages: data collection and packaging, data preprocessing and encryption, consensus verification and on-chain, and on-chain record and traceability. Data consensus generally refers to the process of reaching an agreement on the value or state of certain data among multiple nodes in a distributed system. Concrete is a commonly used material in highway construction, and high compressive strength concrete can effectively resist the damage of vehicle load and natural environmental factors, prolonging the service life of the road. Therefore, applying a blockchain to the compressive strength data of concrete in highway infrastructure can ensure the authority of on-chain data through the data consensus stage in the blockchain.

[0003] In the prior art, data consensus based on a blockchain is cross-verification of on-chain data from multiple nodes before on-chain, solving the problem of data sharing in cross-department collaboration. However, in the measurement process of concrete strength data, the carbonation process of pavement concrete will have a virtual high impact on the rebound value of concrete strength data, and the carbonation of the pavement may deviate from the abnormal situation reflecting the real concrete strength data, thereby reducing the authenticity and credibility of the on-chain data for data consensus. SUMMARY

[0004] To solve the technical problem that the carbonation process of pavement concrete will have a virtual high impact on the rebound value of concrete strength data, and the carbonation of the pavement may deviate from the abnormal situation reflecting the real concrete strength data, thereby reducing the authenticity and effectiveness of the on-chain data and affecting the credibility of related data, the present application provides an engineering test detection data consensus method based on a blockchain, and the technical solution adopted is as follows:

[0005] The present application provides an engineering test detection data consensus method based on a blockchain, which comprises the following steps:

[0006] Obtain the rebound value of different detection points of the road panel to be detected, determine the carbonation depth data of the core sample when it is completely carbonated based on the phenolphthalein method, and obtain the crystallinity of calcium carbonate in the core sample based on the XRD method;

[0007] determine the equivalent depth data of the partially carbonated region according to the comparison of the crystallinity of calcium carbonate in the partially carbonated and fully carbonated concrete and the carbonation depth data; determine the carbonation intensity index of the carbonation condition of the current detection point in combination with the equivalent depth data; determine the reliability of the carbonation intensity index of the current detection point according to the difference between the distance of the current detection point and other detection points and the carbonation intensity index and the comparison of the carbonation intensity index and the drilling depth of the current detection point in different drilling times;

[0008] determine the rebound value correction coefficient according to the difference between the rebound value of the current detection point and other detection points and the carbonation intensity index, and determine the corrected rebound value in combination with the rebound value of the current detection point, the rebound value correction coefficient and the carbonation intensity index of all detection points;

[0009] perform consensus verification on the corrected rebound value and the reliability of the detection point, package the consensus qualified data as a structured data block, and store the structured data block as chain data.

[0010] Further, the determination of the equivalent depth data of the partially carbonated region according to the comparison of the crystallinity of calcium carbonate in the partially carbonated and fully carbonated concrete and the carbonation depth data comprises:

[0011] determine the degree of partial carbonation in combination with the comparison of the crystallinity of calcium carbonate in the fully carbonated and partially carbonated concrete;

[0012] take the product value of the degree of partial carbonation and the carbonation depth data as the reference depth data;

[0013] calculate the product value of the preset carbonation conversion coefficient adjusted based on the type of admixture and the reference depth data as a depth conversion value, and take the sum value of the depth conversion value and the carbonation depth data of the fully carbonated concrete as the equivalent depth data.

[0014] Further, the determination of the degree of partial carbonation in combination with the comparison of the crystallinity of calcium carbonate in the fully carbonated and partially carbonated concrete comprises:

[0015] calculate the ratio of the crystallinity of calcium carbonate in the partially carbonated concrete to the crystallinity of calcium carbonate in the fully carbonated concrete as the degree of partial carbonation.

[0016] Further, the carbonation intensity index is divided into 1-10 levels, and the higher the level, the greater the value of the equivalent depth data.

[0017] Further, the determination of the reliability of the carbonation intensity index of the current detection point according to the difference between the distance of the current detection point and other detection points and the carbonation intensity index and the comparison of the carbonation intensity index and the drilling depth of the current detection point in different drilling times comprises:

[0018] According to the comparison of the carbonization intensity index and the drilling depth of the current detection point in different drilling holes, a depth change trust factor is determined;

[0019] The absolute value of the difference between the carbonization intensity index of the current detection point and other detection points is calculated as an intensity difference;

[0020] In combination with the intensity difference and the distance between the current detection point and other detection points, a point position trust factor is determined;

[0021] The product value of the point position trust factor and the depth change trust factor is calculated and normalized as the reliability.

[0022] Further, the depth change trust factor is determined according to the comparison of the carbonization intensity index and the drilling depth of the current detection point in different drilling holes, comprising:

[0023] A two-dimensional coordinate system is constructed with the drilling depth as the horizontal coordinate and the carbonization intensity index as the vertical coordinate, and the coordinate points of different drilling holes in the two-dimensional coordinate system are determined;

[0024] The distance sum value of all coordinate points and the fitting straight line is calculated, and the reciprocal of the distance sum value is normalized as the first trust coefficient;

[0025] The reciprocal of the slope of the fitting straight line is normalized as the second trust coefficient;

[0026] The product value of the first trust coefficient and the second trust coefficient is calculated to obtain the depth change trust factor.

[0027] Further, the point position trust factor is determined in combination with the intensity difference and the distance between the current detection point and other detection points, comprising:

[0028] The product of the intensity difference and the distance between the current detection point and any other detection point is calculated, and the reciprocal of the product value is normalized as the point position trust factor.

[0029] Further, the rebound value correction coefficient is determined according to the difference between the rebound value and the carbonization intensity index of the current detection point and other detection points, comprising:

[0030] The rebound value and the carbonization intensity index ratio of the same detection point is calculated as a carbonization analysis coefficient;

[0031] The median of the rebound values of all detection points is taken as the median rebound value, and the median of the carbonization analysis coefficients of all detection points is taken as the median analysis coefficient;

[0032] The absolute value of the difference between the carbonization analysis coefficient of the current detection point and the median analysis coefficient is calculated, and the reciprocal of the absolute value is normalized as the authenticity;

[0033] The difference between the rebound value at the current detection point and the median rebound value is used as the rebound adjustment value;

[0034] Calculate the product of the rebound adjustment value and the accuracy, and use it as the rebound value correction coefficient.

[0035] Furthermore, the corrected rebound value is determined by combining the rebound value of the current detection point, the rebound value correction coefficient, and the carbonization intensity index of all detection points. The corresponding calculation formula is as follows:

[0036] In the formula, H represents the corrected rebound value, H0 represents the rebound value at the current detection point, h represents the rebound value correction coefficient at the current detection point, and D represents the carbonization intensity index at the current detection point. max This represents the maximum value of the carbonization intensity index at all detection points.

[0037] Furthermore, the consensus verification of the corrected rebound value and confidence level of the detection point includes:

[0038] Different detection units are assigned preset consensus weights. Based on the consensus algorithm, the detection points that pass the consensus are analyzed and the corrected rebound value and confidence level corresponding to the detection points that pass the consensus are used as the data that passes the consensus.

[0039] The present invention has the following beneficial effects:

[0040] In this embodiment of the invention, before uploading concrete strength data from each testing point to the blockchain, the carbonation strength index of the testing point is determined by specifically analyzing the crystallinity and carbonation depth data of calcium carbonate, as well as the reliability of the corresponding carbonation analysis. This effectively analyzes the impact of the carbonation process of pavement concrete on the artificially high rebound value of concrete strength data, and obtains the actual carbonation strength of the testing point. Subsequently, by combining the consistency of the concrete carbonation process among all testing points on the same pavement slab to be tested, abnormal situations where the measurement results deviate from reflecting the true concrete rebound value are eliminated. The artificially high rebound value deviation caused by carbonation is automatically identified and corrected, resulting in a more reliable and accurate corrected rebound value. This achieves cross-validation of the corrected rebound value, effectively solving the problem of the artificially high impact of the carbonation process of pavement concrete on the rebound value of concrete strength data, and improving the authenticity and reliability of data consensus for uploading data to the blockchain. Attached Figure Description

[0041] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0042] Figure 1 A blockchain-based engineering test detection data consensus method flowchart provided by an embodiment of the present application;

[0043] Figure 2 A drilling scene schematic diagram provided by an embodiment of the present application;

[0044] Figure 3 A core sample schematic diagram provided by an embodiment of the present application;

[0045] Figure 4 A node permission weight distribution schematic diagram provided by an embodiment of the present application. DETAILED DESCRIPTION

[0046] In order to further illustrate the technical means and effects taken by the present application to achieve the predetermined purpose, the following describes the specific implementation, structure, features and effects of the blockchain-based engineering test detection data consensus method according to the present application in combination with the preferred embodiments and the drawings. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0047] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs.

[0048] The specific scheme of the blockchain-based engineering test detection data consensus method provided by the present application is described in detail below in combination with the drawings.

[0049] Please refer to Figure 1 which shows a blockchain-based engineering test detection data consensus method flowchart provided by an embodiment of the present application. The method comprises:

[0050] S101: Obtain the rebound value of different detection points of the road panel to be detected, determine the carbonization depth data of the core sample when the core sample is completely carbonized based on the phenolphthalein method, and obtain the crystallinity of calcium carbonate in the core sample based on the XRD method.

[0051] In the stage of highway pavement or bridge structure, the compressive strength of concrete needs to be detected. For a road panel to be detected, the rebound method + on-site coring method are used for detection, and a four-level collaborative detection system including a supervision unit, a third-party detection institution, a construction party and a quality inspection party needs to be established. Each detection unit node selects a plurality of detection points on the road panel to be detected, and the compressive strength of the concrete at the detection points is measured according to the following method.

[0052] Rebound method: for a certain to be detected pavement slab, at least 10 detection points are arranged, the distance between the detection points is less than 2 m, a digital rebound hammer is used, 16 times of rebound are performed on each detection point, 3 maximum values and 3 minimum values are removed, and the average value of all the remaining data is taken as the rebound value of the detection point.

[0053] Field coring method: the coring position is selected, the coring device is used, intelligent drilling is performed, and the core sample is processed to obtain a standard test piece, and multidimensional detection is performed, refer to Figure 2 and Figure 3 , Figure 2 a drilling scene schematic diagram provided by an embodiment of the present application, Figure 3 a core sample schematic diagram provided by an embodiment of the present application. Since complete carbonization is controllable, it can be used as a standard sample, the carbonization depth data of the core sample when the core sample is completely carbonized is determined based on the phenolphthalein method, and the crystallinity of calcium carbonate in the core sample is obtained based on the XRD method.

[0054] As a kind of traffic facilities, highway is exposed to natural environment for a long time, is influenced by vehicle exhaust and carbon dioxide in atmosphere, and carbonization risk is extremely high. Carbonization is the process that concrete surface and carbon dioxide in external environment occur chemical reaction to generate calcium carbonate, and calcium carbonate (CaCO3) film covers the pore of concrete surface, improves surface hardness and compactness, thereby rebound value is improved. However, the increase of this hardness does not mean that the actual strength of concrete is improved, but the change of surface hardness leads to the increase of rebound value. And the increase of carbonization depth will lead to the increase of concrete surface hardness, thereby the rebound value data is increased.

[0055] To solve the problem that carbonization intensity will affect the authenticity of rebound value data, therefore, the fresh cut surface of the core sample is detected by using the phenolphthalein method, the phenolphthalein detection carbonization intensity data of the core sample at this time is obtained, and the carbonization depth of the complete carbonization area is represented. However, when the phenolphthalein method is used to detect carbonization intensity, the mix proportion of the concrete in the core sample will affect the detection result of the phenolphthalein, when admixture (such as fly ash) or release agent exists, the neutralization of the concrete surface will be caused, the phenolphthalein does not show color, but the carbonization reaction does not actually occur, which leads to the misjudgment of carbonization depth, and further incorrect correction of rebound value, thereby affecting the evaluation of concrete compressive strength.

[0056] Therefore, when the rebound value of the on-site core sample verification is carried out at each node unit, XRD (X-ray diffraction) analysis is carried out on the obtained core sample to identify and distinguish the carbonization product and the influence of the admixture, and the crystallinity of calcium carbonate is obtained. XRD identifies the carbonization product through characteristic peaks to avoid false positive results of the phenolphthalein method, but XRD cannot directly measure the depth of carbonization, so the contribution amount of the part not completely carbonized is quantified according to the XRD detection result, the depth of complete carbonization is measured by the phenolphthalein method, and finally the carbonization depth data is obtained. The accurate and effective rebound value is obtained, so that the compressive strength of the concrete is effectively consensus before being chained.

[0057] Since calcium carbonate is one of the main products of carbonation of concrete, powder samples are selected from the completely carbonated region and the partially carbonated region, and the crystallinity of calcium carbonate is obtained according to the identification of the characteristic peaks of various components.

[0058] S102: According to the comparison of the crystallinity of calcium carbonate in the partially carbonated and completely carbonated concrete and the carbonation depth data, the equivalent depth data of the partially carbonated region is determined; the carbonation intensity index of the carbonation condition of the current detection point is determined in combination with the equivalent depth data; and the reliability of the carbonation intensity index of the current detection point is determined according to the distance between the current detection point and other detection points and the difference of the carbonation intensity index, and the comparison of the carbonation intensity index and the drilling depth in different drilling holes.

[0059] The crystallinity of calcium carbonate can reflect the degree of carbonation to some extent, so the carbonation degree analysis can be carried out based on the comparison of the crystallinity of calcium carbonate in the partially carbonated and completely carbonated concrete, and the carbonation depth analysis of the partially carbonated region is realized in combination with the carbonation depth data under complete carbonation, and the equivalent depth data is obtained.

[0060] Further, in some embodiments of the present application, the equivalent depth data of the partially carbonated region is determined according to the comparison of the crystallinity of calcium carbonate in the partially carbonated and completely carbonated concrete and the carbonation depth data, which comprises: determining the degree of partial carbonation in combination with the comparison of the crystallinity of calcium carbonate in the completely carbonated and partially carbonated concrete; taking the product value of the degree of partial carbonation and the carbonation depth data as the reference depth data; calculating the product value of the preset carbonation conversion coefficient adjusted based on the type of admixture and the reference depth data as the depth conversion value; and taking the sum value of the depth conversion value and the carbonation depth data of the completely carbonated carbonation as the equivalent depth data.

[0061] It can be understood that the crystallinity of calcium carbonate in the completely carbonated and partially carbonated concrete basically presents a linear change, so linear analysis can be directly carried out to determine the degree of partial carbonation.

[0062] Further, in some embodiments of the present application, in combination with the comparison of the crystallinity of calcium carbonate in complete carbonation and partial carbonation, the degree of partial carbonation is determined by calculating the ratio of the crystallinity of calcium carbonate in partial carbonation to the crystallinity of calcium carbonate in complete carbonation as the degree of partial carbonation.

[0063] That is, the ratio of the crystallinity is directly taken as the degree of partial carbonation, so as to analyze the area of incomplete carbonation. The product value of the degree of partial carbonation and the reference depth data is taken as the reference depth data, which represents the carbonation degree of the area of partial carbonation after the carbonation analysis.

[0064] Due to the presence of admixtures (such as fly ash) or release agents, the surface of the concrete is neutralized, and phenolphthalein does not develop color, but the carbonation reaction does not actually occur, resulting in misjudgment of the carbonation depth. Therefore, the preset carbonation conversion coefficient adjusted according to the type of admixture needs to be combined for specific analysis. The preset carbonation conversion coefficient adjusted according to the type of admixture is a parameter value preset according to the type of admixture, and specifically, it can be 0.75.

[0065] The product value of the preset carbonation conversion coefficient adjusted according to the type of admixture and the reference depth data is taken as the depth conversion value, and the sum of the depth conversion value and the carbonation depth data of complete carbonation is taken as the equivalent depth data. Thus, the equivalent depth data of the core sample under partial carbonation is obtained, that is, the theoretical carbonation depth of partial carbonation is obtained by analyzing the components as a standard sample through complete carbonation. Thus, the rebound value is analyzed in combination with the carbonation depth.

[0066] Thus, the equivalent depth data of the core sample is obtained as the actual carbonation depth, and the carbonation intensity index of the current detection point is determined according to the equivalent depth data, in combination with the actual concrete admixture composition and the specification, which can reflect the degree of virtual high rebound value of the current detection pavement slab due to the carbonation reaction of concrete.

[0067] When the carbonation depth is deeper, it may be accompanied by the expansion of internal cracks or the stagnation of hydration reaction, which further affects the decrease of the compressive strength of concrete. At this time, the degree of virtual high rebound value will be greater, and based on the experience of the influence of carbonation depth on rebound value, when the carbonation depth is within a certain range, there is a specific linear relationship in the correction of rebound value. When the carbonation depth is large enough, the decisive factor of the carbonation depth on the rebound value is very large, and the maximum value needs to be processed according to the specification.

[0068] In the embodiment of the present application, the carbonation intensity index is set to 1-10. When the carbonation depth data is within the range of linear relationship, the carbonation intensity index of the current detection point is determined based on the measured possible carbonation depth data in this range, that is, the higher the level of the carbonation intensity index, the greater the value of the equivalent depth data. It can be linearly mapped to the value range of [1, 10], and the level is determined by rounding, to obtain the carbonation intensity index.

[0069] Further, in some embodiments of the present application, the reliability of the carbonation intensity index of the current detection point is determined according to the distance between the current detection point and other detection points and the difference in carbonation intensity index, and the comparison of the carbonation intensity index and the drilling depth of the current detection point in different drilling holes, including: determining a depth change trust factor according to the comparison of the carbonation intensity index and the drilling depth of the current detection point in different drilling holes; calculating the absolute value of the difference in carbonation intensity index between the current detection point and other detection points as the intensity difference; combining the intensity difference and the distance between the current detection point and other detection points to determine a point trust factor; and calculating the product value of the point trust factor and the depth change trust factor, and normalizing it as the reliability.

[0070] In the road surface quality detection scene, the concrete of the same to-be-detected slab usually uses a unified raw material mix ratio and is under the same environmental exposure condition, and theoretically the carbonation depth and the rebound value of each detection point should present stable correlation. However, in actual detection, some detection points may have data deviation phenomenon: when the rebound value of a detection point is significantly higher than that of the surrounding area, the carbonation intensity of the detection point should also be relatively large at this time.

[0071] Moreover, for the carbonation intensity of a detection point, it does not exist in isolation, and it may have mutual influence with the carbonation intensity of the surrounding detection points. In all detection points selected in the same to-be-detected road slab, when the detection points are close enough, the carbonation intensity of the detection points is related. For any detection point, when the distance between the detection point and the remaining all detection points in the same to-be-detected road slab is closer, the difference in carbonation intensity is smaller, and the value presents more in line with the carbonation condition of the road surface.

[0072] In addition, in the drilling measurement process of the carbonation depth of a detection point, multiple drilling may occur because a single drilling does not reach the actual carbonation bottom. At this time, the carbonation intensity in multiple drilling should present a gradually decreasing trend, because as the drilling depth gradually approaches the actual carbonation bottom, the carbonation intensity will gradually decrease.

[0073] In combination with the above features, the reliability of the carbonation intensity index of the current detection point can be specifically analyzed. First, linear analysis is performed on the drilling depth and the carbonation intensity, so as to determine the abnormality of the detection point.

[0074] Further, in some embodiments of the present application, according to the comparison of the carbonation intensity index and the drilling depth in different drilling holes at the current detection point, the depth change trust factor is determined, including: taking the drilling depth as the horizontal coordinate and the carbonation intensity index as the vertical coordinate to construct a two-dimensional coordinate system, and determining the coordinate points of different drilling holes in the two-dimensional coordinate system; performing linear fitting on all coordinate points to obtain a fitting straight line, calculating the distance sum value of all coordinate points and the fitting straight line, and normalizing the inverse of the distance sum value as a first trust coefficient; normalizing the inverse of the slope of the fitting straight line as a second trust coefficient; and calculating the product value of the first trust coefficient and the second trust coefficient to obtain the depth change trust factor.

[0075] Among them, the fitting straight line can be constructed by the least square method, so as to perform specific analysis, select the slope of the fitting straight line of the carbonation intensity data drilled from top to bottom as the data support of the carbonation intensity data, and when the slope is less than zero and smaller, the trend that the carbonation intensity in the multiple drilling holes of the current detection point decreases with the increase of the drilling depth is more obvious, which means that the measurement result is more in line with the expected carbonation intensity change rule, and the authenticity of the carbonation intensity data of the current detection point is higher.

[0076] Therefore, the smaller the slope value of the fitting straight line is, the higher the authenticity is, and the inverse of the slope of the fitting straight line is normalized as the second trust coefficient.

[0077] With the change of depth, the carbonation intensity should present linear change, that is, the greater the distance between the coordinate point and the fitting straight line is, the lower the linear degree of the carbonation intensity is, and the smaller the authenticity is, so the inverse of the distance sum value is normalized as the first trust coefficient. The product value of the first trust coefficient and the second trust coefficient is calculated to obtain the depth change trust factor.

[0078] Secondly, the reliability is also affected by the distance between different detection points. The closer the distance is, the more similar the carbonation of the detection points should be. According to the analysis of this feature, the point trust factor is determined by combining the intensity difference and the distance between the current detection point and other detection points, including: calculating the intensity difference and distance product of the current detection point and any other detection point, normalizing the inverse of the product value as the point trust factor.

[0079] The other detection points around a detection point are very close to it, and the carbonation depths are also similar, so the carbonation depth of the detection point is more reliable, which means that the carbonation depth is more reliable; on the contrary, if the carbonation depths of the surrounding detection points are greatly different or the distance is far, the reliability of the carbonation depth of the detection point will be relatively low.

[0080] Thus, the absolute value of the difference between the current detection point and other detection points in the carbonation intensity index is calculated as the intensity difference. The smaller the intensity difference and the shorter the distance, the higher the trust degree. The point trust factor is calculated.

[0081] In summary, the product value of the point trust factor and the depth change trust factor is directly calculated and normalized as the trust degree. The trust degree can represent the reliability of the current detection point in the carbonation intensity analysis.

[0082] S103: According to the difference between the current detection point and other detection points in the rebound value and the carbonation intensity index, the rebound value correction coefficient is determined. The rebound value correction coefficient is combined with the rebound value of the current detection point and the carbonation intensity index of all detection points to determine the corrected rebound value.

[0083] For the data measured by the detection point, the data with deviation needs to be corrected by combining the carbonation intensity and rebound value data of the current remaining detection points to ensure that all detection data before chaining can truly reflect the concrete compression resistance of the road panel to be detected.

[0084] Firstly, the correction of the rebound value is analyzed. According to the difference between the current detection point and other detection points in the rebound value and the carbonation intensity index, the rebound value correction coefficient is determined, including: calculating the rebound value and the carbonation intensity index ratio of the same detection point as the carbonation analysis coefficient; the median of the rebound value of all detection points is taken as the median rebound value; the median of the carbonation analysis coefficient of all detection points is taken as the median analysis coefficient; the absolute value of the difference between the carbonation analysis coefficient of the current detection point and the median analysis coefficient is calculated, and the inverse of the absolute value is normalized as the authenticity; the difference between the rebound value of the current detection point and the median rebound value is taken as the rebound adjustment value; the product value of the rebound adjustment value and the authenticity is taken as the rebound value correction coefficient.

[0085] The median of the rebound value data of all detection points is selected as the reference. When the difference between the rebound value measured by the current detection point and the median (i.e. the rebound adjustment value) is greater than zero, it means that the current detection point is greater than the median, and the rebound value needs to be initially reduced. When the rebound adjustment value is less than zero, it means that the current detection point is less than the median, and it needs to be initially increased.

[0086] The carbonation analysis coefficient represents the ratio of the rebound value of the current detection point to the carbonation intensity index. The difference between the carbonation analysis coefficient of the current detection point and the median of the carbonation analysis coefficient of all detection points is analyzed. When the difference is smaller, it means that the authenticity of the detection data of the current detection point is higher, and the correction is more accurate. Therefore, the inverse of the absolute value of the difference is normalized as the authenticity, and the accuracy of the measurement data of the current detection point is measured by the authenticity.

[0087] The rebound value of the current detection point, the rebound value correction coefficient and the carbonation intensity index of all detection points are combined to determine the corrected rebound value, and the corresponding calculation formula is:

[0088]

[0089] In the formula, H represents the corrected rebound value, H0 represents the rebound value of the current detection point, and h represents the rebound value correction coefficient of the current detection point; D represents the carbonation intensity index of the current detection point; D max represents the maximum value of the carbonation intensity index of all detection points.

[0090] H0*(1-h) is corrected according to the rebound value of the current detection point relative to the data of the remaining detection points, when h is greater than zero, it is indicated that the rebound value data of the current detection point is high, therefore (1-h) is less than zero, the value of H0 is reduced, and when h is less than zero, the opposite is true, so as to ensure that the current detection unit can detect the real compression resistance of the to-be-detected road panel.

[0091] In the carbonation process of the concrete, the carbonation intensity index is further corrected, when the carbonation intensity index D is greater, the virtual high rebound value data of the concrete at this time will be greater, therefore the corrected rebound value should be smaller, and the corrected rebound value is ensured to be affected by the carbonation intensity index.

[0092] The correction value of the rebound value, that is, the corrected rebound value, is obtained, the measured rebound value of all detection points of the to-be-detected road panel is corrected, the corrected rebound value data is submitted again, and the data consensus phase is performed.

[0093] S104: The consensus test is performed on the corrected rebound value and the credibility of the detection point, the data that passes the consensus test is packaged as a structured data block, and is stored as chain data.

[0094] The two verification nodes are randomly selected for comparison, so that the data is not tampered with by people, the credibility of different nodes is combined, so that the real and effective corrected rebound value is ensured to be finally chained, each node can independently measure and upload data, the data consensus process is realized, an accurate consensus result is obtained, and it is ensured that only effective and consistent data can be chained and packaged as a structured data block.

[0095] Further, in some embodiments of the present application, the consensus test is performed on the corrected rebound value and the credibility of the detection point, including: different detection units are respectively given a preset consensus weight, analysis is performed based on a consensus algorithm, and the detection point that passes the consensus test is determined, and the corrected rebound value and the credibility corresponding to the detection point that passes the consensus test are taken as the data that passes the consensus test.

[0096] ​In the embodiment of the present application, the existing standard strength curve can be used to convert the corrected rebound value into concrete compressive strength data.

[0097] In the verification process, different node permission weights are given to each detection node on the alliance chain to ensure the authenticity of the data after data consensus and then on-chain, realizing the data consensus multi-node verification stage.

[0098] For example, referring to Figure 4 , Figure 4 The node permission weight distribution diagram provided by an embodiment of the present application; the construction party data is used as the basic input (25% weight), the third-party independent detection forms the arbitration reference (35%), the supervision unit improves the data credibility through process monitoring (30%), and the quality inspection party final inspection (10%). The four node data are cross-verified on the alliance chain, and any abnormal node data will trigger the smart contract warning.

[0099] After the above steps, it is ensured that all on-chain data meets the rules and reaches an agreement through the consensus algorithm, and then the block is added to the chain, avoiding subsequent disputes and data inconsistency problems. The compressive strength data, corrected rebound value, carbonation depth and other data passing the consensus are packaged as structured data blocks, and if the detection result is abnormal (such as the strength does not meet the standard), the smart contract triggers the warning notification and freezes the subsequent construction process until manual review; the private key of the multi-detection unit node is used to perform multiple signatures on the data block, improving the traceability accuracy; the signed block is broadcast to the block chain network, triggering the smart contract verification logic; thereby realizing the data consensus of the concrete strength detection.

[0100] In the embodiment of the present application, in the process of obtaining the concrete strength data before on-chain at each detection point, the carbonation intensity index of the detection point and the credibility of the corresponding carbonation analysis are determined through specific analysis of the crystallinity and carbonation depth data of calcium carbonate, which can effectively analyze the virtual high influence of the carbonation process of the pavement concrete on the rebound value of the concrete strength data, and obtain the actual carbonation intensity of the detection point; then, combined with the consistency of the concrete carbonation process among all detection points on the same to-be-detected pavement slab, the abnormal situation of the measurement result deviating from the real concrete rebound value is excluded, the rebound value virtual high deviation caused by the carbonation effect is automatically identified and corrected, a more reliable and accurate corrected rebound value is obtained, the cross verification of the corrected rebound value is realized, and the authenticity and consistency of the on-chain data are ensured.

[0101] It should be noted that the above-mentioned embodiment of the present application is only for description, and does not represent the advantages and disadvantages of the embodiment. The process depicted in the drawing does not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multi-task processing and parallel processing are also possible or may be advantageous.

[0102] The various embodiments described in this specification are presented by way of example, and each embodiment is not inherently more important than any other embodiment.

Claims

1. A consensus method for engineering test and detection data based on blockchain, characterized in that, The method includes: The rebound values ​​of different test points of the road surface slab to be tested were obtained, the carbonization depth data when the core sample was fully carbonized was determined based on the phenolphthalein method, and the crystallinity of calcium carbonate in the core sample was obtained based on the XRD method. Based on the comparison of the crystallinity of calcium carbonate in partially and fully carbonated concrete and the carbonation depth data, the equivalent depth data of the partially carbonized area is determined; combined with the equivalent depth data, the carbonation intensity index of the current detection point is determined; based on the distance between the current detection point and other detection points and the difference in carbonation intensity index, as well as the comparison of the carbonation intensity index of the current detection point with the borehole depth in different drilling sessions, the reliability of the carbonation intensity index of the current detection point is determined. Based on the differences in rebound value and carbonization intensity between the current test point and other test points, a rebound value correction coefficient is determined. Combining the rebound value of the current test point, the rebound value correction coefficient, and the carbonization intensity index of all test points, the corrected rebound value is determined. Consensus verification is performed on the correction bounce value and credibility of the detection points. Data that passes the consensus is packaged into structured data blocks and stored as on-chain data. The methods for determining the rebound value correction factor include: Calculate the ratio of the rebound value to the carbonization intensity index at the same test point, and use it as the carbonization analysis coefficient; The median rebound value of all test points was taken as the median rebound value; the median carbonization analysis coefficient of all test points was taken as the median analysis coefficient. Calculate the absolute value of the difference between the carbonization analysis coefficient and the median analysis coefficient at the current detection point, and normalize the negative of the absolute value of the difference as the accuracy. The difference between the rebound value at the current detection point and the median rebound value is used as the rebound adjustment value; Calculate the product of the rebound adjustment value and the accuracy, and use it as the rebound value correction coefficient.

2. The blockchain-based consensus method for engineering test and detection data as described in claim 1, characterized in that, The determination of equivalent depth data for partially carbonated regions based on a comparison of the crystallinity of calcium carbonate in partially and fully carbonated concrete, and carbonation depth data, includes: The degree of partial carbonation was determined by comparing the crystallinity of calcium carbonate in fully carbonized and partially carbonized samples. The product of partial carbonization degree and carbonization depth data is used as the reference depth data; The product of the preset carbonization conversion coefficient adjusted based on the admixture type and the reference depth data is calculated as the depth conversion value. The sum of the depth conversion value and the carbonization depth data of fully carbonized material is used as the equivalent depth data.

3. The blockchain-based consensus method for engineering test and detection data as described in claim 2, characterized in that, The determination of the degree of partial carbonation by comparing the crystallinity of calcium carbonate in fully carbonized and partially carbonized processes includes: The ratio of the crystallinity of calcium carbonate in partial carbonation to that in complete carbonation is calculated as the degree of partial carbonation.

4. The blockchain-based consensus method for engineering test and detection data as described in claim 1, characterized in that, The carbonization intensity index is divided into 1-10 levels, with higher levels corresponding to larger values ​​of equivalent depth data.

5. The blockchain-based consensus method for engineering test and detection data as described in claim 1, characterized in that, The determination of the reliability of the carbonization intensity index of the current detection point based on the distance between the current detection point and other detection points, the difference in carbonization intensity index, and the comparison of the carbonization intensity index of the current detection point with the borehole depth in different drilling operations includes: The depth change confidence factor is determined by comparing the carbonization intensity index with the borehole depth at the current detection point in different drilling sessions. Calculate the absolute value of the difference in carbonization intensity index between the current detection point and other detection points, as the intensity difference; The location confidence factor is determined by combining the intensity difference and the distance between the current detection point and other detection points; Calculate the product of the location trust factor and the depth change trust factor, and normalize it to obtain the credibility score.

6. The blockchain-based consensus method for engineering test and detection data as described in claim 5, characterized in that, The method of determining the depth change confidence factor based on the comparison of the carbonization intensity index and borehole depth at the current detection point in different drilling sessions includes: A two-dimensional coordinate system was constructed with the borehole depth as the abscissa and the carbonization intensity index as the ordinate, and the coordinate points of different borehole conditions in the two-dimensional coordinate system were determined. A straight line is fitted to all coordinate points to obtain a fitted straight line. The sum of the distances between all coordinate points and the fitted straight line is calculated, and the negative of the sum of the distances is normalized and used as the first confidence coefficient. The negative of the slope of the fitted line is normalized and used as the second confidence coefficient. The product of the first trust coefficient and the second trust coefficient is calculated to obtain the deep change trust factor.

7. The blockchain-based consensus method for engineering test and detection data as described in claim 5, characterized in that, The determination of the point confidence factor, based on the combination of intensity differences and the distance between the current detection point and other detection points, includes: Calculate the product of the intensity difference and distance between the current detection point and any other detection point, normalize the negative of the product value, and use it as the point confidence factor.

8. The blockchain-based consensus method for engineering test and detection data as described in claim 1, characterized in that, The corrected rebound value is determined by combining the rebound value of the current detection point, the rebound value correction coefficient, and the carbonization intensity index of all detection points. The corresponding calculation formula is as follows: In the formula, H represents the corrected springback value. This indicates the rebound value at the current detection point. This represents the rebound value correction coefficient at the current detection point; This indicates the carbonization intensity index at the current detection point; This represents the maximum value of the carbonization intensity index at all detection points.

9. A blockchain-based consensus method for engineering test and detection data as described in claim 1, characterized in that, The consensus verification of the corrected rebound value and confidence level of the detection point includes: Different detection units are assigned preset consensus weights. Based on the consensus algorithm, the detection points that pass the consensus are analyzed and the corrected rebound value and confidence level corresponding to the detection points that pass the consensus are used as the data that passes the consensus.

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