CN113159635A - 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 the 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 road greening projects not only reduces the influence of the development of the transportation industry on urban environment, but also improves the urban aesthetic degree, so that the quality of the road greening projects needs to be supervised in order to guarantee the construction effect of the road greening projects.
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, road area division: 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 sequentially marking the sections 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, a.
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 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: 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 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 and the width of the green belt, and further 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.
Further, 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 constructedd(Cd1,Cd2,...Cdj,...Cdm) and a set C 'of tree verticality at right side of each road segment'd(C′d1′,C′d2′,...C′dj′,...C′dm′)，Cdj represents the verticality, C ', corresponding to the jth tree in the left green belt of the d road section'dj '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 is 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 the central points corresponding to each sub-road section as road section detection points, 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,. once.x,. once.y;
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 the preset dividing distance of the road section, distributing the center points of the left green areas as left green detection points, and 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, marking 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, sequentially marking the left detection line segments as 1,2,. k,. t, numbering the right detection line segments corresponding to the road segments according to the preset sequence, and sequentially marking the right detection line segments as 1 ', 2,. k,. t';
s76, respectively acquiring 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, obtaining the corresponding difference 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;
and S78, obtaining 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 section of the green area with the width corresponding to the green belt on the left side of each section and the width corresponding to the green belt on the right side of each section according to the width corresponding to each section of the green area, the width corresponding to the green belt on the left side of each section and the width corresponding to the green belt on the right side of each section, and further counting the quality coincidence influence coefficient of the width ratio of the green belt on the left side of each section and the quality coincidence influence coefficient of the width ratio of the green belt on the right side of each 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, 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 the adjacent trees of the green belts on the left side of each road section and the distance between the 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 respectively according to the distance between the adjacent trees of the green belts on the left side of each road section and the distance between the adjacent trees of the green belts on the right side of each road section, and counting the quality conformity between the trees of the green belts on the left side of each road section and the quality conformity between the trees of the green belts on the right side of each road section according with the influence coefficients;
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, and counting the quality conformity influence coefficient of the parallelism quality of the green belts on the left side of each road section and the quality conformity influence coefficient of the parallelism quality of the green belts on the right side of each road section
Further, the road greening analysis also comprises the step of carrying out comprehensive quality analysis on the left green belts of all the road sections and the right green belts of all the road sections, further carrying out statistics on the comprehensive quality coincidence influence coefficient of the left green belt quality of all the road sections according to the statistics that the left green belt width ratio quality of all the road sections accords with the influence coefficient, the tree perpendicularity quality coincidence influence coefficient of the left green belt of all the road sections, the tree parallelism quality coincidence influence coefficient of all the road sections and the left green belt parallelism quality coincidence influence coefficient of all the road sections, further carrying out statistics on the comprehensive quality coincidence influence coefficient of the left green belt quality of all the road sections according to the quality coincidence influence coefficient of the right green belt width ratio of all the road sections, the tree perpendicularity quality coincidence influence coefficient of the right green belt of all the road sections, the tree interval quality coincidence influence coefficient of the right green belt of all the road sections and the parallel quality coincidence influence coefficient of all the road sections, carrying out statistics on the right green belt quality coincidence influence coefficient of all the road sections, and then, according to the counted comprehensive quality coincidence influence coefficients of the green belts on the left side of each road section, the calculated comprehensive quality coincidence influence coefficients of the green belts on the right side of each road section and the calculated symmetrical quality coincidence influence coefficients of the green belts on the right side of the road section, the calculated comprehensive quality coincidence influence coefficients of the green belts on the road are counted.
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 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 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, in a first aspect, the present invention provides a method for monitoring quality of a municipal engineering construction project based on feature recognition, the method comprising the following steps:
s1, road area division: 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 sequentially marking the sections 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;
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 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, a.
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, and then the three-dimensional laser scanner is used for respectively detecting the green belt on the left side of each road section and the green belt on the right side of each road sectionScanning and shooting trees in greenbelts, further acquiring point cloud data corresponding to trees in the greenbelts on the left sides of all the road sections and spatial three-dimensional point cloud data corresponding to trees in the greenbelts on the right sides of all the road sections, acquiring angles of the trees corresponding to the ground through a third-party website, recording the angles as theta, further counting the verticality corresponding to the trees in the greenbelts on the left sides of all the road sections and the verticality corresponding to the trees in the greenbelts on the right sides of all the road sections, and further constructing a verticality set C of the trees in the greenbelts on the left sides of all the road sectionsd(Cd1,Cd2,...Cdj,...Cdm) and a set C 'of tree verticality at right side of each road segment'd(C′d1′,C′d2′,...C′dj′,...C′dm′)，Cdj represents the verticality, C ', corresponding to the jth tree in the left green belt of the d road section'dj '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 is 1, 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.
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 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;
specifically, the tree spacing detection includes 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 embodiment of the invention detects the tree spacing, the infrared sensor is used for detecting the distance between adjacent numerical values of green belts on two sides of each road section, so that the authenticity and the accuracy of the 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 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;
specifically, 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 the central points corresponding to each sub-road section as road section detection points, 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,. once.x,. once.y;
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 the preset dividing distance of the road section, distributing the center points of the left green areas as left green detection points, and 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, marking 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, sequentially marking the left detection line segments as 1,2,. k,. t, numbering the right detection line segments corresponding to the road segments according to the preset sequence, and sequentially marking the right detection line segments as 1 ', 2,. k,. t';
s76, respectively acquiring 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, obtaining the corresponding difference 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
PdRepresenting the corresponding parallelism of the green belts on the left side of the d-th road section, fc dRepresents the length corresponding to the length of the c-th left detection line of the d-th path, fc-1 dThe length corresponding to the length of the c-1 left detection line segment of the d-th road section is represented, c represents the number of the left detection line segment of each road section, and c is 1,2, aStandard of meritRepresenting 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 is 2,. k,. t;
and S78, acquiring the parallelism corresponding to the right green belt of each road section according to the statistical method of the parallelism of the left green belt 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 by detecting 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 engineering supervision method is not comprehensive is effectively solved, the authenticity and the reference of the road greening engineering quality supervision result are greatly improved, and the road greening engineering 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 section of the green area with the width corresponding to the green belt on the left side of each section and the width corresponding to the green belt on the right side of each section according to the width corresponding to each section of the green area, the width corresponding to the green belt on the left side of each section and the width corresponding to the green belt on the right side of each section, and further counting the quality coincidence influence coefficient of the width ratio of the green belt on the left side of each section and the quality coincidence influence coefficient of the width ratio of the green belt on the right side of each 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
αdRepresenting the width ratio quality coincidence influence coefficient, k, corresponding to the green belt on the left side of the d-th road sectiondIndicates the width corresponding to the green belt on the left side of the d-th road section, bdIndicating 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
αd'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'dShowing 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 calculation formula of the symmetry quality coincidence influence coefficient of the road green belt is as follows
And expressing the quality corresponding to the symmetry of the road green belt to accord 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, 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;
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
βdRepresenting 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 Cd rRepresents the corresponding verticality of the r-th tree in the green belt on the left side of the d-th road section, CStandard of meritShowing the standard verticality, r table, corresponding to the trees in the green beltThe tree number of the green belt on the left side of each road section is shown, and r is 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′dRepresenting 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 '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 'is 1', 2, a.
S84, comparing the distance between the adjacent trees of the green belts on the left side of each road section and the distance between the 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 respectively according to the distance between the adjacent trees of the green belts on the left side of each road section and the distance between the adjacent trees of the green belts on the right side of each road section, and counting the quality conformity between the trees of the green belts on the left side of each road section and the quality conformity between the trees of the green belts on the right side of each road section according with the influence coefficients;
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
δdExpressing the quality coincidence influence coefficient, L, corresponding to the tree spacing of the green belt on the left side of the d-th road sectionr,r-1 dRepresents 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, LStandard of meritRepresenting the standard spacing, a ', corresponding to the trees of the green belt'dThe length of the green belt on the left side of the d-th road section is represented, 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′dIs shown asThe quality corresponding to the distance between trees in the green belts on the right sides of the d road sections conforms to the influence coefficient Lr′,r′-1 dShows the distance, a ″, between the r 'r th tree and the r' -1 th tree in the green belt on the left side of the d-th road sectiondThe 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, and counting the quality conformity influence coefficient of the parallelism quality of the left green belt of each road section and the quality conformity influence coefficient of the parallelism quality of the right green belt of each road section.
Wherein, the calculation formula of the parallelism quality coincidence influence coefficient of the green belt at the left side of each road section is
φdRepresenting the quality coincidence influence coefficient, P, corresponding to the parallelism of the green belts on the left side of the d-th road sectionStandard of meritAnd 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′dRepresenting quality coincidence influence coefficient P 'corresponding to the parallelism of the green belts on the right side of the d-th road section'dAnd 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 the step of carrying out comprehensive quality analysis on the left green belts of each road section and the right green belts of each road section, further carrying out statistics on the comprehensive quality coincidence influence coefficient of the left green belt quality of each road section according to the statistics that the left green belt width ratio quality of each road section conforms to the influence coefficient, the tree perpendicularity quality of the left green belt of each road section conforms to the influence coefficient, the tree parallelism quality of the left green belt of each road section conforms to the influence coefficient, and the comprehensive quality coincidence influence coefficient of the right green belt quality of each road section according to the statistics that the right green belt width ratio quality of each road section conforms to the influence coefficient, the tree perpendicularity quality of the right green belt of each road section conforms to the influence coefficient, the tree spacing quality of the right green belt of each road section conforms to the influence coefficient, and the right green belt parallelism quality of each road section conforms to the influence coefficient, and then, according to the counted comprehensive quality coincidence influence coefficients of the green belts on the left side of each road section, the calculated comprehensive quality coincidence influence coefficients of the green belts on the right side of each road section and the calculated symmetrical quality coincidence influence coefficients of the green belts on the right side of the road section, the calculated comprehensive quality coincidence influence coefficients of the green belts on the road are counted.
Specifically, the calculation formula of the comprehensive quality conformity influence coefficient of the green belt at the left side of each road section is
λdAnd (4) representing that the 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
λd' 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, which includes 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 merely exemplary and illustrative of the principles of the present invention and various modifications, additions and substitutions of the specific embodiments described herein may be made by those skilled in the art without departing from the principles of the present invention or exceeding the scope of the claims set forth herein.
Claims (10)
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, road area division: 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 sequentially marking the sections 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, a.
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 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: 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.
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 perpendicularity detection comprises a plurality of tree detection units, wherein the tree detection units 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, 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, 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 perpendicularity corresponding to each tree in the green belt on the right side of each road section are further counted, and a tree perpendicularity set C on the left side of each road section is constructedd(Cd1,Cd2,...Cdj,...Cdm) and a set C 'of tree verticality at right side of each road segment'd(C′d1′,C′d2′,...C′dj′,...C′dm′)，Cdj represents the left of the d-th road sectionPerpendicularity, C 'corresponding to j tree in side green belt'dj '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 is 1, 2.
4. The feature identification-based municipal engineering construction project quality supervision method according to claim 1, wherein: the tree spacing 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 marked as L, and the distance between two adjacent trees of the green belts on the right side of each road section is marked as L'.
5. The feature identification-based municipal engineering construction project quality supervision method according to claim 1, wherein: 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 the central points corresponding to each sub-road section as road section detection points, 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,. once.x,. once.y;
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 the preset dividing distance of the road section, distributing the center points of the left green areas as left green detection points, and 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, marking 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, sequentially marking the left detection line segments as 1,2,. k,. t, numbering the right detection line segments corresponding to the road segments according to the preset sequence, and sequentially marking the right detection line segments as 1 ', 2,. k,. t';
s76, respectively acquiring 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, obtaining the corresponding difference 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;
and S78, obtaining 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.
6. The feature identification-based municipal engineering construction project quality supervision method according to claim 1, wherein: the specific process of the road greening analysis comprises the following steps:
s81, comparing the width corresponding to each section of the green area with the width corresponding to the green belt on the left side of each section and the width corresponding to the green belt on the right side of each section according to the width corresponding to each section of the green area, the width corresponding to the green belt on the left side of each section and the width corresponding to the green belt on the right side of each section, and further counting the quality coincidence influence coefficient of the width ratio of the green belt on the left side of each section and the quality coincidence influence coefficient of the width ratio of the green belt on the right side of each 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, 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 the adjacent trees of the green belts on the left side of each road section and the distance between the 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 respectively according to the distance between the adjacent trees of the green belts on the left side of each road section and the distance between the adjacent trees of the green belts on the right side of each road section, and counting the quality conformity between the trees of the green belts on the left side of each road section and the quality conformity between the trees of the green belts on the right side of each road section according with the influence coefficients;
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, and counting the quality conformity influence coefficient of the parallelism quality of the left green belt of each road section and the quality conformity influence coefficient of the parallelism quality of the right green belt of each road section.
7. The feature identification-based municipal engineering construction project quality supervision method according to claim 1, wherein: the road greening analysis also comprises the step of carrying out comprehensive quality analysis on the green belts on the left side of each road section and the green belts on the right side of each road section, further counting the quality comprehensive coincidence influence coefficient of the green belts on the left side of each road section according to the counted quality coincidence influence coefficient of the width ratio of the green belts on the left side of each road section, the quality coincidence influence coefficient of the trees on the left side of each road section according to the verticality quality coincidence of the green belts on the left side of each road section, and the quality coincidence influence coefficient of the trees on the right side of each road section according to the quality coincidence influence coefficient of the width ratio of the green belts on the right side of each road section, the quality coincidence influence coefficient of the trees on the right side of each road section, the quality comprehensive coincidence influence coefficient of the trees on the right side of each road section, further carrying out comprehensive coincidence of the quality influence coefficient of the green belts on the left side of each road section according to the counted quality, And counting the comprehensive quality coincidence influence coefficient of the road greening according to the comprehensive quality coincidence influence coefficient of the right green belt of each road section and the symmetry quality coincidence influence coefficient of the road green belt.
8. The utility model provides a municipal works construction project quality supervision system based on feature identification which 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.
9. 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 claims 1-7.
10. A readable storage medium applied to a computer, characterized in that: 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 1-7.
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