A quality evaluation method and system for municipal engineering construction

Abstract

The application discloses a quality evaluation method and system for municipal engineering construction, and relates to the technical field of municipal engineering construction quality detection and data processing. The method comprises the following steps: obtaining a plurality of construction units of municipal engineering to be evaluated; obtaining construction quality detection data, construction process data, construction environment data and construction quality standard data corresponding to each construction unit; and the construction quality standard data at least comprises standard values and allowable deviations corresponding to different construction quality detection indexes. The application provides a quality evaluation method and system for municipal engineering construction. The construction quality detection data, the construction process data, the construction environment data and the construction quality standard data corresponding to each construction unit in the municipal engineering to be evaluated are obtained, the quality deviation is obtained according to the detection values, the standard values and the allowable deviations of the different construction quality detection indexes, and the quality deviation vector is further constructed.

Description

Technical Field

[0001] This invention relates to the field of municipal engineering construction quality inspection and data processing technology, specifically to a quality assessment method and system for municipal engineering construction. Background Technology

[0002] Municipal engineering is an important component of urban infrastructure construction, typically including municipal roads, bridges, drainage networks, underground utility tunnels, and other public infrastructure projects. The construction quality of municipal engineering projects directly affects the safety, durability, and operational stability of the engineering structure. Therefore, during and after the construction of municipal engineering projects, it is usually necessary to inspect and evaluate the construction quality of different construction areas to determine whether the corresponding construction areas meet the design requirements and construction quality acceptance standards.

[0003] In current municipal engineering construction quality assessment processes, multiple construction quality testing indicators are typically obtained according to the project type and construction sequence. For example, during municipal road construction, indicators such as compaction degree, structural layer thickness, pavement smoothness, elevation, and deflection value can be tested; during municipal pipeline construction, indicators such as pipeline burial depth, pipeline slope, interface deviation, and pipeline pressure can be tested; and during concrete structure construction, indicators such as concrete strength, structural dimensions, protective layer thickness, and structural displacement can also be tested. By comparing the test results of these construction quality testing indicators with the corresponding design values ​​or acceptance allowable deviations, a preliminary judgment on the construction quality can be made.

[0004] In the actual process of quality inspection of municipal engineering construction, there are a large number of construction quality inspection indicators, and different construction quality inspection indicators have different dimensions, allowable deviations and quality importance. If we directly evaluate based on the difference between each construction quality inspection indicator and the standard value, it is difficult to accurately reflect the actual impact of different inspection indicators on the overall construction quality.

[0005] Construction site testing data is easily affected by factors such as the operating status of testing equipment, calibration errors of the equipment, missing data, and fluctuations from repeated testing. When the testing data corresponding to a certain construction quality testing indicator fluctuates significantly or the corresponding testing equipment has obvious calibration deviations, directly using this testing data as the basis for quality evaluation can easily lead to low-reliability testing data having a significant impact on the overall construction quality assessment results, thereby reducing the reliability of the quality evaluation results.

[0006] The construction quality of municipal engineering projects is not only related to the final test results, but also closely related to the construction process parameters and environmental conditions. For example, the number of compaction passes, compaction speed, and paving temperature during road construction affect the compaction quality, while environmental factors such as temperature, humidity, and rainfall can also influence the construction status and test results. Some existing quality evaluation methods typically rely solely on the final test data for quality judgment, failing to effectively correlate construction result data, construction process data, and construction environment data. This makes it difficult to distinguish between test deviations caused by actual construction quality anomalies and temporary anomalies caused by environmental changes or test fluctuations.

[0007] The test results obtained by the same construction unit at multiple consecutive test times may fluctuate to some extent. If the quality judgment is based solely on the results of a single test, it is easy to identify occasional test errors as actual quality anomalies. On the other hand, for construction units that continuously show anomalies at multiple consecutive test times, there is a lack of further analysis on their temporal variation characteristics, making it difficult to identify persistent quality anomalies in a timely manner.

[0008] Municipal roads, pipelines, and bridges are typically constructed continuously. The material sources, construction techniques, and construction environments of adjacent construction units usually share a certain degree of consistency. Therefore, the construction quality of adjacent construction units often exhibits strong spatial continuity. Existing quality evaluation methods often evaluate each construction unit independently, failing to fully consider the quality differences between the target construction unit and adjacent units. This may make it difficult to identify localized, abrupt construction quality defects in a timely manner.

[0009] Existing construction quality evaluation results are usually output in the form of qualified or unqualified, quality score or quality grade. After determining that the quality of a certain construction unit is abnormal, it is difficult to further determine the main construction quality inspection indicators that caused the quality decline and the priority of re-inspection of different abnormal indicators. This limits the guiding role of the quality evaluation results in subsequent re-inspection and construction quality rectification.

[0010] Therefore, this application proposes a quality assessment method and system for municipal engineering construction. Summary of the Invention

[0011] The purpose of this invention is to provide a quality assessment method and system for municipal engineering construction to solve the problems mentioned in the background art.

[0012] To achieve the above objectives, the present invention provides the following technical solution: a quality assessment method for municipal engineering construction, comprising the following steps:

[0013] Acquire several construction units of the municipal engineering project to be evaluated, and acquire construction quality inspection data, construction process data, construction environment data and construction quality standard data corresponding to each construction unit. The construction quality standard data shall at least include the standard values ​​and allowable deviations corresponding to different construction quality inspection indicators.

[0014] Based on the test value, corresponding standard value and allowable deviation of each construction quality test indicator, the quality deviation of each construction quality test indicator in each construction unit is obtained, and a quality deviation vector is constructed based on the quality deviation of each construction quality test indicator.

[0015] The degree of missing test data, the degree of dispersion of repeated tests, and the calibration deviation of test equipment corresponding to each construction quality test indicator are obtained. Based on the degree of missing test data, the degree of dispersion of repeated tests, and the calibration deviation of test equipment, the data reliability corresponding to each construction quality test indicator is obtained.

[0016] Based on the quality deviation, data reliability, and index weight of each construction quality inspection index, the initial quality evaluation quantity for each construction unit is obtained.

[0017] The deviation amount of the construction process is obtained based on the degree of deviation between the construction process data and the preset construction process benchmark data, and the environmental disturbance amount is obtained based on the degree of deviation between the construction environment data and the preset construction environment benchmark data; the construction process correction coefficient is obtained based on the degree of correlation between the construction process deviation amount and each construction quality inspection index, and the environmental correction coefficient is obtained based on the degree of correlation between the environmental disturbance amount and each construction quality inspection index.

[0018] Based on the degree of change in construction quality inspection data obtained by the same construction unit at multiple consecutive inspection times, the time-series stability correction coefficient of the corresponding construction unit is obtained;

[0019] Based on the initial quality evaluation quantity, construction process correction coefficient, environmental correction coefficient, and time-series stability correction coefficient, the first corrected quality deviation of each construction unit is obtained;

[0020] The difference between the first corrected mass deviation of the target construction unit and its adjacent construction units is obtained. Based on the difference, the spatial anomaly correction coefficient of the target construction unit is obtained. Based on the spatial anomaly correction coefficient, the first corrected mass deviation of the target construction unit is corrected to obtain the final mass deviation.

[0021] The construction quality score of the corresponding construction unit is obtained based on the final quality deviation, and the construction quality level is determined based on the relationship between the construction quality score and the preset quality level threshold. At the same time, the abnormal construction quality detection index is determined based on the contribution of each construction quality detection index to the final quality deviation.

[0022] As a specific solution to the technical solution of this application, the method for obtaining the quality deviation corresponding to each construction quality inspection index includes:

[0023] Let any construction unit be denoted as the target construction unit, and let the detection value corresponding to the i-th construction quality inspection index of the target construction unit be denoted as... The corresponding standard value is denoted as The corresponding allowable deviation is denoted as ;according to:

[0024]

[0025] Obtain the quality deviation corresponding to the i-th construction quality inspection index. ;

[0026] In the formula, These are preset non-zero constants;

[0027] According to the preset arrangement order of each construction quality inspection index, all quality deviations are combined to form the quality deviation vector of the target construction unit:

[0028]

[0029] Where n represents the number of construction quality inspection indicators included in the target construction unit.

[0030] As a specific solution to the technical solution of this application, the method for obtaining the data reliability corresponding to each construction quality inspection index includes:

[0031] Obtain the data missing rate of the i-th construction quality inspection indicator within the preset inspection period. ;

[0032] The coefficient of variation for repeated testing is obtained based on the results of multiple repeated tests of the i-th construction quality inspection index. ;

[0033] Obtain the calibration deviation between the current calibration result and the standard calibration result of the corresponding testing equipment. ;

[0034] according to:

[0035] in, , as well as These are the preset data missing impact coefficient, repeated detection impact coefficient, and calibration deviation impact coefficient, respectively.

[0036] As a specific solution to the technical solution of this application, the method for obtaining the initial quality evaluation quantity corresponding to each construction unit based on the quality deviation, data reliability, and index weight of each construction quality inspection index includes:

[0037] The initial weights of each construction quality testing indicator are determined based on the allowable deviations of each indicator and the importance level of the corresponding indicator in the municipal engineering acceptance standards.

[0038] The weights of all initial indicators are normalized to obtain the indicator weight corresponding to the i-th construction quality inspection indicator. ;

[0039] according to:

[0040] Obtain the initial quality evaluation quantity corresponding to the target construction unit. ;

[0041] in, Let be the quality deviation corresponding to the i-th construction quality inspection index. Let represent the data reliability corresponding to the i-th construction quality inspection.

[0042] As a specific solution to the technical solution of this application, the method for obtaining the construction process correction coefficient includes:

[0043] Obtain the actual values ​​of different construction process parameters and the corresponding benchmark construction intervals during the construction of the target construction unit;

[0044] When the actual value of the construction process parameter is within the corresponding benchmark construction range, the process deviation of the corresponding construction process parameter is set to zero.

[0045] When the actual value of the construction process parameter is outside the corresponding benchmark construction interval, the corresponding process deviation is obtained based on the difference between the actual value and the nearest boundary value of the corresponding benchmark construction interval and the width of the benchmark construction interval.

[0046] Obtain the correlation coefficients between each construction process parameter and each construction quality inspection index in the historical construction samples, and construct a construction process quality correlation matrix based on the correlation coefficients;

[0047] The construction process influence is obtained based on the process deviation of the target construction unit, the construction process quality correlation matrix, and the quality deviation of each construction quality inspection index. ;

[0048] according to:

[0049] Obtain the construction process correction coefficient corresponding to the target construction unit. ;

[0050] in, This is a preset correction factor for the construction process.

[0051] As a specific solution to the technical solution of this application, the method for obtaining the environmental correction coefficient includes:

[0052] Obtain at least one environmental parameter during the construction of the target construction unit, wherein the environmental parameter includes one or more of ambient temperature, ambient humidity, rainfall, and wind speed;

[0053] The environmental deviation is obtained by determining the degree of deviation between the actual value of each environmental parameter and the corresponding baseline environmental range.

[0054] The environmental sensitivity coefficients between different environmental parameters and different construction quality testing indicators are obtained based on historical construction quality testing data.

[0055] The comprehensive environmental impact E of the target construction unit is obtained based on each environmental deviation and the corresponding environmental sensitivity coefficient;

[0056] according to:

[0057] Obtain the environmental correction factor corresponding to the target construction unit. ;

[0058] in, This is the preset environmental correction factor.

[0059] As a specific solution of the technical solution of this application, the method for obtaining the timing stability correction coefficient includes:

[0060] For each construction quality inspection index of the target construction unit, obtain the detection values ​​corresponding to multiple consecutive detection times within a preset time window;

[0061] The temporal fluctuation of the corresponding construction quality testing index is obtained by using the average and standard deviation of multiple consecutive test values.

[0062] The total time-series fluctuations are weighted and integrated based on the weights of each construction quality inspection indicator to obtain the comprehensive time-series fluctuation T of the target construction unit.

[0063] according to:

[0064] Obtain the timing stability correction coefficient ,in This is the preset timing correction coefficient.

[0065] As a specific solution to the technical solution of this application, the method for obtaining the first corrected quality deviation of each construction unit includes: according to: Obtain the first corrected quality deviation corresponding to the target construction unit. ;

[0066] in, This is the initial quality evaluation value. This is a correction factor for the construction process. This is the environmental correction factor. This is a time-stability correction factor. This is a normalization function that maps the calculation results to a preset range of mass deviation values.

[0067] As a specific solution to the technical solution of this application, the method for obtaining the spatial anomaly correction coefficient and the final mass deviation includes:

[0068] Construction units that are adjacent to the target construction unit and / or belong to the same continuous construction section are identified as adjacent construction units of the target construction unit.

[0069] Obtain the first corrected mass deviation for each adjacent construction unit, and obtain the median and absolute median difference of the first corrected mass deviation for all adjacent construction units;

[0070] The spatial anomaly is obtained based on the difference between the first corrected mass deviation of the target construction unit and the median value:

[0071]

[0072] In the formula, This is the median value of the first corrected quality deviation of adjacent construction units. The absolute median difference of the first corrected quality deviation of adjacent construction units;

[0073] according to: Obtain the spatial anomaly correction coefficient for the target construction unit. ;

[0074] And according to: Obtain the final quality deviation corresponding to the target construction unit. .

[0075] As a specific embodiment of the technical solution of this application, the method for obtaining a construction quality score and determining abnormal construction quality detection indicators based on the final quality deviation includes:

[0076] according to: To obtain the construction quality score S of the target construction unit;

[0077] Based on the relationship between the construction quality score S and multiple preset construction quality level thresholds, the target construction unit is divided into at least one of the following construction quality levels: excellent, qualified, pending re-inspection, and unqualified.

[0078] The quality deviation, data reliability, and corresponding index weight of each construction quality inspection index are obtained respectively. Based on the quality deviation, data reliability, and index weight, the quality anomaly contribution value of each construction quality inspection index to the final quality deviation is obtained.

[0079] The construction quality inspection indicators are sorted from largest to smallest according to their quality anomaly contribution value. The construction quality inspection indicators whose quality anomaly contribution value exceeds the preset anomaly contribution threshold are identified as abnormal construction quality inspection indicators. The re-inspection priority of each abnormal construction quality inspection indicator is determined according to the sorting.

[0080] A quality assessment system for municipal engineering construction includes:

[0081] The data acquisition module is used to acquire several construction units of the municipal engineering project to be evaluated, as well as the construction quality inspection data, construction process data, construction environment data and construction quality standard data corresponding to each construction unit;

[0082] The quality deviation calculation module is used to obtain the quality deviation amount corresponding to each construction quality inspection index and construct the quality deviation vector based on construction quality inspection data and construction quality standard data.

[0083] The data credibility calculation module is used to obtain the data credibility of each construction quality inspection index based on the degree of data missingness, the degree of dispersion of repeated inspections, and the calibration deviation of the inspection equipment.

[0084] The initial evaluation module is used to obtain the initial quality evaluation quantity based on the quality deviation, data reliability, and indicator weight of each construction quality inspection indicator.

[0085] The process correction module is used to obtain the construction process correction coefficient based on the degree of deviation between the construction process data and the preset construction process benchmark data, as well as the correlation between the construction process parameters and the construction quality inspection indicators.

[0086] The environmental correction module is used to obtain environmental correction coefficients based on the degree of deviation between construction environment data and preset construction environment benchmark data, as well as the correlation between environmental parameters and construction quality inspection indicators.

[0087] The timing correction module is used to obtain the timing stability correction coefficient based on the degree of change in construction quality inspection data at multiple consecutive inspection times of the same construction unit.

[0088] The first correction module is used to obtain the first corrected quality deviation based on the initial quality evaluation quantity, the construction process correction coefficient, the environmental correction coefficient, and the time-series stability correction coefficient.

[0089] The spatial anomaly correction module is used to obtain the spatial anomaly correction coefficient based on the difference between the first corrected quality deviation between the target construction unit and the adjacent construction unit, and to obtain the final quality deviation based on the spatial anomaly correction coefficient.

[0090] The system also includes a quality result output module, which is used to obtain the construction quality score and construction quality grade based on the final quality deviation, and to determine the abnormal construction quality detection indicators and re-inspection priorities based on the contribution of each construction quality detection indicator to the final quality deviation.

[0091] As a specific solution of the technical solution of this application, the system includes a memory, a processor, and a computer program stored in the memory and capable of running on the processor. When the computer program is executed by the processor, it implements the steps of a quality assessment method for municipal engineering construction as described in any of the above embodiments.

[0092] Compared with the prior art, the beneficial effects of the present invention are:

[0093] This invention provides a quality assessment method and system for municipal engineering construction. It acquires construction quality inspection data, construction process data, construction environment data, and construction quality standard data corresponding to each construction unit in the municipal engineering project to be assessed. Based on the inspection values, standard values, and allowable deviations of different construction quality inspection indicators, it obtains the quality deviation amount and further constructs a quality deviation vector. By converting construction quality inspection indicators with different dimensions and value ranges into a unified quality deviation amount, it can reduce the impact of differences in dimensions and numerical ranges of different inspection indicators on the comprehensive evaluation process, providing a data foundation for the unified processing of different quality inspection indicators.

[0094] Simultaneously, the degree of data missing, the degree of dispersion of repeated testing, and the calibration deviation of testing equipment corresponding to each construction quality testing indicator are further obtained. Based on this, the data reliability of each construction quality testing indicator is determined. When conducting a comprehensive evaluation based on the quality deviation, the reliability of the testing data is introduced. Testing data with high data integrity, stable repeated testing, and good equipment calibration status have a higher evaluation value, while testing data with large data missing, repeated testing fluctuations, or equipment calibration deviations have a reduced evaluation impact. This reduces the interference of low-reliability testing data on the comprehensive evaluation results of construction quality and improves the reliability of the construction quality evaluation results.

[0095] This invention obtains an initial quality evaluation quantity based on the quality deviation, data reliability, and indicator weight of each construction quality inspection indicator. This enables the comprehensive evaluation result of construction quality to simultaneously reflect the actual deviation of different quality indicators, the reliability of the inspection data, and the importance of each quality indicator in the project quality acceptance. Compared with simple averaging or fixed weight evaluation methods, this invention can more reasonably reflect the impact of different construction quality inspection indicators on the overall quality status of the construction unit.

[0096] The deviation of the construction process is obtained by analyzing the degree of deviation between the construction process data and the preset construction process benchmark data. Further, a correction coefficient is obtained by combining the correlation between the construction process parameters and different construction quality inspection indicators. When a construction quality inspection indicator deviates significantly, and construction process parameters with a high degree of correlation to that indicator also show abnormalities, the correction degree for the corresponding construction unit's quality anomaly results can be improved. This allows the anomaly in the construction result to be corroborated by the construction process state that may have caused the anomaly, thus improving the accuracy of construction quality anomaly identification. Attached Figure Description

[0097] Figure 1 This is a schematic diagram of the quality assessment method for municipal engineering construction according to the present invention. Detailed Implementation

[0098] To further illustrate the technical means employed and the resulting technical effects of this invention in achieving its intended objectives, the following detailed description, in conjunction with the accompanying drawings and specific embodiments, provides a method and system for quality assessment in municipal engineering construction. It should be noted that the following embodiments are merely illustrative of the technical solutions of this invention and are not intended to limit the scope of protection of this invention.

[0099] Unless otherwise defined, the technical and scientific terms used in this specification have the meanings commonly understood by those skilled in the art. Technical features in the different embodiments described below can be combined with each other without causing technical conflict.

[0100] This invention addresses the challenges of numerous testing indicators, varying reliability of different testing data, fluctuations in test results due to construction process and environmental conditions, and spatial continuity between adjacent construction areas during the evaluation of municipal engineering construction quality. By sequentially acquiring quality deviation, data reliability, initial quality evaluation, construction process correction coefficient, environmental correction coefficient, temporal stability correction coefficient, and spatial anomaly correction coefficient, the invention performs multi-level corrections on the construction quality testing results, ultimately obtaining the construction quality score and construction quality level corresponding to each construction unit.

[0101] Please see Figure 1 , Figure 1The diagram illustrates a step-by-step flowchart of a quality assessment method for municipal engineering construction provided by an embodiment of the present invention, which includes the following steps.

[0102] Step S001: Obtain the construction unit and its corresponding basic construction quality data.

[0103] Step S001: Obtain several construction units of the municipal engineering project to be evaluated, and obtain the construction quality inspection data, construction process data, construction environment data and construction quality standard data corresponding to each construction unit.

[0104] Specifically, the municipal engineering project to be evaluated is divided into construction units based on the project type, construction section, construction procedure, and quality acceptance unit.

[0105] As one implementation method, when the municipal engineering project to be evaluated is a municipal road project, it can be divided according to road stationing sections, structural layers, and construction batches. For example, construction sections can be divided along the road length direction according to a preset length of 20m to 100m, and construction units can be formed according to different construction structural layers such as roadbed, base course, and surface course.

[0106] When the municipal engineering project to be evaluated is a municipal drainage pipeline project, construction units can be formed according to the pipeline sections between adjacent inspection wells; when the municipal engineering project to be evaluated is a bridge project, construction units can be formed according to bridge piers, abutments, beams, or pre-set construction sections.

[0107] It should be noted that the specific form of dividing construction units is not limited to the above-mentioned methods. Those skilled in the art can determine the division criteria of construction units based on the actual project acceptance requirements. This invention divides the overall municipal engineering project into multiple construction units, enabling subsequent quality evaluation to pinpoint specific construction areas.

[0108] Furthermore, the construction quality inspection data corresponding to each construction unit is obtained.

[0109] The construction quality inspection data are used to represent the inspection results that directly reflect the construction quality after completion or during construction. Different types of municipal engineering projects may have different construction quality inspection indicators.

[0110] For example, in municipal road engineering, construction quality inspection indicators may include one or more of the following: compaction degree, structural layer thickness, flatness, elevation, cross slope, and deflection value; in the construction of concrete structures, construction quality inspection indicators may include one or more of the following: concrete strength, structural dimensions, protective layer thickness, and structural displacement; in municipal pipeline engineering, construction quality inspection indicators may include one or more of the following: pipeline burial depth, pipeline slope, pipeline interface offset, and pipeline pressure.

[0111] Construction quality inspection data can be obtained through on-site testing equipment, construction testing instruments, engineering monitoring sensors, and manual inspection records.

[0112] Furthermore, the construction process data corresponding to each construction unit is obtained.

[0113] The construction process data is used to represent the technological parameters that affect the quality of the construction project. Taking road construction as an example, the construction process data may include paving speed, paving temperature, number of compaction cycles, compaction speed, and vibration parameters of construction machinery; for concrete construction, the construction process data may include concrete placement temperature, vibration time, number of vibration cycles, and curing time.

[0114] Furthermore, acquire the construction environment data corresponding to each construction unit. The construction environment data includes at least one or more of the following: ambient temperature, ambient humidity, rainfall, and wind speed.

[0115] Furthermore, construction quality standard data should be obtained. This data should include at least the standard values ​​and allowable deviations for each construction quality testing indicator.

[0116] As one implementation method, the corresponding standard values ​​and allowable deviations can be obtained from engineering design documents, construction technical documents, and a pre-established database of municipal engineering construction quality standards.

[0117] This provides the basic data for assessing the construction quality of municipal engineering projects.

[0118] Step S002: Obtain the quality deviation of the construction quality inspection indicators.

[0119] Step S002: Based on the test value of each construction quality test index, the corresponding standard value and allowable deviation, obtain the quality deviation amount corresponding to different construction quality test indexes in each construction unit, and construct the corresponding quality deviation vector.

[0120] It should be noted that different construction quality testing indicators have different physical dimensions and allowable ranges of variation. For example, compaction degree is usually expressed as a percentage, structural layer thickness is expressed as length, and flatness can be expressed as millimeters. If the original test values ​​of different indicators are directly compared, they will be affected by the different dimensions and numerical ranges.

[0121] Therefore, this invention converts different construction quality testing indicators into quality deviations within a unified value range based on the degree of deviation of the detected values ​​from the standard values ​​and the allowable deviations.

[0122] Specifically, any construction unit is designated as the target construction unit, and the detection value corresponding to the i-th construction quality inspection index of the target construction unit is designated as... The corresponding tag value is denoted as The corresponding allowable deviation is denoted as .

[0123] The quality deviation corresponding to the i-th construction quality inspection index is obtained according to the following formula. ;

[0124]

[0125] In the formula, Let be the detection value corresponding to the i-th construction quality inspection index. These are the standard values ​​for the corresponding construction quality inspection indicators. This refers to the allowable deviation corresponding to this construction quality inspection index. This indicates taking the absolute value. This is a preset non-zero constant used to avoid the denominator being zero.

[0126] As one implementation method, The precision of the construction quality inspection data can be set to 0.001, 0.01, or other small positive numbers. This embodiment uses... Please provide an explanation.

[0127] It should be noted that when the detected value is exactly the same as or close to the standard value, the corresponding quality deviation approaches 0. As the difference between the detected value and the standard value increases, the quality deviation gradually increases.

[0128] when When the deviation is greater than or equal to the corresponding allowable deviation, the min function is used to limit the corresponding quality deviation to 1, so that the quality deviation corresponding to different construction quality inspection indicators is uniformly between 0 and 1.

[0129] For example, if the design thickness of a road surface in a certain road construction unit is 100mm, with a corresponding allowable deviation of 5mm, and the actual measured thickness is 98mm, then the corresponding quality deviation is approximately:

[0130]

[0131] This indicates that the construction quality inspection index has deviated to some extent from the allowable deviation, but has not yet reached the maximum deviation state.

[0132] Furthermore, according to the preset material arrangement sequence of each construction quality inspection index, all quality deviations in the target construction unit are combined into a quality deviation vector:

[0133]

[0134] In the formula, Let n be the quality deviation vector corresponding to the target construction unit, and n be the number of construction quality inspection indicators contained in the target construction unit.

[0135] It should be noted that the same index arrangement order is used for different construction units so that the quality deviation vectors formed by different construction units have the same dimensional meaning, which facilitates subsequent time series analysis and spatial comparison.

[0136] At this point, the quality deviation vector corresponding to each construction unit is obtained.

[0137] Step S003: Obtain the data reliability of construction quality inspection data

[0138] Step S003: Obtain the data missingness, repeated detection dispersion, and detection equipment calibration deviation corresponding to each construction quality inspection indicator, and obtain the data reliability corresponding to different construction quality inspection indicators based on the above data.

[0139] It should be noted that in the actual process of municipal engineering construction and testing, even if the quality deviation corresponding to different testing indicators is the same, the reliability of the test results may vary significantly.

[0140] For example, if a testing device has not been calibrated for a long time, its test results will have large systematic errors; if the fluctuations between different test results are large when multiple tests are performed at the same test location, it indicates that the stability of the corresponding test results is poor; if a certain test indicator has a lot of missing data within a preset test period, it will also reduce the reliability of the test indicator when used for comprehensive quality evaluation.

[0141] Therefore, this invention further establishes data credibility to avoid the excessive influence of construction quality inspection data with low credibility on the final quality evaluation results.

[0142] Specifically, obtain the data missing rate of the i-th construction quality inspection indicator within the preset inspection period. .

[0143] Theoretically, the following data should be obtained within the preset detection period: There are 100000 data points detected, of which the actual number of missing data points is 10 ... The missing data rate can then be expressed as:

[0144]

[0145] When there is no missing detection data, As the proportion of missing data increases, Gradually increase.

[0146] Furthermore, the coefficient of variation for repeated testing is obtained based on the results of multiple repeated tests of the i-th construction quality inspection index. .

[0147] As one implementation method, the same detection location can be repeatedly detected at least three times, and the coefficient of variation for repeated detections can be obtained based on the ratio of the standard deviation to the mean of the multiple repeated detection values.

[0148]

[0149] In the formula, Let be the standard deviation of multiple repeated test values ​​for the i-th quality construction inspection index. This is the average of multiple repeated detection values.

[0150] The larger the coefficient of variation of repeated tests, the more obvious the fluctuation of the test results at the same construction location, and the lower the stability of the corresponding test data.

[0151] Furthermore, the calibration deviation between the current calibration result and the standard calibration result of the corresponding testing equipment is obtained. .

[0152] As one implementation method, the absolute difference between the calibration measurement value obtained by the testing equipment and the standard quantity is normalized to obtain the calibration deviation of the corresponding testing equipment. .

[0153] Furthermore, the data reliability corresponding to the i-th construction quality inspection index is obtained according to the following formula. :

[0154]

[0155] In the formula, The data reliability corresponding to the i-th construction quality inspection index is... For data missing rate, The coefficient of variation is for repeated detection. To detect equipment calibration deviation, , as well as These are the preset impact coefficients for missing data, duplicate detection, and standard deviation.

[0156] As one implementation method, settings can be configured based on the characteristics of the testing data from different municipal engineering projects. , as well as For example, when the accuracy of the testing equipment has a significant impact on the engineering verification results, the accuracy can be appropriately increased. .

[0157] In this embodiment, they can be set separately. , , The parameters mentioned above are for illustrative purposes only and do not constitute a limitation on the present invention.

[0158] It should be noted that when the i-th construction quality inspection indicator has no missing data, the repeated test results are stable, and the testing equipment has no obvious calibration deviation, Approaching 1, as the aforementioned abnormal temperatures increase, Gradually decrease.

[0159] Therefore, data credibility can be comprehensively characterized by three aspects: data integrity, detection stability, and equipment accuracy, to represent the credibility of the corresponding construction quality detection indicators.

[0160] At this point, the data reliability corresponding to each construction quality testing indicator is obtained.

[0161] Step S004: Obtain the initial quality assessment quantity

[0162] Step S004: Based on the quality deviation, data reliability, and index weight of each construction quality inspection index, obtain the initial quality evaluation quantity corresponding to the target construction unit.

[0163] It should be noted that different construction quality testing indicators have varying degrees of impact on the overall construction quality of municipal engineering projects. For example, for road base construction, compaction degree usually has a significant impact on the overall structural stability, while some dimensional indicators have a relatively low impact on overall performance.

[0164] Therefore, it is necessary to determine the weight of each indicator based on its importance in the quality acceptance of municipal engineering projects.

[0165] Specifically, the initial index weights are determined based on the allowable deviations of each construction quality inspection index and the importance level of that construction quality inspection index in the municipal engineering acceptance standards.

[0166] As one implementation method, construction quality inspection indicators can be divided into primary quality indicators and general quality indicators, and primary quality indicators can be assigned a larger initial indicator weight.

[0167] Meanwhile, all other things being equal, the smaller the allowable deviation range of a construction quality inspection index, the stricter the control requirements for that index in the project, and its initial index weight can be increased accordingly.

[0168] After obtaining the initial index weights corresponding to each construction quality inspection index, the initial index weights are normalized to obtain the index weight corresponding to the i-th construction quality inspection index. ,satisfy:

[0169]

[0170] Furthermore, the initial quality evaluation quantity corresponding to the target construction unit is obtained according to the following formula. :

[0171]

[0172] In the formula, This represents the initial quality evaluation quantity corresponding to the target construction unit. Let i be the index weight corresponding to the i-th construction quality inspection index. The data reliability corresponding to the i-th construction quality inspection index is... Let be the quality deviation corresponding to the i-th construction quality inspection index. This refers to the number of construction quality inspection indicators.

[0173] It should be noted that in the above calculation process, through This reflects the importance of different construction quality testing indicators to the overall construction quality, through... Adjustments were made to the effective impact of the detection data.

[0174] When a certain construction quality inspection indicator has a large quality deviation, but its inspection data has large fluctuations in repeated testing or large equipment calibration deviations, the reliability of the corresponding data is reduced, thereby reducing the direct impact of the inspection indicator on the initial quality evaluation.

[0175] Conversely, when a construction quality inspection indicator has a large quality deviation and the corresponding data has high reliability, it indicates that the abnormal inspection result has a high degree of reliability and has a significant impact on the initial quality evaluation.

[0176] It should be noted that, The closer the result is to 0, the closer the overall test result of the target construction unit is to the corresponding construction quality standard. The larger the value, the more significant the deviation in the overall construction quality of the target construction unit.

[0177] At this point, the initial quality evaluation value corresponding to each construction unit is obtained.

[0178] Step S005: Obtain the correction coefficient for the construction process

[0179] Step S005: Obtain the deviation amount of the construction process based on the degree of deviation between the construction process data and the preset construction process benchmark data, and obtain the construction process correction coefficient based on the correlation between the construction process deviation amount and the construction quality inspection index.

[0180] It should be noted that construction quality inspection results are result data after construction is completed or during construction, while construction process data can reflect the possible causes of quality abnormalities from the perspective of construction technology.

[0181] When a construction quality inspection index deviates significantly, and construction process parameters that are highly correlated with that index also become abnormal, it indicates that the corresponding quality abnormality has a high degree of consistency with the construction process. Therefore, the degree of quality abnormality of the corresponding construction unit should be appropriately increased.

[0182] Specifically, the actual values ​​of different construction process parameters and the corresponding benchmark construction intervals are obtained during the construction of the target construction unit.

[0183] Let the actual value of the j-th construction process parameter be denoted as... The corresponding benchmark construction section is denoted as: ,in, This is the lower limit of the benchmark construction area. This is the upper limit of the baseline construction section.

[0184] when At that time, the process deviation corresponding to the j-th construction process parameter will be... Set to 0.

[0185] when At that time, the process deviation is obtained according to the following formula:

[0186]

[0187] when At that time, the process deviation is obtained according to the following formula:

[0188]

[0189] Furthermore, the obtained process deviation is normalized to limit the process deviation to a preset range.

[0190] It should be noted that when the construction process parameters are within the specified normal construction range, the corresponding process deviation is 0; the more significantly the actual construction process parameters deviate from the normal construction range, the greater the corresponding process deviation.

[0191] Furthermore, the correlation coefficients between various construction process parameters and various construction quality inspection indicators in historical construction samples were obtained.

[0192] As one approach, the correlation between construction process parameters and corresponding quality inspection indicators in historical construction samples can be determined using the Pearson correlation coefficient.

[0193] Let the correlation coefficient between the j-th construction process parameter and the i-th construction quality inspection index be denoted as . Construct a construction process quality correlation matrix based on all correlation coefficients:

[0194]

[0195] In the formula, m represents the number of construction process parameters, and n represents the number of construction quality inspection indicators.

[0196] In one implementation, the construction process influence quantity P is obtained based on the process deviation, the construction process quality correlation matrix, and the quality deviation of each construction quality inspection index, and can be expressed as:

[0197]

[0198] In the formula, Let j be the process deviation of the j-th construction process parameter. Let be the absolute value of the correlation coefficient between the j-th construction process parameter and the i-th construction quality inspection index. Let be the quality deviation corresponding to the i-th construction quality inspection index. This represents the normalization function.

[0199] It should be noted that when a certain construction process parameter deviates significantly from the normal construction range, and this construction process parameter has a high degree of correlation with the construction quality inspection index that is currently deviating, the corresponding construction process influence quantity P increases.

[0200] The construction process correction coefficient corresponding to the target construction unit is obtained according to the following formula. :

[0201]

[0202] In the formula, A preset construction process correction coefficient is used to control the degree of correction of the initial quality evaluation results by abnormalities in the construction process.

[0203] As one implementation method, It can be set to 0.1-0.5; this implementation uses... Please provide an explanation.

[0204] When the construction process data of the target construction unit are all within the corresponding baseline construction range, the construction process influence quantity P approaches 0. When the value approaches 1, the construction process data will not be subject to any additional corrections to the initial quality evaluation results.

[0205] Thus, the construction process correction coefficients corresponding to the target construction are obtained.

[0206] Step S006: Obtain the environmental correction factor

[0207] Step S006: Obtain the environmental disturbance amount based on the degree of deviation between the construction environment data and the preset construction environment benchmark data, and obtain the environmental correction coefficient based on the degree of correlation between the environmental disturbance amount and different construction quality detection indicators.

[0208] It should be noted that external environmental parameters such as temperature, humidity, rainfall, and wind speed may affect the construction process and the results of construction quality testing.

[0209] For example, during the construction of asphalt pavement, ambient temperature may affect the paving and compaction effect; during concrete construction, ambient temperature and humidity may affect the setting and curing of concrete; and large amounts of rainfall may also affect the quality of earthwork and base course construction.

[0210] Therefore, the present invention further utilizes the construction environment conditions to correct the construction quality evaluation results.

[0211] Specifically, obtain one or more of the following during the construction of the target construction unit: ambient temperature, ambient humidity, rainfall, and wind speed.

[0212] Let the actual value of the Kth environmental parameter be denoted as The corresponding baseline environment range is denoted as:

[0213] When the actual value of the environmental parameter is within the corresponding baseline environmental range, the corresponding environmental deviation is set to 0.

[0214] When the actual value of an environmental parameter exceeds the corresponding baseline environmental range, the corresponding environmental deviation is obtained based on the distance between the actual value and the nearest boundary of the baseline environmental range, as well as the width of the baseline environmental range.

[0215] Furthermore, environmental sensitivity coefficients between different environmental parameters and different construction quality testing indicators are obtained based on historical construction quality testing data.

[0216] Let the environmental sensitivity coefficient between the Kth environmental parameter and the i-th construction quality inspection index be denoted as . .

[0217] In one implementation, the comprehensive environmental impact E corresponding to the target construction unit can be obtained according to the following formula:

[0218]

[0219] In the formula, This represents the environmental deviation corresponding to the k-th environmental parameter. For the number of environmental parameters, Let be the environmental sensitivity coefficient between the k-th environmental parameter and the ith construction quality inspection index.

[0220] The environmental correction factor corresponding to the target construction unit is obtained according to the following formula. :

[0221]

[0222] In the formula, This is the preset environmental correction factor.

[0223] As one implementation method, The value can be set to 0.05-0.4 depending on the project type. This embodiment uses... Please provide an explanation.

[0224] It should be noted that when the construction environment is within the normal range, the comprehensive environmental impact E approaches 0, and the environmental correction factor... The closer the value is to 1, the more significant the deviation of the construction environment from normal environmental conditions, and the higher the environmental sensitivity between relevant environmental parameters and abnormal quality indicators, the larger the environmental correction coefficient will be.

[0225] Thus, the environmental correction coefficient corresponding to the target construction unit is obtained.

[0226] Step S007: Obtain the timing stability correction coefficient

[0227] Step S007: Based on the degree of change in the construction quality inspection data obtained by the same construction unit at multiple consecutive inspection times, obtain the time-series stability correction coefficient of the corresponding construction unit.

[0228] It should be noted that during construction quality inspection, a single test value may exhibit momentary anomalies due to random errors. Judging solely based on the results of a single test might misinterpret random measurement fluctuations as actual construction quality anomalies.

[0229] On the other hand, when the test data of the same construction unit changes significantly over multiple consecutive test times, it indicates that the stability of the corresponding quality status has decreased, and more attention needs to be paid to the construction unit.

[0230] Therefore, the present invention obtains the time-series stability correction coefficient by analyzing continuous detection data.

[0231] Specifically, for each construction quality inspection indicator in the target construction unit, the detection values ​​at multiple consecutive inspection times within a preset time window are obtained.

[0232] As one implementation method, the preset time window can be set to the current detection time and the previous 4 detection times, that is, to obtain 5 consecutive detection results.

[0233] The detection value of the i-th construction quality inspection index within the time window is recorded as:

[0234]

[0235] Where L is the number of detection moments included in the time window.

[0236] The average value of the corresponding detection index is obtained based on the continuous detection values:

[0237]

[0238] and standard deviation:

[0239]

[0240] Furthermore, the time-series fluctuation corresponding to the i-th construction quality inspection index is obtained based on the mean and standard deviation. :

[0241]

[0242] The timing stability correction coefficient is obtained according to the following formula. :

[0243]

[0244] In the formula, This is the preset timing correction coefficient.

[0245] As one implementation method, It can be set to 0.05-0.3; this embodiment uses... Please provide an explanation.

[0246] It should be noted that when the data changes are small at multiple consecutive detection times of the target construction unit, the overall time series fluctuation T is small, and the time series stability correction coefficient is appropriate. Approaching 1, the time-series stability correction coefficient increases as the fluctuation of continuous detection data increases.

[0247] Thus, the time-series stability correction coefficient corresponding to the target construction unit is obtained.

[0248] Step S008: Obtain the first corrected mass deviation.

[0249] Step S008: Obtain the first corrected quality deviation for each construction unit based on the initial quality evaluation quantity, construction process correction coefficient, environmental correction coefficient, and time-series stability correction coefficient.

[0250] It should be noted that the aforementioned initial quality evaluation quantity is mainly obtained based on the construction quality inspection results and data reliability, while the construction process correction coefficient, environmental correction coefficient, and time series stability correction coefficient reflect the impact of construction process anomalies, construction environment disturbances, and the stability of continuous test results on the construction quality status, respectively.

[0251] Therefore, the above-mentioned different correction factors are integrated with the initial quality evaluation quantity to obtain the first corrected quality deviation quantity that more completely reflects the abnormal quality state of the target construction unit.

[0252] Specifically, the first corrected quality deviation corresponding to the target construction unit is obtained according to the following formula. :

[0253]

[0254] In the formula, This is the initial quality assessment metric. This is a correction factor for the construction process. This is the environmental correction factor. This is a time-stability correction factor. This is a normalization function that maps the calculation results to a preset range of mass deviation values.

[0255] In one implementation, the first corrected mass deviation can be limited to between 0 and 1, when If the result is greater than 1, set the corresponding result to 1; otherwise, keep the original calculation result.

[0256] Right now:

[0257]

[0258] It should be noted that when no obvious abnormalities are found in the construction process, construction environment, and timing, , as well as Both are close to 1, at which point the first corrected quality deviation is mainly determined by the initial quality evaluation value.

[0259] When the quality inspection results are abnormal, and at the same time there are abnormalities in the construction process, environmental conditions, or unstable continuous test results, the corresponding first correction quality deviation will be further increased.

[0260] At this point, the first corrected quality deviation for each construction unit is obtained.

[0261] Step S009: Obtain the spatial anomaly correction coefficient and the final mass deviation.

[0262] Step S009: Obtain the spatial anomaly correction coefficient based on the difference in the first corrected quality deviation between the target construction unit and its adjacent construction units, and use the spatial anomaly correction coefficient to obtain the final quality deviation.

[0263] It should be noted that municipal roads, pipelines, and bridges typically have a clear spatial continuity. When the construction techniques, materials, and environment are basically the same, the overall quality of adjacent construction units usually does not change drastically.

[0264] If the quality deviation of a certain construction unit is significantly higher than that of the adjacent construction units, it indicates that the construction unit may have local material abnormalities, local construction process abnormalities, or construction quality defects.

[0265] Therefore, the present invention further utilizes the spatial differences between adjacent construction units to correct the quality evaluation.

[0266] Specifically, construction units that are adjacent to the target construction unit and / or belong to the same continuous construction section are identified as adjacent construction units of the target construction unit.

[0267] For example, in road engineering, adjacent construction units along the road extension direction of the target road construction unit can be regarded as adjacent construction units; if necessary, adjacent lane construction units located on the same transverse section can also be regarded as adjacent construction units.

[0268] Obtain the first corrected quality deviation for all adjacent construction units.

[0269] The first corrected quality deviation of all adjacent construction units is sorted to obtain the corresponding median value. .

[0270] Furthermore, based on the first corrected quality deviation and median value corresponding to each adjacent construction unit... The absolute values ​​between them yield the absolute median difference. .

[0271] Specifically, it is expressed as follows:

[0272]

[0273] In the formula, This is the first corrected quality deviation corresponding to the j-th adjacent construction unit.

[0274] The spatial anomaly A is obtained based on the difference between the first corrected mass deviation of the target construction unit and the median value of the adjacent construction units:

[0275]

[0276] In the formula, This represents the first corrected quality deviation corresponding to the target construction unit. This is the median value of the first corrected quality deviation of adjacent construction units. The absolute median difference of the first corrected quality deviation of adjacent construction units.

[0277] It should be noted that this invention uses the median and absolute median difference instead of the mean and standard deviation, which can reduce the impact of outliers from a few adjacent construction units on the calculation of spatial anomalies.

[0278] When the first corrected mass deviation of the target construction unit is close to the overall level of the adjacent construction unit, the spatial anomaly A is small; when the first corrected mass deviation of the target construction unit deviates significantly from the adjacent construction unit, the spatial anomaly A increases.

[0279] Furthermore, the spatial outlier A can be normalized to avoid excessively large correction results from a single outlier.

[0280] The spatial anomaly correction coefficient corresponding to the target construction unit is obtained according to the following formula. .

[0281]

[0282] In the formula, These are preset parameters for correcting spatial anomalies.

[0283] As one implementation method, It can be set to 0.05-0.3; this embodiment uses... Please provide an explanation.

[0284] The first quality deviation is corrected based on the spatial anomaly correction coefficient to obtain the final quality deviation corresponding to the target construction unit. .

[0285]

[0286] In the formula, The value range is 0-1.

[0287] It should be noted that when there is no significant spatial abrupt change between the target construction unit and its adjacent construction units, The value approaches 1 when the target construction unit exhibits a significant anomaly relative to its surrounding construction units. Increase, thereby increasing the final quality deviation.

[0288] Thus, the final quality deviation for each construction unit in the municipal engineering project to be evaluated is obtained.

[0289] Step S010: Obtain the construction quality score, construction quality grade, and abnormal indicators.

[0290] Step S010: Obtain the construction quality score of the corresponding construction unit based on the final quality deviation, and further determine the construction quality level and abnormal construction quality detection indicators.

[0291] Specifically, the construction quality score S corresponding to the target construction unit is obtained according to the following formula:

[0292]

[0293] In the formula, S represents the construction quality score of the target construction unit. This represents the final quality deviation corresponding to the target construction unit.

[0294] because The value range of is 0 to 1, therefore the value range of the construction quality score S is 0 to 100.

[0295] It should be noted that the smaller the final quality deviation, the higher the construction quality score; the larger the final quality deviation, the lower the construction quality score.

[0296] Furthermore, multiple construction quality level thresholds are preset, and the construction quality level of the corresponding construction unit is obtained based on the relationship between the construction quality score and the construction quality level threshold.

[0297] As one implementation method, the first quality level threshold can be set to 90, the second quality level threshold to 75, and the third quality level threshold to 60.

[0298] when: At that time, the target construction unit was designated as excellent.

[0299] when: At that time, the target construction unit is determined to be of qualified level;

[0300] when: At that time, the target construction unit was identified as the level to be re-inspected;

[0301] when: At that time, the target construction unit will be classified as unqualified.

[0302] It should be noted that the above-mentioned quality grade threshold is only one specific implementation method, and those skilled in the art can adjust the quality grade threshold according to the quality acceptance standards of different municipal engineering projects.

[0303] Furthermore, in order to determine the main anomaly detection indicators that affect the final quality results of the target construction unit, the quality deviation, data reliability, and indicator weights corresponding to each construction quality detection indicator were obtained.

[0304] In one implementation, the initial anomaly contribution corresponding to the i-th construction quality inspection index is obtained according to the following formula. :

[0305]

[0306] The initial anomaly contribution values ​​corresponding to all construction quality inspection indicators are normalized to obtain the quality anomaly contribution value corresponding to the i-th construction quality inspection indicator:

[0307]

[0308] In the formula, This represents the contribution value of quality anomalies corresponding to the i-th construction quality inspection index.

[0309] It should be noted that when construction quality inspection indicators have a large quality deviation, high data reliability, and high indicator weight, their contribution value for quality anomalies is usually large.

[0310] The construction quality testing indicators are ranked from largest to smallest based on their contribution value to quality anomalies.

[0311] A threshold for abnormal contribution is preset, and construction quality inspection indicators whose abnormal contribution value is greater than the threshold are identified as abnormal construction quality inspection indicators.

[0312] Meanwhile, the re-inspection priority is determined based on the ranking of each abnormal construction quality detection indicator, with the construction quality detection indicator with the larger the contribution value of the quality abnormality being the higher the re-inspection priority.

[0313] For example, if the quality anomaly contribution values ​​for compaction, smoothness, and structural layer thickness in the target road construction unit are 0.46, 0.31, and 0.15 respectively, and the quality anomaly contribution values ​​for the other test indicators are all below 0.08, then compaction can be prioritized as the first-level re-inspection indicator, smoothness as the second-level re-inspection indicator, and structural layer thickness as the third-level re-inspection indicator.

[0314] Therefore, this invention can not only provide the overall quality level of the target construction unit, but also further identify the main construction quality inspection indicators that lead to the reduction of the quality score of the construction unit, which facilitates construction management personnel to conduct re-inspection, cause analysis and rework for abnormal indicators.

[0315] The above steps complete a quality assessment method for municipal engineering construction.

[0316] To further illustrate the quality assessment process of this invention, the following explanation uses the quality assessment of municipal road base construction as an example.

[0317] Assume that the road base course to be evaluated is divided into multiple construction units along the road extension direction, and the length of each construction unit is set to 50m.

[0318] For each construction unit, four construction quality test data were obtained: compaction degree, structural layer thickness, flatness, and elevation.

[0319] Simultaneously, the number of times the road roller compacts, the compaction speed, and the paving temperature of the mixture are acquired as construction process data, and the ambient temperature, ambient humidity, and rainfall during the corresponding construction period are acquired as construction environment data.

[0320] One of the construction units is designated as the target construction unit.

[0321] Assume the construction quality inspection data corresponding to the target construction unit is as follows:

[0322] detection indicators Detection value Standard value Allowable deviation compaction 94.5% 96% 2% Structural layer thickness 148mm 150mm 5mm flatness 8mm 6mm 3mm Elevation deviation 7mm 0mm 10mm

[0323] According to the method corresponding to step S002, the quality deviation of the above four construction quality inspection indicators is obtained respectively.

[0324] The mass deviation corresponding to the compaction degree is approximately:

[0325]

[0326] The mass deviation corresponding to the thickness of the structural layer is approximately:

[0327]

[0328] The mass deviation corresponding to flatness is approximately:

[0329]

[0330] The elevation deviation corresponds to a mass deviation of approximately:

[0331]

[0332] This yields the quality deviation vector corresponding to the target construction unit:

[0333]

[0334] Furthermore, the data missing rate, coefficient of variation of repeated testing, and calibration deviation of testing equipment corresponding to the above-mentioned different construction quality testing indicators are obtained, and the corresponding data reliability is obtained through step S003.

[0335] Assuming that the compaction test data is complete, repeated tests are stable, and the testing equipment is calibrated, the reliability of the compaction data is relatively high. However, if the multiple test data corresponding to the flatness testing equipment fluctuate significantly, the reliability of the data will decrease accordingly.

[0336] Further, the weights of the indicators are determined based on their importance levels, and the initial quality evaluation is obtained by combining the quality deviation and data reliability. .

[0337] After obtaining the construction process data of the target construction unit, if it is found that the specified number of compaction times is 6 to 8 times, while the actual average number of compaction times of the target construction unit is 5 times, then the deviation of the construction process corresponding to the number of compaction times is greater than 0.

[0338] Historical construction data shows a strong correlation between the number of compaction passes and the degree of compaction. Furthermore, the current deviation in the compaction quality of the target construction unit is significant. Therefore, the influence quantity P of the construction process corresponding to the target construction unit increases, thereby increasing the construction process correction coefficient. Greater than 1.

[0339] Further data on temperature, humidity, and rainfall during the construction period of the target construction unit were obtained. When all of the above environmental parameters are within the allowable construction environment range, the comprehensive environmental impact E is low, therefore an environmental correction factor is needed. Close to 1.

[0340] Acquire detection data for multiple consecutive detection times of the target construction unit. When the compaction degree shows significantly low values ​​in multiple consecutive detection results and the detection data exhibits large fluctuations, the overall time-series fluctuation T increases, thereby increasing the time-series stability correction coefficient. Increase.

[0341] according to , , as well as Obtain the first corrected mass deviation .

[0342] Next, obtain the first corrected mass deviation corresponding to the adjacent construction units before and after the target construction unit. If the overall first corrected mass deviation of the adjacent construction units is small, but the first corrected mass deviation corresponding to the target construction unit is significantly larger, then the corresponding spatial anomaly A increases, and the spatial anomaly correction coefficient increases. It increases accordingly.

[0343] This yields the final quality deviation corresponding to the target construction unit. This allows us to further obtain the construction quality score S and the corresponding construction quality level.

[0344] Meanwhile, the quality anomaly contribution values ​​of different construction quality inspection indicators are ranked. When the quality anomaly contribution value corresponding to compaction degree is the highest, compaction degree is determined as the primary abnormal construction quality inspection indicator for that construction unit, and the re-inspection priority of compaction degree is increased.

[0345] Therefore, this invention enables joint analysis of quality inspection results with the reliability of inspection data, construction process anomalies, environmental disturbances, time variations, and spatial differences. Compared to threshold judgment based solely on a single quality inspection result, it can more comprehensively reflect the actual construction quality status of the target construction unit.

[0346] Another embodiment of the present invention provides a quality assessment system for municipal engineering construction, the system including a data acquisition module, a quality deviation calculation module, a data reliability calculation module, an initial evaluation module, a process correction module, an environmental correction module, a time series correction module, a first correction module, a spatial anomaly correction module, and a quality result output module.

[0347] The data acquisition module is used to acquire several construction units of the municipal engineering project to be evaluated, as well as the construction quality inspection data, construction process data, construction environment data and construction quality standard data corresponding to each construction unit.

[0348] The quality deviation calculation module is used to obtain the quality deviation corresponding to each construction quality inspection index based on the construction quality inspection data and construction quality standard data, and to construct a quality deviation vector based on the quality deviation corresponding to different construction quality inspection indicators.

[0349] The data credibility calculation module is used to obtain the degree of data missing, the degree of dispersion of repeated testing, and the calibration deviation of testing equipment in the construction quality inspection data, and to obtain the data credibility corresponding to each construction quality inspection index based on the degree of data missing, the degree of dispersion of repeated testing, and the calibration deviation of testing equipment.

[0350] The initial evaluation module is used to obtain the initial quality evaluation quantity based on the quality deviation, data reliability, and indicator weight of each construction quality inspection indicator.

[0351] The process correction module is used to obtain the deviation amount of the construction process based on the degree of deviation between the construction process data and the preset construction process benchmark data, and to obtain the construction process correction coefficient based on the degree of correlation between the construction process parameters and the construction quality inspection indicators.

[0352] The environmental correction module is used to obtain the environmental disturbance amount based on the degree of deviation between the construction environment data and the preset construction environment benchmark data, and to obtain the environmental correction coefficient based on the environmental sensitivity between the environmental parameters and the construction quality detection indicators.

[0353] The timing correction module is used to obtain a timing stability correction coefficient based on the degree of change in construction quality inspection data obtained by the same construction unit at multiple consecutive inspection times.

[0354] The first correction module is used to obtain the first corrected quality deviation based on the initial quality evaluation quantity, the construction process correction coefficient, the environmental correction coefficient, and the time-series stability correction coefficient.

[0355] The spatial anomaly correction module is used to obtain the difference between the first corrected quality deviation between the target construction unit and the adjacent construction unit, and to obtain the spatial anomaly correction coefficient based on the difference, and to obtain the final quality deviation corresponding to the target construction unit based on the spatial anomaly correction coefficient.

[0356] The quality result output module is used to obtain a construction quality score based on the final quality deviation, determine the construction quality level of the corresponding construction unit based on the relationship between the construction quality score and the preset quality level threshold, and further determine the abnormal construction quality detection indicators and the re-inspection priority based on the contribution of different construction quality detection indicators to the final quality deviation.

[0357] Furthermore, the quality assessment system for municipal engineering construction provided by the present invention may also include a memory and a processor, wherein the memory stores a computer program that can run on the processor.

[0358] When the computer program is executed by the processor, the processor performs the following operations:

[0359] Obtain several construction units in the municipal engineering project to be evaluated, as well as the construction quality inspection data, construction process data, construction environment data, and construction quality standard data corresponding to each construction unit;

[0360] The quality deviation is obtained based on the detected value, standard value, and allowable deviation, and a quality deviation vector is constructed.

[0361] Data reliability is determined based on the degree of data missingness, the degree of dispersion in repeated detections, and the calibration deviation of the detection equipment.

[0362] The initial quality evaluation value is obtained based on the quality deviation, data reliability, and indicator weights.

[0363] The construction process correction coefficient is obtained based on the construction process data.

[0364] The environmental correction factor is obtained based on the construction environment data;

[0365] The time-series stability correction coefficient is obtained based on the construction quality inspection data from multiple consecutive inspection times.

[0366] The first corrected quality deviation is obtained based on the initial quality evaluation quantity, the construction process correction coefficient, the environmental correction coefficient, and the time-series stability correction coefficient.

[0367] The spatial anomaly correction coefficient and the final quality deviation are obtained based on the differences between the target construction unit and adjacent construction units;

[0368] The construction quality score and grade are obtained based on the final quality deviation, and the abnormal construction quality detection indicators and re-inspection priorities are determined.

[0369] It should be noted that the above functional modules can be implemented by software programs or by a combination of software and hardware. The specific division of each functional module is only for illustrating the corresponding function and does not limit the function to be implemented by independent hardware structures.

[0370] This invention achieves a unified description of quality inspection indicators with different dimensions by using quality deviation, reduces the impact of abnormal and unreliable inspection data on the comprehensive evaluation results by improving data reliability, and further uses construction process correction coefficients, environmental correction coefficients, and temporal stability correction coefficients to perform multi-level corrections on the initial quality evaluation results. Then, it combines the spatial differences between adjacent construction units to obtain the final quality deviation, so that the obtained construction quality assessment results can simultaneously reflect the construction results, construction process, construction environment, temporal stability, and spatial continuity.

[0371] Ultimately, by using construction quality scores and quality anomaly contribution values, we can not only determine the construction quality level of different construction units, but also further identify the main construction quality inspection indicators that lead to a decline in construction quality and their re-inspection priorities. This will facilitate construction management personnel to conduct targeted quality re-inspections and construction quality control in abnormal construction areas.

[0372] The above description is merely a preferred embodiment of the present invention. Any equivalent substitutions, modifications, or improvements made by those skilled in the art based on the disclosure of this invention without departing from the inventive concept should fall within the protection scope of this invention.

[0373] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended embodiments and their equivalents.

Claims

1. A quality assessment method for municipal engineering construction, characterized in that, Includes the following steps: Acquire several construction units of the municipal engineering project to be evaluated, and acquire construction quality inspection data, construction process data, construction environment data and construction quality standard data corresponding to each construction unit. The construction quality standard data shall at least include the standard values ​​and allowable deviations corresponding to different construction quality inspection indicators. Based on the test value, corresponding standard value and allowable deviation of each construction quality test indicator, the quality deviation of each construction quality test indicator in each construction unit is obtained, and a quality deviation vector is constructed based on the quality deviation of each construction quality test indicator. The degree of missing test data, the degree of dispersion of repeated tests, and the calibration deviation of test equipment corresponding to each construction quality test indicator are obtained. Based on the degree of missing test data, the degree of dispersion of repeated tests, and the calibration deviation of test equipment, the data reliability corresponding to each construction quality test indicator is obtained. Based on the quality deviation, data reliability, and index weight of each construction quality inspection index, the initial quality evaluation quantity for each construction unit is obtained. The deviation amount of the construction process is obtained based on the degree of deviation between the construction process data and the preset construction process benchmark data, and the environmental disturbance amount is obtained based on the degree of deviation between the construction environment data and the preset construction environment benchmark data; the construction process correction coefficient is obtained based on the degree of correlation between the construction process deviation amount and each construction quality inspection index, and the environmental correction coefficient is obtained based on the degree of correlation between the environmental disturbance amount and each construction quality inspection index. Based on the degree of change in construction quality inspection data obtained by the same construction unit at multiple consecutive inspection times, the time-series stability correction coefficient of the corresponding construction unit is obtained; Based on the initial quality evaluation quantity, construction process correction coefficient, environmental correction coefficient, and time-series stability correction coefficient, the first corrected quality deviation of each construction unit is obtained; The difference between the first corrected mass deviation of the target construction unit and its adjacent construction units is obtained. Based on the difference, the spatial anomaly correction coefficient of the target construction unit is obtained. Based on the spatial anomaly correction coefficient, the first corrected mass deviation of the target construction unit is corrected to obtain the final mass deviation. The construction quality score of the corresponding construction unit is obtained based on the final quality deviation, and the construction quality level is determined based on the relationship between the construction quality score and the preset quality level threshold. At the same time, the abnormal construction quality detection index is determined based on the contribution of each construction quality detection index to the final quality deviation.

2. The quality assessment method for municipal engineering construction according to claim 1, characterized in that, The method for obtaining the quality deviation corresponding to each construction quality inspection index includes: Let any construction unit be denoted as the target construction unit, and let the detection value corresponding to the i-th construction quality inspection index of the target construction unit be denoted as... The corresponding standard value is denoted as The corresponding allowable deviation is denoted as ;according to: Obtain the quality deviation corresponding to the i-th construction quality inspection index. ; In the formula, These are preset non-zero constants; According to the preset arrangement order of each construction quality inspection index, all quality deviations are combined to form the quality deviation vector of the target construction unit: Where n is the number of construction quality inspection indicators included in the target construction unit.

3. The quality assessment method for municipal engineering construction according to claim 1, characterized in that, The method for obtaining the data reliability corresponding to each construction quality inspection index includes: Obtain the data missing rate of the i-th construction quality inspection indicator within the preset inspection period. ; The coefficient of variation for repeated testing is obtained based on the results of multiple repeated tests of the i-th construction quality inspection index. ; Obtain the calibration deviation between the current calibration result and the standard calibration result of the corresponding testing equipment. ; according to: in, , as well as These are the preset data missing impact coefficient, repeated detection impact coefficient, and calibration deviation impact coefficient, respectively.

4. The quality assessment method for municipal engineering construction according to claim 1, characterized in that, The method for obtaining the initial quality evaluation value for each construction unit based on the quality deviation, data reliability, and index weight of each construction quality inspection index includes: The initial weights of each construction quality testing indicator are determined based on the allowable deviations of each indicator and the importance level of the corresponding indicator in the municipal engineering acceptance standards. The weights of all initial indicators are normalized to obtain the indicator weight corresponding to the i-th construction quality inspection indicator. ; according to: Obtain the initial quality evaluation quantity corresponding to the target construction unit. ; in, Let be the quality deviation corresponding to the i-th construction quality inspection index. Let represent the data reliability corresponding to the i-th construction quality inspection.

5. A quality assessment method for municipal engineering construction according to claim 1, characterized in that, The method for obtaining the construction process correction coefficient includes: Obtain the actual values ​​of different construction process parameters and the corresponding benchmark construction intervals during the construction of the target construction unit; When the actual value of the construction process parameter is within the corresponding benchmark construction range, the process deviation of the corresponding construction process parameter is set to zero. When the actual value of the construction process parameter is outside the corresponding benchmark construction interval, the corresponding process deviation is obtained based on the difference between the actual value and the nearest boundary value of the corresponding benchmark construction interval and the width of the benchmark construction interval. Obtain the correlation coefficients between each construction process parameter and each construction quality inspection index in the historical construction samples, and construct a construction process quality correlation matrix based on the correlation coefficients; The construction process influence is obtained based on the process deviation of the target construction unit, the construction process quality correlation matrix, and the quality deviation of each construction quality inspection index. ; according to: Obtain the construction process correction coefficient corresponding to the target construction unit. ; in, This is a preset correction factor for the construction process.

6. The quality assessment method for municipal engineering construction according to claim 1, characterized in that, The method for obtaining the environmental correction coefficient includes: Acquire at least one environmental parameter during the construction of the target construction unit, wherein the environmental parameter includes one or more of ambient temperature, ambient humidity, rainfall, and wind speed; The environmental deviation is obtained by determining the degree of deviation between the actual value of each environmental parameter and the corresponding benchmark environmental range. The environmental sensitivity coefficients between different environmental parameters and different construction quality testing indicators are obtained based on historical construction quality testing data. The comprehensive environmental impact E of the target construction unit is obtained based on each environmental deviation and the corresponding environmental sensitivity coefficient; according to: Obtain the environmental correction factor corresponding to the target construction unit. ; in, This is the preset environmental correction factor.

7. The quality assessment method for municipal engineering construction according to claim 1, characterized in that, The method for obtaining the time-stability correction coefficient includes: For each construction quality inspection index of the target construction unit, obtain the detection values ​​corresponding to multiple consecutive detection times within a preset time window; The temporal fluctuation of the corresponding construction quality testing index is obtained by using the average and standard deviation of multiple consecutive test values. The total time-series fluctuations are weighted and integrated based on the weights of each construction quality inspection indicator to obtain the comprehensive time-series fluctuation T of the target construction unit. according to: Obtain the timing stability correction coefficient ,in This is the preset timing correction coefficient.

8. A quality assessment method for municipal engineering construction according to claim 1, characterized in that, The method for obtaining the first corrected quality deviation for each construction unit includes: based on: Obtain the first corrected quality deviation corresponding to the target construction unit. ; in, This is the initial quality evaluation value. This is a correction factor for the construction process. This is the environmental correction factor. This is a time-stability correction factor. This is a normalization function that maps the calculation results to a preset range of mass deviation values.

9. A quality assessment method for municipal engineering construction according to claim 1, characterized in that, The method for obtaining the spatial anomaly correction coefficient and the final mass deviation includes: Construction units that are adjacent to the target construction unit and / or belong to the same continuous construction section are identified as adjacent construction units of the target construction unit. Obtain the first corrected mass deviation for each adjacent construction unit, and obtain the median and absolute median difference of the first corrected mass deviation for all adjacent construction units; The spatial anomaly is obtained based on the difference between the first corrected mass deviation of the target construction unit and the median value: In the formula, This is the median value of the first corrected quality deviation of adjacent construction units. The absolute median difference of the first corrected quality deviation of adjacent construction units; according to: Obtain the spatial anomaly correction coefficient for the target construction unit. ; And according to: Obtain the final quality deviation corresponding to the target construction unit. .

10. A quality assessment method for municipal engineering construction according to claim 1, characterized in that, The method for obtaining a construction quality score and determining abnormal construction quality detection indicators based on the final quality deviation includes: according to: To obtain the construction quality score S of the target construction unit; Based on the relationship between the construction quality score S and multiple preset construction quality level thresholds, the target construction unit is divided into at least one of the following construction quality levels: excellent, qualified, pending re-inspection, and unqualified. The quality deviation, data reliability, and corresponding index weight of each construction quality inspection index are obtained respectively. Based on the quality deviation, data reliability, and index weight, the quality anomaly contribution value of each construction quality inspection index to the final quality deviation is obtained. The construction quality inspection indicators are sorted from largest to smallest according to their quality anomaly contribution value. The construction quality inspection indicators whose quality anomaly contribution value exceeds the preset anomaly contribution threshold are identified as abnormal construction quality inspection indicators. The re-inspection priority of each abnormal construction quality inspection indicator is determined according to the sorting.

11. A quality assessment system for municipal engineering construction, characterized in that, include: The data acquisition module is used to acquire several construction units of the municipal engineering project to be evaluated, as well as the construction quality inspection data, construction process data, construction environment data and construction quality standard data corresponding to each construction unit; The quality deviation calculation module is used to obtain the quality deviation amount corresponding to each construction quality inspection index and construct the quality deviation vector based on construction quality inspection data and construction quality standard data. The data credibility calculation module is used to obtain the data credibility of each construction quality inspection index based on the degree of data missingness, the degree of dispersion of repeated inspections, and the calibration deviation of the inspection equipment. The initial evaluation module is used to obtain the initial quality evaluation quantity based on the quality deviation, data reliability, and indicator weight of each construction quality inspection indicator. The process correction module is used to obtain the construction process correction coefficient based on the degree of deviation between the construction process data and the preset construction process benchmark data, as well as the degree of correlation between the construction process parameters and the construction quality inspection indicators. The environmental correction module is used to obtain environmental correction coefficients based on the degree of deviation between construction environment data and preset construction environment benchmark data, as well as the degree of correlation between environmental parameters and construction quality inspection indicators. The timing correction module is used to obtain the timing stability correction coefficient based on the degree of change in construction quality inspection data at multiple consecutive inspection times of the same construction unit. The first correction module is used to obtain the first corrected quality deviation based on the initial quality evaluation quantity, the construction process correction coefficient, the environmental correction coefficient, and the time-series stability correction coefficient. The spatial anomaly correction module is used to obtain the spatial anomaly correction coefficient based on the difference between the first corrected quality deviation between the target construction unit and the adjacent construction unit, and to obtain the final quality deviation based on the spatial anomaly correction coefficient. It also includes a quality result output module, which is used to obtain the construction quality score and construction quality grade based on the final quality deviation, and to determine the abnormal construction quality detection indicators and re-inspection priorities based on the contribution of each construction quality detection indicator to the final quality deviation.

12. A quality assessment system for municipal engineering construction according to claim 11, characterized in that, The system includes a memory, a processor, and a computer program stored in the memory and capable of running on the processor. When the computer program is executed by the processor, it implements the steps of a quality assessment method for municipal engineering construction as described in any one of claims 1-10.

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