CN114459372A - Online intelligent early warning method for deformation and damage of steel frame steel column - Google Patents
Online intelligent early warning method for deformation and damage of steel frame 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
Abstract
The invention discloses an online intelligent early warning method for deformation damage of a steel column with a steel frame structure, belonging to the technical field of civil engineering measurement, and comprising the steps of carrying out regional division and labeling treatment on a target steel column to obtain a regional division set; 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 performing early warning and prompting according to the evaluation result; the method can solve the technical problems of low accuracy of early warning of deformation damage of the steel column of the steel framework 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 steel column.
Background
The steel structure is a structure made of steel materials and is one of main building structure types, the structure mainly comprises steel beams, steel columns, steel trusses and other members made of section steel, steel plates and the like, and all the members or parts are usually connected by welding seams, bolts or rivets; the steel structure steel column bears overload 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 fire, which is disclosed by the invention with the publication number of CN106767718B and is named as a method for monitoring the collapse risk of the steel structure building in fire, and the invention uses a digital close-range photogrammetry technology to shoot photos before and after the fire on site, then obtains space coordinates by processing the photos before and during the fire to compare the photos, and further calculates the deformation of a steel structure.
However, this solution has certain drawbacks: firstly, the state of a steel structure is monitored and analyzed through images in a fire or under a normal condition, and the influence of the environment and the processing technology is easy to cause poor accuracy of image analysis and early warning; secondly, the specific position of deformation cannot be accurately determined according to the image analysis result, and further accurate early warning prompt cannot be performed; finally, the slight deformation cannot be monitored and analyzed, so that the effect of deformation monitoring prompt is limited.
Disclosure of Invention
Aiming at the defects 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, and solves the following technical problems: how to solve the technical problems of low accuracy of early warning and fuzzy early warning content of deformation damage of a steel frame steel column in the existing scheme.
The purpose of the invention can be realized by the following technical scheme:
an online intelligent early warning method for deformation and damage of a steel frame structure steel column comprises the following steps:
acquiring a target steel column, and performing region division and labeling treatment on the target steel column to obtain a region division set;
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 performing early warning and prompting according to the evaluation result.
Further, the specific step of obtaining the region partition set includes:
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 central points of the plurality of dividing sub-columns and setting the central points as label 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 sequentially numbering the plurality of dividing sub-columns from bottom to top to obtain a number set ZBHi of the dividing sub-columns, wherein i is 1, 2, 3. n is a positive integer; labeling and combining label points on the molecular dividing column to obtain a label set ZBHi 1; the number set and the label set constitute a region partition 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 label points of the target steel column in the image by using an image processing algorithm, acquiring a distance between a first identification column label point and a second identification column label point, and setting the distance as a total fatigue value PZ;
setting the label point of the first identification column as an original point, establishing a two-dimensional coordinate system according to a preset distance value and an axis direction, acquiring coordinates corresponding to the label points of a plurality of marking sub-columns on the target steel column and marking the coordinates as detection coordinates (xi, yi), wherein the coordinates of the label points of the marked plurality of marking sub-columns form a coordinate set;
sequentially acquiring distances between label points of adjacent division sub-columns from bottom to top and setting the distances as fatigue scores, sequentially marking a plurality of fatigue scores as PLFi, and arranging and combining the marked fatigue scores and fatigue total values of the plurality of division sub-columns from bottom to top to obtain a distance set;
the set of coordinates and the set of distances constitute image processing information.
Further, the specific steps of obtaining the image values include:
acquiring fatigue scores and total fatigue values of a plurality of dividing sub-columns in the image processing information, normalizing the values, and obtaining the fatigue scores and the total fatigue values of a plurality of dividing sub-columns in the image processing information through a formula
The image values TX, a1 and a2 of the target steel column are calculated and obtained, are different proportionality coefficients and are both larger than zero, and the value ranges of a1 and a2 can be (0, 5).
Further, the specific step of obtaining the image analysis set includes:
acquiring an image standard value corresponding to the target steel column, calculating a ratio between the image value and the image standard value, acquiring 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 ratio;
if P1 is less than P10 and P2 is more than P20, judging that the target steel column in the image has deformation, and generating a first matching signal; p10 and P20 are respectively preset integers and decimals;
otherwise, judging that the target steel column in the image is in a normal state, and generating a second matching signal; and further verifying the deformation condition according to the first matching signal.
Further, the concrete steps of further verifying the deformation condition include:
acquiring detection coordinates (xi, yi) corresponding to label points of a plurality of dividing sub-columns on a two-dimensional coordinate system and preset standard coordinates (xi0, yi 0);
calculating and obtaining a deflection PY through a formula PY ═ xi 0-xi | + | yi 0-yi |, and analyzing the deflection to determine the specific deformation position of the target steel column;
matching the offset degree with a preset offset threshold, and if the offset degree is smaller than the offset threshold, judging that the detection coordinate corresponding to the offset degree is normal;
if the deviation degree is not smaller than the deviation threshold value, judging that the detection coordinate corresponding to the deviation degree is abnormal, and setting the detection coordinate as a selected coordinate;
sequencing and combining a plurality of selected coordinates from bottom to top to obtain a coordinate sequencing set;
acquiring a difference value between the offset degree corresponding to the selected coordinate in the coordinate sorting set and an offset threshold value, setting the selected coordinate corresponding to the maximum difference value as a deformation positioning point coordinate, and generating a first prompt instruction;
the first and second match signals and the coordinate ordering set and the first cue instruction constitute an image analysis set.
Further, the specific steps of preprocessing the detection information include:
acquiring transmitted data and received data of probe waves in the probe information, extracting values of the intensity and the sending duration of the waves transmitted to a plurality of partitioned sub-column label points in the transmitted data, and respectively marking the values as a first intensity FBQi and a first duration FBSi; extracting values of wave intensity and receiving time length reflected by a plurality of divided sub-column label points in the received data, and respectively marking the values as second wave intensity SBQi and second time length SBSi;
respectively arranging and combining the first wave intensities and the corresponding second wave intensities, the first time lengths and the corresponding second time lengths of the label points of the plurality of divided sub-columns from bottom to top according to numbers to obtain a wave intensity ordered set and a time length ordered set; the wave intensity sorting set and the duration sorting set form detection processing information.
Further, the specific steps of acquiring the sounding set include:
acquiring various numerical values of a wave intensity sorting set and a time-length sorting set in detection processing information, carrying out normalization processing, calculating and acquiring wave detection values BT of a plurality of label points of the division subcolumns on a target steel column through a formula BT-b 1 x (FBQi + SBQi +0.1624) + b2 x (PLFi + SBSi +0.1473), wherein b1 and b2 are different proportional coefficients and are both larger than zero, and the value ranges of b1 and b2 can be (0, 10);
and arranging and combining a plurality of wave detection values from bottom to top according to numbers to obtain a wave detection set of the target steel column.
Further, the specific steps of obtaining 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 the P3 is not more than P30, the molecular marking column label point is judged to be in a normal state, and a first wave measurement signal is generated; p30 is a preset real number;
if P3 is greater than P30, the molecular column marking point is judged to be in a deformation state, a second wave detection signal is generated, and the marking point corresponding to the second wave detection signal is set as a selected marking;
analyzing the selected label according to the second wave detection signal, acquiring a number corresponding to the selected label and marking the number as a selected number, and performing ascending arrangement on a plurality of selected numbers 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 adjacent numbers is not less than m, and m is a positive integer, generating a second prompt instruction, and setting the adjacent numbers as the numbers of deformation positioning points;
and the selected sequencing set, the second wave detection signal, the second prompt instruction and the number of the deformation positioning point form a wave detection analysis set together.
Further, the specific steps of performing the comprehensive assessment include:
acquiring an image analysis set and a wave detection analysis set, and analyzing and early warning;
if the image analysis set comprises a first prompt instruction and the wave detection analysis set comprises a second prompt instruction, judging that the target steel column is deformed, needing to be overhauled and generating a first early warning signal, and sending an overhaul prompt to a manager according to the first early warning signal and the coordinates of the deformation positioning point in the image analysis set;
if the wave detection analysis set contains a second prompt instruction but the image analysis set does not contain the first prompt instruction, judging that the target steel column is slightly deformed, performing inspection and generating a second early warning signal, and sending an inspection prompt to a manager according to the second early warning signal and the serial numbers of a plurality of deformation positioning points 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 generates a normal signal;
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 method and the device, 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 the 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, the specific position of the deformation in the image is further determined according to the offset degree, and 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 steel column can be obtained through the transmitted data and the received data of the detection wave, the real object of the steel frame steel column is monitored and analyzed based on the wave detection value, whether the steel frame steel column is deformed or not is judged, and the specific position where the deformation occurs is determined based on the divided area number, so that more reliable analysis and more accurate position early warning can be realized.
3. According to the invention, the deformation damage of the steel frame structure steel column is monitored by combining image analysis and detection wave detection, and comprehensive evaluation is carried out according to the image analysis result and the detection wave analysis result, and monitoring and early warning in different modes are carried out, so that the accuracy and diversity of the deformation early warning of the steel frame structure steel column can be effectively improved.
Drawings
Fig. 1 is a flow chart of an online intelligent early warning method for deformation and damage of a steel frame structure steel column.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, the invention relates to an online intelligent early warning method for deformation and damage of a steel frame structure steel column, which comprises the following steps:
acquiring a target steel column, and performing region division and labeling treatment on the target steel column to obtain a region division set; the method comprises the following specific steps:
acquiring the height of a target steel column, in this embodiment, monitoring and analyzing a vertical target steel column, when the target steel column is horizontal, adaptively acquiring the length of the target steel column for monitoring and analyzing, equally dividing the target steel column according to a preset dividing distance to obtain a plurality of dividing sub-columns, setting a specific numerical value of the dividing distance according to the height of the target steel column, for example, if the height of the target steel column is 8m, the dividing distance may be 0.2m, that is, equally dividing every 0.2m on the target steel column;
it should be noted that although the more the target steel column is divided, the higher the accuracy of the deformation monitoring analysis is, the analysis of the target steel column is realized based on the image, and the target steel column on the image is in an equal-scale reduction state, so that the analysis result is affected by the excessive dividing times 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 central points of a plurality of dividing sub-columns and setting the central points as label points, and respectively setting the lowermost dividing sub-column and the uppermost dividing 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 target steel column from the upper side and the lower side;
numbering a plurality of dividing sub-columns from bottom to top in sequence to obtain a numbering set ZBHi of the dividing sub-columns, wherein i is 1, 2, 3. n is a positive integer; labeling and combining label points on the molecular dividing column to obtain a label set ZBHi 1; the numbering set and the label set form a region division set;
it should be noted that in this embodiment, by performing the purpose of area division and labeling processing on the target steel column, the obtained image and the obtained detection wave of the target steel column are conveniently subjected to targeted processing and analysis, so that the efficiency of monitoring and analyzing the deformation of the target steel column can be effectively improved, and the specific position of the deformation can be accurately analyzed and positioned, so that the manager can perform processing in different manners 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 emission data and receiving data of detection waves;
it should be noted that the image information and the detection information obtained in this embodiment are obtained right in front of the target steel column, in an actual situation, the image information and the detection information of the target steel column are also obtained from the left side or the right side, and the whole target steel column is comprehensively monitored and analyzed from different directions;
it is worth noting that 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 achieve early warning, so that the accuracy of the deformation early warning can be effectively improved; in practical application, the accuracy of image analysis is not high due to the influence of the environment in the image acquisition and processing, and meanwhile, slight deformation cannot be directly acquired from the image; therefore, whether the target steel column really has deformation and the specific degree and the specific position of the deformation is verified under the assistance of radar detection waves, so that the accuracy and the flexibility of deformation monitoring analysis can be effectively improved; the external change of the target steel column can be observed visually conveniently according to the image acquisition and processing result;
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 the target steel column according to the image processing information and the detection processing information;
the specific steps of preprocessing the image information comprise:
acquiring an image of a target steel column in image information, performing gray processing on the image, and extracting a frame and a plurality of label points of the target steel column in the image by using an image gradient algorithm, wherein the image processing algorithm can be an image gradient algorithm, and the distance between a first identification column label point and a second identification column label point is acquired and set as a fatigue total value PZ;
setting the label point of the first identification column as an original point, 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 the target steel column, acquiring coordinates corresponding to the label points of a plurality of marking sub-columns on the 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 plurality of marking sub-columns;
sequentially acquiring distances between label points of adjacent division sub-columns from bottom to top and setting the distances as fatigue scores, sequentially marking a plurality of fatigue scores as PLFi, and arranging and combining the marked fatigue scores and fatigue total values of the plurality of division 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 of obtaining the image values include:
acquiring fatigue scores and total fatigue values of a plurality of dividing sub-columns in the image processing information, normalizing the values, and obtaining the fatigue scores and the total fatigue values of a plurality of dividing sub-columns in the image processing information through a formula
Calculating to obtain image values TX of the target steel column, wherein a1 and a2 are different proportionality coefficients and are both larger than zero;
in this embodiment, a1 may take the value of 2, and a2 may take the value of 0.2372; when the target steel column deforms, the numerical value of the total fatigue value is reduced, the sum of the fatigue values of a plurality of dividing molecular columns is increased, the deformation position can be regarded as a triangle, and the sum of three sides of the triangle is larger than the sum of original straight lines; therefore, simultaneous analysis is carried out from the whole aspect and the local aspect, and the target steel column on the image is digitally analyzed and judged based on the image value;
the specific steps of preprocessing the detection information include:
acquiring transmitted data and received data of probe waves in the probe information, extracting values of the intensity and the sending duration of the waves transmitted to a plurality of partitioned sub-column label points in the transmitted data, and respectively marking the values as a first intensity FBQi and a first duration FBSi;
extracting values of wave intensity and receiving time length reflected by a plurality of divided sub-column label points in the received data, and respectively marking the values as second wave intensity SBQi and second time length SBSi;
respectively arranging and combining the first wave intensities and the corresponding second wave intensities, the first time lengths and the corresponding second time lengths of the label points of the plurality of divided sub-columns from bottom to top according to numbers to obtain a wave intensity ordered set and a time length ordered set; the wave intensity sorting set and the duration sorting set form detection processing information;
the specific steps for acquiring the wave detection set comprise:
acquiring various numerical values of a wave intensity sorting set and a time-length sorting set in detection processing information, carrying out normalization processing, calculating and acquiring wave detection values BT of a plurality of label points of the division subcolumns on a target steel column through a formula BT (b 1 x (FBQi + SBQi +0.1624) + b2 x (PLFi + SBSi +0.1473), wherein b1 and b2 are different proportional coefficients and are both larger than zero;
a plurality of wave detection values are arranged and combined from bottom to top according to numbers to obtain a wave detection set of the target steel column;
in this embodiment, b1 may take a value of 0.5671, b2 may take a value of 2.7686, when a probe wave emitted by a radar meets a deformed region on a target steel column, the intensity of the probe wave reflected back will be reduced, and the reflection duration will also be increased, because the distance between the deformed probe point and the radar is equal to the hypotenuse in a triangle, the distance will be longer; but there is no area of deformation, for example, the intensity and transmission duration of the detection wave received by the first marker post label point are the same as those of the reflected detection wave, there may be an error due to the influence of the environment, but the calculation of the wave detection value is not affected, and the decimal in the formula plays a role in correcting the error;
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 of obtaining the image analysis set comprise:
acquiring an image standard value corresponding to the target steel column, wherein the image standard value is an image value corresponding to the target steel column which is not deformed, calculating a ratio between the image value and the image standard value, acquiring 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 target steel column in the image has deformation, and generating a first matching signal; p10 and P20 are respectively preset integers and decimals;
in this embodiment, P10 may take a value of 3, and P20 may take a value of 0.5;
otherwise, judging that the target steel column in the image is in a normal state, and generating a second matching signal; further verifying the deformation condition according to the first matching signal; the method comprises the following steps:
acquiring detection coordinates (xi, yi) corresponding to label points of a plurality of dividing sub-columns on a two-dimensional coordinate system and preset standard coordinates (xi0, 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 to obtain a deflection PY through a formula PY | xi 0-xi | + | yi 0-yi | and analyzing the deflection PY to determine the specific deformation position of the target steel column;
matching the offset degree with a preset offset threshold, and if the offset degree is smaller than the offset threshold, judging that the detection coordinate corresponding to the offset degree is normal;
if the deviation degree is not smaller than the deviation threshold value, judging that the detection coordinate corresponding to the deviation degree is abnormal, and setting the detection coordinate as a selected coordinate;
sequencing and combining a plurality of selected coordinates from bottom to top to obtain a coordinate sequencing set;
acquiring a difference value between the offset degree corresponding to the selected coordinate in the coordinate sorting set and an offset threshold value, setting the selected coordinate corresponding to the maximum difference value as a deformation positioning point coordinate, and generating a first prompt instruction;
the first matching signal, the second matching signal, the coordinate sorting 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 are changed, the deformation condition is further verified to eliminate the influence caused by individual coordinate abnormality, and the deformation and the specific deformation area of the target steel column can be determined through the coordinates of the deformation positioning points;
the specific steps for obtaining the 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, wherein the wave detection standard value is a wave detection value corresponding to different label points of the target steel column which is not deformed, and marking the difference value as P3 for analysis;
if the P3 is not more than P30, the molecular marking column label point is judged to be in a normal state, and a first wave measurement signal is generated; p30 is a preset real number;
if P3 is greater than P30, the molecular column marking point is judged to be in a deformation state, a second wave detection signal is generated, and the marking point corresponding to the second wave detection signal is set as a selected marking;
analyzing the selected label according to the second wave detection signal, acquiring a number corresponding to the selected label and marking the number as a selected number, and performing ascending arrangement on a plurality of selected numbers 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 adjacent numbers is not less than m, m is a positive integer and can take the value of m as 3, generating a second prompt instruction, and setting the number of adjacent numbers as the number of the deformation positioning points;
selecting the sequencing set, the second wave detection signal, the second prompt instruction and the number of the deformation positioning point to form a wave detection analysis set;
it is worth noting that the serial function of the deformation positioning point is the same as the coordinate function of the deformation positioning point, and the position of the deformation area detected by the detection wave 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 performing early warning and prompting according to the evaluation result; the method comprises the following specific steps:
if the image analysis set comprises a first prompt instruction and the wave detection analysis set comprises a second prompt instruction, judging that the target steel column is deformed, needing to be overhauled and generating a first early warning signal, and sending an overhaul prompt to a manager according to the first early warning signal and the coordinates of the deformation positioning point in the image analysis set;
if the wave detection analysis set contains a second prompt instruction but the image analysis set does not contain the first prompt instruction, judging that the target steel column is slightly deformed, performing inspection and generating a second early warning signal, and sending an inspection prompt to a manager according to the second early warning signal and the serial numbers of a plurality of deformation positioning points 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 generates a normal signal;
the first early warning signal, the second early warning signal and the normal signal form an evaluation result.
It is worth noting that the deformation of the target steel column can be determined based on the first prompt instruction and the second prompt instruction which occur simultaneously, and the specific position of the deformation can be obtained, so that more accurate prompt can be performed; when only the second prompt instruction appears, the slight deformation of the target steel column cannot be found in an image analysis mode, the detection and the positioning can be realized by the detection waves, and accurate prompt can be performed according to the serial number of the deformation positioning point; compared with the scheme of analyzing only through images in the existing scheme, the embodiment can realize more reliable analysis and more accurate position early warning prompting effect.
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 embodiments, and all technical solutions belonging to the idea of the present invention belong to the protection scope of the present invention. It should be noted that modifications and embellishments within the scope of the invention may occur to those skilled in the art without departing from the principle of the invention, and are considered to be within the scope of the invention.
Claims (9)
1. The utility model provides an online intelligent early warning method of deformation damage of steel frame structure steel column which characterized in that includes:
acquiring a target steel column, and performing region division and labeling treatment on the target steel column to obtain a region division set;
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 fatigue values and total fatigue values of a plurality of dividing sub-columns in the image processing information; the wave detection set is a value set obtained by carrying out normalization processing calculation on various values of a wave intensity ordering set and a time-length ordering set in detection processing information;
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 performing early warning and prompting according to a first early warning signal and a second early warning signal in the evaluation result.
2. The on-line intelligent early warning method for deformation damage of steel frame structural columns according to claim 1, wherein the specific steps of obtaining the region partition set comprise:
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 plurality of dividing sub-columns as label points, setting the lowermost dividing sub-columns and the uppermost dividing sub-columns as first identification columns and second identification columns respectively, numbering the plurality of dividing sub-columns and corresponding label points from bottom to top in sequence, obtaining a numbering set and a label set of the dividing sub-columns, and enabling the numbering set and the label set to form an area dividing set.
3. The on-line intelligent early warning method for deformation damage of steel structural columns according to claim 2, wherein the image information comprises images of target steel columns, and the detection information comprises transmitted data and received data of detection waves.
4. The on-line intelligent early warning method for deformation damage of steel-frame structural columns according to claim 3, wherein the specific steps of preprocessing image information comprise:
performing gray processing on an image of a target steel column in the image information, extracting a frame and a plurality of label points of the target steel column in the image by using an image processing algorithm, obtaining a distance between a first identification column label point and a second identification column label point, and setting the distance as a total fatigue 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 plurality of dividing sub-columns;
setting the distance between label points of adjacent dividing sub-columns as a fatigue score, 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 set of coordinates and the set of distances constitute image processing information.
5. The on-line intelligent early warning method for deformation damage of steel structural columns according to claim 4, wherein the specific steps of obtaining the image analysis set comprise:
acquiring an image standard value corresponding to the target steel column, calculating a ratio between the image value and the image standard value, and performing matching analysis on the ratio to obtain a first matching signal and a second matching signal; and further verifying the deformation condition according to the first matching signal.
6. The on-line intelligent early warning method for deformation damage of steel-frame structural columns according to claim 5, wherein the specific steps of further verifying the deformation condition comprise:
acquiring the offset between detection coordinates corresponding to label points of a plurality of divided sub-columns on a two-dimensional coordinate system and a preset standard coordinate, and analyzing the offset to determine the specific deformation position of the target steel column;
if the deviation degree is not smaller than the deviation threshold value, judging that the detection coordinate corresponding to the deviation degree is abnormal, and setting the detection coordinate as a selected coordinate; sequencing and combining a plurality of selected coordinates from bottom to top to obtain a coordinate sequencing set; obtaining a difference value between the offset degree corresponding to the selected coordinate in the coordinate sorting set and an offset threshold value, setting the selected coordinate corresponding to the maximum difference value as a deformation positioning point coordinate, and generating a first prompt instruction;
the first and second match signals and the coordinate ordering set and the first cue instruction constitute an image analysis set.
7. The on-line intelligent early warning method for deformation damage of steel structural columns according to claim 6, wherein the specific steps of preprocessing detection information comprise:
acquiring transmitted data and received data of detection waves in the detection information, extracting numerical values of wave intensity and sending duration transmitted to a plurality of label points of the divided sub-columns in the transmitted data, and respectively marking the numerical values as first wave intensity and first duration; extracting numerical values of the wave intensity and the receiving time length reflected by a plurality of sub-column label points in the received data, and respectively marking the numerical values as a second wave intensity and a second time length;
respectively arranging and combining the first wave intensities and the corresponding second wave intensities, the first time lengths and the corresponding second time lengths of the label points of the plurality of divided sub-columns from bottom to top according to numbers to obtain a wave intensity ordered set and a time length ordered set; the wave intensity sorting set and the duration sorting set form detection processing information.
8. The on-line intelligent early warning method for deformation damage of steel structural columns according to claim 7, wherein the specific steps of obtaining a wave detection analysis set comprise:
calculating 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 the label point corresponding to the second wave detection signal as a selected label; acquiring numbers corresponding to the selected labels, marking the numbers as selected numbers, and performing ascending arrangement on a plurality of selected numbers 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 adjacent numbers is not less than m, and m is a positive integer, generating a second prompt instruction, and setting the adjacent numbers as the numbers of deformation positioning points; and the selected sequencing set, the second wave detection signal, the second prompt instruction and the number of the deformation positioning point form a wave detection analysis set together.
9. The on-line intelligent early warning method for deformation damage of steel frame structural columns according to claim 8, wherein the specific steps of carrying out comprehensive evaluation comprise:
if the image analysis set comprises a first prompt instruction and the wave detection analysis set comprises a second prompt instruction, generating a first early warning signal and sending a maintenance prompt to a manager according to the coordinates of the deformation positioning points in the image analysis set;
and if the wave detection analysis set contains a second prompt instruction but the image analysis set does not contain the first prompt instruction, generating a second early warning signal and sending an inspection prompt to a manager according to the serial numbers of the plurality of deformation positioning points in the wave detection analysis set.
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