A method for detecting broken wires of a steel wire rope

Abstract

The present application relates to a kind of steel wire rope broken wire detection method, it includes the following steps: S1.in the starting detection point of steel wire rope is sleeved with oil scraper, multiple shooting devices are arranged in spiral uniform interval on the side of clean steel wire rope output by oil scraper;S2.open each shooting device continues to the moving steel wire rope camera, image processing device is compared with the picture data of the specific posture of steel wire rope by the image that is shot by the shooting device close to the oil scraper, each time comparison coincides, counter counts once and controls each shooting device synchronous photograph, by image processing device to the photo that is shot is handled comparison;S3.it is assumed that the photo that comparison is out when counting N times has obvious difference in similarity degree, then it is judged as suspected broken wire, according to N value, the distance S of suspected broken wire from the starting detection point of steel wire rope can be calculated.The advantage is that the broken wire condition of steel wire rope can be determined relatively quickly and accurately, and the distance of broken wire position and starting detection point is conveniently positioned.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of steel wire rope safety monitoring, in particular to a steel wire rope broken wire detection method. BACKGROUND

[0002] Steel wire rope is generally a flexible rope twisted by multiple thin steel wires, which has the characteristics of high strength, light weight, large load capacity, not easy to break, high safety factor, and is widely used in mining, shipbuilding, metallurgy, port and shipping, etc. In the use process, due to rust, wear or fatigue, etc. Broken wire is prone to occur, and the strength is reduced. When the broken wire is serious, there is a risk of steel wire rope breaking.

[0003] In order to avoid the occurrence of unexpected accidents such as sudden breaking of steel wire rope in use, it is necessary to regularly carry out flaw detection on steel wire rope. The current steel wire rope flaw detection includes manual visual inspection, electromagnetic detection and machine vision detection: manual visual inspection has the disadvantages of heavy workload, high labor intensity, easy fatigue and strong subjectivity; electromagnetic detection needs to magnetize the steel wire rope and then detect the magnetic flux leakage, the equipment is complex, the cost is high, and it is easy to be distorted by external interference; machine vision is the most likely to be widely used steel wire rope broken wire detection method at present, but the current detection method needs to shoot a standard steel wire rope without broken wire and broken strand to obtain a reference picture, and the detection steel wire rope and the standard steel wire rope need to be shot at the same position during comparison, otherwise it is difficult to compare and obtain the detection result, and it is difficult to realize online detection, see CN104063716A for details. Moreover, in actual use, the surface of the steel wire rope will accumulate dust and grease, even if there is no broken wire, the steel wire rope with dust and grease covered at the same position will also have a large difference with the standard steel wire rope; in addition, the current machine vision detection method also has the problem that after the suspected broken wire position is determined in the video or image, it is still difficult to quickly and accurately find the broken wire position in the later stage, because the steel wire rope is always moving, and it is difficult to ensure uniform speed due to the existence of slipping phenomenon, and there is cumulative error. Based on the above problems, it is necessary to provide a new steel wire rope broken wire detection system and method based on machine vision method. SUMMARY

[0004] The present application provides a steel wire rope broken wire detection method, which aims to overcome the above-mentioned deficiencies in the prior art.

[0005] The technical solution of the present application to solve the above technical problems is as follows: a steel wire rope broken wire detection method, comprising the following steps:

[0006] S1. A scraper is sleeved on the starting detection point of the steel wire rope, a plurality of shooting devices are arranged on the side of the scraper outputting the cleaned steel wire rope in a spiral and uniform interval, the interval between two adjacent shooting devices in the axial direction of the steel wire rope is n times of the lay length L of the steel wire rope, n is an integer not less than 1, and the distance between the shooting device closest to the scraper and the starting detection point of the steel wire rope is s;

[0007] S2. The steel wire rope is pulled by the pulling device to move relative to the scraper, each shooting device is turned on to continuously shoot the steel wire rope moving and cleaned by the scraper, the image processing device synchronously compares the image shot by the shooting device closest to the scraper with the picture data of the specific posture of the steel wire rope, the counter counts once each time the comparison is consistent, and each shooting device synchronously shoots the picture of the steel wire rope at the position opposite to the shooting device at this moment, the image processing device processes the shot picture and performs similarity comparison.

[0008] S3. When the comparison shows that there is a picture with obvious difference in similarity for N times, the picture is determined as an abnormal picture and the corresponding position is determined as the suspected broken wire position of the steel wire rope, the value of N at this moment is extracted as the pre-warning data record, the distance S between the suspected broken wire position and the starting detection point of the steel wire rope can be calculated according to the value of N, S=(N-1+λ×n)×L+s, λ is the number value of the shooting device shooting the abnormal picture, the number value of the shooting device closest to the scraper is 0, the number value of the subsequent shooting device is 1, and the number value of the subsequent shooting device is sequentially increased.

[0009] On the basis of the above technical solution, the application can further have the following further specific options.

[0010] Specifically, in S2, when the image processing device processes the shot picture and performs similarity comparison, the processed and compared picture is the picture shot by the same shooting device twice in succession, and the picture shot by each shooting device is processed and compared.

[0011] Specifically, in S1, when the shooting devices are distributed in a spiral around the steel wire rope, the angle between two adjacent shooting devices in the circumferential direction of the steel wire rope is adjusted to ensure that the posture of the steel wire rope picture shot by each shooting device at any moment is the same, and the steel wire rope pictures shot by all the shooting devices cover all angles of a circle of the steel wire rope, in this case, in S2, when the image processing device processes the shot picture and performs similarity comparison, the processed and compared picture is the picture shot by each shooting device at the same time.

[0012] Specifically, in S1, the shooting devices are two, and the angle between the two shooting devices in the circumferential direction of the steel wire rope is 180 degrees.

[0013] Specifically, the three shooting devices in S1 are staggered by 120 degrees in the circumferential direction of the steel wire rope.

[0014] Specifically, the shooting device in S1 is a digital camera or a camera.

[0015] Specifically, the picture of the specific posture of the steel wire rope in S2 refers to a picture of the steel wire rope taken by the shooting device in advance, and the specific posture of the picture data refers to the specific angle and starting point of the line on the surface of the steel wire rope extracted after image processing.

[0016] Specifically, the obvious difference between the two pictures in S2 refers to the similarity data of the two pictures after comparison by the picture similarity comparison software being below 95%.

[0017] Compared with the prior art, the beneficial effects of the present application are:

[0018] The present application is unique in that the oil scraper for the steel wire rope is first cleaned, and then a plurality of shooting devices are distributed in a spiral shape near the cleaned steel wire rope. The shooting devices are staggered in the circumferential direction of the steel wire rope and spaced apart by an integer multiple of the lay distance in the axial direction. In this way, the shooting devices do not affect each other when shooting the steel wire rope, and because the steel wire rope is spaced apart by an integer multiple of the lay distance, the posture of the steel wire rope is the same as the current posture. Therefore, although the shooting devices do not shoot the same part of the steel wire rope at different angles, as the steel wire rope continues to move, the overall effect is equivalent to a complete shot of the same part of the steel wire rope. Therefore, when detecting a broken wire, the overall detection of the steel wire rope is comprehensive. The present application uses video shooting and image comparison method to detect broken wires. When a suspected broken wire of the steel wire rope is detected, the distance of the broken wire from the starting point of the steel wire rope detection can be calculated according to the corresponding number of shots N. By playing back the video and actually observing the condition of the steel wire rope at the corresponding distance, the broken wire condition of the steel wire rope can be quickly and accurately determined, with high efficiency and good precision. BRIEF DESCRIPTION OF DRAWINGS

[0019] Figure 1 A flowchart for detecting broken wires of the steel wire rope according to the present application is provided.

[0020] Figure 2 A schematic diagram of the position distribution relationship of the three shooting devices relative to the steel wire rope and the oil scraper in the method for detecting broken wires of the steel wire rope according to the present application is provided.

[0021] Figure 3 A schematic diagram of the specific posture picture of the steel wire rope taken by the shooting device in the method for detecting broken wires according to the present application is provided.

[0022] Figure 4An abnormal photo of a suspected broken wire of the steel wire rope taken by the shooting device in the broken wire detection method provided by the application is shown in the schematic diagram.

[0023] In the drawings, the components represented by each reference numeral are listed as follows:

[0024] 1, shooting device; 2, steel wire rope; 3, oil scraper. DETAILED DESCRIPTION

[0025] The principles of the application are further described in detail below in combination with the drawings and specific examples, and the examples are only used to explain the application and are not used to limit the scope of the application.

[0026] As shown in Figure 1 , the application provides a steel wire rope broken wire detection method, which comprises the following steps:

[0027] S1. An oil scraper is sleeved at the starting detection point of the steel wire rope, and a plurality of shooting devices (as shown in Figure 2 , the shooting device is a camera, and there are three in total) are uniformly and regularly arranged in a spiral around the steel wire rope on the side of the oil scraper output clean steel wire rope, and the adjacent two shooting devices are spaced apart by n times the lay length L of the steel wire rope in the axial direction of the steel wire rope, n is an integer not less than 1, and the distance between the shooting device closest to the oil scraper and the starting detection point of the steel wire rope is s;

[0028] S2. The end of the steel wire rope is pulled by a pulling device to move relative to the oil scraper, each shooting device is turned on to continuously take pictures of the moving steel wire rope that has been cleaned by the oil scraper, and an image processing device synchronously compares the image taken by the shooting device closest to the oil scraper with the picture data of a specific posture of the steel wire rope. When the comparison is consistent each time, a counter counts once and simultaneously controls each shooting device to synchronously take pictures of the steel wire rope at the position directly opposite each shooting device at that moment, and the image processing device processes the taken pictures and performs similarity comparison;

[0029] S3. Assuming that N times of comparison result in a picture with a significant difference in similarity, the picture is determined to be an abnormal picture (as shown in Figure 4 ) and the corresponding position is a suspected broken wire position of the steel wire rope, and the value of N at this time is extracted as pre-warning data record. According to the value of N, the distance S of the suspected broken wire position from the starting detection point of the steel wire rope can be calculated, S = (N-1+λ×n)×L+s, λ is the number value of the shooting device that takes the abnormal picture, the number value of the shooting device closest to the oil scraper is 0, the number value of the subsequent shooting device is 1, and the number value of the subsequent shooting device is 1.

[0030] It should be noted that after the oil scraper cleans the steel wire rope, the steel wire rope has a clean rope surface, which can obtain a better image processing effect.

[0031] In one embodiment of the present application, when the image processing device in S2 processes the photographed pictures and performs the similarity comparison, the processed and compared pictures are the pictures photographed by the same photographing device in two adjacent times, and the pictures photographed by each photographing device are processed and compared. It should be noted that, due to the spiral distribution of the photographing devices, the individual planes of a small range of the wire rope at the starting end cannot be photographed at the beginning, so the image comparison cannot determine whether there is a broken wire, and manual inspection of a small range of the wire rope at the starting end (the starting detection point) is required to prevent missing detection. Since it is only a small range of the wire rope, the workload of manual inspection is not large. Of course, in this embodiment, the wire images photographed by the same photographing device in two adjacent times are compared, so the comparison amount is large, and the image processing device needs to have strong processing capability. When the processing capability of the image processing device cannot meet the requirements, the method provided in the next embodiment can be used, and the picture comparison workload can be reduced by half.

[0032] In another embodiment of the present application, when the photographing devices in S1 are spirally distributed around the wire rope, the angle of the adjacent two photographing devices around the circumference of the wire rope needs to be adjusted to ensure that the posture of the wire rope photographed by each photographing device at any time is the same, and the wire rope pictures photographed by all the photographing devices cover all the angles around the wire rope. At this time, when the image processing device in S2 processes the photographed pictures and performs the similarity comparison, the processed and compared pictures are the pictures photographed by each photographing device at the same time. By using the structural characteristics that the wire rope is twisted into a strand by a plurality of or a plurality of thin steel wires, the posture images of the wire rope at the front integer multiple twist pitches are completely the same. Therefore, when the four walls around a certain position of the wire rope need to be photographed, the photographing devices can be spaced apart by an integer multiple twist pitch and do not interfere with each other to photograph the angles of the wire rope. In addition, due to the twisting feature of the wire rope, after rotating by a certain angle at the same point, the photographed posture images of the wire rope are also the same.

[0033] In one embodiment of the present application, the photographing devices in S1 are two, and the angle of the two photographing devices around the circumference of the wire rope is 180 degrees.

[0034] In another embodiment of the present application, as shown in Figure 2 , the photographing devices in S1 are three, and the angle of any two photographing devices around the circumference of the wire rope is 120 degrees.

[0035] In each of the above embodiments, the photographing device in S1 is a digital camera or a camera head.

[0036] In each of the above embodiments, the picture of the specific posture of the wire rope in S2 (such as Figure 3The picture data of the specific posture refers to the specific angle and starting point of the wire surface line extracted from the pre-shot picture by image processing.

[0037] In the above embodiments, the obvious difference in the picture comparison in S2 refers to the similarity data of the two pictures after the picture similarity comparison software comparison is below 95%. It can be understood that in order to improve the detection accuracy, the above 95% can be adjusted to 90% or less. At this time, once the abnormal picture is detected, the possibility of wire breakage is very high, so the detection is more accurate. In order to avoid missing detection, some subtle wire breakage may not be enough to make the similarity data reach below 95%. At this time, the above 95% can be adjusted to 98%, so more abnormal pictures are detected, and missing detection can be avoided, but the workload of subsequent video playback or on-site investigation and confirmation will be increased.

[0038] The above only describes the preferred embodiments of the present application and is not intended to limit the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A broken wire detection method for a steel wire rope, characterized by, The method comprises the following steps: S1. Wrapping the oil scraper around the starting detection point of the steel wire rope, and arranging a plurality of photographing devices spirally and uniformly spaced on the side of the output clean steel wire rope of the oil scraper, the adjacent two photographing devices being spaced by n times of the lay length L of the steel wire rope in the axial direction of the steel wire rope, n being an integer not less than 1, and the photographing device closest to the oil scraper being spaced by a distance s from the starting detection point of the steel wire rope; S2. Pulling one end of the steel wire rope by the pulling device to move relative to the oil scraper, starting the photographing device to continuously photograph the moving steel wire rope which has been cleaned by the oil scraper, and synchronously comparing the image photographed by the photographing device closest to the oil scraper with the picture data of the specific posture of the steel wire rope by the image processing device, counting once by the counter and synchronously controlling the photographing of the photographing device each time the comparison is consistent, collecting the picture of the steel wire rope opposite to the photographing device at this moment, processing the photographed picture by the image processing device, and comparing the similarity; S3. Assuming that the comparison is N times and a picture with obvious difference in similarity is found, the picture is determined as an abnormal picture and the corresponding position is the suspected broken wire position of the steel wire rope, and the N value at this moment is extracted as the pre-warning data record, the distance S of the suspected broken wire position from the starting detection point of the steel wire rope is calculated according to the N value, S=(N-1+λ×n)×L+s, λ being the number value of the photographing device that photographs the abnormal picture, the number value of the photographing device closest to the oil scraper being 0, the number value of the subsequent photographing device being 1, and the number value of the photographing device after that being sequentially increased.

2. The broken wire detection method of a steel wire rope according to claim 1, characterized by, In S2, the processed and compared pictures are the pictures photographed by the same photographing device adjacent to each other, and the pictures photographed by each photographing device are processed and compared.

3. The broken wire detection method of a steel wire rope according to claim 1, characterized by, In S1, when the photographing devices are spirally distributed around the steel wire rope, the angle between the adjacent two photographing devices in the circumferential direction of the steel wire rope is adjusted to ensure that the posture of the steel wire rope photographed by each photographing device at any moment is the same, and the pictures photographed by all the photographing devices cover all the angles of the steel wire rope, and in S2, the processed and compared pictures are the pictures photographed by each photographing device at the same time.

4. The broken wire detection method of a steel wire rope according to claim 1, characterized by, In S1, the photographing devices are two, and the angle between the two photographing devices in the circumferential direction of the steel wire rope is 180 degrees.

5. The method of claim 1, wherein, In S1, the photographing devices are three, and the angle between any two photographing devices in the circumferential direction of the steel wire rope is 120 degrees.

6. The method of claim 1, wherein, In S1, the photographing devices are digital cameras or cameras.

7. The method of claim 1, wherein, In S2, the picture of the specific posture of the steel wire rope is the picture photographed by the photographing device in advance, and the picture data of the specific posture is the specific angle and starting point of the line on the surface of the steel wire rope extracted after the picture is processed by the image processing device.

8. A broken wire detection method of a steel wire rope according to any one of claims 1 to 7, characterized in that, In S2, the obvious difference in the comparison of the pictures refers to the similarity data of the two pictures being below 95% after the comparison by the picture similarity comparison software.

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