CN115329098A - Pavement expansion and shrinkage early warning method and system - Google Patents
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Abstract
The invention discloses a road surface expansion and shrinkage early warning method and a system, which relate to the field of computer application, and the method comprises the following steps: historical pavement swelling and shrinking data are acquired based on big data, wherein the historical pavement swelling and shrinking data comprise a plurality of groups of swelling and shrinking data with time and position marks; sequentially analyzing to obtain historical expansion and shrinkage analysis results; obtaining an expansion and contraction influence factor set, wherein the expansion and contraction influence factor set comprises a plurality of expansion and contraction influence factors; constructing a road surface swelling and shrinking knowledge map; carrying out multi-dimensional data acquisition on a target road surface to obtain target road surface data; rendering to obtain a target pavement swelling and shrinking knowledge map; and performing expansion and shrinkage early warning on the target pavement based on the expansion and shrinkage knowledge graph of the target pavement. The technical problems that the pavement expansion and shrinkage problems are not found timely, the problem cannot be treated at the first time, normal use of a road is influenced, and even traffic accidents are caused in the prior art are solved. The visual and intelligent degree of the pavement swelling and shrinking early warning is improved, and the technical effects of timeliness and accuracy of the pavement swelling and shrinking early warning are further improved.
Description
Technical Field
The invention relates to the field of computer application, in particular to a pavement swelling and shrinking early warning method and system.
Background
With the continuous advance and development of science and technology, the economy of China is rapidly developed when people walk on an uphill road, and accordingly the number of traffic vehicles on a road is increased day by day. Road pavement crack and bloated crack are the main disease that influences road engineering quality, and crack and bloated crack can influence the long-term use of road appearing in the road surface, in case suffer rainstorm or surface water invasion, under the effect of vehicle load, lead to the decline of road surface intensity very easily, can induce the settlement scheduling problem moreover, very be unfavorable for driving safety. The prior art is through regularly patrolling and examining to correspond the processing to the road surface breathing condition, has the road surface breathing problem discovery untimely, and then can't deal with the very first time, influences road normal use, causes the technical problem of traffic accident even. Therefore, the real-time monitoring of the road surface expansion and shrinkage conditions by using the computer technology has important significance in improving the real-time property of finding the road surface expansion and shrinkage problems, improving the processing efficiency and the like.
However, in the prior art, the road surface expansion and shrinkage conditions are correspondingly processed through periodic inspection, the problem of road surface expansion and shrinkage is not found timely, and then the problem cannot be processed at the first time, so that the normal use of the road is influenced, and even traffic accidents are caused.
Disclosure of Invention
The invention aims to provide a pavement swelling and shrinking early warning method and a pavement swelling and shrinking early warning system, which are used for solving the technical problems that in the prior art, the pavement swelling and shrinking condition is correspondingly processed through regular inspection, the pavement swelling and shrinking problem is not found timely, the problem cannot be processed in the first time, the normal use of a road is influenced, and even traffic accidents are caused.
In view of the above problems, the present invention provides a method and a system for warning road surface expansion and contraction.
In a first aspect, the present invention provides a method for warning road surface swelling and shrinking, where the method is implemented by a system for warning road surface swelling and shrinking, and the method includes: historical road surface expansion and contraction data are collected based on big data, wherein the historical road surface expansion and contraction data comprise multiple sets of expansion and contraction data with time and position marks; analyzing the multiple sets of expansion and contraction data with time and position marks in sequence to obtain a historical expansion and contraction analysis result; obtaining an expansion and contraction influence factor set according to the historical expansion and contraction analysis result, wherein the expansion and contraction influence factor set comprises a plurality of expansion and contraction influence factors; constructing a pavement swelling and shrinking knowledge map based on the swelling and shrinking influence factors; carrying out multi-dimensional data acquisition on a target road surface to obtain target road surface data; rendering the target pavement data to the pavement swelling and shrinking knowledge map to obtain a target pavement swelling and shrinking knowledge map; and carrying out expansion and shrinkage early warning on the target road surface based on the expansion and shrinkage knowledge map of the target road surface.
In a second aspect, the present invention further provides a road surface swell-shrink early warning system, configured to execute the road surface swell-shrink early warning method according to the first aspect, where the system includes: the data acquisition module is used for acquiring historical road surface expansion and contraction data based on big data, wherein the historical road surface expansion and contraction data comprises multiple sets of expansion and contraction data with time and position marks; the data analysis module is used for sequentially analyzing the multiple sets of expansion and shrinkage data with time and position marks to obtain a historical expansion and shrinkage analysis result; the factor determining module is used for obtaining an expansion and contraction influence factor set according to the historical expansion and contraction analysis result, wherein the expansion and contraction influence factor set comprises a plurality of expansion and contraction influence factors; the map construction module is used for constructing a road surface expansion and contraction knowledge map based on the expansion and contraction influence factors; the target map early warning module, the target map early warning module includes: the target data acquisition module is used for carrying out multi-dimensional data acquisition on a target road surface to obtain target road surface data; the target map obtaining module is used for rendering the target pavement data to the pavement swelling and shrinking knowledge map to obtain a target pavement swelling and shrinking knowledge map; and the target map application module is used for carrying out expansion and shrinkage early warning on the target road surface based on the target road surface expansion and shrinkage knowledge map.
One or more technical schemes provided by the invention at least have the following technical effects or advantages:
historical road surface expansion and shrinkage data are collected based on big data, wherein the historical road surface expansion and shrinkage data comprise multiple sets of expansion and shrinkage data with time and position marks; analyzing the multiple sets of expansion and contraction data with time and position marks in sequence to obtain a historical expansion and contraction analysis result; obtaining an expansion and contraction influence factor set according to the historical expansion and contraction analysis result, wherein the expansion and contraction influence factor set comprises a plurality of expansion and contraction influence factors; constructing a pavement swelling and shrinking knowledge map based on the swelling and shrinking influence factors; carrying out multi-dimensional data acquisition on a target road surface to obtain target road surface data; rendering the target pavement data to the pavement swelling and shrinking knowledge map to obtain a target pavement swelling and shrinking knowledge map; and carrying out expansion and shrinkage early warning on the target road surface based on the expansion and shrinkage knowledge map of the target road surface. Historical road surface swelling and shrinking data are acquired by utilizing big data, a road surface swelling and shrinking knowledge map is analyzed and constructed, and then related data of a target road surface are rendered into the road surface swelling and shrinking knowledge map to obtain the target road surface swelling and shrinking knowledge map, so that the technical goal of visually displaying the real-time swelling and shrinking condition of the road surface is achieved. The expansion and shrinkage related data of the target road surface are visually displayed in real time by utilizing the expansion and shrinkage knowledge map of the target road surface, so that the visual and intelligent degrees of the pavement expansion and shrinkage early warning are improved, and the technical effects of timeliness and accuracy of the pavement expansion and shrinkage early warning are further improved.
The above description is only an overview of the technical solutions of the present invention, and the present invention can be implemented in accordance with the content of the description so as to make the technical means of the present invention more clearly understood, and the above and other objects, features, and advantages of the present invention will be more clearly understood.
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In order to more clearly illustrate the present invention or the technical solutions in the prior art, the drawings used in the embodiments or the description of the prior art will be briefly described below, it is obvious that the drawings in the following description are only exemplary, and other drawings can be obtained by those skilled in the art without inventive efforts based on the provided drawings.
FIG. 1 is a schematic flow chart of a pavement swelling and shrinking early warning method according to the present invention;
FIG. 2 is a schematic flow chart of a set of expansion and contraction influence factors established in the road surface expansion and contraction early warning method of the present invention;
FIG. 3 is a schematic flow diagram of a road surface swell-shrink knowledge graph constructed in the road surface swell-shrink early warning method of the invention;
fig. 4 is a schematic flow chart of a road surface swell-shrink knowledge element set formed in the road surface swell-shrink early warning method of the invention;
fig. 5 is a schematic structural diagram of a pavement swelling and shrinking early warning system according to the present invention.
Description of reference numerals:
the system comprises a data acquisition module M100, a data analysis module M200, a factor determination module M300, a map construction module M400, a target map early warning module M500, a target data acquisition module M510, a target map obtaining module M520 and a target map application module M530.
Detailed Description
The invention provides a road surface expansion and shrinkage early warning method and system, and solves the technical problems that in the prior art, the road surface expansion and shrinkage condition is correspondingly processed through periodic inspection, the road surface expansion and shrinkage problem is not found timely, the problem cannot be processed in the first time, the normal use of a road is influenced, and even traffic accidents are caused. The expansion and shrinkage related data of the target road surface are visually displayed in real time by utilizing the expansion and shrinkage knowledge map of the target road surface, so that the visual and intelligent degrees of the pavement expansion and shrinkage early warning are improved, and the technical effects of timeliness and accuracy of the pavement expansion and shrinkage early warning are further improved.
In the technical scheme of the invention, the data acquisition, storage, use, processing and the like all conform to relevant regulations of national laws and regulations.
In the following, the technical solutions in the present invention will be clearly and completely described with reference to the accompanying drawings, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments of the present invention, and it should be understood that the present invention is not limited by the example embodiments described herein. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without making any creative effort, shall fall within the protection scope of the present invention. It should be further noted that, for the convenience of description, only some but not all of the features relevant to the present invention are shown in the drawings.
Example one
Referring to fig. 1, the present invention provides a road surface swell-shrink early warning method, wherein the method is applied to a road surface swell-shrink early warning system, and the method specifically includes the following steps:
step S100: historical road surface expansion and contraction data are collected based on big data, wherein the historical road surface expansion and contraction data comprise multiple sets of expansion and contraction data with time and position marks;
specifically, the pavement swelling and shrinking early warning method is applied to the pavement swelling and shrinking early warning system, historical pavement swelling and shrinking data can be acquired through big data, a pavement swelling and shrinking knowledge map is analyzed and constructed, then relevant data of a target pavement is rendered into the pavement swelling and shrinking knowledge map, the target pavement swelling and shrinking knowledge map is obtained, and the goal of visually displaying real-time swelling and shrinking conditions of the pavement is achieved.
The historical road surface expansion and shrinkage data refers to recorded data acquired based on big data when expansion and shrinkage faults occur on various historical road surfaces, and the recorded data comprises road surface expansion and shrinkage faults occurring on various roads and at various times. Exemplary road expansion and contraction events, event inducements, consequences, solutions, etc. occur in a city in a certain month and a certain day of a certain year. Each time of historical road surface expansion and contraction data in the historical road surface expansion and contraction data comprises corresponding time and place of occurrence of road surface expansion and contraction, namely the historical road surface expansion and contraction data comprises multiple sets of expansion and contraction data with time and position marks. Historical road surface swelling and shrinking data are collected based on big data, and the technical effect of providing a data base for subsequently constructing a road surface swelling and shrinking knowledge map is achieved.
Step S200: sequentially analyzing the multiple sets of expansion and shrinkage data with time and position marks to obtain a historical expansion and shrinkage analysis result;
step S300: obtaining an expansion and shrinkage influence factor set according to the historical expansion and shrinkage analysis result, wherein the expansion and shrinkage influence factor set comprises a plurality of expansion and shrinkage influence factors;
further, as shown in fig. 2, step S300 of the present invention further includes:
step S310: extracting a plurality of analysis results of multiple times of historical expansion and contraction in the historical expansion and contraction analysis results;
step S320: constructing a historical swelling and shrinking index-event scatter diagram according to the plurality of analysis results, wherein the historical swelling and shrinking index-event scatter diagram comprises a plurality of index-event scatter diagrams;
further, the invention also comprises the following steps:
step S321: building a set of swelling and shrinking indexes based on big data, wherein the set of swelling and shrinking indexes comprises a plurality of swelling and shrinking indexes;
step S322: extracting index parameters of the analysis results in sequence based on the expansion and shrinkage indexes to obtain multiple groups of index parameters;
step S323: and constructing the multiple index-event scatter diagrams according to the mapping relation between the multiple groups of index parameters and the multiple times of historical swelling and shrinking, and forming the historical swelling and shrinking index-event scatter diagram.
Step S330: carrying out correlation analysis on the index-event scatter diagrams in sequence by using the SPSS to obtain a plurality of correlation analysis results;
step S340: screening results of which the correlation meets the preset correlation requirement in the multiple correlation analysis results, and reversely matching to obtain multiple indexes;
step S350: and according to the indexes, establishing the expansion and contraction influence factor set.
Specifically, before analyzing each historical road surface expansion and shrinkage event to obtain a corresponding event analysis result, firstly, obtaining indexes related to road surface expansion and shrinkage based on big data analysis, and building an expansion and shrinkage index set. And then, performing data corresponding extraction on each historical road surface expansion and contraction event based on each expansion and contraction index in the expansion and contraction index set, so as to obtain index parameters of each historical road surface expansion and contraction event, and obtain a plurality of groups of index parameters. And then constructing the multiple index-event scatter diagrams according to the mapping relation between the multiple groups of index parameters and the multiple times of historical swelling and shrinking, and forming the historical swelling and shrinking index-event scatter diagram. The method is characterized by comprising the following steps of (1) exemplarily drawing a scatter-point relation between indexes such as road materials, ambient temperature and ambient humidity when a road surface expansion and contraction event occurs and corresponding events.
Further, a plurality of analysis results of a plurality of times of historical expansion and contraction in the historical expansion and contraction analysis results are extracted, and a historical expansion and contraction index-event scatter diagram is constructed according to the plurality of analysis results, wherein the historical expansion and contraction index-event scatter diagram comprises a plurality of index-event scatter diagrams. And then, sequentially performing correlation analysis on the index-event scatter diagrams by using data processing analysis software such as SPSS (software platform service), and the like to obtain a plurality of correlation analysis results. And then screening results of which the correlation meets the preset correlation requirement in the correlation analysis results, and reversely matching to obtain a plurality of indexes. Exemplary, the indexes with significant correlation are screened to form a swelling and shrinking influence factor set.
The historical road surface swell-shrink data is analyzed, so that index factors influencing the road surface swell-shrink are obtained, the technical goal of comprehensively, scientifically and visually analyzing the road surface swell-shrink influence factors is realized, and an index factor basis is provided for the subsequent construction of a road surface swell-shrink knowledge map.
Further, as shown in fig. 3, the present invention further includes step S360:
step S361: sequentially performing data crawling on the multiple expansion and contraction influence factors by utilizing a web crawler technology to obtain a target data set;
step S362: performing word segmentation processing on target data in the target data set to obtain a data word segmentation result, wherein the data word segmentation result comprises a plurality of word segmentation texts;
step S363: screening texts meeting preset text requirements in the word segmentation texts to form a key text set;
step S364: and taking the key text set as a road surface swelling and shrinking knowledge element set, and constructing the road surface swelling and shrinking knowledge map according to the road surface swelling and shrinking knowledge element set.
Further, as shown in fig. 4, step S364 of the present invention further includes:
step S3641: obtaining a first preset word segmentation requirement;
step S3642: removing the word segmentation texts meeting the first preset word segmentation requirement in the plurality of word segmentation texts to obtain a removal result;
step S3643: obtaining a second preset word segmentation requirement;
step S3644: extracting the word segmentation texts meeting the second preset word segmentation requirement in the elimination result to obtain an extraction result;
step S3645: classifying the word segmentation texts in the extraction result to obtain word segmentation classification results, wherein the word segmentation classification results comprise concept word segmentation, attribute word segmentation and relation word segmentation;
step S3646: and taking the concept word as a concept knowledge element, taking the attribute word as an attribute knowledge element, taking the relationship word as a relationship knowledge element, and forming the road surface expansion knowledge element set.
Specifically, after the expansion and contraction influence factor set influencing the road surface expansion and contraction fault is analyzed and determined, data crawling is sequentially performed on the expansion and contraction influence factors by utilizing a web crawler technology, network data knowledge related to each expansion and contraction influence factor in the expansion and contraction influence factor set is obtained, and therefore a target data set is established. And then, performing word segmentation processing on the target data in the target data set to obtain a data word segmentation result, wherein the data word segmentation result comprises a plurality of word segmentation texts. Exemplarily, data in a format such as PDF and a picture are recognized by using an OCR character recognition technology, and then word segmentation is performed by using a Jieba word segmentation technology, so that a word segmentation result of the data is obtained.
Further, a plurality of word segmentation texts obtained after the word segmentation processing are subjected to screening processing, and the word segmentation texts left after the screening processing form the key text set. Firstly, the word segmentation texts meeting the first preset word segmentation requirement in the word segmentation texts are removed, and a removal result is obtained. Wherein the first preset participle requirement refers to stop word text in the data text, exemplarily words such as "and the like", "and", "further", "for example", and the like. And then, extracting the word segmentation texts meeting the second preset word segmentation requirement in the elimination result to obtain an extraction result. The second preset word segmentation requirement refers to a text which does not belong to the influence factors of the road surface expansion and shrinkage faults and the related attributes and relations of the influence factors. And finally, carrying out category division on the word segmentation texts in the extraction result to obtain word segmentation classification results, wherein the word segmentation classification results comprise concept word segmentation, attribute word segmentation and relation word segmentation, the concept word segmentation is used as a concept knowledge element, the attribute word segmentation is used as an attribute knowledge element, the relation word segmentation is used as a relation knowledge element, and the road surface expansion and contraction knowledge element set is formed. And finally, taking the key text set as a road surface expansion and shrinkage knowledge element set, and constructing the road surface expansion and shrinkage knowledge map according to the road surface expansion and shrinkage knowledge element set.
The road surface swell-shrink knowledge element set is obtained through screening and analyzing, then the road surface swell-shrink knowledge map is constructed, and useless data texts are removed, so that the condition that the road surface swell-shrink knowledge map constructed subsequently is large and useless, and the running performance of the system is influenced is avoided.
Step S400: constructing a pavement swelling and shrinking knowledge map based on the swelling and shrinking influence factors;
step S500: carrying out multi-dimensional data acquisition on a target road surface to obtain target road surface data;
step S600: rendering the target pavement data to the pavement swelling and shrinking knowledge map to obtain a target pavement swelling and shrinking knowledge map;
step S700: and carrying out expansion and shrinkage early warning on the target road surface based on the expansion and shrinkage knowledge map of the target road surface.
Specifically, after a road surface swell-shrink knowledge graph is constructed based on the plurality of swell-shrink influence factors obtained through analysis and screening, multi-dimensional data acquisition is firstly carried out on a target road surface to obtain target road surface data. The target pavement refers to any pavement to be intelligently monitored and early warned of pavement expansion and contraction by using the pavement expansion and contraction early warning system. Further, rendering the target pavement data to the pavement swelling and shrinking knowledge map to obtain a target pavement swelling and shrinking knowledge map, and finally performing swelling and shrinking early warning on the target pavement based on the target pavement swelling and shrinking knowledge map. The road surface swell-shrink data real-time monitoring based on the knowledge graph is realized, and the technical effects of intuitiveness and reliability of road surface swell-shrink monitoring are improved.
Further, the invention also comprises the following steps:
step S810: acquiring pavement expansion and shrinkage early warning;
step S820: building an expansion fault data set based on the big data;
further, the invention also comprises the following steps:
step S821: establishing a pavement expansion and shrinkage fault set based on big data, wherein the pavement expansion and shrinkage fault set comprises a plurality of pavement expansion and shrinkage faults;
step S822: analyzing various pavement expansion and shrinkage faults in the multiple pavement expansion and shrinkage faults in sequence to obtain multiple groups of fault characteristics;
step S823: according to the multiple groups of fault characteristics, a plurality of fault processing schemes are obtained through sequential analysis;
step S824: and establishing the expansion fault data set according to the mapping relation among the multiple road surface expansion faults, the multiple groups of fault characteristics and the multiple fault processing schemes.
Step S830: traversing in the expansion fault data set to obtain a target expansion fault type based on the pavement expansion fault early warning;
step S840: and matching a target fault processing scheme of the target expansion and contraction fault type, and processing the road surface expansion and contraction fault according to the processing scheme.
Specifically, expansion and shrinkage pre-warning of the target road surface is carried out based on the target road surface expansion and shrinkage knowledge graph, road surface expansion and shrinkage early warning is obtained, the type of the current early-warning road surface expansion and shrinkage is analyzed by combining big data, and a fault solving and processing scheme is established in a targeted mode. Firstly, an expansion and contraction fault data set is established based on big data, so that the road surface expansion and contraction fault is early warned, traversal is carried out in the expansion and contraction fault data set, and a target expansion and contraction fault type is obtained. The method comprises the steps that a road surface expansion and contraction fault set is established on the basis of big data, the road surface expansion and contraction fault set comprises multiple road surface expansion and contraction faults, then, various road surface expansion and contraction faults in the multiple road surface expansion and contraction faults are sequentially analyzed to obtain multiple groups of fault characteristics, multiple fault processing schemes are sequentially analyzed according to the multiple groups of fault characteristics, and the expansion and contraction fault data set is established according to the mapping relations among the multiple road surface expansion and contraction faults, the multiple groups of fault characteristics and the multiple fault processing schemes. Further, matching a target fault processing scheme of the target expansion and contraction fault type, and processing the road surface expansion and contraction fault according to the processing scheme.
The swell-shrink fault data set is established by combining big data, a database basis is provided for traversal analysis of road swell-shrink early warning, and the technical effects of improving the reliability of a processing scheme and being close to the reality are further achieved.
In summary, the pavement swelling and shrinking early warning method provided by the invention has the following technical effects:
historical road surface expansion and contraction data are collected based on big data, wherein the historical road surface expansion and contraction data comprise multiple sets of expansion and contraction data with time and position marks; analyzing the multiple sets of expansion and contraction data with time and position marks in sequence to obtain a historical expansion and contraction analysis result; obtaining an expansion and contraction influence factor set according to the historical expansion and contraction analysis result, wherein the expansion and contraction influence factor set comprises a plurality of expansion and contraction influence factors; constructing a pavement swelling and shrinking knowledge map based on the swelling and shrinking influence factors; carrying out multi-dimensional data acquisition on a target pavement to obtain target pavement data; rendering the target pavement data to the pavement swelling and shrinking knowledge map to obtain a target pavement swelling and shrinking knowledge map; and carrying out expansion and shrinkage early warning on the target pavement based on the expansion and shrinkage knowledge map of the target pavement. Historical road surface swelling and shrinking data are acquired by utilizing big data, a road surface swelling and shrinking knowledge map is analyzed and constructed, and then related data of a target road surface are rendered into the road surface swelling and shrinking knowledge map to obtain the target road surface swelling and shrinking knowledge map, so that the technical goal of visually displaying the real-time swelling and shrinking condition of the road surface is achieved. The expansion and shrinkage related data of the target road surface are visually displayed in real time by utilizing the expansion and shrinkage knowledge map of the target road surface, so that the visual and intelligent degrees of the pavement expansion and shrinkage early warning are improved, and the technical effects of timeliness and accuracy of the pavement expansion and shrinkage early warning are further improved.
Example two
Based on the same inventive concept as the road surface swell-shrink early warning method in the foregoing embodiment, the present invention further provides a road surface swell-shrink early warning system, please refer to fig. 5, which includes:
the data acquisition module M100 is used for acquiring historical road surface expansion and contraction data based on big data, wherein the historical road surface expansion and contraction data comprise multiple sets of expansion and contraction data with time and position marks;
the data analysis module M200 is used for sequentially analyzing the multiple sets of expansion and contraction data with time and position marks to obtain a historical expansion and contraction analysis result;
a factor determining module M300, where the factor determining module M300 is configured to obtain an expansion and contraction influence factor set according to the historical expansion and contraction analysis result, where the expansion and contraction influence factor set includes a plurality of expansion and contraction influence factors;
the map construction module M400 is used for constructing a road surface expansion and contraction knowledge map based on the expansion and contraction influence factors;
a target map early warning module M500, wherein the target map early warning module M500 comprises:
the target data acquisition module M510 is configured to perform multidimensional data acquisition on a target road surface to obtain target road surface data;
the target map obtaining module M520 is configured to render the target road data to the road swelling and shrinking knowledge map to obtain a target road swelling and shrinking knowledge map;
a target map application module M530, where the target map application module M530 is configured to perform swelling and shrinking early warning on the target road surface based on the target road surface swelling and shrinking knowledge map.
Further, the factor determining module M300 in the system is further configured to:
extracting a plurality of analysis results of multiple times of historical expansion and contraction in the historical expansion and contraction analysis results;
constructing a historical swelling and shrinking index-event scatter diagram according to the plurality of analysis results, wherein the historical swelling and shrinking index-event scatter diagram comprises a plurality of index-event scatter diagrams;
carrying out correlation analysis on the index-event scatter diagrams in sequence by using the SPSS to obtain a plurality of correlation analysis results;
screening results of which the correlation meets the preset correlation requirement in the multiple correlation analysis results, and reversely matching to obtain multiple indexes;
and according to the indexes, establishing the expansion and contraction influence factor set.
Further, the factor determining module M300 in the system is further configured to:
building a set of swelling and shrinking indexes based on big data, wherein the set of swelling and shrinking indexes comprises a plurality of swelling and shrinking indexes;
extracting index parameters of the analysis results in sequence based on the expansion and contraction indexes to obtain a plurality of groups of index parameters;
and constructing the multiple index-event scatter diagrams according to the mapping relation between the multiple groups of index parameters and the multiple times of historical swelling and shrinking, and forming the historical swelling and shrinking index-event scatter diagram.
Further, the factor determining module M300 in the system is further configured to:
sequentially performing data crawling on the multiple expansion and contraction influence factors by utilizing a web crawler technology to obtain a target data set;
performing word segmentation processing on target data in the target data set to obtain a data word segmentation result, wherein the data word segmentation result comprises a plurality of word segmentation texts;
screening texts meeting preset text requirements in the word segmentation texts to form a key text set;
and taking the key text set as a pavement swelling and shrinking knowledge element set, and constructing the pavement swelling and shrinking knowledge map according to the pavement swelling and shrinking knowledge element set.
Further, the factor determining module M300 in the system is further configured to:
obtaining a first preset word segmentation requirement;
removing the word segmentation texts meeting the first preset word segmentation requirement in the plurality of word segmentation texts to obtain a removal result;
obtaining a second preset word segmentation requirement;
extracting the word segmentation texts meeting the second preset word segmentation requirement in the elimination result to obtain an extraction result;
classifying the word segmentation texts in the extraction result to obtain word segmentation classification results, wherein the word segmentation classification results comprise concept word segmentation, attribute word segmentation and relation word segmentation;
and taking the concept word as a concept knowledge element, taking the attribute word as an attribute knowledge element, taking the relationship word as a relationship knowledge element, and forming the road surface expansion knowledge element set.
Further, the system further comprises a fault handling module, configured to:
acquiring pavement expansion and shrinkage early warning;
building an expansion fault data set based on the big data;
traversing in the expansion and contraction fault data set to obtain a target expansion and contraction fault type based on the pavement expansion and contraction fault early warning;
and matching a target fault processing scheme of the target expansion and contraction fault type, and processing the road surface expansion and contraction fault according to the processing scheme.
Further, the fault handling module in the system is further configured to:
building a pavement expansion and contraction fault set based on the big data, wherein the pavement expansion and contraction fault set comprises a plurality of pavement expansion and contraction faults;
analyzing various pavement expansion and shrinkage faults in the multiple pavement expansion and shrinkage faults in sequence to obtain multiple groups of fault characteristics;
according to the multiple groups of fault characteristics, a plurality of fault processing schemes are obtained through sequential analysis;
and establishing the expansion and contraction fault data set according to the multiple road surface expansion and contraction faults, the multiple groups of fault characteristics and the mapping relation among the multiple fault processing schemes.
Each embodiment in the present specification is described in a progressive manner, and the main point of the description of each embodiment is that the embodiment is different from other embodiments, and the road surface swell-shrink early warning method and the specific example in the first embodiment in fig. 1 are also applicable to a road surface swell-shrink early warning system in the present embodiment. The device disclosed in the embodiment corresponds to the method disclosed in the embodiment, so that the description is simple, and the relevant points can be referred to the description of the method part.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the present invention and its equivalent technology, it is intended that the present invention also encompass such modifications and variations.
Claims (8)
1. A pavement swelling and shrinking early warning method is characterized by comprising the following steps:
historical road surface expansion and shrinkage data are collected based on big data, wherein the historical road surface expansion and shrinkage data comprise multiple sets of expansion and shrinkage data with time and position marks;
analyzing the multiple sets of expansion and contraction data with time and position marks in sequence to obtain a historical expansion and contraction analysis result;
obtaining an expansion and shrinkage influence factor set according to the historical expansion and shrinkage analysis result, wherein the expansion and shrinkage influence factor set comprises a plurality of expansion and shrinkage influence factors;
constructing a pavement swelling and shrinking knowledge map based on the swelling and shrinking influence factors;
carrying out multi-dimensional data acquisition on a target pavement to obtain target pavement data;
rendering the target pavement data to the pavement swelling and shrinking knowledge map to obtain a target pavement swelling and shrinking knowledge map;
and carrying out expansion and shrinkage early warning on the target road surface based on the expansion and shrinkage knowledge map of the target road surface.
2. The method according to claim 1, wherein the deriving a set of expansion and contraction influencing factors according to the historical expansion and contraction analysis result comprises:
extracting a plurality of analysis results of multiple times of historical expansion and contraction in the historical expansion and contraction analysis results;
constructing a historical swelling and shrinking index-event scatter diagram according to the plurality of analysis results, wherein the historical swelling and shrinking index-event scatter diagram comprises a plurality of index-event scatter diagrams;
carrying out correlation analysis on the index-event scatter diagrams in sequence by using the SPSS to obtain a plurality of correlation analysis results;
screening results of which the correlation meets the preset correlation requirement in the multiple correlation analysis results, and reversely matching to obtain multiple indexes;
and establishing the expansion and contraction influence factor set according to the indexes.
3. The method of claim 2, wherein constructing a historical dilatational index-event scatter plot from the plurality of analysis results comprises:
building a set of swelling and shrinking indexes based on big data, wherein the set of swelling and shrinking indexes comprises a plurality of swelling and shrinking indexes;
extracting index parameters of the analysis results in sequence based on the expansion and contraction indexes to obtain a plurality of groups of index parameters;
and constructing the multiple index-event scatter diagrams according to the mapping relation between the multiple groups of index parameters and the multiple times of historical swelling and shrinking, and forming the historical swelling and shrinking index-event scatter diagram.
4. The method of claim 2, wherein after said constructing the set of expansion and contraction influencing factors according to the plurality of indicators, further comprising:
sequentially performing data crawling on the multiple expansion and contraction influence factors by utilizing a web crawler technology to obtain a target data set;
performing word segmentation processing on target data in the target data set to obtain a data word segmentation result, wherein the data word segmentation result comprises a plurality of word segmentation texts;
screening texts meeting preset text requirements in the word segmentation texts to form a key text set;
and taking the key text set as a road surface swelling and shrinking knowledge element set, and constructing the road surface swelling and shrinking knowledge map according to the road surface swelling and shrinking knowledge element set.
5. The method of claim 4, wherein prior to the constructing the road surface breathing knowledge map from the set of road surface breathing knowledge elements, further comprising:
obtaining a first preset word segmentation requirement;
removing the word segmentation texts meeting the first preset word segmentation requirement from the plurality of word segmentation texts to obtain a removal result;
obtaining a second preset word segmentation requirement;
extracting the word segmentation texts meeting the second preset word segmentation requirement in the elimination result to obtain an extraction result;
classifying the word segmentation texts in the extraction result to obtain word segmentation classification results, wherein the word segmentation classification results comprise concept word segmentation, attribute word segmentation and relation word segmentation;
and taking the concept participles as concept knowledge elements, taking the attribute participles as attribute knowledge elements, taking the relationship participles as relationship knowledge elements, and forming the road surface expansion knowledge element set.
6. The method of claim 1, further comprising:
acquiring pavement expansion and shrinkage early warning;
building an expansion fault data set based on the big data;
traversing in the expansion and contraction fault data set to obtain a target expansion and contraction fault type based on the pavement expansion and contraction fault early warning;
and matching a target fault processing scheme of the target expansion and contraction fault type, and processing the road surface expansion and contraction fault according to the processing scheme.
7. The method of claim 6, wherein the building a breathing fault data set based on big data comprises:
establishing a pavement expansion and shrinkage fault set based on big data, wherein the pavement expansion and shrinkage fault set comprises a plurality of pavement expansion and shrinkage faults;
analyzing various pavement expansion and shrinkage faults in the multiple pavement expansion and shrinkage faults in sequence to obtain multiple groups of fault characteristics;
according to the multiple groups of fault characteristics, a plurality of fault processing schemes are obtained through sequential analysis;
and establishing the expansion fault data set according to the mapping relation among the multiple road surface expansion faults, the multiple groups of fault characteristics and the multiple fault processing schemes.
8. The utility model provides a road surface breathing early warning system which characterized in that includes:
the data acquisition module is used for acquiring historical road surface expansion and shrinkage data based on big data, wherein the historical road surface expansion and shrinkage data comprise multiple sets of expansion and shrinkage data with time and position marks;
the data analysis module is used for sequentially analyzing the multiple sets of expansion and shrinkage data with time and position marks to obtain a historical expansion and shrinkage analysis result;
the factor determining module is used for obtaining an expansion and contraction influence factor set according to the historical expansion and contraction analysis result, wherein the expansion and contraction influence factor set comprises a plurality of expansion and contraction influence factors;
the map construction module is used for constructing a road surface expansion and contraction knowledge map based on the expansion and contraction influence factors;
the target map early warning module, the target map early warning module includes:
the target data acquisition module is used for carrying out multi-dimensional data acquisition on a target road surface to obtain target road surface data;
the target map obtaining module is used for rendering the target pavement data to the pavement swelling and shrinking knowledge map to obtain a target pavement swelling and shrinking knowledge map;
and the target map application module is used for carrying out expansion and shrinkage early warning on the target road surface based on the target road surface expansion and shrinkage knowledge map.
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| CN116703246B (en) * | 2023-08-02 | 2023-10-31 | 北京松岛菱电电力工程有限公司 | Intelligent management method and system for power distribution system |
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