CN-121996898-A - Data analysis early warning method and system for concrete defect detection

CN121996898ACN 121996898 ACN121996898 ACN 121996898ACN-121996898-A

Abstract

The invention relates to a data analysis early warning method and a system for concrete defect detection, wherein the method comprises the steps of dividing a concrete detection area, arranging defect detection equipment, setting scientific monitoring periods, collecting abnormal data detected in each period and tracing a source mark; and constructing a tracing sample set and a tracing behavior matrix based on the abnormal data, calculating regional center early warning weights among different detection devices, determining an early warning relation according to the weights, counting the behavior proportion and generating a sequenced early warning table. The system comprises a data acquisition and tracing mark, a tracing sample set construction, a tracing behavior matrix construction, weight calculation, early warning relation determination and early warning table generation module and a main control unit. The method realizes systematic integration and association analysis of the concrete defect detection data, reduces the manual screening cost, improves the pertinence and timeliness of defect early warning, and provides a quick response decision for the safety maintenance of the concrete structure.

Inventors

WEI KUIYE
SONG XINJIANG
ZHU SHIBIN

Assignees

安徽省（水利部淮河水利委员会）水利科学研究院（安徽省水利工程质量检测中心站）

Dates

Publication Date: 20260508
Application Date: 20260121

Claims (10)

1. The invention discloses a data analysis and early warning method for concrete defect detection, which is characterized by comprising the following steps of: s1, dividing a concrete detection area, arranging defect detection equipment, setting defect monitoring periods according to a concrete defect development rule, collecting and feeding back detection abnormal index items in each defect monitoring period in real time, and tracing and marking the defect detection equipment for feeding back the detection abnormal index items; S2, counting the detection abnormality index items of each defect detection device in different defect monitoring periods, and constructing a traceable sample set of each defect detection device corresponding to different defect monitoring periods; S3, a tracing behavior matrix is established based on the tracing sample set, the mapping relation between the tracing sample set and the tracing behavior matrix is clarified, the detection area where each defect detection device is located is taken as the center of the simulation area, and the area center early warning weight between the defect detection device and other defect detection devices is calculated; S4, determining related early warning objects and early warning relations among the defect detection devices according to the regional center early warning weight, counting the number of times of behavior of each defect detection device which is confirmed to be the related early warning object when the defect detection device is used as the simulation regional center, and generating a data analysis early warning table according to the proportion sequence and outputting the data analysis early warning table.
2. The strong interference environment holographic enhancement system generated based on reverse diffusion of claim 1, wherein S1 comprises the steps of: s11, dividing a detection area based on a concrete structure, and arranging defect detection equipment in the corresponding detection area based on the concrete structure characteristics and the working condition characteristics of the detection area; S12, presetting a defect monitoring period, wherein the defect monitoring period is formulated based on a defect development rule presented by the concrete structure influenced by the use environment and the structure type; S13, recording and collecting detection abnormality index items fed back by each defect detection device in each defect monitoring period in real time to form a corresponding abnormality triggering feedback set in each defect monitoring period, and carrying out tracing marking on the defect detection devices fed back with the detection abnormality index items to form an abnormality feedback tracing feature.
3. The method for analyzing and pre-warning the concrete defect detection data according to claim 2, wherein the step S2 comprises the following steps: s21, constructing an abnormal trigger feedback set corresponding to the defect monitoring period, wherein the abnormal trigger feedback set is as follows: , wherein, Is the first An anomaly triggering feedback set for each defect monitoring period, R and E respectively represent the defect detection equipment and the code sequence numbers of the detected anomaly index items, For the e-th detection of an abnormality index item, Is the first A defect detection device is provided for detecting the defects of the object, Is the first A defect monitoring period; S22, based on an anomaly triggering feedback set, counting abnormal detection index items fed back by each defect detection device in different defect monitoring periods to form a tracing sample set, wherein the tracing sample set is as follows: Wherein, the Representing defect detection apparatus During the defect monitoring period And the tracing sample set is formed when the internal feedback detects abnormal index items.
4. The method for analyzing and pre-warning data for detecting concrete defects according to claim 3, wherein S3 comprises the following steps: S31, constructing a tracing behavior matrix based on the tracing sample set, wherein the line number corresponds to the coding sequence number of the defect monitoring period, the column number corresponds to the coding sequence number of the detection abnormal index item, and the mapping relation between the tracing sample set and the tracing behavior matrix is formed, if the detection abnormal index item exists in the tracing sample set, the tracing behavior matrix is obtained Line 1 The matrix element value of the column is marked as 1, and if the detected abnormal index item does not exist in the tracing sample set, the tracing behavior matrix is the first Line 1 The matrix element value of the column is marked as 0; s32, obtaining a tracing behavior matrix of the defect detection device based on the mapping relation between the tracing sample set and the tracing behavior matrix; s33, based on the traceability behavior matrix, taking a detection area where the defect detection equipment is located as a simulation area center of the concrete structure, and evaluating area center early warning weights between the defect detection equipment and the defect detection equipment; the calculation formula of the regional center early warning weight is as follows: Wherein, the Representing an xth defect detection apparatus Corresponding to the generated tracing behavior matrix, and x is not equal to r, Representing defect detection apparatus Is a traceable behavior matrix of (1) And defect detection apparatus Is a traceable behavior matrix of (1) The number of 1's included after the logical AND operation, Representing defect detection apparatus Is a traceable behavior matrix of (1) And defect detection apparatus Is a traceable behavior matrix of (1) The number of 1's included after the exclusive OR operation.
5. The method for analyzing and pre-warning the concrete defect detection data according to claim 4, wherein the step S4 comprises the following steps: s41, determining an early warning relation among defect detection equipment based on the regional center early warning weight; The early warning relation is as follows: wherein argmax is a feedback function for determining defect detection equipment corresponding to the simulation area center when the area center early warning weight is maximum, locking early warning relation among the defect detection equipment, and the defect detection equipment The corresponding simulation area center is defect detection equipment Related early warning objects of (2); s42, statistics defect detection equipment As the center of the simulation area, the behavior frequency ratio of the related early warning object is confirmed, and the behavior frequency ratio is the defect detection equipment Corresponding behavior times account for each defect detection device The ratio of the sum of the corresponding behavior times; s43, sequencing the defect detection devices according to the order of the times of behavior from high to low, generating a data analysis early warning table and outputting the data analysis early warning table to a worker port.
6. A data analysis and early warning system for concrete defect detection is characterized by comprising the following components: The data acquisition and tracing marking module is used for dividing a concrete detection area, arranging defect detection equipment, setting defect monitoring periods according to a concrete defect development rule, collecting detection abnormal index items in each defect monitoring period in real time, and tracing the defect detection equipment feeding back abnormal indexes; The traceability sample set construction module is used for counting detection abnormal index items of each defect detection device in different defect monitoring periods and constructing traceability sample sets of each defect detection device corresponding to different defect monitoring periods; The traceability behavior matrix construction and weight calculation module is used for establishing a traceability behavior matrix based on the traceability sample set, defining the mapping relation between the traceability sample set and the traceability behavior matrix, and calculating the regional center early warning weight between each defect detection device and other defect detection devices by taking the detection region where the defect detection device is located as the simulation regional center; And the early warning relation determining and early warning table generating module is used for determining related early warning objects and early warning relations among the defect detection devices according to the regional center early warning weight, counting the number of times of behavior of each defect detection device which is confirmed to be the related early warning object when the defect detection device is used as the simulation regional center, and generating and outputting a data analysis early warning table according to the order of the number of times of behavior.
7. The data analysis and early warning system for concrete defect detection according to claim 6, wherein the data acquisition and traceability marking module comprises: the detection area dividing and equipment laying unit is used for dividing detection areas according to the concrete structural characteristics and the working condition characteristics and laying corresponding defect detection equipment in each area; the monitoring period setting unit is used for setting a defect monitoring period based on a defect development rule of the concrete structure affected by the use environment and the structure type; The abnormal data collection unit is used for recording and collecting detection abnormal index items fed back by each defect detection device in each monitoring period in real time; And the tracing marking unit is used for tracing the defect detection equipment for feeding back the detection abnormal index item to form an abnormal feedback tracing characteristic.
8. The data analysis and early warning method for concrete defect detection according to claim 7, wherein the traceability sample set construction module comprises: The abnormal index statistics unit is used for counting abnormal index items to be detected fed back by each defect detection device in different defect monitoring periods based on the abnormal trigger feedback set; And the traceability sample set generating unit is used for constructing a traceability sample set containing feedback abnormal index items for each defect detection device in the corresponding defect monitoring period.
9. The method for analyzing and pre-warning data for concrete defect detection according to claim 8, wherein the traceability behavior matrix construction and weight calculation module comprises: The traceability behavior matrix construction unit is used for constructing a traceability behavior matrix of which the line number corresponds to the monitoring period and the column number corresponds to the abnormal index item based on the traceability sample set, and determining the mapping relation between the sample set and the matrix; and the regional center early warning weight calculation unit is used for calculating regional center early warning weights between the defect detection equipment and other detection equipment by taking the detection region where the defect detection equipment is located as the simulation regional center.
10. The method for analyzing and pre-warning data for concrete defect detection according to claim 9, wherein the pre-warning relation determining and pre-warning table generating module comprises: The early warning relation determining unit is used for determining related early warning objects and early warning relations among the defect detection devices based on the regional center early warning weight; the behavior duty ratio statistics unit is used for counting the number of times of behavior duty ratio of the related early warning object confirmed when each defect detection device is used as the center of the simulation area; The early warning table generation and output unit is used for sequencing the behavior times according to the proportion from large to small, generating a data analysis early warning table and outputting the data analysis early warning table to the worker port.

Description

Data analysis early warning method and system for concrete defect detection Technical Field The invention relates to the technical field of concrete defect detection, in particular to a data analysis and early warning method and system for concrete defect detection. Background The concrete structure is widely applied to various projects such as sluice, pump station, gravity dam, arch dam, bridge, tunnel, high-rise building and the like, and the structural safety of the concrete structure is directly related to the overall stability and service life of the project. The timely discovery and early warning of concrete defects (such as cracks, insufficient strength, abnormal water content and the like) are key links for guaranteeing structural safety. The existing concrete defect detection technology has the defects that firstly, data acquisition is scattered, single equipment is relied on for monitoring or manual inspection is carried out, all areas of a large-scale concrete structure are difficult to be covered with defect data omission, secondly, data analysis lacks systematicness, the acquired abnormal data does not establish association with detection equipment and a monitoring period, defect sources and development trends are difficult to trace, thirdly, an early warning mechanism is imperfect, workers need to manually screen massive data, a great deal of time and effort are consumed, subjective factors are easy to influence, early warning lag or pertinence is insufficient, and fourthly, association analysis among detection equipment is not established, potential large-scale defect risks cannot be captured through abnormal association of equipment in different areas, and defect monitoring requirements of the large-scale and complex concrete structure are difficult to meet. Disclosure of Invention The invention provides a data analysis early warning method and a data analysis early warning system for concrete defect detection, which aim to solve the technical problems of data dispersion, low analysis efficiency and early warning lag in the prior art. In order to achieve the purpose, the invention adopts the following technical scheme that the data analysis and early warning method for concrete defect detection comprises the following steps: s1, dividing a concrete detection area, arranging defect detection equipment, setting defect monitoring periods according to a concrete defect development rule, collecting and feeding back detection abnormal index items in each defect monitoring period in real time, and tracing and marking the defect detection equipment for feeding back the detection abnormal index items; S2, counting the detection abnormality index items of each defect detection device in different defect monitoring periods, and constructing a traceable sample set of each defect detection device corresponding to different defect monitoring periods; S3, a tracing behavior matrix is established based on the tracing sample set, the mapping relation between the tracing sample set and the tracing behavior matrix is clarified, the detection area where each defect detection device is located is taken as the center of the simulation area, and the area center early warning weight between the defect detection device and other defect detection devices is calculated; S4, determining related early warning objects and early warning relations among the defect detection devices according to the regional center early warning weight, counting the number of times of behavior of each defect detection device which is confirmed to be the related early warning object when the defect detection device is used as the simulation regional center, and generating a data analysis early warning table according to the proportion sequence and outputting the data analysis early warning table. Preferably, the step S1 includes the following steps: s11, dividing a detection area based on a concrete structure, and arranging defect detection equipment in the corresponding detection area based on the concrete structure characteristics and the working condition characteristics of the detection area; S12, presetting a defect monitoring period, wherein the defect monitoring period is formulated based on a defect development rule presented by the concrete structure affected by the use environment and the structure type; S13, recording and collecting detection abnormality index items fed back by each defect detection device in each defect monitoring period in real time to form a corresponding abnormality triggering feedback set in each defect monitoring period, and carrying out tracing marking on the defect detection devices fed back with the detection abnormality index items to form an abnormality feedback tracing feature. Preferably, the step S2 includes the steps of: s21, constructing an abnormal trigger feedback set corresponding to the defect monitoring period, wherein the abnormal trigger feedback set is as follows: , wherein, Is the firstAn