CN114459372B - Online intelligent early warning method for deformation damage of steel frame structure steel column - Google Patents
Online intelligent early warning method for deformation damage of steel frame structure steel column Download PDFInfo
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- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/16—Measuring arrangements characterised by the use of optical techniques for measuring the deformation in a solid, e.g. optical strain gauge
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B15/00—Measuring arrangements characterised by the use of electromagnetic waves or particle radiation, e.g. by the use of microwaves, X-rays, gamma rays or electrons
- G01B15/06—Measuring arrangements characterised by the use of electromagnetic waves or particle radiation, e.g. by the use of microwaves, X-rays, gamma rays or electrons for measuring the deformation in a solid
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Abstract
The invention discloses an online intelligent early warning method for deformation damage of a steel frame structure steel column, which belongs to the technical field of civil engineering measurement and comprises the steps of carrying out regional division and labeling treatment on a target steel column to obtain regional division groups; acquiring image information and detection information of a target steel column, and preprocessing the image information and the detection information to obtain image processing information and detection processing information; acquiring an image value and a wave detection set of a target steel column according to the image processing information and the detection processing information, respectively matching the image value and the wave detection set with an image standard value and a wave detection standard set to obtain an image analysis set and a wave detection analysis set, comprehensively evaluating the target steel column to obtain an evaluation result, and carrying out early warning and prompting according to the evaluation result; the invention can solve the technical problems of low accuracy of early warning of deformation damage of the steel frame structure steel column and fuzzy early warning content in the existing scheme.
Description
Technical Field
The invention relates to the technical field of civil engineering measurement, in particular to an online intelligent early warning method for deformation damage of a steel frame structure steel column.
Background
The steel structure is a structure formed by steel materials, is one of main building structure types, and mainly comprises steel beams, steel columns, steel trusses and other components made of section steel, steel plates and the like, and all the components or parts are connected by adopting welding seams, bolts or rivets; the steel column with steel structure is overloaded for a long time and is easy to generate arch bending deformation.
The invention discloses a method for monitoring collapse risk of a steel structure building in a fire disaster, which is disclosed by the invention with the publication number of CN106767718B and the name of a method for monitoring collapse risk of the steel structure building in the fire disaster, wherein a digital close-range photogrammetry technology is used for shooting pictures before the fire disaster and after the fire disaster, then the space coordinates of the pictures are obtained by processing the pictures before the fire disaster and the pictures during the fire disaster, and further the deformation of the steel structure is calculated, when the deformation is larger than the limit state of the bearing capacity, the building can be considered to have the collapse risk.
However, this solution has certain drawbacks: firstly, the state of a steel structure is monitored and analyzed through images in a fire disaster or under normal conditions, and the steel structure is easily influenced by environment and processing technology, so that the accuracy of image analysis and early warning is poor; secondly, the specific position of deformation cannot be accurately determined according to the image analysis result, and further accurate early warning prompt cannot be carried out; finally, the slight deformation cannot be monitored and analyzed for prompting, so that the deformation monitoring and prompting effect is limited.
Disclosure of Invention
Aiming at the defects existing in the prior art, the invention aims to provide an online intelligent early warning method for deformation damage of a steel frame structure steel column, which solves the following technical problems: how to solve the technical problems of low accuracy and fuzzy early warning content of deformation damage of the steel frame structure steel column in the existing scheme.
The aim of the invention can be achieved by the following technical scheme:
an online intelligent early warning method for deformation damage of a steel frame structure steel column comprises the following steps:
Obtaining a target steel column, carrying out regional division and labeling treatment on the target steel column to obtain regional division groups;
Acquiring image information and detection information of a target steel column through a binocular camera and a radar respectively, and preprocessing the image information and the detection information to obtain image processing information and detection processing information;
Acquiring an image value and a wave detection set of a target steel column according to the image processing information and the detection processing information, and respectively matching the image value and the wave detection set with an image standard value and a wave detection standard set to obtain an image analysis set and a wave detection analysis set;
and comprehensively evaluating the target steel column according to the image analysis set and the wave detection analysis set to obtain an evaluation result, and carrying out early warning and prompting according to the evaluation result.
Further, the specific steps of obtaining the regional division set include:
The method comprises the steps of obtaining the height of a target steel column, equally dividing the target steel column according to a preset dividing distance to obtain a plurality of dividing sub-columns, respectively obtaining the center points of the plurality of dividing sub-columns, setting the center points as tag points, respectively setting the lowermost dividing sub-column and the uppermost dividing sub-column as a first identification column and a second identification column, and numbering the plurality of dividing sub-columns from bottom to top in sequence to obtain a number set ZBH i of the dividing sub-columns, i=1, 2,3, n; n is a positive integer; marking and combining the label points on the molecular dividing column to obtain a label set ZBH i 1; the number set and the tag set constitute a region division set.
Further, the image information includes an image of the target steel column, and the detection information includes transmission data and reception data of the detection wave.
Further, the specific steps of preprocessing the image information include:
acquiring an image of a target steel column in image information, carrying out gray processing on the image, extracting a frame and a plurality of tag points of the target steel column in the image by utilizing an image processing algorithm, acquiring the distance between the tag points of a first tag column and a second tag column, and setting the distance as a fatigue total value PZ;
setting a label point of a first identification column as an origin, establishing a two-dimensional coordinate system according to a preset distance value and an axial direction, acquiring coordinates corresponding to the label points of a plurality of dividing sub-columns on a target steel column, marking the coordinates as detection coordinates (xi, yi), and forming a coordinate set by the marked coordinates of the label points of the dividing sub-columns;
Sequentially obtaining the distances between the label points of the adjacent dividing sub-columns from bottom to top, setting the distances as fatigue scores, marking a plurality of fatigue scores as PLFi in sequence, and arranging and combining the fatigue scores and the total fatigue values of the marked dividing sub-columns from bottom to top to obtain a distance set;
The coordinate set and the distance set constitute image processing information.
Further, the specific step of obtaining the image value includes:
Obtaining fatigue scores and total fatigue values of a plurality of division sub-columns in the image processing information, carrying out normalization processing, and obtaining a fatigue score and total fatigue value of the division sub-columns through a formula And calculating and acquiring image values TX of the target steel column, wherein a1 and a2 are different scale coefficients and are larger than zero, and the value ranges of a1 and a2 can be (0 and 5).
Further, the specific step of acquiring the image analysis set includes:
Obtaining an image standard value corresponding to a target steel column, calculating a ratio between the image value and the image standard value, obtaining an integer part and a decimal part of the ratio, respectively setting the integer part and the decimal part as P1 and P2, and analyzing the comparison value;
if P1 is less than P10 and P2 is more than P20, judging that the deformation condition of the target steel column in the image exists, and generating a first matching signal; p10 and P20 are preset integers and decimal numbers respectively;
judging that the target steel column in the image is in a normal state under other conditions, and generating a second matching signal; and further verifying the deformation condition according to the first matching signal.
Further, the specific steps for further verifying the deformation condition include:
Acquiring detection coordinates (xi, yi) corresponding to a plurality of label points dividing a sub-column on a two-dimensional coordinate system and preset standard coordinates (xi 0, yi 0);
Calculating and obtaining a deflection PY through a formula PY= |xi0-xi|+|yi0-yi|, and analyzing the deflection to determine a specific deformation position of the target steel column;
Matching the offset with a preset offset threshold, and if the offset is smaller than the offset threshold, judging that the detection coordinate corresponding to the offset is normal;
if the offset is not less than the offset threshold, judging that the detection coordinate corresponding to the offset is abnormal, and setting the detection coordinate as a selected coordinate;
sorting and combining a plurality of selected coordinates from bottom to top to obtain a coordinate sorting set;
Obtaining a difference value between an offset degree and an offset threshold value corresponding to a selected coordinate in a coordinate sorting set, setting the selected coordinate corresponding to the maximum difference value as a deformation positioning point coordinate, and generating a first prompting instruction;
The first and second matching signals, the ordered set of coordinates and the first hint instruction form an image analysis set.
Further, the specific steps of preprocessing the detection information include:
Acquiring transmitting data and receiving data of detection waves in the detection information, extracting the values of the wave intensity and the transmitting time length transmitted by a plurality of sub-column label points in the transmitting data, and marking the values as a first wave intensity FBQi and a first time length FBSi respectively; extracting the values of the wave intensity and the receiving time length reflected by a plurality of sub-column dividing tag points in the received data and marking the values as a second wave intensity SBQi and a second time length SBSi respectively;
Respectively arranging and combining the first wave intensities of a plurality of sub-column label points and the corresponding second wave intensities, the first time lengths and the corresponding second time lengths according to numbers from bottom to top to obtain a wave intensity ordered set and a time length ordered set; the wave intensity ordered set and the duration ordered set form detection processing information.
Further, the specific steps of acquiring the wave probe set include:
Acquiring various values of a wave intensity ordered set and a time length ordered set in detection processing information, carrying out normalization processing, and calculating and acquiring the wave detection values BT of a plurality of sub-column label points on a target steel column through the formula BT=b1× (FBQi + SBQi + 0.1624) +b2× (FBSi + SBSi + 0.1473), wherein b1 and b2 are different scale coefficients and are both larger than zero, and the value ranges of b1 and b2 can be (0, 10);
and a plurality of wave detection values are arranged and combined according to numbers from bottom to top to obtain a wave detection set of the target steel column.
Further, the specific steps of acquiring the sounding analysis set include:
calculating and obtaining a difference value between a wave detection value in the wave detection analysis set and a wave detection standard value corresponding to the wave detection standard set, marking the difference value as P3, and analyzing;
If P3 is less than or equal to P30, judging that the marking molecular column label point is in a normal state, and generating a first wave measurement signal; p30 is a preset real number;
If P3 is more than P30, judging that the mark point of the dividing sub-column is in a deformation state, generating a second wave measurement signal, and setting the mark point corresponding to the second wave measurement signal as a selected mark;
Analyzing the selected labels according to the second wave measurement signals, obtaining numbers corresponding to the selected labels, marking the numbers as selected numbers, and arranging a plurality of selected numbers in ascending order to obtain a selected ordered set;
Counting the numbers of adjacent numbers in a plurality of selected numbers in the selected sorting set, if the numbers of the adjacent numbers are not smaller than m, wherein m is a positive integer, generating a second prompting instruction, and setting the adjacent numbers as deformation positioning point numbers;
The selected ordered set, the second wave detection signal, the second prompting instruction and the deformation positioning point number form a wave detection analysis set together.
Further, the specific steps of performing the comprehensive evaluation include:
acquiring an image analysis set and a wave detection analysis set, and analyzing and warning;
if the image analysis set contains a first prompt instruction and the wave detection analysis set contains a second prompt instruction, judging that the target steel column is deformed, overhauling the target steel column, generating a first early warning signal, and sending an overhauling prompt to a manager according to the first early warning signal and deformation locating point coordinates in the image analysis set;
If the wave detection analysis set contains a second prompt instruction but the image analysis set does not contain a first prompt instruction, judging that the target steel column has slight deformation, carrying out inspection and generating a second early warning signal, and sending an inspection prompt to a manager according to the second early warning signal and a plurality of deformation positioning point numbers in the wave detection analysis set;
If the wave detection analysis set does not contain the second prompt instruction and the image analysis set does not contain the first prompt instruction, the target steel column is not deformed and a normal signal is generated;
the first early warning signal, the second early warning signal and the normal signal form an evaluation result.
Compared with the prior art, the invention has the beneficial effects that:
1. According to the invention, the target steel column is subjected to regional division and labeling treatment, the image value of the steel frame structure steel column is obtained based on a plurality of label points after division, the deformation of the steel frame structure steel column in the image is subjected to digital analysis based on the image value, and the specific position of the deformation in the image is further determined according to the offset, so that the reliability of image analysis and early warning is effectively improved.
2. According to the invention, the wave detection value detected by the steel frame structure steel column can be obtained through the transmitted data and the received data of the detection wave, the real object of the steel frame structure steel column is monitored and analyzed based on the wave detection value, whether the steel frame structure steel column is deformed or not is judged, the specific position where the deformation occurs is determined based on the divided region numbers, and more reliable analysis and more accurate position early warning can be realized.
3. In the invention, the deformation damage of the steel frame structural steel column is monitored in a mode of combining image analysis and detection wave detection, comprehensive evaluation is carried out according to the image analysis result and the detection wave analysis result, and different modes of monitoring and early warning are carried out, so that the accuracy and the diversity of the deformation early warning of the steel frame structural steel column can be effectively improved.
Drawings
FIG. 1 is a flow chart diagram of an online intelligent early warning method for deformation damage of a steel frame structure steel column.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to FIG. 1, the invention provides an online intelligent early warning method for deformation damage of a steel frame structure steel column, comprising the following steps:
Obtaining a target steel column, carrying out regional division and labeling treatment on the target steel column to obtain regional division groups; the method comprises the following specific steps of:
The method comprises the steps of obtaining the height of a target steel column, monitoring and analyzing the vertical target steel column, when the target steel column is horizontal, obtaining the length of the target steel column in a self-adaptive mode to conduct monitoring and analyzing, equally dividing the target steel column according to a preset dividing distance to obtain a plurality of dividing sub-columns, setting specific values of the dividing distance according to the height of the target steel column, for example, the height of the target steel column is 8m, and then the dividing distance can be 0.2m, namely, equal dividing is conducted on the target steel column at intervals of 0.2 m;
It should be noted that, although the more the number of times the target steel column is divided, the higher the accuracy of deformation monitoring analysis is, the analysis on the target steel column is realized based on the image, and the target steel column on the image is in a state of equal proportion reduction, so that the result of the analysis is affected by the excessive number of times of the division during the analysis, and the preset dividing distance can be dynamically set according to the height of the target steel column and the corresponding specific image;
Respectively acquiring center points of a plurality of division sub-columns, setting the center points as tag points, and respectively setting the lowermost division sub-column and the uppermost division sub-column as a first identification column and a second identification column, wherein the first identification column and the second identification column are convenient for positioning and dividing the whole of the target steel column from the upper side and the lower side;
Numbering a plurality of division sub-columns sequentially from bottom to top to obtain a number set zbhi of the division sub-columns, i=1, 2,3, & gt, n; n is a positive integer; marking and combining the label points on the molecular dividing column to obtain a label set ZBH i 1; the numbering set and the label set form regional division set;
It should be noted that, in this embodiment, the purpose of performing region division and labeling processing on the target steel column is convenient for performing targeted processing and analysis on the acquired image and detection wave of the target steel column, so that the efficiency of monitoring and analyzing the deformation of the target steel column can be effectively improved, and the deformation can be accurately analyzed and positioned to a specific position, so that management personnel can perform processing in different modes according to different deformation conditions;
Acquiring image information and detection information of a target steel column through a binocular camera and a radar respectively, wherein the image information comprises an image of the target steel column, and the detection information comprises transmitting data and receiving data of detection waves;
It should be noted that, in the present embodiment, the image information and the detection information are acquired right in front of the target steel column, in actual situations, the image information and the detection information of the target steel column are also acquired from the left side or the right side, and the whole of the target steel column is monitored and analyzed comprehensively from different directions;
Notably, in the embodiment, the deformation condition of the target steel column is comprehensively analyzed and evaluated under the condition that the binocular camera and the radar are combined to realize early warning, so that the accuracy of deformation early warning can be effectively improved; in practical application, the image acquisition and the influence of the environment in the processing can lead to low accuracy of image analysis, and slight deformation can not be directly acquired from the image; therefore, with the aid of radar detection waves, whether deformation exists in the target steel column truly or not and the specific degree and specific position of the deformation are verified, so that the accuracy and the flexibility of deformation monitoring analysis can be effectively improved; the acquisition and processing results of the images are convenient for intuitively observing the external change of the target steel column;
preprocessing the image information and the detection information to obtain image processing information and detection processing information, and acquiring an image value and a wave detection set of a target steel column according to the image processing information and the detection processing information;
the specific steps of preprocessing the image information include:
acquiring an image of a target steel column in image information, carrying out gray processing on the image, extracting a frame of the target steel column in the image and a plurality of tag points by using an image gradient algorithm, wherein the image processing algorithm can be the image gradient algorithm, and acquiring the distance between the tag points of a first tag column and a second tag column and setting the distance as a fatigue total value PZ;
Setting a label point of a first identification column as an origin, establishing a two-dimensional coordinate system according to a preset distance value and an axial direction, setting the preset distance value according to the width of a target steel column, acquiring coordinates corresponding to label points of a plurality of dividing sub-columns on the target steel column, marking the coordinates as detection coordinates (xi, yi), and forming a coordinate set by the coordinates of the label points of the dividing sub-columns;
Sequentially obtaining the distances between the label points of the adjacent dividing sub-columns from bottom to top, setting the distances as fatigue scores, marking a plurality of fatigue scores as PLFi in sequence, and arranging and combining the fatigue scores and the total fatigue values of the marked dividing sub-columns from bottom to top to obtain a distance set;
The coordinate set and the distance set form image processing information;
the specific steps for acquiring the image value comprise:
Obtaining fatigue scores and total fatigue values of a plurality of division sub-columns in the image processing information, carrying out normalization processing, and obtaining a fatigue score and total fatigue value of the division sub-columns through a formula Calculating and acquiring image values TX of a target steel column, wherein a1 and a2 are different scale coefficients and are both larger than zero;
In this embodiment, a1 may have a value of 2, and a2 may have a value of 0.2372; when the target steel column is deformed, the value of the total fatigue value is reduced, and the sum of the fatigue scores of the plurality of division sub-columns is increased, because the deformed position can be seen as a triangle, and the three-side sum of the triangle is larger than the original linear sum; therefore, the method performs simultaneous analysis from the whole and partial aspects, and performs digital analysis and judgment on the target steel column on the image based on the image value;
the specific steps of preprocessing the detection information include:
Acquiring transmitting data and receiving data of detection waves in the detection information, extracting the values of the wave intensity and the transmitting time length transmitted by a plurality of sub-column label points in the transmitting data, and marking the values as a first wave intensity FBQi and a first time length FBSi respectively;
Extracting the values of the wave intensity and the receiving time length reflected by a plurality of sub-column dividing tag points in the received data and marking the values as a second wave intensity SBQi and a second time length SBSi respectively;
respectively arranging and combining the first wave intensities of a plurality of sub-column label points and the corresponding second wave intensities, the first time lengths and the corresponding second time lengths according to numbers from bottom to top to obtain a wave intensity ordered set and a time length ordered set; the wave intensity ordered set and the duration ordered set form detection processing information;
The specific steps of acquiring the wave probe set comprise:
Acquiring various values of a wave intensity ordered set and a time length ordered set in detection processing information, carrying out normalization processing, and calculating and acquiring the wave detection values BT of a plurality of sub-column label points on a target steel column through the formula BT=b1× (FBQi + SBQi + 0.1624) +b2× (FBSi + SBSi + 0.1473), wherein b1 and b2 are different scale coefficients and are both larger than zero;
The plurality of wave detection values are arranged and combined according to the number from bottom to top to obtain a wave detection set of the target steel column;
In this embodiment, b1 may take a value 0.5671, b2 may take a value 2.7686, when a probe wave sent by the radar encounters a deformed area on the target steel column, the intensity of the reflected probe wave will decrease, and the reflection duration will also increase, because the distance between the deformed probe point and the radar is equal to the hypotenuse in the triangle, and the distance is longer; however, in the area where no deformation occurs, for example, the intensity and the transmission time length of the detected wave received by the tag point of the first identification column are the same as those of the reflected detected wave, and errors possibly exist due to the influence of the environment, but the calculation of the wave detection value cannot be influenced, and the decimal in the formula plays a role in correcting the errors;
matching the image value and the wave detection set with an image standard value and a wave detection standard set respectively to obtain an image analysis set and a wave detection analysis set; the specific steps for acquiring the image analysis set comprise:
Obtaining an image standard value corresponding to a target steel column, wherein the image standard value is an image value corresponding to the target steel column which is not deformed, calculating the ratio between the image value and the image standard value, obtaining an integer part and a decimal part of the ratio, setting the integer part and the decimal part as P1 and P2 respectively, and analyzing the comparison value;
if P1 is less than P10 and P2 is more than P20, judging that the deformation condition of the target steel column in the image exists, and generating a first matching signal; p10 and P20 are preset integers and decimal numbers respectively;
In this embodiment, P10 may take a value of 3, and P20 may take a value of 0.5;
judging that the target steel column in the image is in a normal state under other conditions, and generating a second matching signal; further verifying the deformation condition according to the first matching signal; comprising the following steps:
Acquiring detection coordinates (xi, yi) corresponding to a plurality of label points dividing a sub-column on a two-dimensional coordinate system and preset standard coordinates (xi 0, yi 0); the standard coordinates are coordinates of all label points on the image when the target steel column is in a normal state;
Calculating and obtaining a deflection PY through a formula PY= |xi0-xi|+|yi0-yi|, and analyzing the deflection to determine a specific deformation position of the target steel column;
Matching the offset with a preset offset threshold, and if the offset is smaller than the offset threshold, judging that the detection coordinate corresponding to the offset is normal;
if the offset is not less than the offset threshold, judging that the detection coordinate corresponding to the offset is abnormal, and setting the detection coordinate as a selected coordinate;
sorting and combining a plurality of selected coordinates from bottom to top to obtain a coordinate sorting set;
Obtaining a difference value between an offset degree and an offset threshold value corresponding to a selected coordinate in a coordinate sorting set, setting the selected coordinate corresponding to the maximum difference value as a deformation positioning point coordinate, and generating a first prompting instruction;
the first matching signal, the second matching signal, the coordinate ordered set and the first prompt instruction form an image analysis set;
it should be noted that when the target steel column is deformed, coordinates of at least three detection points on the corresponding image change, deformation conditions are further verified to eliminate influence caused by individual coordinate abnormality, and deformation of the target steel column and a specific deformation area can be determined through deformation positioning point coordinates;
The specific steps for acquiring the wave detection analysis set comprise:
Calculating and obtaining a difference value between a wave detection value in a wave detection analysis set and a wave detection standard value corresponding to a wave detection standard set, wherein the wave detection standard value is a wave detection value corresponding to different label points of an undeformed target steel column, marking the difference value as P3, and analyzing;
If P3 is less than or equal to P30, judging that the marking molecular column label point is in a normal state, and generating a first wave measurement signal; p30 is a preset real number;
If P3 is more than P30, judging that the mark point of the dividing sub-column is in a deformation state, generating a second wave measurement signal, and setting the mark point corresponding to the second wave measurement signal as a selected mark;
Analyzing the selected labels according to the second wave measurement signals, obtaining numbers corresponding to the selected labels, marking the numbers as selected numbers, and arranging a plurality of selected numbers in ascending order to obtain a selected ordered set;
Counting the number of adjacent numbers in a plurality of selected numbers in the selected sorting set, if the number of the adjacent numbers is not smaller than m, m is a positive integer, and m can take a value of 3, generating a second prompting instruction, and setting the plurality of adjacent numbers as deformation positioning point numbers;
the selected ordered set, the second wave measurement signal, the second prompting instruction and the deformation positioning point number form a wave detection analysis set together;
it is worth noting that the function of the deformation positioning point numbers is the same as the function of the deformation positioning point coordinates, and the deformation area positions detected by the detection waves can be further determined;
Comprehensively evaluating the target steel column according to the image analysis set and the wave detection analysis set to obtain an evaluation result, and carrying out early warning and prompting according to the evaluation result; the method comprises the following specific steps of:
if the image analysis set contains a first prompt instruction and the wave detection analysis set contains a second prompt instruction, judging that the target steel column is deformed, overhauling the target steel column, generating a first early warning signal, and sending an overhauling prompt to a manager according to the first early warning signal and deformation locating point coordinates in the image analysis set;
If the wave detection analysis set contains a second prompt instruction but the image analysis set does not contain a first prompt instruction, judging that the target steel column has slight deformation, carrying out inspection and generating a second early warning signal, and sending an inspection prompt to a manager according to the second early warning signal and a plurality of deformation positioning point numbers in the wave detection analysis set;
If the wave detection analysis set does not contain the second prompt instruction and the image analysis set does not contain the first prompt instruction, the target steel column is not deformed and a normal signal is generated;
the first early warning signal, the second early warning signal and the normal signal form an evaluation result.
Notably, the deformation of the target steel column can be determined based on the first prompt instruction and the second prompt instruction which are simultaneously generated, and the specific position of the deformation can be obtained so as to carry out more accurate prompt; under the condition that only the second prompting instruction appears, the slight deformation of the target steel column cannot be found in an image analysis mode, detection and positioning can be realized by the detection wave, and accurate prompting can be performed according to the serial number of the deformation positioning point; compared with the scheme that only the image is used for analysis in the existing scheme, the embodiment can achieve the effects of more reliable analysis and more accurate position early warning prompt.
The above description is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above examples, and all technical solutions belonging to the concept of the present invention belong to the protection scope of the present invention. It should be noted that modifications and adaptations to the present invention may occur to one skilled in the art without departing from the principles of the present invention and are intended to be within the scope of the present invention.
Claims (6)
1. An online intelligent early warning method for deformation damage of a steel frame structure steel column is characterized by comprising the following steps:
Obtaining a target steel column, carrying out regional division and labeling treatment on the target steel column to obtain regional division groups;
Acquiring image information and detection information of a target steel column, and preprocessing the image information and the detection information to obtain image processing information and detection processing information;
Acquiring an image value and a wave detection set of a target steel column according to the image processing information and the detection processing information, and respectively matching the image value and the wave detection set with an image standard value and a wave detection standard set to obtain an image analysis set and a wave detection analysis set; the image value is a numerical value obtained by carrying out normalization processing calculation on the fatigue scores and the total fatigue values of a plurality of division sub-columns in the image processing information; the wave detection set is a numerical value set obtained by carrying out normalization processing on various numerical values of a wave intensity ordered set and a duration ordered set in detection processing information;
Comprehensively evaluating the target steel column according to the image analysis set and the wave detection analysis set to obtain an evaluation result, wherein the evaluation result comprises a first early warning signal and a second early warning signal, and early warning and prompting are carried out according to the first early warning signal and the second early warning signal in the evaluation result;
The specific steps of the regional division set acquisition include:
The method comprises the steps of obtaining the height of a target steel column, equally dividing the target steel column according to a preset dividing distance to obtain a plurality of dividing sub-columns, setting the central points of the dividing sub-columns as tag points, respectively setting the dividing sub-columns at the lowest part and the uppermost part as a first identification column and a second identification column, numbering the dividing sub-columns and the corresponding tag points in sequence from bottom to top to obtain a numbering set and a tag set of the dividing sub-columns, wherein the numbering set and the tag set form regional dividing set;
the image information comprises an image of the target steel column, and the detection information comprises emission data and receiving data of detection waves;
the specific steps of preprocessing the image information include:
Carrying out gray processing on an image of a target steel column in the image information, extracting a frame of the target steel column in the image and a plurality of tag points by utilizing an image processing algorithm, acquiring the distance between the tag points of the first tag column and the tag points of the second tag column, and setting the distance as a fatigue total value;
Establishing a two-dimensional coordinate system according to the label points of the first identification column, a preset distance value and an axial direction, setting coordinates corresponding to the label points of a plurality of dividing sub-columns on the target steel column as detection coordinates, and forming a coordinate set by the coordinates of the label points of the dividing sub-columns;
Setting the distance between adjacent dividing sub-column label points as fatigue scores, and arranging and combining the fatigue scores and the total fatigue values of a plurality of dividing sub-columns to obtain a distance set; the coordinate set and the distance set constitute image processing information.
2. The online intelligent early warning method for deformation damage of a steel frame structure steel column according to claim 1, wherein the specific step of obtaining an image analysis set comprises the following steps:
Obtaining an image standard value corresponding to a target steel column, calculating the ratio between the image value and the image standard value, and carrying out matching analysis on the comparison value to obtain a first matching signal and a second matching signal; and further verifying the deformation condition according to the first matching signal.
3. The online intelligent early warning method for deformation damage of a steel frame structure steel column according to claim 2, wherein the specific steps of further verifying the deformation condition comprise:
Acquiring the offset between detection coordinates corresponding to the label points of a plurality of dividing sub-columns on a two-dimensional coordinate system and preset standard coordinates, and analyzing the offset to determine the specific deformation position of the target steel column;
If the offset is not less than the offset threshold, judging that the detection coordinate corresponding to the offset is abnormal, and setting the detection coordinate as a selected coordinate; sorting and combining a plurality of selected coordinates from bottom to top to obtain a coordinate sorting set; obtaining a difference value between an offset degree and an offset threshold value corresponding to a selected coordinate in a coordinate sorting set, setting the selected coordinate corresponding to the maximum difference value as a deformation positioning point coordinate, and generating a first prompting instruction;
The first and second matching signals, the ordered set of coordinates and the first hint instruction form an image analysis set.
4. The online intelligent early warning method for deformation damage of a steel frame structure steel column according to claim 3, wherein the specific steps of preprocessing the detection information comprise:
Acquiring transmitting data and receiving data of detection waves in the detection information, extracting the values of the wave intensity and the transmitting time length transmitted by a plurality of sub-column label points in the transmitting data, and marking the values as first wave intensity and first time length respectively; extracting the values of the wave intensity and the receiving time length reflected by a plurality of sub-column dividing tag points in the received data and marking the values as second wave intensity and second time length respectively;
Respectively arranging and combining the first wave intensities of a plurality of sub-column label points and the corresponding second wave intensities, the first time lengths and the corresponding second time lengths according to numbers from bottom to top to obtain a wave intensity ordered set and a time length ordered set; the wave intensity ordered set and the duration ordered set form detection processing information.
5. The online intelligent early warning method for deformation damage of a steel frame structure steel column according to claim 4, wherein the specific steps of obtaining a wave detection analysis set comprise:
Calculating and obtaining a difference value between a wave detection value in the wave detection analysis set and a wave detection standard value corresponding to the wave detection standard set, and analyzing the difference value to obtain a first wave detection signal and a second wave detection signal;
Setting a label point corresponding to the second wave measurement signal as a selected label; the method comprises the steps of obtaining numbers corresponding to selected labels, marking the numbers as selected numbers, and arranging a plurality of selected numbers in ascending order to obtain a selected ordered set;
counting the numbers of adjacent numbers in a plurality of selected numbers in the selected sorting set, if the numbers of the adjacent numbers are not smaller than m, wherein m is a positive integer, generating a second prompting instruction, and setting the adjacent numbers as deformation positioning point numbers; the selected ordered set, the second wave detection signal, the second prompting instruction and the deformation positioning point number form a wave detection analysis set together.
6. The online intelligent early warning method for deformation damage of the steel frame structure steel column according to claim 5, wherein the specific steps of comprehensive evaluation comprise:
If the image analysis set contains a first prompt instruction and the wave detection analysis set contains a second prompt instruction, generating a first early warning signal and sending an overhaul prompt to a manager according to deformation positioning point coordinates in the image analysis set;
If the wave detection analysis set contains the second prompt instruction but the image analysis set does not contain the first prompt instruction, generating a second early warning signal and sending a patrol prompt to a manager according to a plurality of deformation positioning point numbers in the wave detection analysis set.
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