CN117407823A - Method and system for preventing error in bolt tightening based on vision-aided positioning - Google Patents

Method and system for preventing error in bolt tightening based on vision-aided positioning Download PDF

Info

Publication number
CN117407823A
CN117407823A CN202311713781.4A CN202311713781A CN117407823A CN 117407823 A CN117407823 A CN 117407823A CN 202311713781 A CN202311713781 A CN 202311713781A CN 117407823 A CN117407823 A CN 117407823A
Authority
CN
China
Prior art keywords
bolt
abnormal
plane
workpiece
tightening
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN202311713781.4A
Other languages
Chinese (zh)
Other versions
CN117407823B (en
Inventor
南宫恩
魏巍
李孝楠
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Changchun Titans Technology Co ltd
Original Assignee
Changchun Titans Technology Co ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Changchun Titans Technology Co ltd filed Critical Changchun Titans Technology Co ltd
Priority to CN202311713781.4A priority Critical patent/CN117407823B/en
Publication of CN117407823A publication Critical patent/CN117407823A/en
Application granted granted Critical
Publication of CN117407823B publication Critical patent/CN117407823B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00Pattern recognition
    • G06F18/20Analysing
    • G06F18/24Classification techniques
    • G06F18/243Classification techniques relating to the number of classes
    • G06F18/2433Single-class perspective, e.g. one-against-all classification; Novelty detection; Outlier detection
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B23MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
    • B23PMETAL-WORKING NOT OTHERWISE PROVIDED FOR; COMBINED OPERATIONS; UNIVERSAL MACHINE TOOLS
    • B23P19/00Machines for simply fitting together or separating metal parts or objects, or metal and non-metal parts, whether or not involving some deformation; Tools or devices therefor so far as not provided for in other classes
    • B23P19/04Machines for simply fitting together or separating metal parts or objects, or metal and non-metal parts, whether or not involving some deformation; Tools or devices therefor so far as not provided for in other classes for assembling or disassembling parts
    • B23P19/06Screw or nut setting or loosening machines
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00Pattern recognition
    • G06F18/20Analysing
    • G06F18/21Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
    • G06F18/213Feature extraction, e.g. by transforming the feature space; Summarisation; Mappings, e.g. subspace methods
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/0002Inspection of images, e.g. flaw detection
    • G06T7/0004Industrial image inspection
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F2218/00Aspects of pattern recognition specially adapted for signal processing
    • G06F2218/08Feature extraction
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F2218/00Aspects of pattern recognition specially adapted for signal processing
    • G06F2218/12Classification; Matching
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/30Subject of image; Context of image processing
    • G06T2207/30108Industrial image inspection
    • G06T2207/30164Workpiece; Machine component

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Data Mining & Analysis (AREA)
  • General Physics & Mathematics (AREA)
  • Physics & Mathematics (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Evolutionary Biology (AREA)
  • Evolutionary Computation (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • General Engineering & Computer Science (AREA)
  • Artificial Intelligence (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Quality & Reliability (AREA)
  • Mechanical Engineering (AREA)
  • Image Processing (AREA)

Abstract

The invention relates to the technical field of tightening assembly, and particularly discloses a method and a system for preventing error in bolt tightening based on vision-aided positioning, wherein the method comprises the steps of acquiring a bolt tightening image to obtain bolt tightening characteristic data; identifying a bolt status signal based on the bolt tightening characteristic data, wherein the bolt status signal comprises a bolt normal signal and a bolt abnormal signal; identifying the priority of the monitoring plane on the workpiece based on the bolt processing value of the normal signal of the bolt; the method comprises the steps of completing tightening bolts on a workpiece according to the obtained priority treatment level of a monitoring plane and the priority treatment level of the bolts on the monitoring plane; obtaining an abnormal plane of the workpiece based on the abnormal signal of the bolt, obtaining an abnormal base value of the workpiece based on the abnormal plane of the workpiece and the number of abnormal bolts on the abnormal plane, and identifying the abnormal emergency degree of the workpiece by obtaining the abnormal base value of the workpiece, so that the visual operation management of the bolts on the workpiece by subsequent operators is facilitated.

Description

Method and system for preventing error in bolt tightening based on vision-aided positioning
Technical Field
The invention relates to the technical field of tightening and assembling, in particular to a method and a system for preventing error in bolt tightening based on vision-aided positioning.
Background
The error prevention of bolt tightening refers to preventing errors in the bolt tightening process by adopting a certain method or device, and avoiding the problems of unqualified tightening, too high or too low torque, incorrect control angle and the like.
As disclosed in patent application number CN201910566631.2, a method for tightening and preventing errors of a bolt in a vision-aided positioning is disclosed, a vision-aided positioning bolt tightening and error preventing system is adopted, the system comprises a vision positioning system, an industrial control meter comprising the tightening and error preventing system, a tightening controller comprising tightening control software and a tightening tool, first positioning reference information of a product to be assembled and information of the bolt to be tightened are set in an industrial control computer comprising the tightening and error preventing system, when the tightening tool is used for tightening the bolt to be tightened, the industrial control computer comprising the tightening and error preventing system dynamically acquires the position of the tightening tool through the vision positioning system and compares the position of the tightening tool with the position of the bolt to be tightened, when the position of the tightening tool is coincident with the position of the bolt to be tightened or within an error range, the tightening tool is set to be in a tightening state, otherwise, the tightening tool cannot be tightened.
According to the scheme, screw tightening is completed through adjustment of the tightening tool, in the prior art, as the planes of the workpiece (power assembly) for installing bolts are more, detection of the installation degree of the bolts in a plurality of planes of the workpiece is lacking in the bolt installation process, so that the planar bolts in the workpiece are completely and completely tightened, and other planar bolts are seriously tightened and lack, so that dislocation of the workpiece in the machining process is caused, and meanwhile, regulation and control of the time sequence of tightening the bolts in one plane are also lacking in the prior art.
Disclosure of Invention
The invention aims to provide a method and a system for preventing error in bolt tightening based on vision-aided positioning, which are used for processing a bolt tightening image on a workpiece to obtain bolt tightening characteristic data, identifying the state of the bolt on the workpiece by acquiring a bolt angle deviation value and a bolt height distance value in the bolt tightening characteristic data, respectively enabling the bolt on the workpiece to be normal and abnormal, namely corresponding to a bolt normal signal, and enabling the abnormal bolt to be corresponding to a bolt abnormal signal, so that identification of all bolt states on the workpiece is completed, and visual operation management of subsequent operators on the bolt on the workpiece is facilitated.
The aim of the invention can be achieved by the following technical scheme:
the method for preventing the error in tightening the bolts based on the vision-aided positioning comprises the following steps:
step one: acquiring a bolt tightening image, preprocessing the acquired bolt tightening image, and extracting characteristics of the preprocessed bolt tightening image to obtain bolt tightening characteristic data;
step two: identifying a bolt status signal based on the bolt tightening characteristic data, wherein the bolt status signal comprises a bolt normal signal and a bolt abnormal signal;
processing the bolt tightening characteristic data based on the normal signal of the bolt to obtain a bolt processing value;
step three: identifying the priority of the monitoring plane on the workpiece based on the bolt processing value of the normal signal of the bolt;
the method comprises the steps of completing tightening bolts on a workpiece according to the obtained priority treatment level of a monitoring plane and the priority treatment level of the bolts on the monitoring plane;
step four: obtaining an abnormal plane of the workpiece based on the abnormal signal of the bolt, obtaining an abnormal base value of the workpiece based on the abnormal plane of the workpiece and the number of abnormal bolts on the abnormal plane, and identifying the abnormal emergency degree of the workpiece by acquiring the abnormal base value of the workpiece.
As a further scheme of the invention: in the first step, the bolt tightening characteristic data comprises a bolt angle deviation value and a bolt height distance value;
equally dividing the bolt head plane according to the cross shape, and obtaining the vertical distances from the upper end point, the lower end point, the left end point and the right end point of the cross shape to the screw rod end plane, wherein the vertical distances are respectively marked as an upper end point h1, a lower end point h2, a left end point h3 and a right end point h4;
wherein:
the upper end point h1 is the maximum distance between the bolt head plane and the bolt end plane;
the lower end point h2 is the minimum distance between the plane of the head of the bolt and the plane of the end of the bolt;
the distance of the left and right end points h3 and h4 from the screw end plane is between the maximum and minimum distances.
As a further scheme of the invention: the specific process for acquiring the bolt angle deviation value comprises the following steps:
calculating the difference value of the vertical distance values of the upper endpoint h1 and the lower endpoint h2 to obtain a distance deviation value h12;
obtaining a linear distance value h21 of an upper endpoint h1 and a lower endpoint h 2;
calculating the ratio of the distance deviation value h12 to the linear distance value h21 to obtain a bolt angle deviation predicted value;
if the bolt angle deviation predicted value is greater than or equal to a preset bolt angle deviation value threshold value, the bolt is abnormal in tightening, a bolt abnormal signal is obtained, and the bolt abnormal signal and the bolt position corresponding to the bolt abnormal signal are marked;
if the bolt angle deviation predicted value is smaller than a preset bolt angle deviation value threshold, the bolt is normally screwed, a bolt normal signal is obtained, and the bolt angle deviation predicted value corresponding to the bolt normal signal is recorded as a bolt angle deviation value ji.
As a further scheme of the invention: the concrete process for acquiring the height and distance values of the bolts comprises the following steps:
based on the normal signal of the bolt, summing the vertical distance values of the upper endpoint h1, the lower endpoint h2, the left endpoint h3 and the right endpoint h4 to obtain a mean value, and obtaining a bolt height distance value Hi;
and pass through the formulaCalculating to obtain a bolt processing value Hj, < >>Is a preset proportionality coefficient.
As a further scheme of the invention: acquiring all the planes to be screwed down on the workpiece, and recording the corresponding bolt screwing down planes as monitoring planes m, wherein m is a natural number greater than or equal to 1;
and acquiring the bolt processing value on each independent monitoring plane to obtain a bolt processing value monitoring group corresponding to each monitoring plane.
As a further scheme of the invention: calculating to obtain standard deviation alpha of each monitoring plane bolt processing value monitoring group according to a standard deviation calculation formula;
acquiring the maximum bolt processing value and the minimum bolt processing value in the monitoring plane bolt processing value monitoring group;
carrying out difference value calculation on the maximum bolt processing value and the minimum bolt processing value in the monitoring plane to obtain an amplitude value difference Kf of a monitoring group of the bolt processing values of the monitoring plane;
then, carrying out product calculation on the standard deviation alpha of the bolt processing value monitoring group in the monitoring plane and the amplitude value difference Kf of the bolt processing value monitoring group to obtain an abnormal swing ratio of the bolt processing value monitoring group of the monitoring plane;
and obtaining abnormal swing ratio values of all the monitoring planes of the workpiece, and screwing bolts on the corresponding monitoring planes according to the sequence from large to small.
As a further scheme of the invention: the bolt tightening process in the monitoring plane is processed, and specifically comprises the following steps:
acquiring bolt processing values corresponding to all bolts on a monitoring plane, and recording a bolt corresponding to the minimum bolt processing value on the monitoring plane as a reference bolt;
respectively carrying out difference value calculation on the bolt processing values of the rest bolts on the monitoring plane and the bolt processing values of the reference bolts to respectively obtain bolt adjustment values of the rest bolts and the reference bolts;
sequentially tightening bolts on a monitoring plane according to the sequence of the bolt adjustment values from large to small, so that the bolts on the monitoring plane are all in the same tightening degree, and then tightening all the bolts on the monitoring plane according to an initially set tightening flow;
the initial set screwing process is a screw tightening sequence in the process of fixing the workpiece screw.
As a further scheme of the invention: acquiring a bolt abnormal signal and a bolt position corresponding to the bolt abnormal signal, and marking the abnormal bolt with the bolt corresponding to the bolt abnormal signal;
acquiring a workpiece plane corresponding to each abnormal bolt on the workpiece, and marking the corresponding workpiece plane as an abnormal plane;
obtaining the number of abnormal bolts on each abnormal plane of the workpiece, and calculating the ratio of the number of the abnormal bolts on the abnormal plane to the total number of the bolts on the abnormal plane to obtain the abnormal ratio of the plane bolts;
summing the plane bolt anomaly ratios corresponding to all the anomaly planes on the workpiece, and obtaining an average value of the plane bolt anomaly ratios;
obtaining the number of abnormal planes on the workpiece, and calculating the ratio of the number of the abnormal planes on the workpiece to the total number of the screw-down planes of the workpiece bolts to obtain the abnormal ratio of the plane of the workpiece;
and carrying out product operation on the workpiece plane abnormal ratio and the average value of the plane bolt abnormal ratio, thereby obtaining an abnormal base value of the workpiece.
As a further scheme of the invention: comparing the abnormal base value of the workpiece with a preset abnormal base value threshold value of the workpiece to obtain a workpiece-level signal to be processed;
the workpiece-level to-be-processed signals comprise a workpiece primary to-be-processed signal, a workpiece secondary to-be-processed signal and a workpiece tertiary to-be-processed signal.
As another embodiment of the present invention: the system comprises an image acquisition module, a feature analysis module, a decision judgment module, an abnormality identification module and a cloud management and control platform;
the image acquisition module is used for acquiring bolt tightening images, preprocessing the acquired bolt tightening images, extracting characteristics of the preprocessed bolt tightening images to obtain bolt tightening characteristic data, and sending the bolt tightening characteristic data to the cloud management and control platform;
the characteristic analysis module receives bolt tightening characteristic data transmitted by the cloud Guan Kong platform, and identifies bolt state signals based on the bolt tightening characteristic data, wherein the bolt state signals comprise bolt normal signals and bolt abnormal signals;
processing the bolt tightening characteristic data based on the normal signal of the bolt to obtain a bolt processing value;
the characteristic analysis module sends a bolt normal signal and a bolt abnormal signal to the cloud control platform;
the decision judging module receives a bolt normal signal sent by the cloud control platform, obtains a bolt processing value based on the bolt normal signal, and identifies the priority of a monitoring plane on the workpiece and the priority of the bolt on the monitoring plane;
the method comprises the steps of completing tightening bolts on a workpiece according to the obtained priority treatment level of a monitoring plane and the priority treatment level of the bolts on the monitoring plane;
the abnormal recognition module receives a bolt abnormal signal sent by the cloud control platform, obtains an abnormal plane of the workpiece based on the bolt abnormal signal, obtains an abnormal base value of the workpiece based on the abnormal plane of the workpiece and the processing of the number of abnormal bolts on the abnormal plane, and recognizes the abnormal emergency degree of the workpiece by acquiring the abnormal base value of the workpiece.
The invention has the beneficial effects that:
according to the invention, bolt tightening characteristic data are obtained by processing a bolt tightening image on a workpiece, and the states of the bolts on the workpiece are identified by acquiring the bolt angle deviation value and the bolt height distance value in the bolt tightening characteristic data, so that the bolts on the workpiece are respectively normal bolts and abnormal bolts, namely corresponding to normal signals of the bolts, and the abnormal bolts are corresponding to abnormal signals of the bolts, thereby completing the identification of the states of all the bolts on the workpiece, and facilitating the visual operation management of the bolts on the workpiece by subsequent operators;
when all bolts on a workpiece are in a normal state, acquiring bolt processing values of each bolt, processing the bolt processing values to obtain bolt processing value monitoring groups corresponding to each monitoring plane, carrying out product calculation on standard deviations of the bolt processing value monitoring groups in the monitoring planes and amplitude differences of the bolt processing value monitoring groups to obtain abnormal swing ratios of the monitoring planes, carrying out bolt tightening on all the monitoring planes of the workpiece according to the corresponding sequence of the abnormal swing ratios, acquiring bolt processing values corresponding to all the bolts on any monitoring plane, marking bolts corresponding to the minimum bolt processing values on the monitoring plane as reference bolts, carrying out difference calculation on the bolt processing values of the rest bolts on the monitoring plane and the bolt processing values of the reference bolts respectively to obtain bolt adjusting values of the rest bolts and the reference bolts, and carrying out tightening adjustment on the rest bolts in sequence according to the sequence of the bolt adjusting values so as to finish the adjustment of the bolts on the workpiece monitoring plane and the monitoring plane;
according to the method, when the bolts are in an abnormal state on the workpiece, the abnormal plane of the workpiece is obtained according to the abnormal signals of the bolts, the abnormal base value of the workpiece is obtained based on the abnormal plane of the workpiece and the processing of the number of the abnormal bolts on the abnormal plane, the abnormal emergency degree of the workpiece is identified through the acquisition of the abnormal base value of the workpiece, the abnormal workpiece is effectively matched with staff to carry out classification processing based on the abnormal emergency degree of the workpiece, the visual and planned regular maintenance processing of the abnormal workpiece is realized, the pertinence is high, and the workpieces with different abnormal emergency degrees can be processed in batches and pertinence.
Drawings
The invention is further described below with reference to the accompanying drawings.
FIG. 1 is a flow chart of a method of bolt tightening error proofing based on vision-aided positioning in an embodiment of the present invention;
FIG. 2 is a flow diagram of a system for vision-aided positioning-based bolt tightening error proofing in accordance with an embodiment of the present invention.
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.
Example 1
Referring to fig. 1, the invention provides a method for preventing error in tightening bolts based on vision-aided positioning, which comprises the following steps:
step one: acquiring a bolt tightening image, preprocessing the acquired bolt tightening image, and extracting characteristics of the preprocessed bolt tightening image to obtain bolt tightening characteristic data;
step two: identifying a bolt status signal based on the bolt tightening characteristic data, wherein the bolt status signal comprises a bolt normal signal and a bolt abnormal signal;
processing the bolt tightening characteristic data based on the normal signal of the bolt to obtain a bolt processing value;
step three: identifying the priority of the monitoring plane on the workpiece based on the bolt processing value of the normal signal of the bolt;
the method comprises the steps of completing tightening bolts on a workpiece according to the obtained priority treatment level of a monitoring plane and the priority treatment level of the bolts on the monitoring plane;
step four: obtaining an abnormal plane of the workpiece based on the abnormal signal of the bolt, obtaining an abnormal base value of the workpiece based on the abnormal plane of the workpiece and the number of abnormal bolts on the abnormal plane, and identifying the abnormal emergency degree of the workpiece by acquiring the abnormal base value of the workpiece.
In the first step, the acquisition of the bolt tightening image is that the image is acquired through equipment such as a camera or a scanner;
in the first step, as the acquired bolt tightening image may have noise, uneven illumination and other problems, the preprocessing of the bolt tightening image comprises filtering, denoising and contrast enhancement;
in the first step, a computer vision algorithm is adopted for feature extraction in the bolt tightening image, including but not limited to edge detection and corner detection;
in the first step, the bolt tightening characteristic data comprises a bolt angle deviation value and a bolt height distance value;
equally dividing the plane of the head of the bolt according to the cross shape, and obtaining the vertical distance from the cross-shaped end point (upper, lower, left and right) to the plane of the screw rod end, wherein the vertical distances are respectively marked as an upper end point h1, a lower end point h2, a left end point h3 and a right end point h4;
in this embodiment, the bolt head plane is circular, wherein:
the upper end point h1 is the maximum distance between the bolt head plane and the bolt end plane;
the lower end point h2 is the minimum distance between the plane of the head of the bolt and the plane of the end of the bolt;
the distance between the left end point h3 and the right end point h4 and the plane of the screw end is between the maximum distance and the minimum distance;
the specific process for acquiring the bolt angle deviation value comprises the following steps:
calculating the difference value of the vertical distance values of the upper endpoint h1 and the lower endpoint h2 to obtain a distance deviation value h12;
obtaining a linear distance value h21 of an upper endpoint h1 and a lower endpoint h 2;
calculating the ratio of the distance deviation value h12 to the linear distance value h21 to obtain a bolt angle deviation predicted value;
if the bolt angle deviation predicted value is greater than or equal to a preset bolt angle deviation value threshold value, the bolt is abnormal in tightening, a bolt abnormal signal is obtained, and the bolt abnormal signal and the bolt position corresponding to the bolt abnormal signal are marked;
if the bolt angle deviation predicted value is smaller than a preset bolt angle deviation value threshold value, the bolt is normally screwed, a bolt normal signal is obtained, and the bolt angle deviation predicted value corresponding to the bolt normal signal is recorded as a bolt angle deviation value ji;
the concrete process for acquiring the height and distance values of the bolts comprises the following steps:
based on the normal signal of the bolt, summing the vertical distance values of the upper endpoint h1, the lower endpoint h2, the left endpoint h3 and the right endpoint h4 to obtain a mean value, and obtaining a bolt height distance value Hi;
by the formulaCalculating to obtain a bolt processing value Hj, < >>Is a preset proportionality coefficient;
respectively obtaining a bolt processing value Hj corresponding to each bolt position on a workpiece (power assembly);
in a particular embodiment
Acquiring all the planes to be screwed down on the workpiece, and recording the corresponding bolt screwing down planes as monitoring planes m, wherein m is a natural number greater than or equal to 1;
acquiring bolt processing values on each independent monitoring plane to obtain a bolt processing value monitoring group corresponding to each monitoring plane;
calculating to obtain standard deviation alpha of each monitoring plane bolt processing value monitoring group according to a standard deviation calculation formula;
acquiring the maximum bolt processing value and the minimum bolt processing value in the monitoring plane bolt processing value monitoring group;
carrying out difference value calculation on the maximum bolt processing value and the minimum bolt processing value in the monitoring plane to obtain an amplitude value difference Kf of a monitoring group of the bolt processing values of the monitoring plane;
then, carrying out product calculation on the standard deviation alpha of the bolt processing value monitoring group in the monitoring plane and the amplitude value difference Kf of the bolt processing value monitoring group to obtain an abnormal swing ratio of the bolt processing value monitoring group of the monitoring plane;
obtaining abnormal swing ratio values of all monitoring plane bolt processing value monitoring groups of the workpiece, arranging the abnormal swing ratio values of all the monitoring planes according to the sequence from large to small to obtain an abnormal swing ratio group, and screwing bolts on all the monitoring planes of the workpiece according to the corresponding sequence from large to small of the abnormal swing ratio values in the abnormal swing ratio group;
in this embodiment, taking any monitoring plane as an example, the bolt tightening process in the monitoring plane is processed, specifically:
acquiring bolt processing values corresponding to all bolts on the monitoring plane, and recording the bolt corresponding to the minimum bolt processing value on the monitoring plane as a reference bolt;
respectively carrying out difference value calculation on the bolt processing values of the rest bolts on the monitoring plane and the bolt processing values of the reference bolts to respectively obtain bolt adjusting values of the rest bolts and the reference bolts;
sequentially tightening bolts on the monitoring plane according to the sequence from the big bolt adjusting value to the small bolt adjusting value, so that the bolts on the monitoring plane are all in the same tightening degree, and then tightening all the bolts on the monitoring plane according to the preset tightening flow;
the initial set screwing process is a screw tightening sequence in the process of fixing the workpiece screw.
Acquiring a bolt abnormal signal and a bolt position corresponding to the bolt abnormal signal, and marking the abnormal bolt with the bolt corresponding to the bolt abnormal signal;
acquiring a workpiece plane corresponding to each abnormal bolt on the workpiece, and marking the corresponding workpiece plane as an abnormal plane;
obtaining the number of abnormal bolts on each abnormal plane of the workpiece, and calculating the ratio of the number of the abnormal bolts on the abnormal plane to the total number of the bolts on the abnormal plane to obtain the abnormal ratio of the plane bolts;
summing the plane bolt anomaly ratios corresponding to all the anomaly planes on the workpiece, and obtaining an average value of the plane bolt anomaly ratios;
obtaining the number of abnormal planes on the workpiece, and calculating the ratio of the number of the abnormal planes on the workpiece to the total number of the screw-down planes of the workpiece bolts to obtain the abnormal ratio of the plane of the workpiece;
the total number of the bolt tightening planes of the workpiece is the sum of the number of all the bolt tightening planes of the workpiece;
carrying out product operation on the plane abnormal ratio value of the workpiece and the average value of the plane bolt abnormal ratio value, so as to obtain an abnormal base value of the workpiece;
marking the abnormal base value of the workpiece as Gci, and presetting the limiting value of the abnormal base value threshold of the workpiece as Gci1 and Gci2, wherein Gci1< Gci2:
when Gci is less than Gci1, the number of abnormal planes on the workpiece and the number of abnormal bolts on the abnormal planes are relatively less, and a workpiece primary to-be-processed signal is generated;
when Gci is less than or equal to Gci and is less than Gci2, the number of the abnormal planes on the workpiece and the number of the abnormal bolts on the abnormal planes are relatively moderate, and a workpiece secondary signal to be processed is generated;
when Gci is more than or equal to Gci2, the number of abnormal planes on the workpiece and the number of abnormal bolts on the abnormal planes are relatively large, and three-level signals to be processed of the workpiece are generated;
the workpiece abnormality emergency degree corresponding to the workpiece three-level signal to be processed is higher than the workpiece abnormality emergency degree corresponding to the workpiece two-level signal to be processed, and the workpiece abnormality emergency degree corresponding to the workpiece two-level signal to be processed is higher than the workpiece abnormality emergency degree corresponding to the workpiece one-level signal to be processed;
the workpiece rejection rate or the failure rate is indicated to be higher in the abnormal emergency degree of the workpiece;
the abnormal workpieces are effectively matched based on the abnormal emergency degree of the workpieces to be classified by workers, so that the visual and planned and regular maintenance treatment of the abnormal workpieces is realized, the pertinence is high, and the workpieces with different abnormal emergency degrees can be processed in batches and pertinence.
Example 2
Referring to fig. 2, the invention discloses a bolt tightening error-proofing system based on vision-aided positioning, which comprises an image acquisition module, a feature analysis module, a decision judgment module, an abnormality identification module and a cloud management and control platform;
the image acquisition module, the feature analysis module, the decision judgment module and the anomaly identification module are electrically connected with the cloud control platform;
the image acquisition module is used for acquiring a bolt tightening image, preprocessing the acquired bolt tightening image, extracting the characteristics of the preprocessed bolt tightening image to obtain bolt tightening characteristic data, and sending the bolt tightening characteristic data to the cloud management and control platform;
the characteristic analysis module receives bolt tightening characteristic data transmitted by the cloud Guan Kong platform, and identifies bolt state signals based on the bolt tightening characteristic data, wherein the bolt state signals comprise bolt normal signals and bolt abnormal signals;
processing the bolt tightening characteristic data based on the normal signal of the bolt to obtain a bolt processing value;
the characteristic analysis module sends a bolt normal signal and a bolt abnormal signal to the cloud control platform;
the decision judging module receives a bolt normal signal sent by the cloud control platform, obtains a bolt processing value based on the bolt normal signal, and identifies the priority of the monitoring plane on the workpiece and the priority of the bolt on the monitoring plane;
the method comprises the steps of completing tightening bolts on a workpiece according to the obtained priority treatment level of a monitoring plane and the priority treatment level of the bolts on the monitoring plane;
the abnormal recognition module receives a bolt abnormal signal sent by the cloud control platform, obtains an abnormal plane of the workpiece based on the bolt abnormal signal, obtains an abnormal base value of the workpiece based on the abnormal plane of the workpiece and the processing of the number of abnormal bolts on the abnormal plane, and recognizes the abnormal emergency degree of the workpiece by acquiring the abnormal base value of the workpiece.
Example 3
On the basis of the embodiment 1, another treatment process for tightening bolts on workpieces is proposed in the embodiment, specifically:
arranging all bolts on the workpiece according to the sequence of the bolt processing values Hj from large to small to obtain a bolt processing value group;
sequentially tightening bolts in the bolt treatment value group according to the sequence from the big bolt treatment value to the small bolt treatment value;
selecting a bolt corresponding to the maximum bolt processing value, marking the bolt as a target bolt, acquiring a plane corresponding to the target bolt on a workpiece, and marking the plane as a target plane;
acquiring bolt processing values corresponding to all bolts on a target plane, and recording a bolt corresponding to the minimum bolt processing value on the target plane as a reference bolt;
respectively carrying out difference value calculation on the bolt processing values of the rest bolts on the target plane and the bolt processing values of the reference bolts to respectively obtain bolt adjustment values of the rest bolts and the reference bolts;
sequentially tightening bolts on the target plane according to the sequence of the bolt adjustment values from large to small, so that the bolts on the target plane are all in the same tightening degree, and then tightening all the bolts on the target plane according to an initially set tightening flow;
the initial set screwing process is a screw tightening sequence in the process of fixing the workpiece screw.
One of the core points of the present invention is: the method comprises the steps of processing a bolt tightening image on a workpiece to obtain bolt tightening characteristic data, identifying the states of bolts on the workpiece by acquiring bolt angle deviation values and bolt height distance values in the bolt tightening characteristic data, respectively identifying normal bolts and abnormal bolts of the bolts on the workpiece, wherein the normal bolts correspond to normal bolt signals, and the abnormal bolts correspond to abnormal bolt signals, so that identification of all the bolt states on the workpiece is completed, and visual operation management of the bolts on the workpiece by subsequent operators is facilitated;
one of the core points of the present invention is: when all bolts on a workpiece are in a normal state, acquiring bolt processing values of each bolt, processing the bolt processing values to obtain bolt processing value monitoring groups corresponding to each monitoring plane, performing product calculation on standard deviations of the bolt processing value monitoring groups in the monitoring planes and amplitude differences of the bolt processing value monitoring groups to obtain abnormal swing ratio values of the monitoring planes, and screwing the bolts on all the monitoring planes of the workpiece according to the corresponding sequence from the abnormal swing ratio values to the small abnormal swing ratio values;
in any monitoring plane, acquiring bolt processing values corresponding to all bolts on the monitoring plane, recording bolts corresponding to the minimum bolt processing value on the monitoring plane as reference bolts, respectively carrying out difference value calculation on the bolt processing values of the rest bolts on the monitoring plane and the bolt processing values of the reference bolts to respectively obtain bolt adjusting values of the rest bolts and the reference bolts, and sequentially tightening and adjusting the rest bolts according to the sequence of the bolt adjusting values so as to finish the adjustment of the bolts on the workpiece monitoring plane and the monitoring plane;
one of the core points of the present invention is: when a bolt is in an abnormal state on a workpiece, an abnormal plane of the workpiece is obtained according to a bolt abnormal signal, an abnormal base value of the workpiece is obtained based on the abnormal plane of the workpiece and the processing of the number of the abnormal bolts on the abnormal plane, the abnormal emergency degree of the workpiece is identified through the acquisition of the abnormal base value of the workpiece, the abnormal workpiece is effectively matched with a worker to carry out classification processing based on the abnormal emergency degree of the workpiece, the visual and planned regular maintenance processing of the abnormal workpiece is realized, the pertinence is high, and the workpieces with different abnormal emergency degrees can be processed in batches.
The foregoing describes one embodiment of the present invention in detail, but the description is only a preferred embodiment of the present invention and should not be construed as limiting the scope of the invention. All equivalent changes and modifications within the scope of the present invention are intended to be covered by the present invention.

Claims (10)

1. The method for preventing the error in tightening the bolts based on the vision-aided positioning is characterized by comprising the following steps of:
step one: acquiring a bolt tightening image, preprocessing the acquired bolt tightening image, and extracting characteristics of the preprocessed bolt tightening image to obtain bolt tightening characteristic data;
step two: identifying a bolt status signal based on the bolt tightening characteristic data, wherein the bolt status signal comprises a bolt normal signal and a bolt abnormal signal;
processing the bolt tightening characteristic data based on the normal signal of the bolt to obtain a bolt processing value;
step three: identifying the priority of the monitoring plane on the workpiece based on the bolt processing value of the normal signal of the bolt;
the method comprises the steps of completing tightening bolts on a workpiece according to the obtained priority treatment level of a monitoring plane and the priority treatment level of the bolts on the monitoring plane;
step four: obtaining an abnormal plane of the workpiece based on the abnormal signal of the bolt, obtaining an abnormal base value of the workpiece based on the abnormal plane of the workpiece and the number of abnormal bolts on the abnormal plane, and identifying the abnormal emergency degree of the workpiece by acquiring the abnormal base value of the workpiece.
2. The method for preventing error in tightening a bolt based on vision-aided positioning of claim 1, wherein in the first step, the bolt tightening characteristic data includes a bolt angle deviation value and a bolt height distance value;
equally dividing the bolt head plane according to the cross shape, and obtaining the vertical distances from the upper end point, the lower end point, the left end point and the right end point of the cross shape to the screw rod end plane, wherein the vertical distances are respectively marked as an upper end point h1, a lower end point h2, a left end point h3 and a right end point h4;
wherein:
the upper end point h1 is the maximum distance between the bolt head plane and the bolt end plane;
the lower end point h2 is the minimum distance between the plane of the head of the bolt and the plane of the end of the bolt;
the distance of the left and right end points h3 and h4 from the screw end plane is between the maximum and minimum distances.
3. The method for preventing error in tightening bolts based on vision-aided positioning according to claim 2, wherein the specific process for obtaining the bolt angle deviation value is as follows:
calculating the difference value of the vertical distance values of the upper endpoint h1 and the lower endpoint h2 to obtain a distance deviation value h12;
obtaining a linear distance value h21 of an upper endpoint h1 and a lower endpoint h 2;
calculating the ratio of the distance deviation value h12 to the linear distance value h21 to obtain a bolt angle deviation predicted value;
if the bolt angle deviation predicted value is greater than or equal to a preset bolt angle deviation value threshold value, the bolt is abnormal in tightening, a bolt abnormal signal is obtained, and the bolt abnormal signal and the bolt position corresponding to the bolt abnormal signal are marked;
if the bolt angle deviation predicted value is smaller than a preset bolt angle deviation value threshold, the bolt is normally screwed, a bolt normal signal is obtained, and the bolt angle deviation predicted value corresponding to the bolt normal signal is recorded as a bolt angle deviation value ji.
4. The method for preventing error in tightening bolts based on vision-aided positioning of claim 3, wherein the specific process for obtaining the height-distance value of the bolts is as follows:
based on the normal signal of the bolt, summing the vertical distance values of the upper endpoint h1, the lower endpoint h2, the left endpoint h3 and the right endpoint h4 to obtain a mean value, and obtaining a bolt height distance value Hi;
and pass through the formulaCalculating to obtain a bolt processing value Hj, < >>Is a preset proportionality coefficient.
5. The method for preventing error in bolt tightening based on vision-aided positioning according to claim 1, wherein all planes to be tightened on the workpiece are obtained, the corresponding planes to be tightened are recorded as monitoring planes m, and m is a natural number greater than or equal to 1;
and acquiring the bolt processing value on each independent monitoring plane to obtain a bolt processing value monitoring group corresponding to each monitoring plane.
6. The method for preventing error in tightening bolts based on vision-aided positioning according to claim 5, wherein the standard deviation α of each monitoring plane bolt processing value monitoring group is calculated according to a standard deviation calculation formula;
acquiring the maximum bolt processing value and the minimum bolt processing value in the monitoring plane bolt processing value monitoring group;
carrying out difference value calculation on the maximum bolt processing value and the minimum bolt processing value in the monitoring plane to obtain an amplitude value difference Kf of a monitoring group of the bolt processing values of the monitoring plane;
then, carrying out product calculation on the standard deviation alpha of the bolt processing value monitoring group in the monitoring plane and the amplitude value difference Kf of the bolt processing value monitoring group to obtain an abnormal swing ratio of the bolt processing value monitoring group of the monitoring plane;
and obtaining abnormal swing ratio values of all the monitoring planes of the workpiece, and screwing bolts on the corresponding monitoring planes according to the sequence from large to small.
7. The method for preventing error in tightening bolts based on vision-aided positioning of claim 6, wherein the in-plane bolt tightening process is processed, in particular:
acquiring bolt processing values corresponding to all bolts on a monitoring plane, and recording a bolt corresponding to the minimum bolt processing value on the monitoring plane as a reference bolt;
respectively carrying out difference value calculation on the bolt processing values of the rest bolts on the monitoring plane and the bolt processing values of the reference bolts to respectively obtain bolt adjustment values of the rest bolts and the reference bolts;
sequentially tightening bolts on a monitoring plane according to the sequence of the bolt adjustment values from large to small, so that the bolts on the monitoring plane are all in the same tightening degree, and then tightening all the bolts on the monitoring plane according to an initially set tightening flow;
the initial set screwing process is a screw tightening sequence in the process of fixing the workpiece screw.
8. The method for preventing error in tightening a bolt based on vision-aided positioning according to claim 1, wherein a bolt abnormality signal and a bolt position corresponding to the bolt abnormality signal are obtained, and the abnormal bolt is marked by the bolt corresponding to the bolt abnormality signal;
acquiring a workpiece plane corresponding to each abnormal bolt on the workpiece, and marking the corresponding workpiece plane as an abnormal plane;
obtaining the number of abnormal bolts on each abnormal plane of the workpiece, and calculating the ratio of the number of the abnormal bolts on the abnormal plane to the total number of the bolts on the abnormal plane to obtain the abnormal ratio of the plane bolts;
summing the plane bolt anomaly ratios corresponding to all the anomaly planes on the workpiece, and obtaining an average value of the plane bolt anomaly ratios;
obtaining the number of abnormal planes on the workpiece, and calculating the ratio of the number of the abnormal planes on the workpiece to the total number of the screw-down planes of the workpiece bolts to obtain the abnormal ratio of the plane of the workpiece;
and carrying out product operation on the workpiece plane abnormal ratio and the average value of the plane bolt abnormal ratio, thereby obtaining an abnormal base value of the workpiece.
9. The method for preventing error in tightening bolts based on vision-aided positioning according to claim 8, wherein the abnormal base value of the workpiece is compared with a preset abnormal base value threshold value of the workpiece to obtain a workpiece-level signal to be processed;
the workpiece-level to-be-processed signals comprise a workpiece primary to-be-processed signal, a workpiece secondary to-be-processed signal and a workpiece tertiary to-be-processed signal.
10. The system for preventing the error in the bolt tightening based on the vision auxiliary positioning is characterized by comprising an image acquisition module, a characteristic analysis module, a decision judgment module, an abnormality identification module and a cloud management and control platform;
the image acquisition module is used for acquiring bolt tightening images, preprocessing the acquired bolt tightening images, extracting characteristics of the preprocessed bolt tightening images to obtain bolt tightening characteristic data, and sending the bolt tightening characteristic data to the cloud management and control platform;
the characteristic analysis module receives bolt tightening characteristic data transmitted by the cloud Guan Kong platform, and identifies bolt state signals based on the bolt tightening characteristic data, wherein the bolt state signals comprise bolt normal signals and bolt abnormal signals;
processing the bolt tightening characteristic data based on the normal signal of the bolt to obtain a bolt processing value;
the characteristic analysis module sends a bolt normal signal and a bolt abnormal signal to the cloud control platform;
the decision judging module receives a bolt normal signal sent by the cloud control platform, obtains a bolt processing value based on the bolt normal signal, and identifies the priority of a monitoring plane on the workpiece and the priority of the bolt on the monitoring plane;
the method comprises the steps of completing tightening bolts on a workpiece according to the obtained priority treatment level of a monitoring plane and the priority treatment level of the bolts on the monitoring plane;
the abnormal recognition module receives a bolt abnormal signal sent by the cloud control platform, obtains an abnormal plane of the workpiece based on the bolt abnormal signal, obtains an abnormal base value of the workpiece based on the abnormal plane of the workpiece and the processing of the number of abnormal bolts on the abnormal plane, and recognizes the abnormal emergency degree of the workpiece by acquiring the abnormal base value of the workpiece.
CN202311713781.4A 2023-12-14 2023-12-14 Method and system for preventing error in bolt tightening based on vision-aided positioning Active CN117407823B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202311713781.4A CN117407823B (en) 2023-12-14 2023-12-14 Method and system for preventing error in bolt tightening based on vision-aided positioning

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202311713781.4A CN117407823B (en) 2023-12-14 2023-12-14 Method and system for preventing error in bolt tightening based on vision-aided positioning

Publications (2)

Publication Number Publication Date
CN117407823A true CN117407823A (en) 2024-01-16
CN117407823B CN117407823B (en) 2024-03-15

Family

ID=89491159

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202311713781.4A Active CN117407823B (en) 2023-12-14 2023-12-14 Method and system for preventing error in bolt tightening based on vision-aided positioning

Country Status (1)

Country Link
CN (1) CN117407823B (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117934464A (en) * 2024-03-21 2024-04-26 温州风涌智能科技有限公司 Defect identification method based on machine vision

Citations (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107984201A (en) * 2017-11-30 2018-05-04 中国地质大学(武汉) A kind of screw hole positioning of view-based access control model servo and lock unload screw method
US20180165804A1 (en) * 2016-12-08 2018-06-14 Toyota Jidosha Kabushiki Kaisha Bolt axial tension measuring apparatus and bolt axial tension measuring method
CN112393837A (en) * 2020-11-25 2021-02-23 三一汽车起重机械有限公司 Monitoring method and monitoring device for wheel bolt and vehicle
CN113447255A (en) * 2021-06-29 2021-09-28 同济大学 Bolt node looseness detection method and system based on unmanned aerial vehicle image space positioning
CN113635286A (en) * 2021-08-20 2021-11-12 菲烁易维(重庆)科技有限公司 Device and method for controlling bolt tightening based on machine vision technology
CN113829034A (en) * 2020-06-24 2021-12-24 华晨宝马汽车有限公司 Quality monitoring method, system and equipment based on bolt tightening working curve
CN113869502A (en) * 2021-10-20 2021-12-31 长春泰坦斯科技有限公司 Deep neural network-based bolt tightening failure reason analysis method
CN113899538A (en) * 2021-09-29 2022-01-07 上汽大众汽车有限公司 Bolt tightening monitoring method and system
CN115994899A (en) * 2023-01-13 2023-04-21 北京理工大学 Bolt loosening detection method, device and detection equipment
CN116393981A (en) * 2023-03-31 2023-07-07 中联重科股份有限公司 Slewing bearing bolt positioning and tightening system, method and readable storage medium
CN116766196A (en) * 2023-07-11 2023-09-19 华东理工大学 Outer hexagon bolt assembly control method, system, equipment and storage medium
CN117161739A (en) * 2023-08-30 2023-12-05 浙江吉利控股集团有限公司 Cylinder head bolt tightening method and device

Patent Citations (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20180165804A1 (en) * 2016-12-08 2018-06-14 Toyota Jidosha Kabushiki Kaisha Bolt axial tension measuring apparatus and bolt axial tension measuring method
CN107984201A (en) * 2017-11-30 2018-05-04 中国地质大学(武汉) A kind of screw hole positioning of view-based access control model servo and lock unload screw method
CN113829034A (en) * 2020-06-24 2021-12-24 华晨宝马汽车有限公司 Quality monitoring method, system and equipment based on bolt tightening working curve
CN112393837A (en) * 2020-11-25 2021-02-23 三一汽车起重机械有限公司 Monitoring method and monitoring device for wheel bolt and vehicle
CN113447255A (en) * 2021-06-29 2021-09-28 同济大学 Bolt node looseness detection method and system based on unmanned aerial vehicle image space positioning
CN113635286A (en) * 2021-08-20 2021-11-12 菲烁易维(重庆)科技有限公司 Device and method for controlling bolt tightening based on machine vision technology
CN113899538A (en) * 2021-09-29 2022-01-07 上汽大众汽车有限公司 Bolt tightening monitoring method and system
CN113869502A (en) * 2021-10-20 2021-12-31 长春泰坦斯科技有限公司 Deep neural network-based bolt tightening failure reason analysis method
CN115994899A (en) * 2023-01-13 2023-04-21 北京理工大学 Bolt loosening detection method, device and detection equipment
CN116393981A (en) * 2023-03-31 2023-07-07 中联重科股份有限公司 Slewing bearing bolt positioning and tightening system, method and readable storage medium
CN116766196A (en) * 2023-07-11 2023-09-19 华东理工大学 Outer hexagon bolt assembly control method, system, equipment and storage medium
CN117161739A (en) * 2023-08-30 2023-12-05 浙江吉利控股集团有限公司 Cylinder head bolt tightening method and device

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117934464A (en) * 2024-03-21 2024-04-26 温州风涌智能科技有限公司 Defect identification method based on machine vision

Also Published As

Publication number Publication date
CN117407823B (en) 2024-03-15

Similar Documents

Publication Publication Date Title
CN117407823B (en) Method and system for preventing error in bolt tightening based on vision-aided positioning
CN114799849A (en) Screw machine operation parameter acquisition and analysis system based on machine vision
CN116766196A (en) Outer hexagon bolt assembly control method, system, equipment and storage medium
CN110728655A (en) Machine vision-based numerical control machine tool workpiece abnormity detection method and device
CN111230862A (en) Handheld workpiece deburring method and system based on visual recognition function
CN114407079B (en) Method for controlling mechanical arm mounting bolt
CN111145159A (en) Method and device for extracting routing inspection key component points
CN113534727B (en) Early warning control system of refrigeration equipment for fishing boat based on artificial intelligence platform
CN117333696A (en) Bolt detection method and device based on machine vision
CN116843761A (en) Bolt size measuring method and device, electronic equipment and storage medium
CN115760690A (en) Photographing-based high-strength bolt group final-screwing detection method
CN114638847A (en) Insulator hardware trimming method and system based on image processing
CN113869502A (en) Deep neural network-based bolt tightening failure reason analysis method
CN111105395B (en) AI intelligent cradle head for monitoring power transmission operation
CN110555840B (en) Closed-loop control method, device, control equipment and readable storage medium
CN111002376A (en) Intelligent fool-proof method for PCB inner layer target hole
CN117911415B (en) Automatic equipment supervision system and method based on machine vision
CN117036360B (en) Screw visual positioning method and system based on image analysis
CN117934464B (en) Defect identification method based on machine vision
CN117456150A (en) Power transmission line insulator string burst identification method and system
CN116429170B (en) Quality detection method for plate blank
CN118038278B (en) Intelligent detection method and system for quality of building engineering
CN116225836A (en) Data analysis processing method for wind control management platform
CN117021009A (en) Torque control system of intelligent electric torque wrench
CN116880250A (en) Thermal power plant motion monitoring method and system

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant