CN115047142A - Method and system for analyzing tunnel lining quality - Google Patents
Method and system for analyzing tunnel lining quality Download PDFInfo
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Abstract
The invention discloses a method for analyzing tunnel lining quality, which comprises the following steps: collecting internal and apparent detection data of the lining and calibrating lining states at different positions; performing cause analysis on the defects inside and outside the lining and determining the degradation level; performing correlation analysis on the internal and external defect combinations according to the internal and external defect states and causes of the lining; fusing data characteristics obtained from the two types of analysis results by adopting a data fusion technology according to internal and apparent detection data of the lining under different lining conditions to construct a tunnel lining quality diagnosis model; and evaluating the quality of the target lining by applying a tunnel lining quality diagnosis model. The invention develops the comprehensive analysis of the influence of the lining state, reveals the correlation between the internal defects and the apparent defects of the tunnel lining, and improves the comprehensive analysis capability of the tunnel lining quality.
Description
Technical Field
The invention relates to the technical field of tunnel lining quality detection, in particular to a method and a system for analyzing tunnel lining quality.
Background
The tunnel lining can effectively support tunnel surrounding rocks, maintain the stable structure of the tunnel and ensure the safety of driving in the tunnel. The tunnel lining is influenced by factors such as tunnel design, construction process and material quality, the tunnel lining has quality defects possibly, tunnel lining diseases occur in specific time under the action of conditions such as stress redistribution, temperature and humidity change and pneumatic load, and the tunnel lining diseases need to be detected and evaluated in time to guide the treatment and maintenance of the tunnel lining diseases.
At present, the evaluation of the quality state of the tunnel lining in China is mainly carried out by adopting an expert evaluation method according to standard procedures such as ' degradation evaluation of buildings of railway bridges and tunnels ' (TB/T2820.2, 2 nd part of tunnels) ' monitoring and evaluation procedures of key bridges and tunnels of national highway networks ' (T/CECSG: E41-04-2019) ' maintenance technical standards of urban rail transit tunnel structures ' (CJJ/T289-2018) '.
In the aspect of comprehensive analysis of tunnel lining quality, in the prior art, lining degradation levels are independently determined according to different indexes such as insufficient lining thickness, cavities, incompact lining, cracks, water leakage and the like, and then experts are used for qualitatively or semi-quantitatively evaluating the quality degradation state of the whole tunnel lining by synthesizing various lining defect degradation levels. But are less involved in research programs regarding the intrinsic association between both apparent and internal diseases.
Disclosure of Invention
It is an object of the present invention to provide a tunnel lining quality analysis scheme capable of mining the inherent link between internal defects and apparent defects of a tunnel lining.
In order to solve the technical problem, an embodiment of the present invention provides a method for analyzing tunnel lining quality, including: collecting internal and apparent detection data of the lining and calibrating lining states at different positions; performing cause analysis on the defects inside and outside the lining and determining the quality degradation level; performing correlation analysis on the internal and external defect combinations according to the internal and external states and causes of the lining; fusing data characteristics obtained from the two types of analysis results by adopting a data fusion technology according to the internal and apparent detection data of the lining under different lining conditions to construct a tunnel lining quality diagnosis model; and evaluating the quality of the target lining by applying the tunnel lining quality diagnosis model.
Preferably, in the step of performing cause analysis on defects inside and outside the brick, the method comprises the following steps: classifying the internal defect types and the external defect types of the linings at different positions in a grading way according to the internal and apparent detection data of the lining and the corresponding lining states, thereby counting the internal and external defect types and quality degradation grades of the linings at different positions; the internal and external defect causes of the lining at different positions are analyzed from the three aspects of construction quality type, stress type and degradation type.
Preferably, in the step of performing correlation analysis on the combination of the internal and external defects according to the states and causes of the internal and external defects of the lining, the correlation analysis comprises the following steps: according to the combination of the internal and external defect states and causes of the lining at different positions, the common characteristics and related parameters are extracted, and independent factors and related factors influencing the expression form of the internal and external defects of the current lining quality are determined.
Preferably, in the process of constructing the tunnel lining quality diagnosis model, the method comprises the following steps: and based on the internal and apparent detection data of the lining under different lining conditions, fusing the internal and external defect types, the degradation grade, the defect cause, the independent factors and the associated factors of the lining at different positions, and constructing a tunnel lining quality diagnosis model based on multi-source heterogeneous information, wherein the lining conditions comprise but are not limited to hydrological characteristics, geological characteristics, material characteristics, equipment structures, type characteristics and construction processes.
Preferably, the method further comprises: and providing a tunnel lining maintenance scheme based on the lining quality state evaluation result.
Preferably, when the tunnel lining quality diagnosis model is applied to evaluate the quality of a target lining, the defect type and the quality degradation grade of the target lining are determined, and key factors influencing the lining quality are further determined, so that the space-time characteristics of lining diseases caused by defects are evaluated.
Preferably, in the step of collecting internal and apparent inspection data of the lining, the method comprises the following steps: collecting lining internal detection data and lining apparent detection data; preprocessing the internal detection data and the apparent detection data of the lining; and calibrating the lining state including the defect type, the defect development scale and the defect boundary for the pretreated lining internal detection data and lining apparent detection data.
Preferably, geological radar technology and/or ultrasonic detection technology are/is adopted to collect detection data inside the lining; and acquiring apparent detection data of the lining by adopting an image shooting and/or three-dimensional laser scanning technology.
Preferably, preprocessing including gain, filtering, deconvolution, static correction and offset is performed on the lining internal detection data collected by the geological radar technology; the apparent image acquired by image capturing is subjected to preprocessing including distortion correction, image enhancement, resolution adjustment, and threshold segmentation.
In another aspect, an embodiment of the present invention further provides a system for analyzing quality of a tunnel lining, including: the information collection module is configured to collect internal and apparent detection data of the lining and calibrate lining states at different positions; a single analysis module configured to perform cause analysis on the intra-and-outer-of-brick defects and determine a quality degradation level; the correlation analysis module is configured to perform correlation analysis on the internal and external defect combinations according to the internal and external states and causes of the lining; the model construction module is configured to fuse data characteristics obtained by the two types of analysis results by adopting a data fusion technology according to the internal and apparent detection data of the lining under different lining conditions, so as to construct a tunnel lining quality diagnosis model; a model application module configured to apply the tunnel lining quality diagnosis model to evaluate a quality of a target lining.
Compared with the prior art, one or more embodiments in the above scheme can have the following advantages or beneficial effects:
the invention provides a method and a system for analyzing tunnel lining quality. The method and the system integrate various factors influencing lining quality and lining internal detection and apparent detection data, and have the following effects:
(1) according to the invention, various factors related to the lining quality are considered, including environmental factors such as hydrological conditions and geological conditions of the tunnel lining, construction factors such as materials, equipment and processes involved in the construction process, and internal detection and apparent detection data acquired by carrying out lining quality detection after the lining is built, and multi-source heterogeneous data formed by the factors represent various information of different dimensions such as defect cause and external appearance, so that a data base is provided for effective tunnel lining quality comprehensive analysis;
(2) on the basis of carrying out single analysis according to lining states and spatial distribution rules of various types of defects, the method analyzes statistical rules of spatial symbiosis of different internal defects and apparent defect types, extracts correlation factors and independent factors influencing lining quality based on correlation analysis, and realizes automatic classification of lining degradation levels based on a machine learning algorithm.
(3) The invention adopts the data fusion technology to carry out feature extraction and fusion analysis on various information with different dimensions, such as lining defect cause, performance and the like, constructs a tunnel lining quality diagnosis model based on multisource heterogeneous information, and realizes quantitative tunnel lining quality comprehensive analysis.
(4) According to the invention, the evaluation of the tunnel lining state is realized based on the comprehensive analysis of the lining quality of multi-source information fusion, and further, a lining maintenance scheme suggestion is proposed to guide the lining maintenance construction and ensure the tunnel operation safety.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
fig. 1 is a step diagram of a method for analyzing tunnel lining quality according to an embodiment of the present application.
Fig. 2 is an overall technical roadmap of a method for analyzing tunnel lining quality according to an embodiment of the present application.
Fig. 3 is a flowchart of a preparation process of a tunnel lining defect database in the method for analyzing tunnel lining quality according to the embodiment of the present application.
Fig. 4 is a block diagram of a system for analyzing tunnel lining quality according to an embodiment of the present application.
Detailed Description
The following detailed description will be given with reference to the accompanying drawings and examples to explain how to apply the technical means to solve the technical problems and to achieve the technical effects. It should be noted that, as long as there is no conflict, the embodiments and the features of the embodiments of the present invention may be combined with each other, and the technical solutions formed are within the scope of the present invention.
Additionally, the steps illustrated in the flow charts of the figures may be performed in a computer system such as a set of computer-executable instructions. Also, while a logical order is shown in the flow diagrams, in some cases, the steps shown or described may be performed in an order different than here.
Effective lining quality detection and evaluation is beneficial to accurately judging the quality of concrete structures, guiding the regulation and maintenance of lining diseases and ensuring the operation safety of tunnels. At present, the lining quality evaluation is mainly to independently determine the deterioration grade of the lining according to different types of lining defects, then the deterioration state of the whole tunnel lining is comprehensively evaluated qualitatively or semi-quantitatively by experts, the efficiency and the precision are low, and the internal relation between the apparent defects and the internal defects cannot be revealed.
In order to clarify key factors influencing the tunnel lining quality, mine the correlation and the void characteristics between the apparent defects and the internal defects, and accurately evaluate structural defects possibly caused by lining defects, the embodiment of the application provides a method and a system for tunnel lining quality. The method and the system are based on multi-source mass data obtained by internal detection and apparent detection of tunnel lining quality, and are used for analyzing the lining state according to indexes such as insufficient lining thickness, cavities, incompact lining, cracks, water leakage and the like in a fusion manner, developing correlation analysis of internal defects and apparent defects of the tunnel lining, excavating internal relations between the internal defects and the apparent defects of the tunnel lining, and achieving the purposes of comprehensive analysis, mutual evidence and improvement of interpretation capability. The comprehensive analysis method for the tunnel lining quality provided by the invention is beneficial to accurately judging the quality of a concrete structure, defining the mechanical service state, guiding the lining disease treatment and maintenance and further ensuring the tunnel operation safety.
Fig. 1 is a step diagram of a method for analyzing tunnel lining quality according to an embodiment of the present application. As shown in fig. 1, a method for analyzing quality of a tunnel lining (hereinafter, referred to as "lining quality analyzing method") according to an embodiment of the present invention includes the steps of: step S110, collecting internal and apparent detection data of the lining and calibrating lining states at different positions; step S120, performing cause analysis on the defects inside and outside the lining and determining the quality degradation level; step S130, performing correlation analysis on the internal and external defect combinations according to the internal and external states and causes of the lining; step S140, fusing data characteristics obtained from the two types of analysis results of the step S130 and the step S140 by adopting a data fusion technology according to the internal and apparent detection data of the lining under different lining conditions, and constructing a tunnel lining quality diagnosis model; and S150, evaluating the quality of the target lining by applying a tunnel lining quality diagnosis model.
Fig. 2 is an overall technical roadmap of the method for analyzing tunnel lining quality according to the embodiment of the present application. A specific flow of the lining quality analysis method according to the embodiment of the present invention will be described with reference to fig. 1 and fig. 2.
In step S110, first, the internal lining detection data and the apparent lining detection data at different positions need to be collected, and then, the corresponding lining states are calibrated in the internal lining at different positions and the corresponding lining states are calibrated in the apparent lining at different positions, so as to finally form a tunnel lining defect large data set.
Fig. 3 is a flowchart of a preparation process of a tunnel lining defect database in the method for analyzing tunnel lining quality according to the embodiment of the present application. As shown in fig. 3, the process of collecting the internal and apparent defect data of the lining includes: firstly, a construction site needs to be determined for a data acquisition field test, so that corresponding detection and data processing modes are determined according to two aspects of internal defects and apparent defects of the lining according to the field condition of a selected work point. Specifically, the method comprises the steps of firstly collecting lining internal detection data at different positions and lining apparent detection data at different positions, then preprocessing the lining internal detection data at different positions and the lining apparent detection data at different positions, and calibrating the lining state at the corresponding positions according to the preprocessed lining internal detection data and the preprocessed lining apparent detection data, so that the interpretation of the internal and external defects of the lining at different positions is completed. Wherein the lining conditions include, but are not limited to: defect type, defect development scale, and defect boundaries. Defect types include, but are not limited to: voids, lack of compaction, lack of thickness, cracks and water leakage.
Further, in the embodiment of the invention, geological radar technology and/or ultrasonic detection technology are adopted to collect the internal detection data of the lining at different positions. In addition, the apparent detection data of the lining at different positions are collected by adopting image shooting and/or three-dimensional laser scanning technology.
In a first preprocessing example, the lining interior detection data collected by geological radar technology is preprocessed, including gain, filtering, deconvolution, statics, and offset.
In the second preprocessing example, preprocessing including distortion correction, image enhancement, resolution adjustment, and threshold segmentation is performed on an apparent image acquired by image capturing.
Therefore, in step S110 of the invention, based on a large number of tunnel lining quality detection engineering practices and field tests, a lining internal defect data set is obtained by means of ground penetrating radar and other technologies, a tunnel lining apparent defect data set is obtained by means of apparent shooting and other technologies, the property states such as the type and scale of lining defects are calibrated according to manual interpretation, expert judgment and other modes, the collection and preparation of a tunnel lining defect big data set are completed, and then the step S120 is carried out.
Step S120, firstly, according to the detection data of the interior of the lining at each position and the lining defect state corresponding to the detection data, performing cause analysis on the interior defects of the lining at different positions, determining the quality degradation level of the interior of the lining at each position, and according to the detection data of the appearance of the lining at each position and the lining defect state corresponding to the detection data, performing cause analysis on the appearance defects of the lining at different positions, and determining the quality degradation level of the appearance of the lining at each position.
Further, in the process of analyzing the cause of the internal defects and the apparent defects of the lining at different positions, firstly, the internal defect types and the external defect types of the lining at different positions are classified in a grading way according to the internal and apparent detection data of the lining and the corresponding lining state, so that the internal and external defect types and the defect grades of the lining at different positions are counted. Specifically, according to internal detection data and corresponding lining states of the lining at different positions collected in a tunnel lining defect big data set, and apparent detection data and corresponding lining states of the lining at different positions, the category grade of the internal defect of each position lining (the grade of the defect condition of the current position in the defect type) and the category grade of the apparent defect of each position lining are determined, and finally, according to different lining types, the spatial geometric distribution rule of each lining type is counted, namely, the distribution states of the internal lining and the external lining of each lining type at different positions of the tunnel and the spatial distribution state of category grade information of the lining type are determined.
After the analysis of the single defect distribution is completed, step S120 further needs to analyze the cause of the internal defect of the lining at different positions and the cause of the apparent (external) defect of the lining at different positions from the three causes of the construction quality type, the stress type and the degradation type, so as to further determine the quality degradation level of the internal defect of the lining at different positions and the quality degradation level of the external (apparent) defect of the lining at different positions according to the detection data of the internal and external defects of the lining at different positions, the lining state, the category level and the cause analysis result.
Specifically, according to theoretical analysis, practical experience and field investigation conditions, from the three aspects of construction quality type, stress type and degradation type, the cause influencing the internal lining state of the current position and the cause influencing the apparent lining state of the current position are analyzed according to the combination condition of the internal and external defect types of different positions, and the influence degree of the position on the structural state of the whole tunnel is determined to be classified into grades, namely the quality degradation grade inside the current position and the apparent quality degradation grade according to the single defect type and the cause of the internal defect and the apparent defect of the lining of different positions. Further, in determining the cause of the internal or apparent lining state at each position, one selected from construction quality, stress, and deterioration is selected.
Accordingly, after the single-type cause analysis of the defect of the tunnel lining is performed, the process proceeds to step S130. Step S130 continues to analyze the correlation between the internal and external defects of the tunnel lining based on the cause analysis result and the degradation level distribution condition.
In step S130, according to the combination of the internal and external defect types and causes of the lining at different positions, the common characteristics and the related parameters are extracted, and the independent factors and the related factors affecting the current internal and external defect expression form of the lining quality are determined. Further, according to the combination of the internal defect type and the apparent defect type of the lining at different positions and the combination of the internal defect cause and the apparent defect cause, the common characteristic and the related parameters which affect the defect combination at the position are extracted, and further aiming at each lining position, the independent factors (including the factors which affect the internal defect at the current position and the factors which affect the apparent defect at the current position) which affect the internal defect type and the external defect type combination and the related factors which simultaneously affect the combination of the internal defect type and the apparent defect type are determined.
Specifically, based on construction quality conditions, stress conditions and material characteristics, expression forms of internal defects and apparent defects of the lining under different internal and external defect types and cause combination conditions are contrastively analyzed, correlation analysis is performed on the internal defects and the apparent defects by combining lining defect states, common characteristics and relevant parameters are extracted, and independent factors and related factors which influence the expression forms of the internal and external defects of the current lining are clearly determined.
Next, after the correlation analysis of the internal and external defects is completed, the process proceeds to step S140. Step S140, a multi-source information fusion lining quality diagnosis model is constructed.
In step S140, based on the internal and apparent detection data of the lining under different lining conditions, the internal and external defect types, quality degradation levels, defect causes, category levels, independent factors, and associated factors of the lining at different positions are fused, and a tunnel lining quality diagnosis model based on multi-source heterogeneous information is constructed. Lining conditions include, but are not limited to: hydrological characteristics, geological characteristics, material characteristics, equipment structure and type characteristics and construction process.
That is to say, in the embodiment of the present invention, the constructed tunnel lining quality diagnosis model can be used to directly convert the collected various lining condition information and internal and external detection data of the target lining position to be evaluated into the lining quality evaluation result. Wherein, the lining quality evaluation result at least comprises the types of the internal and external defects, the quality degradation grades of the internal and external defects, the causes of the internal and external defects, the category grades of the internal and external defects, the independent factors of the internal and external defects and the related factors between the internal and external defects.
Further, after the construction of the multi-source information fusion lining quality diagnosis model is completed, the process proceeds to step S150. And S150, performing quality evaluation on the target lining by using the tunnel lining quality diagnosis model so as to obtain a lining quality evaluation result.
In step S150, the internal defect type and quality degradation level, the apparent defect type and quality degradation level of the target lining are determined, and the key factors (the cause, independent factors and related factors of the internal and external defects) affecting the lining state are further determined, so as to evaluate the spatiotemporal characteristics of the lining diseases caused by the current defects and the combination of the internal and external defects thereof.
In addition, in order to improve the integrity and expandability of the lining quality analysis method, the lining quality analysis method according to the embodiment of the present invention further includes: and providing a tunnel lining maintenance scheme according to the lining quality evaluation result obtained by the tunnel lining quality diagnosis model. That is, based on the lining quality status assessment, a relevant suggestion for a tunnel lining maintenance repair plan is made.
To sum up, the lining quality analysis method according to the embodiment of the present invention comprehensively considers various factor conditions such as hydrology, geology, materials, equipment, and processes that affect the tunnel lining quality according to the logic sequence and the mode of step-by-step progression of the levels, develops the comprehensive analysis of the lining defect state influence based on the observation data of the tunnel lining internal detection and apparent detection technical means, reveals the correlation between the tunnel lining internal defect and the apparent defect, forms an effective tunnel lining quality comprehensive analysis method, and improves the tunnel lining quality comprehensive analysis capability.
Based on the lining quality analysis method, the embodiment of the invention also provides a system for analyzing the quality of the tunnel lining (also called a lining quality analysis system). Fig. 4 is a block diagram of a system for analyzing tunnel lining quality according to an embodiment of the present application. As shown in fig. 4, a lining quality analyzing system according to an embodiment of the present invention includes: an information collection module 41, a single item analysis module 42, an association analysis module 43, a model construction module 44, and a model application module 45.
Specifically, the information collecting module 41 is implemented according to the method described in the above step S110, and is configured to collect internal and apparent detection data of the lining and calibrate the lining state at different positions; the single item analysis module 42, implemented as described above in step S120, is configured to perform cause analysis on the defects inside and outside the lining and determine the degradation level; the correlation analysis module 43 is implemented according to the method described in the above step S130, and is configured to perform correlation analysis on the internal and external defect combinations according to the internal and external states and causes of the lining; the model construction module 44 is implemented according to the method in the step S140, and is configured to fuse the data features obtained from the two types of analysis results according to the internal and apparent detection data of the lining under different lining conditions by using a data fusion technique, so as to construct a tunnel lining quality diagnosis model; the model application module 45 is implemented according to the method described in the above step S150, and is configured to evaluate the quality of the target lining by using the tunnel lining quality diagnosis model.
The invention discloses a method and a system for analyzing tunnel lining quality. The method and the system integrate various factors influencing lining quality and lining internal detection and apparent detection data, and have the following effects:
(1) the invention considers a plurality of factors related to lining quality, including environmental factors such as hydrological conditions and geological conditions of tunnel lining, construction factors such as materials, equipment and processes involved in the construction process, and internal detection and apparent detection data collected by developing lining quality detection after lining is built, wherein multi-source heterogeneous data formed by the factors represent a plurality of information of different dimensions such as defect cause, external expression and the like, and provides a data base for effective tunnel lining quality comprehensive analysis;
(2) on the basis of carrying out single analysis according to the lining defect states and the spatial distribution rules of various types of defects, the invention analyzes the statistical rules of the spatial symbiosis of different internal defects and apparent defect types, extracts the correlation factors and the independent factors influencing the lining quality based on the correlation analysis, and realizes the automatic classification of the lining degradation grade based on the machine learning algorithm.
(3) The invention adopts a data fusion technology to carry out feature extraction and fusion analysis on various information with different dimensions such as lining defect cause, performance and the like, constructs a tunnel lining quality diagnosis model based on multi-source heterogeneous information, and realizes quantitative tunnel lining quality comprehensive analysis.
(4) According to the invention, the evaluation of the tunnel lining state is realized based on the comprehensive analysis of the lining quality of multi-source information fusion, and further, a lining maintenance scheme suggestion is proposed to guide the lining maintenance construction and ensure the tunnel operation safety.
The above description is only a preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.
It is to be understood that the disclosed embodiments of this invention are not limited to the particular structures, process steps, or materials disclosed herein but are extended to equivalents thereof as would be understood by those ordinarily skilled in the relevant arts. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to be limiting.
Reference in the specification to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the invention. Thus, the appearances of the phrase "one embodiment" or "an embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment.
Although the embodiments of the present invention have been described above, the above description is only for the convenience of understanding the present invention, and is not intended to limit the present invention. It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. A method for analyzing tunnel lining quality, comprising:
collecting internal and apparent detection data of the lining and calibrating lining states at different positions;
performing cause analysis on the defects inside and outside the lining and determining the quality degradation level;
performing correlation analysis on the internal and external defect combinations according to the internal and external states and causes of the lining;
fusing data characteristics obtained from the two types of analysis results by adopting a data fusion technology according to the internal and apparent detection data of the lining under different lining conditions to construct a tunnel lining quality diagnosis model;
and evaluating the quality of the target lining by applying the tunnel lining quality diagnosis model.
2. The method of claim 1, wherein the step of performing a causal analysis of intra-and intra-brick defects comprises:
classifying the internal defect types and the external defect types of the linings at different positions in a grading way according to the internal and apparent detection data of the lining and the corresponding lining states, thereby counting the internal and external defect types and quality degradation grades of the linings at different positions;
the internal and external defect causes of the lining at different positions are analyzed from the three aspects of construction quality type, stress type and degradation type.
3. The method of claim 2, wherein the step of performing correlation analysis on the combination of the inner and outer defects according to the states and causes of the inner and outer defects of the lining comprises:
according to the combination of internal and external defect states and causes of the lining at different positions, common characteristics and related parameters are extracted, and independent factors and related factors influencing the expression form of the internal and external defects of the current lining quality are determined.
4. The method of claim 3, wherein in the process of constructing the tunnel lining quality diagnosis model, the method comprises the following steps:
and based on the internal and apparent detection data of the lining under different lining conditions, fusing the internal and external defect types, the degradation grade, the defect cause, the independent factors and the associated factors of the lining at different positions, and constructing a tunnel lining quality diagnosis model based on multi-source heterogeneous information, wherein the lining conditions comprise but are not limited to hydrological characteristics, geological characteristics, material characteristics, equipment structures, type characteristics and construction processes.
5. The method according to any one of claims 1 to 4, further comprising: and providing a tunnel lining maintenance scheme based on the lining quality state evaluation result.
6. The method according to any one of claims 1 to 5, wherein when the tunnel lining quality diagnosis model is applied to evaluate the quality of a target lining, the defect type and the quality degradation grade of the target lining are determined, and key factors influencing the lining quality are further determined, so that the spatiotemporal characteristics of lining diseases caused by defects are evaluated.
7. The method of any one of claims 1 to 6, wherein the step of collecting internal lining and apparent inspection data comprises:
collecting lining internal detection data and lining apparent detection data;
preprocessing the internal detection data and the apparent detection data of the lining;
and calibrating the lining state including the defect type, the defect development scale and the defect boundary for the pretreated lining internal detection data and lining apparent detection data.
8. The method of claim 7,
collecting internal detection data of the lining by adopting a geological radar technology and/or an ultrasonic detection technology;
and acquiring apparent detection data of the lining by adopting an image shooting and/or three-dimensional laser scanning technology.
9. The method of claim 8,
preprocessing the lining internal detection data acquired by the geological radar technology, including gain, filtering, deconvolution, static correction and offset;
the apparent image acquired by image capturing is subjected to preprocessing including distortion correction, image enhancement, resolution adjustment, and threshold segmentation.
10. A system for analyzing tunnel lining quality, comprising:
the information collection module is configured to collect internal and apparent detection data of the lining and calibrate lining states at different positions;
a single analysis module configured to perform cause analysis on the intra-and-outer-of-brick defects and determine a quality degradation level;
the correlation analysis module is configured to perform correlation analysis on the internal and external defect combinations according to the internal and external states and causes of the lining;
the model construction module is configured to fuse data characteristics obtained by the two types of analysis results by adopting a data fusion technology according to the internal and apparent detection data of the lining under different lining conditions, so as to construct a tunnel lining quality diagnosis model;
a model application module configured to apply the tunnel lining quality diagnosis model to evaluate a quality of a target lining.
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| CN116805311A (en) * | 2023-08-18 | 2023-09-26 | 长春师范大学 | Automobile part surface defect monitoring method based on robot vision |
| CN116805311B (en) * | 2023-08-18 | 2023-11-07 | 长春师范大学 | Automobile part surface defect monitoring method based on robot vision |
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