CN112158693A - Detection method for elevator guide rail parameters - Google Patents
Detection method for elevator guide rail parameters Download PDFInfo
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- CN112158693A CN112158693A CN202010965472.6A CN202010965472A CN112158693A CN 112158693 A CN112158693 A CN 112158693A CN 202010965472 A CN202010965472 A CN 202010965472A CN 112158693 A CN112158693 A CN 112158693A
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- Prior art keywords
- guide rail
- elevator guide
- elevator
- point
- camera device
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B5/00—Applications of checking, fault-correcting, or safety devices in elevators
- B66B5/0006—Monitoring devices or performance analysers
-
- G—PHYSICS
- 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
- G01B11/14—Measuring arrangements characterised by the use of optical techniques for measuring distance or clearance between spaced objects or spaced apertures
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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
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/26—Measuring arrangements characterised by the use of optical techniques for measuring angles or tapers; for testing the alignment of axes
- G01B11/27—Measuring arrangements characterised by the use of optical techniques for measuring angles or tapers; for testing the alignment of axes for testing the alignment of axes
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- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Length Measuring Devices By Optical Means (AREA)
Abstract
本发明涉及一种电梯导轨参数的检测方法，其特征在于包括以下步骤：(1)以摄像装置对电梯导轨拍摄图像，使航拍无人机在井道中垂直运动，对电梯导轨通过不同位置的定点悬停进行拍摄；(2)读取步骤(1)中的摄像装置所采集到的导轨图像；(3)对步骤(2)中的导轨图像进行处理，通过序列图像的三维重建算法实现电梯导轨的三维重建；(4)获取电梯导轨的三维实体数据并进行测量，获得电梯导轨的轨距、垂直度、平行度数据，并判断该电梯导轨是否合格。该方法具有操作简单、效率高、精度高的优点，实现了电梯导轨检测技术的自动化、方便化、智能化。
The present invention relates to a method for detecting parameters of elevator guide rails, which is characterized by comprising the following steps: (1) taking images of the elevator guide rails with a camera device, making the aerial photography drone move vertically in the hoistway, and passing fixed points at different positions on the elevator guide rails. Hover to shoot; (2) read the guide rail image collected by the camera device in step (1); (3) process the guide rail image in step (2), and realize the elevator guide rail through a three-dimensional reconstruction algorithm of sequence images (4) Obtain and measure the three-dimensional entity data of the elevator guide rail, obtain the gauge, perpendicularity, and parallelism data of the elevator guide rail, and judge whether the elevator guide rail is qualified. The method has the advantages of simple operation, high efficiency and high precision, and realizes the automation, convenience and intelligence of the elevator guide rail detection technology.
Description
Technical Field
The invention relates to the technical field of elevators, in particular to a detection method for parameters of elevator guide rails.
Background
The elevator guide rail is used as an important component of an elevator, has similar properties with a train guide rail, and is an important factor influencing the safety and the comfort of the elevator. The elevator guide rail has the characteristics of high reliability, strong rigidity, low price and the like, and is a T-shaped guide rail commonly used in modern elevators. The elevator guide rail has high requirements on the plane, and the stable operation of the elevator car can be ensured only by ensuring the plane smoothness. However, the elevator guide rails inevitably bring dimensional deviation in the manufacturing and installation processes, and if the deviation exceeds a specified range, the normal operation of the elevator can be threatened and even safety accidents can be caused. Therefore, it is necessary to detect the guide rails of the elevator before the elevator is put into use after the installation of the guide rails of the elevator or in a maintenance inspection at a later date.
The numerical values of the gauge and the verticality of the guide rail of the elevator are important performance indexes for ensuring the safety and the comfort of the elevator. In the processes of elevator installation, daily maintenance and elevator periodic inspection, how to measure and ensure that the gauge and the verticality of the elevator guide rail meet the requirement of a gauge is always a technical problem in the elevator inspection process.
Currently, the measurement of the gauge and the perpendicularity of the guide rail mostly adopts more traditional measurement methods, namely a measuring tape direct measurement method and a line drop method. In recent years, laser detectors for measuring the gauge and the perpendicularity of guide rails appear in the elevator inspection and detection industry, and even if high-precision laser beams are used for replacing tape measures, the measurement precision is also greatly improved. However, the above-mentioned measuring method requires manual fixing and disassembling of the instrument and equipment during operation, which is prone to cause measuring errors due to human factors during measurement, and lacks a device capable of automatically running along the elevator guide rail, and only one point of track gauge value and verticality can be measured at a time. Therefore, the design of an automatic tester for the gauge and the verticality of the guide rail of the elevator is a trend of realizing automation, convenience and intellectualization of the modern inspection and detection technology.
Disclosure of Invention
The invention aims to provide a method for detecting elevator guide rail parameters, which realizes automation, convenience and intellectualization of a detection technology.
A method for detecting parameters of an elevator guide rail is characterized by comprising the following steps:
(1) shooting images of the elevator guide rail by using a camera device, enabling the aerial unmanned aerial vehicle to vertically move in a hoistway, and shooting the elevator guide rail by hovering at fixed points at different positions;
(2) reading a guide rail image acquired by the camera device in the step (1);
(3) processing the guide rail image in the step (2), and realizing three-dimensional reconstruction of the elevator guide rail through a three-dimensional reconstruction algorithm of the sequence image;
(4) the method comprises the steps of obtaining three-dimensional entity data of the elevator guide rail, measuring the three-dimensional entity data, obtaining gauge data, perpendicularity data and parallelism data of the elevator guide rail, and judging whether the elevator guide rail is qualified or not.
Preferably, the camera device is an aerial unmanned aerial vehicle or a three-dimensional motion platform carrying the camera device.
The three-dimensional reconstruction algorithm of the image comprises the steps of firstly using a Canny operator to carry out edge detection on a target image, and then using prior information such as target shape, size and the like to remove segmented false target edges. And then, calculating a gradient weighted value in the normal direction of the edge point as an initial contour of the workpiece, screening out a coarse matching point pair according to a left-right consistency principle, performing fine search by using sub-pixels near the neighborhood of the matching point pair, estimating the current optimal sub-pixel matching point pair by using a neighborhood distance minimization criterion, and using the current optimal sub-pixel matching point pair for size measurement of the laser-etched workpiece, wherein the total precision can reach 0.1 mm. The method effectively reduces the dependence of the contour reconstruction algorithm on the edge positioning precision, and simultaneously improves the contour reconstruction precision.
Firstly, the normal direction of the current Point on the contour needs to be calculated, and for a straight line, a circle, a rectangle and a rounded rectangle, the local contour is a straight line or an arc, so that the calculation can be realized by searching the current Point in a mode of fixedly spacing points forwards and backwards in the clockwise direction, which are respectively called Point pointspre、Pointnow、PointnextThen the normal direction is defined as PointpreAnd PointnextThe direction of the perpendicular bisector of the straight line. When Point ispreAnd PointnextA straight line connected withWhen the X axis is parallel, the normal direction is parallel to the Y axis, otherwise:
where k is the slope of the normal line,
after the normal direction of the current point is calculated, the extension line of the current point in the normal direction needs to be calculated, and the weighted average gradient on the straight line of the extension line is used as a target contour sub-pixel point, and the specific process is as follows:
(1) two points on the calculation method line that are a fixed distance from the current point can be calculated according to the following formula:
wherein D is a constant for defining the current PointnowAnd Point clockwisepreGeodesic distance between them.
(2) And calculating a connecting line segment between the points P1 and P2, setting the intersection point of the perpendicular bisector of the line segment and the initial contour of the workpiece as P, respectively taking points with equal intervals along the normal direction to connect the points into the line segment, and calculating the mean value of coordinate points (x, y) on the line segment as the final sub-pixel coordinate position.
The sub-pixel exact matching process according to the neighborhood minimum distance criterion is as follows: for the corresponding point P with the current line number ii(x1，y1)、Qi(x1，y1) Fix the y coordinate, and fix the x coordinate of the abscissa1From x1-2 traversal to x1+2, interval 0.2; will be abscissa x2From x2-2 traversal to x2+2, with an interval of 0.2, generating a set of sub-pixel corresponding points { [ P ]i(x1-2，y1)、Qi(x1，y1)]、[Pi(x1-1.8，y1)、Qi(x1，y1)]、[Pi(x1-1.6，y1)、Qi(x1，y1)]……[Pi(x1+2，y1)、Qi(x1+2，y1)]}; repeating the steps on the (i + 1) th row to generate a corresponding point sequence { [ P ]i+1(x1-2，y1)、Qi+1(x1，y1)]、[Pi+1(x1-1.8，y1)、Qi+1(x1，y1)]、[Pi+1(x1-1.6，y1)、Qi+1(x1，y1)]……[Pi+1(x1+2，y1)、Qi+1(x1+2，y1)]}; reconstructing a three-dimensional coordinate set of corresponding points of the ith row and the (i + 1) th row into D by using a triangulation principlei、Di+1Computing a set DiAnd set Di+1The Euclidean distance between any two elements is selected, and the point corresponding set D with the minimum Euclidean distance is selectediThe three-dimensional point in (2) is taken as the current point reconstruction result. Repeating the above steps to obtain Pi(x2，y2)、Qi(x2，y2) And (5) point cloud, traversing the whole image to obtain a complete point cloud reconstruction result.
Compared with the prior art, the method for detecting the elevator guide rail parameters based on the three-dimensional reconstruction algorithm of the images has the advantages of simplicity in operation, high efficiency and high precision, and realizes automation, convenience and intellectualization of the elevator guide rail detection technology.
Drawings
FIG. 1 schematic representation of an elevator guide rail and camera
FIG. 2 Elevator guide rails and camera overhead view
1 elevator guide rail, 2 camera device.
Detailed Description
The method for monitoring the electrical signal of the elevator safety loop provided by the invention is further described below with reference to the accompanying drawings, and it should be noted that the technical solution and the design principle of the invention are explained in detail below only by an optimized technical solution.
A method for detecting parameters of an elevator guide rail is characterized by comprising the following steps:
(1) shooting images of the elevator guide rail by using a camera device, enabling the aerial unmanned aerial vehicle to vertically move in a hoistway, and shooting the elevator guide rail by hovering at fixed points at different positions;
(2) reading a guide rail image acquired by the camera device in the step (1);
(3) processing the guide rail image in the step (2), and realizing three-dimensional reconstruction of the elevator guide rail through a three-dimensional reconstruction algorithm of the sequence image;
(4) the method comprises the steps of obtaining three-dimensional entity data of the elevator guide rail, measuring the three-dimensional entity data, obtaining gauge data, perpendicularity data and parallelism data of the elevator guide rail, and judging whether the elevator guide rail is qualified or not.
Preferably, the camera device is an aerial unmanned aerial vehicle or a three-dimensional motion platform carrying the camera device.
The three-dimensional reconstruction algorithm of the image comprises the steps of firstly using a Canny operator to carry out edge detection on a target image, and then using prior information such as target shape, size and the like to remove segmented false target edges. And then, calculating a gradient weighted value in the normal direction of the edge point as an initial contour of the workpiece, screening out a coarse matching point pair according to a left-right consistency principle, performing fine search by using sub-pixels near the neighborhood of the matching point pair, estimating the current optimal sub-pixel matching point pair by using a neighborhood distance minimization criterion, and using the current optimal sub-pixel matching point pair for size measurement of the laser-etched workpiece, wherein the total precision can reach 0.1 mm. The method effectively reduces the dependence of the contour reconstruction algorithm on the edge positioning precision, and simultaneously improves the contour reconstruction precision.
Firstly, the normal direction of the current point on the contour needs to be calculated, and for a straight line, a circle, a rectangle and a rounded rectangle, the local contour is a straight line or an arc, so that a method for searching the forward and backward fixed spacing points of the current point in the clockwise direction can be adoptedImplementation of formula (II), respectively called Pointpre、Pointnow、PointnextThen the normal direction is defined as PointpreAnd PointnextThe direction of the perpendicular bisector of the straight line. When Point ispreAnd PointnextWhen the connected straight line is parallel to the X axis, the normal direction is parallel to the Y axis, otherwise:
where k is the slope of the normal line,
after the normal direction of the current point is calculated, the extension line of the current point in the normal direction needs to be calculated, and the weighted average gradient on the straight line of the extension line is used as a target contour sub-pixel point, and the specific process is as follows:
(1) two points on the calculation method line that are a fixed distance from the current point can be calculated according to the following formula:
wherein D is a constant for defining the current PointnowAnd Point clockwisepreGeodesic distance between them.
(2) And calculating a connecting line segment between the points P1 and P2, setting the intersection point of the perpendicular bisector of the line segment and the initial contour of the workpiece as P, respectively taking points with equal intervals along the normal direction to connect the points into the line segment, and calculating the mean value of coordinate points (x, y) on the line segment as the final sub-pixel coordinate position.
The sub-pixel exact matching process according to the neighborhood minimum distance criterion is as follows: for the corresponding point P with the current line number ii(x1，y1)、Qi(x1，y1) Fix the y coordinate, and fix the x coordinate of the abscissa1From x1-2 traversal to x1+2, interval 0.2; will be abscissa x2From x2-2 traversal to x2+2, with an interval of 0.2, generating a set of sub-pixel corresponding points { [ P ]i(x1-2，y1)、Qi(x1，y1)]、[Pi(x1-1.8，y1)、Qi(x1，y1)]、[Pi(x1-1.6，y1)、Qi(x1，y1)]……[Pi(x1+2，y1)、Qi(x1+2，y1)]}; repeating the steps on the (i + 1) th row to generate a corresponding point sequence { [ P ]i+1(x1-2，y1)、Qi+1(x1，y1)]、[Pi+1(x1-1.8，y1)、Qi+1(x1，y1)]、[Pi+1(x1-1.6，y1)、Qi+1(x1，y1)]……[Pi+1(x1+2，y1)、Qi+1(x1+2，y1)]}; reconstructing a three-dimensional coordinate set of corresponding points of the ith row and the (i + 1) th row into D by using a triangulation principlei、Di+1Computing a set DiAnd set Di+1The Euclidean distance between any two elements is selected, and the point corresponding set D with the minimum Euclidean distance is selectediThe three-dimensional point in (2) is taken as the current point reconstruction result. Repeating the above steps to obtain Pi(x2，y2)、Qi(x2，y2) And (5) point cloud, traversing the whole image to obtain a complete point cloud reconstruction result.
The method comprises the steps of obtaining three-dimensional entity data of the elevator guide rail, measuring the three-dimensional entity data, obtaining gauge data, perpendicularity data and parallelism data of the elevator guide rail, and judging whether the elevator guide rail is qualified or not. And then the detection of the elevator guide rail parameters is completed.
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| CN113739721A (en) * | 2021-08-27 | 2021-12-03 | 郑州铁路职业技术学院 | Intelligent calibration method and system for perpendicularity of steel pipe column of subway station |
| CN116659419A (en) * | 2023-07-28 | 2023-08-29 | 成都市特种设备检验检测研究院(成都市特种设备应急处置中心) | Elevator guide rail parameter measuring device and method |
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| CN116659419B (en) * | 2023-07-28 | 2023-10-20 | 成都市特种设备检验检测研究院(成都市特种设备应急处置中心) | Elevator guide rail parameter measuring device and method |
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