CN113159635B - Municipal engineering construction project quality supervision method, system, terminal and storage medium based on feature recognition - Google Patents
Municipal engineering construction project quality supervision method, system, terminal and storage medium based on feature recognition Download PDFInfo
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Abstract
The invention discloses a municipal engineering construction project quality supervision method, a system, a terminal and a storage medium based on feature recognition, wherein the municipal engineering construction project quality supervision method based on feature recognition comprises the following steps: carrying out area division on green area roads; acquiring basic parameters corresponding to each divided road section; acquiring basic parameters corresponding to green belts on two sides of each road section; counting the number of trees planted in green belts on two sides of each road section; detecting the verticality of trees planted in green belts on two sides of each road section; detecting the distance between two adjacent trees in green belts on two sides of each road section; detecting the parallelism of the green belts on the two sides of each road section corresponding to each road section; analyzing parameters corresponding to road greening; the method effectively solves the problem that the monitoring content of the existing road greening project supervision method is not comprehensive enough, and greatly improves the road greening project quality supervision efficiency.
Description
Technical Field
The invention belongs to the technical field of project quality supervision, and relates to a municipal engineering construction project quality supervision method, system, terminal and storage medium based on feature recognition.
Background
In recent years, the urban transportation industry is rapidly developed, and the construction of the road greening engineering not only reduces the influence of the development of the transportation industry on the urban environment, but also improves the urban aesthetic degree, so that the quality of the road greening engineering needs to be supervised in order to ensure the construction effect of the road greening engineering.
The existing road greening engineering quality supervision mainly focuses on supervision of the tree types, the tree construction area soil types and other aspects, and specific supervision of the tree perpendicularity and other aspects is not carried out, so that the existing road greening engineering supervision method has certain defects.
Disclosure of Invention
In view of the above, in order to solve the problems proposed in the background art, a method, a system, a terminal and a storage medium for monitoring the quality of municipal engineering construction projects based on feature recognition are proposed for a coal mine underground safety early warning management platform based on environment multi-parameter real-time online monitoring of a street tree greening engineering in a road greening engineering, so that the high-efficiency monitoring of the road greening engineering is realized;
the purpose of the invention can be realized by the following technical scheme:
the invention provides a municipal engineering construction project quality supervision method based on feature recognition, which comprises the following steps:
s1, dividing road areas: the method comprises the steps that a road corresponding to a greening area is subjected to area division through an area division module, the length corresponding to the road of the greening area is further obtained, the road of the greening area is divided into road sections according to a preset sequence, the divided road sections are numbered according to the preset sequence, and the number is sequentially marked as 1,2,. I,. N;
s2, acquiring basic road section parameters: acquiring the length and the width corresponding to each road section of each greening area through a road basic parameter acquisition module, and respectively recording as a and b;
s3, acquiring basic parameters of the green belt: detecting basic parameters corresponding to the green belts on the left side of each road section and the right side of each road section through a green belt basic parameter detection module, and further acquiring the basic parameters corresponding to the green belts on the two sides of each road section;
s4, counting the number of planted trees: the method comprises the steps that a tree number counting module is used for counting the number of trees planted in green belts on the left sides of all road sections and the number of trees planted in green belts on the right sides of all road sections respectively, meanwhile, the trees planted in the green belts on the left sides of all road sections are numbered according to a preset sequence, and are marked as 1,2,. J,. M sequentially, and the trees planted in the green belts on the right sides of all road sections are numbered according to the preset sequence, and are marked as 1',2,. J,. M' sequentially;
s5, detecting the verticality of the tree: detecting the verticality corresponding to each tree in the green belts on the left sides of all the road sections and the verticality corresponding to each tree in the green belts on the right sides of all the road sections through a tree verticality detection module, and further acquiring the verticality corresponding to each tree in the green belts on the left sides of all the road sections and the verticality corresponding to each tree in the green belts on the right sides of all the road sections;
s6, detecting the distance between trees: detecting the distance between two adjacent trees of the green belt on the left side of each road section and the distance between two adjacent trees in the green belt on the right side of each road section through a tree distance detection module, and further acquiring the distance between two adjacent trees of the green belt on the left side of each road section and the distance between two adjacent trees in the green belt on the right side of each road section;
s7, detecting the parallelism of the green belt: detecting the parallelism of the left green belt of each road section and the parallelism of the right green belt of each road section and each road section through a green belt parallelism detection module, and further obtaining the parallelism corresponding to the left green belt of each road section and the parallelism corresponding to the right green belt of each road section;
s8, road greening analysis: and analyzing the basic parameters and the parallelism corresponding to the left green belts and the right green belts of each road section, the verticality of trees planted in the green belts and the distance between the planted trees through a data processing and analyzing module, and further counting the comprehensive quality of road greening and according with the influence coefficient.
Furthermore, the basic parameter detection of the green belt comprises a plurality of laser range finders, which are respectively used for detecting the basic parameters corresponding to the green belt on the left side of each road section and the green belt on the right side of each road section, wherein the basic parameters of the green belt comprise the length of the green belt and the width of the green belt, and then the length and the width corresponding to the green belt on the left side of each road section and the green belt on the right side of each road section are obtained.
Furthermore, the tree verticality detection comprises a plurality of tree detection units, wherein the tree detection units are respectively used for detecting the verticality corresponding to each tree in the green belt on the left side of each road section and the verticality corresponding to each tree in the green belt on the right side of each road section, then the three-dimensional laser scanner is used for respectively scanning and shooting the trees in the green belt on the left side of each road section and the green belt on the right side of each road section, further point cloud data corresponding to the trees in the green belt on the left side of each road section and spatial three-dimensional point cloud data corresponding to the trees in the green belt on the right side of each road section are obtained, and a third-party website is used for obtaining the point cloud data corresponding to the trees in the green belt on the left side of each road section and the spatial three-dimensional point cloud data corresponding to the trees in the green belt on the right side of each road sectionThe angle corresponding to the ground is recorded as theta, the verticality corresponding to each tree in the green belt on the left side of each road section and the verticality corresponding to each tree in the green belt on the right side of each road section are counted, and a tree verticality set C of the green belt on the left side of each road section is constructed d (C d 1,C d 2,...C d j,...C d m) and a set C 'of tree verticality at right side of each road segment' d (C′ d 1′,C′ d 2′,...C′ d j′,...C′ d m′)，C d j represents the verticality, C ', corresponding to the jth tree in the left green belt of the d road section' d j 'represents the corresponding verticality of the j' tree in the green belt on the right side of the d road section, d represents the road section number, and d =1,2.
Further, the tree interval detection comprises a plurality of infrared distance measuring sensors, which are respectively used for detecting the distance between adjacent trees of the green belts on the left side of each road section and the distance between adjacent trees of the green belts on the right side of each road section, so as to obtain the distance between adjacent trees of the green belts on the left side of each road section and the distance between two adjacent trees of the green belts on the right side of each road section, the distance between adjacent trees of the green belts on the left side of each road section is recorded as L, and the distance between two adjacent trees of the green belts on the right side of each road section is recorded as L'.
Further, the specific detection process of the green belt parallelism comprises the following steps:
s71, according to the length corresponding to each road section, further equally dividing each road section into each sub-road section according to a preset distance, distributing a central point corresponding to each sub-road section as a road section detection point, further numbering the road section detection points corresponding to each road section according to a preset sequence, and marking the road section detection points as 1,2,. X,. Y in sequence;
s72, according to the length corresponding to the left green belt of each road section, further equally dividing each green belt into left green areas according to the preset road section dividing distance, distributing the center points of the left green areas as left green detection points, and further numbering the left green detection points corresponding to each road section according to a preset sequence, wherein the numbers are sequentially marked as 1',2',. X ',. Y';
s73, acquiring greening detection points corresponding to the right sides of the road sections according to the acquisition method of the greening detection points on the left sides of the road sections, numbering the greening detection points on the right sides corresponding to the road sections according to a preset sequence, and sequentially marking the greening detection points as 1',2',.
S74, connecting each road section detection point with each left side greening detection point corresponding to each road section respectively, further acquiring a connecting line section corresponding to each road section detection point and each left side greening detection point of each road section, recording the connecting line section as a left side detection line section, and acquiring each right side detection line section corresponding to each road section according to the acquisition method of the left side detection line section;
s75, numbering the left detection line segments corresponding to the road segments according to a preset sequence, and sequentially marking the left detection line segments as 1,2,. K,. T, and numbering the right detection line segments corresponding to the road segments according to the preset sequence, wherein the right detection line segments are sequentially marked as 1',2,. K,. T';
s76, respectively obtaining the length corresponding to each left detection line segment of each road section and the length corresponding to each right detection line segment of each road section, recording the length of each left detection line segment corresponding to each road section as f, and recording the length of each right detection line segment corresponding to each road section as f';
s77, comparing the lengths of the adjacent left detection line segments of each road section with each other according to the length of each left detection line segment of each road section, further obtaining the difference value corresponding to the length of each adjacent left detection line segment of each road section, and counting the parallelism corresponding to the left green belt of each road section;
and S78, acquiring the parallelism corresponding to the green belts on the right side of each road section according to the statistical method of the parallelism of the green belts on the left side of each road section.
Further, the specific process of the road greening analysis comprises the following steps:
s81, comparing the width corresponding to each road section of the greening area with the width corresponding to the left green belt of each road section and the width corresponding to the right green belt of each road section respectively according to the width corresponding to each road section of the greening area, the width corresponding to the left green belt of each road section and the width corresponding to the right green belt of each road section, and further counting the quality coincidence influence coefficient of the width ratio of the left green belt of each road section and the quality coincidence influence coefficient of the width ratio of the right green belt of each road section;
s82, comparing the width corresponding to the green belt on the left side of each road section with the width corresponding to the green belt on the right side of each road section, and further counting the symmetry quality of the green belt of the road according with the influence coefficient;
s83, according to the perpendicularity set of the trees of the green belts on the left side of each road section and the perpendicularity set of the trees on the right side of each road section, obtaining the corresponding perpendicularity of each tree in the green belts on the left side of each road section and the corresponding perpendicularity of each tree in the green belts on the right side of each road section, respectively comparing the corresponding perpendicularity of each tree in the green belts on the left side of each road section and the corresponding perpendicularity of each tree in the green belts on the right side of each road section with the corresponding standard perpendicularity of the corresponding green belts in the database, and further counting the perpendicularity quality of the trees of the green belts on the left side of each road section according with the influence coefficient and the perpendicularity quality of the trees of the green belts on the right side of each road section according with the influence coefficient;
s84, comparing the distance between every two adjacent trees of the green belts on the left side of each road section and the distance between every two adjacent trees of the green belts on the right side of each road section with the standard distance corresponding to the corresponding green belt trees in the database according to the distance between every two adjacent trees of the green belts on the left side of each road section and the distance between every two adjacent trees of the green belts on the right side of each road section, and counting the quality of the space between the trees of the green belts on the left side of each road section according with the influence coefficient and the quality of the space between the trees of the green belts on the right side of each road section according with the influence coefficient;
s85, according to the parallelism corresponding to the green belts on the left side of each road section and the parallelism corresponding to the green belts on the right side of each road section, comparing the parallelism corresponding to the green belts on the left side of each road section and the parallelism corresponding to the green belts on the right side of each road section with the standard parallelism corresponding to the green belts and the roads in the database respectively, and counting the quality conformity influence coefficient of the parallelism of the green belts on the left side of each road section and the quality conformity influence coefficient of the parallelism of the green belts on the right side of each road section
Further, the road greening analysis also comprises comprehensive quality analysis on the left green belts of all the sections and the right green belts of all the sections, the comprehensive quality coincidence influence coefficient of the quality of the left green belts of all the sections is further counted according to the counted quality coincidence influence coefficient of the width of the left green belts of all the sections, the quality coincidence influence coefficient of the verticality of the trees of the left green belts of all the sections, the quality coincidence influence coefficient of the space of the left green belts of all the sections and the parallelism quality coincidence influence coefficient of the left green belts of all the sections, the comprehensive quality coincidence influence coefficient of the verticality of the trees of the right green belts of all the sections is further counted according to the quality coincidence influence coefficient of the width of the right green belts of all the sections, the space quality coincidence influence coefficient of the trees of the right green belts of all the sections and the parallelism quality coincidence influence coefficient of the right green belts of all the sections, the comprehensive quality coincidence influence coefficient of the right green belts of all the sections is counted, and the comprehensive quality coincidence influence coefficient of the green belts of the right green belts of all the roads is counted according to the influence coefficient of the comprehensive quality of the road.
The invention provides a municipal engineering construction project quality supervision system based on feature recognition, which comprises an area division module, a road basic parameter acquisition module, a green belt basic parameter detection module, a tree quantity statistics module, a tree verticality detection module, a tree spacing detection module, a green belt parallelism detection module, a data processing and analysis module and a database, wherein the data processing and analysis module is respectively connected with the road basic parameter acquisition module, the green belt basic parameter detection module, the tree verticality detection module, the tree spacing detection module, the green belt parallelism detection module and the database, the road basic parameter acquisition module is connected with the area division module, and the tree quantity statistics module is connected with the tree verticality detection module.
A third aspect of the present invention provides a terminal, including: the system comprises a processor, a memory and a network interface, wherein the memory and the network interface are connected with the processor; the network interface is connected with a nonvolatile memory in the server; when running, the processor calls the computer program from the nonvolatile memory through the network interface, and runs the computer program through the memory, so as to execute the method of the invention.
A fourth aspect of the present invention provides a readable storage medium applied to a computer, where a computer program is recorded on the readable storage medium, and when the computer program runs in a memory of a server, the method described in the present invention is implemented.
The invention has the beneficial effects that:
(1) According to the municipal engineering construction project quality supervision method based on feature recognition, the problems that monitoring contents of an existing road greening project supervision method are not comprehensive enough are solved effectively by comprehensively detecting and analyzing the four aspects of the width and the parallelism corresponding to green belts on two sides of each road section, the verticality and the space corresponding to trees in the green belts on the two sides, and the like, authenticity and the reference of a road greening project quality supervision result are greatly improved, and meanwhile the road greening project quality supervision efficiency is effectively improved.
(2) When the verticality of trees on the inner sides of the green belts on the two sides of each road section is detected, the trees in the green belts on the left side of each road section and the green belts on the right side of each road section are scanned and shot by using the laser three-dimensional scanner, so that the detection efficiency of the verticality of the trees on the inner sides of the green belts on the two sides of each road section is effectively improved, and meanwhile, the authenticity of a detection result is greatly improved.
(3) According to the invention, through detecting the parallelism of the green belts on the two sides of each road section, accurate data base is provided for the subsequent analysis of the parallelism of the green belts on the left side of each road section and the right side of each road section, and the efficiency of analyzing the quality of the road greening engineering is greatly improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a diagram of a process for carrying out the steps of the method of the present invention;
FIG. 2 is a schematic diagram of the system module connection according to the present invention.
Detailed Description
While the foregoing is directed to embodiments of the present invention, other and further embodiments of the invention may be devised without departing from the basic scope thereof, and the scope thereof is determined by the claims that follow.
Referring to fig. 1, a first aspect of the present invention provides a method for supervising the quality of a municipal engineering construction project based on feature recognition, the method comprising the steps of:
s1, dividing road areas: dividing the road corresponding to the greening area into areas through an area dividing module so as to obtain the length corresponding to the road of the greening area, dividing the road of the greening area into sections according to a preset sequence, numbering the divided sections according to the preset sequence, and marking the divided sections as 1,2,. I,. N in sequence;
s2, acquiring basic parameters of the road section: acquiring the length and the width corresponding to each road section of each greening area through a road basic parameter acquisition module, and respectively recording as a and b;
s3, obtaining basic parameters of the green belt: detecting basic parameters corresponding to the green belts on the left side of each road section and the right side of each road section through a green belt basic parameter detection module, and further acquiring the basic parameters corresponding to the green belts on the two sides of each road section;
specifically, the basic parameter detection of the green belts comprises a plurality of laser range finders, which are respectively used for detecting basic parameters corresponding to the green belts on the left side of each road section and the green belts on the right side of each road section, wherein the basic parameters of the green belts comprise the length and the width of the green belts, and further the length and the width corresponding to the green belts on the left side of each road section and the green belts on the right side of each road section are obtained.
The embodiment of the invention effectively improves the detection efficiency of the basic parameters of the green belts by detecting the length and the width of the green belts on two sides of each road section by using the laser range finder.
S4, counting the number of planted trees: the method comprises the steps that a tree quantity counting module is used for counting the quantity of trees planted in green belts on the left sides of all road sections and the quantity of trees planted in green belts on the right sides of all road sections respectively, meanwhile, the trees planted in the green belts on the left sides of all road sections are numbered according to a preset sequence, the numbers are sequentially marked as 1,2,. J,. M, and meanwhile, the trees planted in the green belts on the right sides of all road sections are numbered according to a preset sequence, and the numbers are sequentially marked as 1',2, '. J,. M ';
s5, detecting the verticality of the tree: detecting the verticality corresponding to each tree in the green belt on the left side of each road section and the verticality corresponding to each tree in the green belt on the right side of each road section through a tree verticality detection module, and further acquiring the verticality corresponding to each tree in the green belt on the left side of each road section and the verticality corresponding to each tree in the green belt on the right side of each road section;
specifically, the tree perpendicularity detection comprises a plurality of tree detection units which are respectively used for detecting the perpendicularity corresponding to each tree in the green belt on the left side of each road section and the perpendicularity corresponding to each tree in the green belt on the right side of each road section, then a three-dimensional laser scanner is used for scanning and shooting the trees in the green belt on the left side of each road section and the green belt on the right side of each road section respectively, point cloud data corresponding to the trees in the green belt on the left side of each road section and spatial three-dimensional point cloud data corresponding to the trees in the green belt on the right side of each road section are obtained, the angle corresponding to the ground of each tree is obtained through a third-party website and recorded as theta, the perpendicularity corresponding to each tree in the green belt on the left side of each road section and the green belt on the right side of each road section are further counted, and then a tree perpendicularity set C of the green belt on the left side of each road section is constructed d (C d 1,C d 2,...C d j,...C d m) and a tree perpendicularity set C 'on the right side of each road section' d (C′ d 1′,C′ d 2′,...C′ d j′,...C′ d m′)，C d j represents the verticality, C ', corresponding to the jth tree in the left green belt of the d road section' d j 'represents the verticality corresponding to the j' tree in the green belt on the right side of the d road section, d represents the road section number, d =1,2,...i,...n。
when the verticality of trees on the inner sides of the green belts on the two sides of each road section is detected, the trees in the green belts on the left side of each road section and the green belts on the right side of each road section are scanned and shot by using the laser three-dimensional scanner, so that the detection efficiency of the verticality of the trees on the inner sides of the green belts on the two sides of each road section is effectively improved, and meanwhile, the authenticity of a detection result is greatly improved.
S6, detecting the distance between trees: detecting the distance between two adjacent trees of the green belt on the left side of each road section and the distance between two adjacent trees in the green belt on the right side of each road section through a tree distance detection module, and further acquiring the distance between two adjacent trees of the green belt on the left side of each road section and the distance between two adjacent trees in the green belt on the right side of each road section;
specifically, the tree distance detection device comprises a plurality of infrared distance measuring sensors which are respectively used for detecting the distance between adjacent trees of the green belts on the left side of each road section and the distance between adjacent trees of the green belts on the right side of each road section, so as to obtain the distance between adjacent trees of the green belts on the left side of each road section and the distance between two adjacent trees of the green belts on the right side of each road section, the distance between adjacent trees of the green belts on the left side of each road section is recorded as L, and the distance between two adjacent trees of the green belts on the right side of each road section is recorded as L'.
When the tree spacing is detected, the distance between adjacent numerical values of green belts on two sides of each road section is detected by using the infrared sensor, so that the authenticity and the accuracy of a tree spacing detection result are greatly guaranteed.
S7, green belt parallelism detection: detecting the parallelism of the left green belt of each road section and the parallelism of the right green belt of each road section and each road section through a green belt parallelism detection module, and further acquiring the parallelism of the left green belt of each road section and the parallelism of the right green belt of each road section;
specifically, the green belt parallelism detection process comprises the following steps:
s71, according to the length corresponding to each road section, further equally dividing each road section into each sub-road section according to a preset distance, distributing a central point corresponding to each sub-road section as a road section detection point, further numbering the road section detection points corresponding to each road section according to a preset sequence, and marking the road section detection points as 1,2,. X,. Y in sequence;
s72, according to the length corresponding to the left green belt of each road section, dividing each green belt into left green areas at equal intervals according to a preset road section dividing distance, arranging the center points of the left green areas as left green detection points, and numbering the left green detection points corresponding to the road sections according to a preset sequence, wherein the numbers are sequentially marked as 1',2',. X ',. Y';
s73, acquiring greening detection points corresponding to the right sides of the road sections according to the acquisition method of the greening detection points on the left sides of the road sections, numbering the greening detection points on the right sides corresponding to the road sections according to a preset sequence, and sequentially marking the greening detection points as 1',2',.
S74, connecting each road section detection point with each left side greening detection point corresponding to each road section respectively, further acquiring a connecting line section corresponding to each road section detection point and each left side greening detection point of each road section, recording the connecting line section as a left side detection line section, and acquiring each right side detection line section corresponding to each road section according to the acquisition method of the left side detection line section;
s75, numbering the left detection line segments corresponding to the road segments according to a preset sequence, and sequentially marking the left detection line segments as 1,2,. K,. T, and numbering the right detection line segments corresponding to the road segments according to the preset sequence, wherein the right detection line segments are sequentially marked as 1',2,. K,. T';
s76, respectively obtaining the length corresponding to each left detection line segment of each road section and the length corresponding to each right detection line segment of each road section, recording the length of each left detection line segment corresponding to each road section as f, and recording the length of each right detection line segment corresponding to each road section as f';
s77, comparing the lengths of the left side detection line segments of each road section with the lengths of the adjacent left side detection line segments of each road section according to the lengths of the left side detection line segments of each road section, acquiring the corresponding difference value of the left side detection line segments of each road section, and counting the parallelism corresponding to the left side green belt of each road section;
wherein, the parallelism calculation formula corresponding to the green belt at the left side of each road section is
P d Represents the corresponding parallelism of the green belts on the left side of the d-th road section, f c d Represents the length corresponding to the length of the c-th left detection line of the d-th path, f c-1 d The length corresponding to the length of the c-1 left detection line segment of the d-th road segment is represented, c represents the number of the left detection line segment of each road segment, and c =1,2 Standard of merit Representing the corresponding standard deviation value between the two detected line segments.
In the formula, the left detection line segment is substituted into the calculation from the second, namely c = 2.
And S78, acquiring the parallelism corresponding to the green belts on the right side of each road section according to the statistical method of the parallelism of the green belts on the left side of each road section, and recording the parallelism as P'.
The embodiment of the invention provides accurate data base for the subsequent analysis of the parallelism of the green belts on the left side of each road section and the right side of each road section through the detection of the parallelism of the green belts on the two sides of each road section, thereby greatly improving the efficiency of the quality analysis of the road greening engineering.
S8, road greening analysis: and analyzing the basic parameters and the parallelism corresponding to the left green belts and the right green belts of each road section, the verticality of trees planted in the green belts and the distance between the planted trees through a data processing and analyzing module, and further counting the comprehensive quality of road greening and according with the influence coefficient.
According to the embodiment of the invention, the width and the parallelism corresponding to the green belts on two sides of each road section, the verticality and the interval corresponding to the trees in the green belts on two sides and the like are comprehensively detected and carefully analyzed, so that the problem that the monitoring content of the existing road greening project supervision method is not comprehensive enough is effectively solved, the authenticity and the referential of the road greening project quality supervision result are greatly improved, and the road greening project quality supervision efficiency is effectively improved.
Specifically, the specific process of the road greening analysis comprises the following steps:
s81, comparing the width corresponding to each road section of the greening area with the width corresponding to the left green belt of each road section and the width corresponding to the right green belt of each road section respectively according to the width corresponding to each road section of the greening area, the width corresponding to the left green belt of each road section and the width corresponding to the right green belt of each road section, and further counting the quality coincidence influence coefficient of the width ratio of the left green belt of each road section and the quality coincidence influence coefficient of the width ratio of the right green belt of each road section;
wherein the calculation formula of the width ratio quality coincidence influence coefficient of the green belt at the left side of each road section is
α d Representing the width ratio quality coincidence influence coefficient, k, corresponding to the green belt on the left side of the d-th road section d Indicates the width corresponding to the green belt on the left side of the d-th road section, b d Indicating the corresponding width to the left of the d-th road segment.
The calculation formula of the width ratio quality coincidence influence coefficient of the green belt on the right side of each road section is
α d 'represents that the width ratio quality corresponding to the green belt on the right side of the d-th road section accords with an influence coefficient, k' d Showing the width corresponding to the green belt on the right side of the d-th road section.
S82, comparing the width corresponding to the green belt on the left side of each road section with the width corresponding to the green belt on the right side of each road section, and further counting the symmetry quality of the green belt of the road according with the influence coefficient;
wherein the symmetry quality of the road green belt conforms to the calculation formula of the influence coefficient
Indicates the road greenThe quality corresponding to the symmetry of the chemical band conforms to the influence coefficient.
S83, according to the tree verticality set of the green belt on the left side of each road section and the tree verticality set of the right side of each road section, further acquiring the corresponding verticality of each tree in the green belt on the left side of each road section and the corresponding verticality of each tree in the green belt on the right side of each road section, respectively comparing the corresponding verticality of each tree in the green belt on the left side of each road section and the corresponding verticality of each tree in the green belt on the right side of each road section with the corresponding standard verticality of the corresponding green belt tree in the database, and further counting the verticality quality conformity influence coefficient of the green belt tree on the left side of each road section and the verticality quality conformity influence coefficient of the green belt tree on the right side of each road section;
wherein, the calculation formula of the verticality quality coincidence influence coefficient of the trees of the green belt on the left side of each road section is
β d Representing that the verticality quality of the trees corresponding to the green belt on the left side of the d-th road section meets the influence coefficient C d r Represents the corresponding verticality of the r-th tree in the green belt on the left side of the d-th road section, C Standard of merit The standard verticality corresponding to the green belt trees is shown, r represents the number of the green belt trees on the left side of each road section, and r =1,2.
The calculation formula of the verticality quality coincidence influence coefficient of the trees of the green belt on the right side of each road section is
β′ d Representing that the verticality quality of the tree corresponding to the green belt on the right side of the d-th road section meets the influence coefficient C' d r′ The verticality corresponding to the r ' -th tree in the green belt on the left side of the d-th road section is shown, r ' represents the number of trees in the green belt on the right side of each road section, and r ' =1',2, '. J ',. M '.
S84, comparing the distance between every two adjacent trees of the green belts on the left side of each road section and the distance between every two adjacent trees of the green belts on the right side of each road section with the standard distance corresponding to the corresponding green belt trees in the database according to the distance between every two adjacent trees of the green belts on the left side of each road section and the distance between every two adjacent trees of the green belts on the right side of each road section, and counting the quality of the space between the trees of the green belts on the left side of each road section according with the influence coefficient and the quality of the space between the trees of the green belts on the right side of each road section according with the influence coefficient;
wherein, the calculation formula of the space quality coincidence influence coefficient of the trees of the green belt at the left side of each road section is
δ d Expressing the quality coincidence influence coefficient, L, corresponding to the tree spacing of the green belt on the left side of the d-th road section r,r-1 d Represents the distance between the r-th tree and the r-1 th tree in the green belt on the left side of the d-th road section, L Standard of reference Representing the standard spacing, a ', corresponding to the trees of the green belt' d The length corresponding to the green belt on the left side of the d-th road section is shown, and m represents the number of trees planted in the green belt on the left side of each road section.
The calculation formula of the space quality coincidence influence coefficient of the trees of the green belt on the right side of each road section is
δ′ d Expressing the quality coincidence influence coefficient, L, corresponding to the spacing between the trees of the green belts at the right side of the d-th road section r′,r′-1 d Shows the distance a between the r '-r tree and the r' -1 tree in the left green belt of the d-th road section d The length of the green belt on the right side of the d-th road section is shown, and m' represents the number of trees planted in the green belt on the right side of each road section.
And S85, according to the parallelism corresponding to the left green belt of each road section and the parallelism corresponding to the right green belt of each road section, comparing the parallelism corresponding to the left green belt of each road section and the parallelism corresponding to the right green belt of each road section with the standard parallelism corresponding to the green belt and the road in the database respectively, and counting the quality conformity influence coefficient of the parallelism of the left green belt of each road section and the quality conformity influence coefficient of the parallelism of the right green belt of each road section.
Wherein, the quality of the parallelism of the green belts at the left side of each road section conforms toThe influence coefficient is calculated by the formula
φ d Representing the quality coincidence influence coefficient, P, corresponding to the parallelism of the green belts on the left side of the d-th road section Standard of merit And indicating the standard parallelism of the green belt and the road.
The calculation formula of the parallelism quality coincidence influence coefficient of the green belts on the right side of each road section is
φ′ d Representing quality corresponding to the parallelism of the green belt at the right side of the d-th road section to meet an influence coefficient P' d And the parallelism of the green belts on the right side of the d-th road section is shown.
Preferably, the road greening analysis further comprises comprehensive quality analysis of the left green belts of each road section and the right green belts of each road section, the comprehensive quality coincidence influence coefficient of the left green belt quality of each road section is counted according to the counted quality coincidence of the left green belt width ratio of each road section, the quality coincidence influence coefficient of the left green belt tree perpendicularity quality of each road section, the quality coincidence influence coefficient of the left green belt tree distance of each road section and the quality coincidence influence coefficient of the left green belt parallelism quality of each road section, the comprehensive quality coincidence influence coefficient of the right green belt tree perpendicularity quality of each road section, the comprehensive quality coincidence influence coefficient of the right green belt tree distance of each road section and the quality coincidence influence coefficient of the right green belt parallelism quality of each road section, the comprehensive quality coincidence influence coefficient of the right green belt quality of each road section and the symmetrical quality coincidence influence coefficient of the road section are counted.
Specifically, the comprehensive coincidence influence coefficient calculation formula of the left green belt quality of each road section is
λ d To representThe quality of the green belt on the left side of the d-th road section comprehensively conforms to the influence coefficient.
Specifically, the comprehensive quality conformity influence coefficient calculation formula of the green belts on the right side of each road section is
λ d ' means that the quality of the green belts on the right side of the d-th road section comprehensively conforms to the influence coefficient.
Specifically, the road greening comprehensive quality conformity influence coefficient calculation formula is
Q represents the comprehensive quality conforming influence coefficient corresponding to the road greening, and n represents the number of the road sections corresponding to the road in the greening area.
Referring to fig. 2, a second aspect of the present invention provides a municipal engineering construction project quality supervision system based on feature recognition, including a region division module, a road basic parameter acquisition module, a green belt basic parameter detection module, a tree number statistics module, a tree perpendicularity detection module, a tree spacing detection module, a green belt parallelism detection module, a data processing and analysis module, and a database, wherein the data processing and analysis module is respectively connected with the road basic parameter acquisition module, the green belt basic parameter detection module, the tree perpendicularity detection module, the tree spacing detection module, the green belt parallelism detection module, and the database, the road basic parameter acquisition module is connected with the region division module, and the tree number statistics module is connected with the tree perpendicularity detection module.
The database is used for storing a corresponding standard difference value between two detection line sections, a corresponding standard verticality of a green belt tree, a corresponding standard distance of the green belt tree and a corresponding standard parallelism of the green belt and a road.
A third aspect of the present invention provides a terminal, including: the system comprises a processor, a memory and a network interface, wherein the memory and the network interface are connected with the processor; the network interface is connected with a nonvolatile memory in the server; when running, the processor calls the computer program from the nonvolatile memory through the network interface, and runs the computer program through the memory, so as to execute the method of the invention.
A fourth aspect of the present invention provides a readable storage medium applied to a computer, where a computer program is burned in the readable storage medium, and when the computer program runs in a memory of a server, the method of the present invention is implemented.
The foregoing is illustrative and explanatory only of the present invention, and it is intended that the present invention cover modifications, additions, or substitutions by those skilled in the art, without departing from the spirit of the invention or exceeding the scope of the claims.
Claims (7)
1. A municipal engineering construction project quality supervision method based on feature recognition is characterized by comprising the following steps: the method comprises the following steps:
s1, dividing road areas: the method comprises the steps that a road corresponding to a greening area is subjected to area division through an area division module, the length corresponding to the road of the greening area is further obtained, the road of the greening area is divided into road sections according to a preset sequence, the divided road sections are numbered according to the preset sequence, and the number is sequentially marked as 1,2,. I,. N;
s2, acquiring basic road section parameters: acquiring the length and the width corresponding to each road section of each greening area through a road basic parameter acquisition module, and recording the lengths and the widths as a and b respectively;
s3, acquiring basic parameters of the green belt: detecting basic parameters corresponding to the green belts on the left side of each road section and the right side of each road section through a green belt basic parameter detection module, and further acquiring the basic parameters corresponding to the green belts on the two sides of each road section;
s4, counting the number of planted trees: the method comprises the steps that a tree number counting module is used for counting the number of trees planted in green belts on the left sides of all road sections and the number of trees planted in green belts on the right sides of all road sections respectively, meanwhile, the trees planted in the green belts on the left sides of all road sections are numbered according to a preset sequence, and are marked as 1,2,. J,. M sequentially, and meanwhile, the trees planted in the green belts on the right sides of all road sections are numbered according to the preset sequence, and are marked as 1',2',. J,. M ';
s5, detecting the verticality of the tree: detecting the verticality corresponding to each tree in the green belt on the left side of each road section and the verticality corresponding to each tree in the green belt on the right side of each road section through a tree verticality detection module, and further acquiring the verticality corresponding to each tree in the green belt on the left side of each road section and the verticality corresponding to each tree in the green belt on the right side of each road section;
s6, detecting the distance between the trees: detecting the distance between two adjacent trees of the green belt on the left side of each road section and the distance between two adjacent trees in the green belt on the right side of each road section through a tree spacing detection module, and further obtaining the distance between two adjacent trees of the green belt on the left side of each road section and the distance between two adjacent trees in the green belt on the right side of each road section;
s7, green belt parallelism detection: detecting the parallelism of the left green belt of each road section and the parallelism of the right green belt of each road section and each road section through a green belt parallelism detection module, and further obtaining the parallelism corresponding to the left green belt of each road section and the parallelism corresponding to the right green belt of each road section;
s8, road greening analysis: analyzing basic parameters and parallelism corresponding to the left green belts and the right green belts of each road section, verticality of trees planted in the green belts and intervals among the planted trees through a data processing and analyzing module, and further counting the comprehensive quality of road greening and according with influence coefficients;
the specific detection process of the green belt parallelism comprises the following steps:
s71, according to the length corresponding to each road section, further equally dividing each road section into each sub-road section according to a preset distance, distributing a central point corresponding to each sub-road section as a road section detection point, further numbering the road section detection points corresponding to each road section according to a preset sequence, and sequentially marking the road section detection points as 1,2,. X,. Y;
s72, according to the length corresponding to the left green belt of each road section, further equally dividing each green belt into left green areas according to the preset road section dividing distance, distributing the center points of the left green areas as left green detection points, and further numbering the left green detection points corresponding to each road section according to a preset sequence, wherein the numbers are sequentially marked as 1',2',. X ',. Y';
s73, acquiring greening detection points corresponding to the right sides of the road sections according to the acquisition method of the greening detection points on the left sides of the road sections, numbering the greening detection points on the right sides corresponding to the road sections according to a preset sequence, and sequentially marking the greening detection points as 1',2',.
S74, connecting each road section detection point with each left side greening detection point corresponding to each road section respectively, further acquiring a connecting line section corresponding to each road section detection point and each left side greening detection point of each road section, recording the connecting line section as a left side detection line section, and acquiring each right side detection line section corresponding to each road section according to the acquisition method of the left side detection line section;
s75, numbering the left detection line segments corresponding to the road segments according to a preset sequence, and sequentially marking the left detection line segments as 1,2,. K,. T, and numbering the right detection line segments corresponding to the road segments according to the preset sequence, wherein the right detection line segments are sequentially marked as 1',2,. K,. T';
s76, respectively obtaining the length corresponding to each left detection line segment of each road section and the length corresponding to each right detection line segment of each road section, recording the length of each left detection line segment corresponding to each road section as f, and recording the length of each right detection line segment corresponding to each road section as f';
s77, comparing the lengths of the adjacent left detection line segments of each road section with each other according to the length of each left detection line segment of each road section, further obtaining the difference value corresponding to the length of each adjacent left detection line segment of each road section, and counting the parallelism corresponding to the left green belt of each road section;
s78, acquiring the parallelism corresponding to the green belts on the right side of each road section according to a statistical method of the parallelism of the green belts on the left side of each road section;
the specific process of the road greening analysis comprises the following steps:
s81, comparing the width corresponding to each road section of the green area with the width corresponding to the green belt on the left side of each road section and the width corresponding to the green belt on the right side of each road section according to the width corresponding to each road section of the green area, the width corresponding to the green belt on the left side of each road section and the width corresponding to the green belt on the right side of each road section respectively, and further counting the quality coincidence influence coefficient of the width ratio of the green belt on the left side of each road section and the quality coincidence influence coefficient of the width ratio of the green belt on the right side of each road section;
s82, comparing the width corresponding to the green belt on the left side of each road section with the width corresponding to the green belt on the right side of each road section, and further counting the symmetry quality of the green belt of the road according with the influence coefficient;
s83, according to the perpendicularity set of the trees of the green belts on the left side of each road section and the perpendicularity set of the trees on the right side of each road section, obtaining the corresponding perpendicularity of each tree in the green belts on the left side of each road section and the corresponding perpendicularity of each tree in the green belts on the right side of each road section, respectively comparing the corresponding perpendicularity of each tree in the green belts on the left side of each road section and the corresponding perpendicularity of each tree in the green belts on the right side of each road section with the corresponding standard perpendicularity of the corresponding green belts in the database, and further counting the perpendicularity quality of the trees of the green belts on the left side of each road section according with the influence coefficient and the perpendicularity quality of the trees of the green belts on the right side of each road section according with the influence coefficient;
s84, according to the distance between every two adjacent trees of the green belt on the left side of each road section and the distance between every two adjacent trees of the green belt on the right side of each road section, comparing the distance between every two adjacent trees of the green belt on the left side of each road section and the distance between every two adjacent trees of the green belt on the right side of each road section with the corresponding standard interval of the corresponding green belt tree in the database respectively, and counting the interval quality conformity influence coefficient of the green belt trees on the left side of each road section and the interval quality conformity influence coefficient of the green belt trees on the right side of each road section;
s85, according to the parallelism corresponding to the green belts on the left side of each road section and the parallelism corresponding to the green belts on the right side of each road section, comparing the parallelism corresponding to the green belts on the left side of each road section and the parallelism corresponding to the green belts on the right side of each road section with the standard parallelism corresponding to the green belts and the roads in the database respectively, and counting the quality conformity influence coefficient of the parallelism of the green belts on the left side of each road section and the quality conformity influence coefficient of the parallelism of the green belts on the right side of each road section;
the road greening analysis also comprises comprehensive quality analysis on the left green belts of all the road sections and the right green belts of all the road sections, further statistics is carried out on the comprehensive quality coincidence influence coefficient of the quality of the left green belts of all the road sections, the verticality quality of the trees of the left green belts of all the road sections, the space quality of the trees of the left green belts of all the road sections, and the parallelism quality of the left green belts of all the road sections according to the statistics, further statistics is carried out on the comprehensive quality coincidence influence coefficient of the quality of the left green belts of all the road sections, the verticality quality of the trees of the right green belts of all the road sections according to the ratio quality coincidence influence coefficient of the right green belts of all the road sections, the space quality coincidence influence coefficient of the trees of the right green belts of all the road sections, and the parallelism quality coincidence influence coefficient of the right green belts of all the road sections, statistics is carried out on the comprehensive quality coincidence influence coefficient of the right green belts of all the road sections, and the comprehensive quality coincidence influence coefficient of the green belts of the left green belts of all the road sections according to the influence coefficient of the road.
2. The feature identification-based municipal engineering construction project quality supervision method according to claim 1, wherein: the basic parameter detection of the green belt comprises a plurality of laser range finders, wherein the laser range finders are respectively used for detecting basic parameters corresponding to the green belts on the left side of each road section and the green belts on the right side of each road section, the basic parameters of the green belts comprise the length and the width of the green belts, and then the length and the width corresponding to the green belts on the left side of each road section and the green belts on the right side of each road section are obtained.
3. The feature identification-based municipal engineering construction project quality supervision method according to claim 1, wherein: the tree verticality detection comprises a plurality of tree detection units which are respectively used for detecting the verticality corresponding to each tree in the green belt on the left side of each road section and the verticality corresponding to each tree in the green belt on the right side of each road section, and then a three-dimensional laser scanner is utilizedRespectively scanning and shooting trees in green belts on the left side of each road section and the right side of each road section, further acquiring point cloud data corresponding to trees in the green belts on the left side of each road section and spatial three-dimensional point cloud data corresponding to trees in the green belts on the right side of each road section, acquiring angles corresponding to the ground of each tree through a third-party website, recording the angles as theta, further counting the verticality corresponding to each tree in the green belts on the left side of each road section and the verticality corresponding to each tree in the green belts on the right side of each road section, and further constructing a tree verticality set C of the green belts on the left side of each road section d (C d 1,C d 2,...C d j,...C d m) and a tree perpendicularity set C 'on the right side of each road section' d (C′ d 1′,C′ d 2′,...C′ d j′,...C′ d m′)，C d j represents the verticality, C ', corresponding to the jth tree in the left green belt of the d road section' d j 'represents the corresponding verticality of the j' tree in the green belt on the right side of the d road section, d represents the road section number, and d =1,2.
4. The feature identification-based municipal engineering construction project quality supervision method according to claim 1, wherein: the tree distance detection device comprises a plurality of infrared distance measuring sensors which are respectively used for detecting the distance between adjacent trees of the green belts on the left side of each road section and the distance between adjacent trees of the green belts on the right side of each road section, so as to obtain the distance between adjacent trees of the green belts on the left side of each road section and the distance between two adjacent trees of the green belts on the right side of each road section, the distance between adjacent trees of the green belts on the left side of each road section is recorded as L, and the distance between two adjacent trees of the green belts on the right side of each road section is recorded as L'.
5. A municipal engineering construction project quality supervision system based on feature recognition for implementing the method of any one of claims 1 to 4, characterized in that: the system comprises an area dividing module, a road basic parameter acquisition module, a green belt basic parameter detection module, a tree quantity statistical module, a tree verticality detection module, a tree spacing detection module, a green belt parallelism detection module, a data processing and analyzing module and a database, wherein the data processing and analyzing module is respectively connected with the road basic parameter acquisition module, the green belt basic parameter detection module, the tree verticality detection module, the tree spacing detection module, the green belt parallelism detection module and the database, the road basic parameter acquisition module is connected with the area dividing module, and the tree quantity statistical module is connected with the tree verticality detection module.
6. A terminal, characterized by: the method comprises the following steps: the system comprises a processor, a memory and a network interface, wherein the memory and the network interface are connected with the processor; the network interface is connected with a nonvolatile memory in the server; the processor, when running, retrieves a computer program from the non-volatile memory via the network interface and runs the computer program via the memory to perform the method of any of the preceding claims 1-4.
7. A readable storage medium for use with a computer, comprising: the readable storage medium is burned with a computer program that, when run in the memory of the server, implements the method of any of the above claims 1-4.
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