CN117893491A - Ship lock large gear tooth surface oil shortage degree judging method based on oil shortage index - Google Patents
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- 238000000034 method Methods 0.000 title claims abstract description 33
- 239000003921 oil Substances 0.000 claims abstract description 129
- 239000010687 lubricating oil Substances 0.000 claims abstract description 5
- 238000012216 screening Methods 0.000 claims abstract description 5
- 230000007812 deficiency Effects 0.000 claims description 42
- 238000001514 detection method Methods 0.000 claims description 12
- 239000002184 metal Substances 0.000 claims description 7
- 230000001502 supplementing effect Effects 0.000 claims description 5
- 230000002950 deficient Effects 0.000 claims description 4
- 239000003086 colorant Substances 0.000 claims description 3
- 230000007797 corrosion Effects 0.000 claims description 3
- 238000005260 corrosion Methods 0.000 claims description 3
- 239000000295 fuel oil Substances 0.000 claims description 3
- 238000012545 processing Methods 0.000 claims description 3
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 3
- 230000011218 segmentation Effects 0.000 claims description 2
- 238000005461 lubrication Methods 0.000 abstract description 13
- 230000000694 effects Effects 0.000 abstract description 2
- 238000012544 monitoring process Methods 0.000 description 11
- 235000003642 hunger Nutrition 0.000 description 4
- 230000037351 starvation Effects 0.000 description 4
- 230000001050 lubricating effect Effects 0.000 description 3
- 230000005540 biological transmission Effects 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 2
- 239000004519 grease Substances 0.000 description 2
- 239000011159 matrix material Substances 0.000 description 2
- 238000005299 abrasion Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000009792 diffusion process Methods 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000001931 thermography Methods 0.000 description 1
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- G06T5/00—Image enhancement or restoration
- G06T5/20—Image enhancement or restoration using local operators
- G06T5/30—Erosion or dilatation, e.g. thinning
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- G06T7/10—Segmentation; Edge detection
- G06T7/136—Segmentation; Edge detection involving thresholding
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- G06T7/00—Image analysis
- G06T7/60—Analysis of geometric attributes
- G06T7/62—Analysis of geometric attributes of area, perimeter, diameter or volume
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10024—Color image
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- G—PHYSICS
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10048—Infrared image
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
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- G06T2207/30232—Surveillance
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Abstract
The invention discloses a ship lock large gear tooth surface oil shortage degree judging method based on an oil shortage index, which comprises the following steps: an infrared thermal image camera is used for acquiring RGB images and thermal image pictures of tooth surfaces of the gears when the gears run; dividing the tooth surface RGB image and the thermal image to obtain a complete and single pure tooth surface RGB image and pure tooth surface thermal image; screening out suspected oil shortage areas from the pure tooth surface RGB image by adopting a preset algorithm; analyzing the pure tooth surface thermal image to obtain characteristic data; judging the oil shortage degree of the related area according to the thermal image characteristic data corresponding to the suspected oil shortage area and a preset logic judgment step; and obtaining the oil shortage area position and the oil shortage degree grade, and taking corresponding measures. The method monitors and accurately judges the tooth surface lubrication effect in real time, greatly reduces equipment wear and lubricating oil loss, and reduces labor cost.
Description
Technical Field
The invention relates to the field of monitoring of lubricating oil states, in particular to a ship lock large gear tooth surface oil shortage degree judging method based on an oil shortage index.
Background
The herringbone door of the ship lock generally adopts large-scale open gear transmission to control the opening and closing of the herringbone door, and lubrication of open gear teeth is an important working content for ensuring safe operation of the ship lock. Open gears are generally used in large heavy duty transmission applications, are fully exposed, and have easily worn tooth surfaces, thus requiring maintenance of a relatively good lubrication condition. The lubrication of open gears is generally protected by applying grease to the tooth surfaces, running in for several minutes to form a lubricating film, the thickness of which is generally less than 5 μm. As open gears run longer and longer, the oil film becomes thinner and even broken, and when the oil film is severely broken, the lubrication effect is lost, and the risk of tooth surface pitting is increased. Therefore, the lubrication state of the open gear needs to be accurately judged, and oil is timely supplemented to avoid equipment abrasion.
Whether the large open gear needs to be supplemented with oil or not in the traditional industrial environment is judged by engineers according to site observation and self experience, and quantitative judgment cannot be given to the oil shortage degree and the oil shortage area, so that the oil is supplemented by adopting a periodical full-tooth-surface smearing mode to ensure the lubricating effect, and a large amount of lubricating grease is wasted. In addition, the traditional method needs to have certain experience and make judgment by manual regular inspection, so that the manual labor intensity is high, and the online real-time monitoring and judgment cannot be realized.
Therefore, it is necessary to research a real-time, online and accurate large open gear lubrication state monitoring method.
Disclosure of Invention
The invention aims to solve the technical problems and provides a ship lock large gear tooth surface oil shortage degree judging method based on an oil shortage index.
The technical scheme of the invention is a large open tooth lubrication state monitoring method of a ship lock hoist, comprising the following steps:
the method comprises the following steps:
step 1: an infrared thermal image camera is used for acquiring RGB images and thermal image pictures of tooth surfaces of the gears when the gears run;
step 2: dividing the obtained RGB image and thermal image of the tooth surface to obtain a complete and single RGB image and a single thermal image of the tooth surface;
step 3: screening out suspected oil shortage areas from the pure tooth surface RGB image in the step 2;
step 3.1: graying the pure tooth surface RGB image obtained in the step 2 to obtain a pure tooth surface gray image;
step 3.2: dividing the pure tooth surface gray level image by using a threshold segmentation method to obtain a binary image;
step 3.3: after the corrosion operation is carried out on the binary image, the expansion operation is carried out, the image noise is removed, and the hole filling is used for obtaining a relatively complete black-and-white connected domain;
step 3.4: setting a threshold T 1 Searching all white connected domains in the image, and enabling pixel points to be smaller than T 1 The connected domain of the white connected domain with larger area is removed;
step 3.5: marking a corresponding region in the gray level map according to the position coordinates of the white connected region with the larger area in the step 3.4;
step 3.6: calculating a gradient value image of the marked area in the step 3.5;
step 3.7: setting a threshold T 2 Solving a gradient mean value for the selected region image obtained in the step 3.6, namely summing all elements in the region gradient image and dividing the sum by the total number of elements to obtain the selected region gradient mean value, if the value is greater than T 2 Namely, the area is considered to have the uneven reflection characteristic, the area is judged to be the lubricating oil surface, otherwise, the area is judged to be the metal surface, and the area judged to be the metal surface is taken as a suspected oil shortage area;
step 4: processing and analyzing the pure tooth surface thermal image in the step 2 to obtain heat distribution characteristic data;
step 4.1: calculating a thermal image mean value I according to the pure tooth surface thermal image pixel value obtained in the step 2 1 I.e. the sum of all pixel values divided by the total number of pixels;
step 4.2: marking and extracting the corresponding region in the thermal image according to the region coordinates marked in the step 3.5, and calculating the thermal image mean value I of the extracted region 2 Calculate heat difference i=i 2 -I 1 ；
Step 4.3: taking the suspected oil-deficient area as an approximate contact surface, and calculating a contact area weighted heat difference E;
step 5: judging the oil shortage degree of the related area according to the heat distribution characteristic data of the thermal image corresponding to the suspected oil shortage area;
step 5.1: starting from the first operation, storing each monitored suspected oil-starved area according to the gear number and the area position, and setting an oil-starved index K with an initial value of 0 for each area;
step 5.2: setting a high threshold Th, a middle threshold Tm and a low threshold Tl of the heat difference, and comparing the weighted heat difference E obtained in the step 4.3 with the set threshold;
step 5.3: setting oil deficiency values Kh, km and Kl, and updating the oil deficiency index K value of the region according to the relation between the weighted heat difference E and the set heat difference high threshold Th, the middle threshold Tm and the low threshold Tl;
step 5.4: updating the oil deficiency index K value during each operation, and judging the oil deficiency degree according to the value of the oil deficiency index K value;
step 6: and (5) determining the oil shortage position and the oil shortage degree level of the oil shortage area according to the oil shortage degree of the relevant area determined in the step (5), and giving corresponding prompts according to different oil shortage levels.
Preferably, in step 3.2, the maximum inter-class variance method is adopted to self-adaptively threshold-segment the pure tooth surface gray level image, so as to obtain a binary image.
Further, in step 3.3, the filling of the holes to obtain the relatively complete black-and-white connected domain specifically includes:
1) Performing flood filling on the image, filling colors from the pixels (0, 0);
2) Inverting the image filled with the water, and changing the black pixels into white and the white pixels into black;
3) The threshold image is combined with the reverse flood fill image using a bitwise OR operation.
Preferably, in step 3.4, the threshold T 1 =1000。
Further, in step 4.3, the weighted heat difference
E=I*M；
Wherein M is the area of the region, and the numerical value is the number of pixels in the region.
Preferably, in the step 5.3, the K value is calculated as follows
Further, in step 5.4, the K value of the oil deficiency index is updated, and after the gear is lubricated, the K value of the lubricated area is reset to 0.
Preferably, in the step 6, the oil deficiency degree is classified into: heavy oil deficiency, medium oil deficiency, light oil deficiency and no oil deficiency; corresponding prompts are given according to different oil shortage grades: the detection area is in a severe oil shortage grade, and an oil supplementing prompt is given; the detection area is at a medium oil shortage level, and gives an early warning prompt; the detection area is at a light oil shortage level, and gives an early warning prompt; the detection area is in the oil shortage level and shows normal.
Preferably, kh=20, km=6, kl=1.
Compared with the prior art, the invention has the beneficial effects that:
1) The monitoring method of the invention realizes the automatic monitoring of the lubrication state of the large open gear, automatically judges the oil shortage degree of the gear according to the thermal image of the gear, is convenient for uninterrupted monitoring of the lubrication state of the gear, replaces manpower and saves manpower;
2) The monitoring method provided by the invention can be used for distinguishing and judging the oil shortage degree of the gear, sending different prompts to the gear manager according to different oil shortage grades, facilitating the gear manager to make an oil supplementing plan, preventing severe oil shortage, avoiding damage to the gear and reducing the risk of unplanned shutdown and damage of ship lock equipment.
Drawings
FIG. 1 is a flow chart of a method for determining oil shortage degree of a large gear tooth surface of a ship lock based on an oil shortage index according to an embodiment;
fig. 2 is a flow chart of calculating K value and determining the level of oil shortage in the embodiment.
Detailed Description
Embodiments of the invention are further described below with reference to the accompanying drawings.
As shown in fig. 1 and 2, the method for judging the oil shortage degree of the tooth surface of the large gear of the ship lock based on the oil shortage index comprises the following steps of:
step 1: an infrared thermographic camera is used to acquire gear tooth face RGB images and thermographs while the gears are running. In this embodiment, after the thermal imaging camera is set up at a proper position, the gear rotation angle data is obtained by using the angle sensor as a standard for controlling the photographing time of the camera, and each tooth surface image is photographed one by one when each tooth surface and the camera form a fixed angle, so that each tooth surface image is ensured to be at a fixed position of the image photographed by the camera.
Step 2: and (3) dividing the tooth surface RGB image and the thermal image obtained in the step (1) to obtain a complete and single pure tooth surface RGB image and a thermal image. In the embodiment, calibrating the gear tooth surface position, fixedly intercepting the area image, and fixedly intercepting a rectangular area image with the abscissa of 480-750 and the ordinate of 0-1400 at the erecting position;
step 3: and (3) screening out the suspected oil shortage area by adopting a preset algorithm for the pure tooth surface image in the step (2). In this embodiment, screening the suspected oil-deficient area includes the steps of:
step 3.1: graying the pure tooth surface image obtained in the step 2 to obtain a pure tooth surface gray image;
step 3.2: dividing the gray level image in the step 3.1 by using a maximum inter-class variance method self-adaptive threshold value to obtain a binary image;
step 3.3: performing corrosion operation on the binary image, performing expansion operation, removing image noise, filling holes to obtain a complete black-white connected domain,
the hole filling steps are as follows:
step 3.3.1: performing flood filling on the image, filling colors from the pixels (0, 0);
step 3.3.2: inverting the image after the water diffusion filling, such as black to white, white to black;
step 3.3.3: combining the threshold image with the reverse flood fill image using a bitwise OR operation;
step 3.4: setting a threshold T 1 Searching all white connected domains in the image, and enabling pixel points to be smaller than T 1 The connected domain of the white connected domain with larger area is removed; in this embodiment, T is selected 1 =1000, searching all white connected domains in the image, and picking out connected domains with pixel points smaller than 1000Removing the white connected domain with larger area;
step 3.5: marking a corresponding region in the gray level map according to the position coordinates of the left white connected region obtained in the step 3.4;
step 3.6: and (3) calculating a gradient value image of the marked area in the step 3.5, wherein the calculation process is as follows:
step 3.6.1: for processing boundary points, expanding the boundary of the selected area image by adopting boundary mirror image expansion;
step 3.6.2: sequentially selecting pixel points from pixel positions before expansion for the expanded regional image obtained in the step 3.6.1;
step 3.6.3: obtaining eight surrounding pixel values for the selected point, namely a 3X3 matrix taking the selected point as the center, searching the maximum value and the minimum value of the matrix element, and taking the absolute value of the difference between the maximum value and the minimum value as a new value of the selected point;
step 3.6.4: and repeating the step 3.6.2 and the step 3.6.3 until all the pixel points of the selected area are traversed, and obtaining the gradient value image.
Step 3.7: setting a threshold T 2 Solving a gradient mean value for the selected region image obtained in the step 3.6, namely summing all elements in the region gradient image and dividing the sum by the total number of elements to obtain the selected region gradient mean value, if the value is greater than T 2 That is, the area is considered to have the uneven reflection characteristic, and is judged to be the lubricating oil surface, otherwise, is judged to be the metal surface, and the area judged to be the metal surface is regarded as the suspected oil shortage area.
Step 4: analyzing the pure tooth surface thermal image in the step 2 to obtain characteristic data, wherein the process is as follows:
step 4.1: calculating a thermal image mean value I according to the pure tooth surface thermal image pixel value obtained in the step 2 1 I.e. the sum of all pixel values divided by the total number of pixels;
step 4.2: marking and extracting the corresponding region in the thermal image according to the region coordinates marked in the step 3.5, and calculating the thermal image mean value I of the extracted region 2 Calculate heat difference i=i 2 -I 1 ;
Step 4.3: taking a suspected oil-deficient area, namely a metal visible area, as an approximate contact surface, and calculating a contact area weighted heat difference E=I×M, wherein M is the area of the area, and the numerical value is the number of pixel points of the area;
step 5: and judging the oil shortage degree of the related area according to the thermal image characteristic data corresponding to the suspected oil shortage area and a preset logic judgment step. In this embodiment, the logic determination of the oil shortage degree is as follows:
step 5.1: starting from the first operation, storing each monitored suspected oil-starved area according to the gear number and the area position, and setting an oil-starved index K with an initial value of 0 for each area;
step 5.2: setting a high threshold Th, a middle threshold Tm and a low threshold Tl of the heat difference, and comparing the weighted heat difference E obtained in the step 4.3 with the set threshold;
step 5.3: the oil deficiency values Kh, km and Kl are set, and the oil deficiency index K value of the region is updated according to the relation between the weighted heat difference E and the set heat difference high threshold Th, the middle threshold Tm and the low threshold Tl.
The oil deficiency scores Kh, km, kl are set mainly for distinguishing the intensity of temperature change, and Kh > Km > Kl are set in principle, for example, kh=20, km=6, kl=1, but are not limited to this value.
Step 5.4: and updating the oil deficiency index K value in each operation, and judging the oil deficiency degree according to the value of the oil deficiency index K value. The calculation of the K value is shown in FIG. 2, and after re-lubricating, the K value of the oil-coated area is initialized to 0.
Step 6: and obtaining the oil shortage area position and the oil shortage degree grade, and taking corresponding measures. The oil deficiency degree grade is divided into: heavy oil starvation, medium oil starvation, light oil starvation, and no oil starvation. Corresponding prompts are given according to different oil shortage grades: the detection area is in a severe oil shortage grade, and an oil supplementing prompt is given; the detection area is at a medium oil shortage level, and gives an early warning prompt; the detection area is at a light oil shortage level, and gives an early warning prompt; the detection area is in the oil shortage level and shows normal.
The implementation result shows that the gear lubrication state monitoring method can accurately detect the oil shortage degree of the large open gear of the ship lock, is time-saving and labor-saving, is convenient for management personnel to make an oil supplementing plan, prevents severe oil shortage, avoids damage to the gear, and reduces the risk of unplanned shutdown and damage of ship lock equipment.
The method for monitoring the lubrication state of the gear is also suitable for monitoring the lubrication state of large-scale gears except for ship locks.
Claims (9)
1. The method for judging the oil shortage degree of the tooth surface of the large gear of the ship lock based on the oil shortage index is characterized by comprising the following steps:
step 1: an infrared thermal image camera is used for acquiring RGB images and thermal image pictures of tooth surfaces of the gears when the gears run;
step 2: dividing the obtained RGB image and thermal image of the tooth surface to obtain a complete and single RGB image and a single thermal image of the tooth surface;
step 3: screening out suspected oil shortage areas from the pure tooth surface RGB image in the step 2;
step 3.1: graying the pure tooth surface RGB image obtained in the step 2 to obtain a pure tooth surface gray image;
step 3.2: dividing the pure tooth surface gray level image by using a threshold segmentation method to obtain a binary image;
step 3.3: after the corrosion operation is carried out on the binary image, the expansion operation is carried out, the image noise is removed, and the hole filling is used for obtaining a relatively complete black-and-white connected domain;
step 3.4: setting a threshold T 1 Searching all white connected domains in the image, and enabling pixel points to be smaller than T 1 The connected domain of the white connected domain with larger area is removed;
step 3.5: marking a corresponding region in the gray level map according to the position coordinates of the white connected region with the larger area in the step 3.4;
step 3.6: calculating a gradient value image of the marked area in the step 3.5;
step 3.7: setting a threshold T 2 Solving a gradient mean value for the selected region image obtained in the step 3.6, namely summing all elements in the region gradient image and dividing the sum by the total number of elements to obtain the selected region gradient mean value, if the value is greater than T 2 Namely, the area is considered to have the uneven reflection characteristic, the area is judged to be the lubricating oil surface, otherwise, the area is judged to be the metal surface, and the area judged to be the metal surface is taken as a suspected oil shortage area;
step 4: processing and analyzing the pure tooth surface thermal image in the step 2 to obtain heat distribution characteristic data;
step 4.1: calculating a thermal image mean value I according to the pure tooth surface thermal image pixel value obtained in the step 2 1 I.e. the sum of all pixel values divided by the total number of pixels;
step 4.2: marking and extracting the corresponding region in the thermal image according to the region coordinates marked in the step 3.5, and calculating the thermal image mean value I of the extracted region 2 Calculate heat difference i=i 2 -I 1 ；
Step 4.3: taking the suspected oil-deficient area as an approximate contact surface, and calculating a contact area weighted heat difference E;
step 5: judging the oil shortage degree of the related area according to the heat distribution characteristic data of the thermal image corresponding to the suspected oil shortage area;
step 5.1: starting from the first operation, storing each monitored suspected oil-starved area according to the gear number and the area position, and setting an oil-starved index K with an initial value of 0 for each area;
step 5.2: setting a high threshold Th, a middle threshold Tm and a low threshold Tl of the heat difference, and comparing the weighted heat difference E obtained in the step 4.3 with the set threshold;
step 5.3: setting oil deficiency values Kh, km and Kl, and updating the oil deficiency index K value of the region according to the relation between the weighted heat difference E and the set heat difference high threshold Th, the middle threshold Tm and the low threshold Tl;
step 5.4: updating the oil deficiency index K value during each operation, and judging the oil deficiency degree according to the value of the oil deficiency index K value;
step 6: and (5) determining the oil shortage position and the oil shortage degree level of the oil shortage area according to the oil shortage degree of the relevant area determined in the step (5), and giving corresponding prompts according to different oil shortage levels.
2. The oil deficiency index-based ship lock large gear tooth surface oil deficiency degree judging method according to claim 1, wherein the step 3.2 is to divide a pure tooth surface gray level image by adopting a maximum inter-class variance method self-adaptive threshold value to obtain a binary image.
3. The oil deficiency degree judging method for the tooth surface of the large gear of the ship lock based on the oil deficiency index as claimed in claim 2, wherein in the step 3.3, the hole filling is used for obtaining a relatively complete black-and-white connected domain, and the method specifically comprises the following steps:
1) Performing flood filling on the image, filling colors from the pixels (0, 0);
2) Inverting the image filled with the water, and changing the black pixels into white and the white pixels into black;
3) The threshold image is combined with the reverse flood fill image using a bitwise OR operation.
4. The method for determining the oil deficiency degree of the tooth surface of the large gear of the ship lock based on the oil deficiency index according to claim 2 or 3, wherein in the step 3.4, the threshold value T is 1 =1000。
5. The oil deficiency degree judging method for ship lock large gear tooth surface based on oil deficiency index as claimed in claim 4, wherein in step 4.3, the weighted heat difference is
E=I*M；
Wherein M is the area of the region, and the numerical value is the number of pixel points of the region.
6. The oil deficiency degree judging method for the ship lock large gear tooth surface based on the oil deficiency index as claimed in claim 5, wherein in the step 5.3, the K value is calculated as follows
。
7. The oil deficiency degree judging method for the ship lock large gear tooth surface based on the oil deficiency index according to claim 6, wherein in the step 5.3, kh=20, km=6, kl=1.
8. The method for determining the oil shortage degree of the tooth surface of the large gear of the ship lock based on the oil shortage index according to claim 5, 6 or 7, wherein in the step 5.4, the K value of the oil shortage index is updated, and after the gear is lubricated, the K value of the lubricated area is reset to 0.
9. The oil deficiency judging method for large gear tooth surfaces of ship locks based on oil deficiency indexes according to claim 5, 6 or 7, wherein in the step 6, the oil deficiency degree is classified into: heavy oil deficiency, medium oil deficiency, light oil deficiency and no oil deficiency; corresponding prompts are given according to different oil shortage grades: the detection area is in a severe oil shortage grade, and an oil supplementing prompt is given; the detection area is at a medium oil shortage level, and gives an early warning prompt; the detection area is at a light oil shortage level, and gives an early warning prompt; the detection area is in the oil shortage level and shows normal.
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| KR101785202B1 (en) * | 2016-04-29 | 2017-10-13 | 한국과학기술원 | Automatic Calibration for RGB-D and Thermal Sensor Fusion and Method thereof |
| CN107729907A (en) * | 2016-08-12 | 2018-02-23 | 南京理工大学 | A kind of fault recognition method based on infra-red thermal imaging system |
| CN110261436B (en) * | 2019-06-13 | 2022-03-22 | 暨南大学 | Rail fault detection method and system based on infrared thermal imaging and computer vision |
| CN110334750B (en) * | 2019-06-21 | 2021-06-08 | 西安工程大学 | Power transmission line iron tower bolt corrosion degree image classification and identification method |
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