CN-120461570-B - Intelligent maintenance method and system for self-repairing concrete material

Abstract

The invention discloses an intelligent maintenance method and system for self-repairing concrete materials, and relates to the technical field of concrete material maintenance, wherein the intelligent maintenance method comprises the steps of acquiring electrophysiological response data and image data of a plurality of preset path sections on a crack path, extracting a density value of a repairing product and a microorganism activation time point and response intensity, judging whether microorganism inactivation or path blockage exists based on a time difference and an intensity difference of adjacent path sections, judging a repairing state by combining the density value and the response intensity, and generating and outputting maintenance strategy instructions according to the density value and the response intensity; the method has the advantages that electrophysiological response and repair product density of each section of the crack can be monitored in real time, microbial activity and path blocking state can be dynamically judged, and a targeted maintenance instruction can be generated, so that the problem that the repair process is uncontrollable in the prior art is solved, and the method has the advantages of improving repair efficiency and stability.

Inventors

• ZHANG HUI
• CHEN GUANGLI

Assignees

• 中国十五冶金建设集团有限公司

Dates

Publication Date

20260505

Application Date

20250707

Claims (10)

1. 1. The intelligent maintenance method of the self-repairing concrete material is characterized by comprising the following steps of: Acquiring electrophysiology response data sets and corresponding image data of a plurality of preset path segments along a target fracture path; extracting corresponding repair product density values according to the image data of each preset path segment; Extracting the microbial activation time points and response intensity of each preset path segment according to the electrophysiological response data set; Judging whether a microorganism inactivation state or a path blocking situation exists or not based on the microorganism activation time difference and the response intensity difference of the adjacent preset path segments; Judging the current repair state of each preset path segment according to the density value of the repair product and the electrophysiological response intensity; Generating corresponding maintenance strategy instructions according to the current repair state of each preset path segment and whether microorganism inactivation or path blocking exists or not, and And outputting the maintenance strategy instruction to an instruction execution end.
2. 2. The intelligent curing method of a self-repairing concrete material according to claim 1, wherein the extracting the corresponding repair product density value comprises: Carrying out graying treatment on the image data to obtain a gray image; Image segmentation is carried out on the gray level image, and a repair product area is identified; Calculating the pixel ratio of the repair product region in the image and the average gray value of the region; carrying out weighted summation on the pixel duty ratio and the average gray value according to a preset weighting coefficient to obtain an image density index; And mapping the image density index with a preset image-density mapping model to obtain a repair product density value corresponding to the path segment.
3. 3. The intelligent maintenance method of self-repairing concrete material according to claim 1, wherein the extracting the microbial activation time point and response intensity of each preset path segment comprises: performing time sequence analysis on the electrophysiological response data set, and identifying the time point when the potential change occurs for the first time in each preset path section as a microorganism activation time point; And calculating the average electrophysiological response amplitude of the preset path segment after the microorganism activation as the response intensity of the preset path segment.
4. 4. The intelligent maintenance method of a self-repairing concrete material according to claim 1, wherein the judging whether a microorganism deactivation state or a path blocking situation exists comprises calculating a microorganism activation time difference and a response intensity difference between adjacent preset path segments; judging whether the activation time difference is larger than a preset time threshold value and whether the response intensity difference is higher than a preset difference threshold value, if the activation time difference is larger than the preset time threshold value or the response intensity difference is lower than the preset difference threshold value, judging that the path is blocked; And if the electrophysiological response of the preset path section in the preset time interval is lower than the preset response amplitude threshold value and microorganisms of the preset path section adjacent to the electrophysiological response are activated, judging that the microorganisms of the path section are deactivated.
5. 5. The intelligent maintenance method of a self-repairing concrete material according to claim 4, wherein the determining the current repairing state of each preset path segment comprises: if the density of the repair product is higher than a preset density threshold value and the response intensity is lower than a preset response threshold value, judging that the repair state of the preset path segment is repair completion; If the density of the repair product is higher than the preset density threshold value and the response intensity is higher than the preset response threshold value, judging that the repair state of the path segment is in repair; and if the density of the repair product is lower than the preset density threshold and the response intensity is lower than the preset response threshold, judging that the repair state of the path segment is repair stagnation.
6. 6. The intelligent curing method of a self-repairing concrete material according to claim 5, wherein the generating the corresponding curing policy instructions comprises: if the repair state of the preset path segment is repair completion, generating a maintenance stopping instruction; if the repair state of the preset path section is repair, generating a maintenance instruction for maintaining water and carbon source supply; If the repair state of the preset path segment is repair stagnation, generating a maintenance instruction for enhancing the water supply of the preset path segment; When the preset path section is blocked, generating a maintenance instruction for dredging the preset path section; and when the preset path section has microbial deactivation, generating a re-inoculated maintenance instruction.
7. 7. The intelligent curing method of a self-repairing concrete material according to claim 6, further comprising: recording the microorganism activation times of each preset path section and the accumulated density value of the corresponding repair product; And when the microbial activation times exceed a preset activation times threshold value and the accumulated density value of the repair product does not reach a preset standard density threshold value, generating an early warning signal for prompting the self-repair capacity of the path segment to be exhausted.
8. 8. An intelligent maintenance system for self-repairing concrete materials, which is applied to the method as claimed in any one of claims 1 to 7, and is characterized by comprising the following steps: The data acquisition module is used for acquiring electrophysiology response data sets and corresponding image data of a plurality of preset path segments on the target fracture path; The repair product density extraction module is used for extracting a corresponding repair product density value according to the image data of each preset path segment; The microbial response extraction module is used for extracting the microbial activation time points and response intensity of each preset path segment according to the electrophysiological response data set; the crack state judging module is used for judging whether a microbial deactivation state or a path blocking situation exists or not based on the microbial activation time difference and the response intensity difference of the adjacent preset path segments; the restoration state judging module is used for judging the current restoration state of each preset path segment according to the restoration product density value and the electrophysiological response intensity; The maintenance strategy generation module is used for generating corresponding maintenance strategy instructions according to the current repair state of each preset path segment and whether microorganism inactivation or path blocking exists; And the execution instruction output module is used for outputting the maintenance strategy instruction to the instruction execution end.
9. 9. An electronic device comprising a memory and a processor, wherein the memory is configured to store computer-executable instructions and the processor is configured to execute the computer-executable instructions, the computer-executable instructions when executed by the processor performing the steps of the method according to any one of claims 1 to 7.
10. 10. A computer storage medium having stored thereon computer executable instructions which when executed by a processor perform the steps of the method according to any of claims 1 to 7.

Description

Intelligent maintenance method and system for self-repairing concrete material Technical Field The invention relates to the technical field of concrete material curing, in particular to an intelligent curing method and system for a self-repairing concrete material. Background Concrete is a widely used structural material in construction engineering, has higher strength and durability, but in the long-term use process, particularly under the influence of stress or environmental change, the concrete structure is inevitably cracked. These cracks not only affect the mechanical properties of the concrete, but also provide channels for the intrusion of moisture, gases and harmful substances, thereby accelerating the deterioration of the concrete, and possibly compromising the safety and the service life of the structure in severe cases. In recent years, microbial self-repairing concrete materials have become a hot spot for research in order to extend the service life and improve the durability of concrete. The material fills the cracks by utilizing specific microorganisms such as alkali-resistant bacillus and the like to mineralize and deposit calcium carbonate in the cracks, so that a self-healing function is realized, microbial spores are in a dormant state in the concrete for a long time, and only when the cracks occur, moisture and air enter, the microbial spores are activated to start metabolism and generate active repair products, so that the cracks are closed. However, the existing microbial self-repairing concrete material still has the following problems in practical application that due to complex environmental conditions inside the crack, microbial activity is not only influenced by external supply conditions such as moisture, carbon sources and the like, but also limited by geometric complexity of a crack path and uncertainty of physiological states of the microorganism, for example, a blocking area possibly exists inside the crack to block penetration of moisture and nutrients, so that the activation degree of the microorganism is uneven in different path sections, and the repairing reaction distribution is discontinuous, so that the repairing activity of the microorganism is difficult to continuously and uniformly exert. The heterogeneity and uncertainty obviously reduce the overall repair efficiency and stability, and restrict the practical application effect of the material in complex engineering structures. Therefore, an intelligent maintenance method and system for the self-repairing concrete material are provided. Disclosure of Invention The present application has been made in view of the above-mentioned state of the art. The embodiment of the application provides an intelligent maintenance method and an intelligent maintenance system for a self-repairing concrete material, which can improve the crack repairing efficiency and stability. According to one aspect of the application, an intelligent curing method of a self-repairing concrete material is provided, which comprises the steps of obtaining electrophysiological response data sets and corresponding image data of a plurality of preset path sections along a target crack path, extracting corresponding repairing product density values according to the image data of each preset path section, extracting microorganism activation time points and response intensity of each preset path section according to the electrophysiological response data sets, judging whether a microorganism deactivation state or a path blocking situation exists or not based on microorganism activation time differences and response intensity differences of adjacent preset path sections, judging the current repairing state of each preset path section according to the repairing product density values and the electrophysiological response intensity, generating corresponding curing strategy instructions according to the current repairing state of each preset path section and whether the microorganism deactivation or the path blocking situation exists, and outputting the curing strategy instructions to an instruction execution end. According to another aspect of the application, an intelligent curing system for self-repairing concrete materials is provided, which comprises a data acquisition module, a repair product density extraction module, a microorganism response extraction module, a crack state judgment module, a repair state judgment module and a curing strategy generation module, wherein the data acquisition module is used for acquiring electrophysiological response data sets and corresponding image data of a plurality of preset path sections along a target crack path, the repair product density extraction module is used for extracting corresponding repair product density values according to the image data of each preset path section, the microorganism response extraction module is used for extracting microorganism activation time points and response intensity of each pres