Outrigger safety testing methods, systems, operating machinery and electronic equipment

Abstract

This invention relates to the field of operational safety assurance technology, and provides a method, system, operational machinery, and electronic equipment for outrigger safety detection. The method includes: acquiring an image to be processed; determining, based on the image, whether the overall road surface type of a preset area belongs to a target road surface type; if the overall road surface type belongs to the target road surface type, determining, based on the image, whether sleepers exist within the preset area; if sleepers are not present within the preset area, determining that the support of the target outrigger is at risk; if sleepers are present within the preset area, determining, based on the image, whether the positional relationship between the sleepers and the target outrigger meets sleeper placement requirements; if the sleeper placement requirements are not met, determining that the support of the target outrigger is at risk. This invention addresses the problem in existing technologies where the safety of outrigger support is not guaranteed because the road surface type and sleepers are not detected during outrigger support safety testing.

Description

Technical Field

[0001] This invention relates to the field of operational safety assurance technology, and in particular to a method, system, operational machinery, and electronic equipment for outrigger safety detection. Background Technology

[0002] To improve the machine's resistance to tipping over during operation, some construction machinery uses outriggers to support the machine body, providing a larger support span. Examples include concrete pump trucks and cranes.

[0003] Taking concrete pump trucks as an example, during construction, the outriggers need to be deployed first, and when the road surface is gravel or mud, sleepers are placed to increase the bearing area in order to prevent the pump truck from tipping over during construction.

[0004] However, current testing for outrigger support safety does not cover road surface type and sleepers. When the working machinery is located on a rough road surface, the safety of the outriggers supporting the working machinery cannot be guaranteed. Summary of the Invention

[0005] This invention provides a method, system, work machinery, and electronic equipment for outrigger safety testing, which solves the problem in the prior art that the safety of outrigger support for work machinery cannot be guaranteed because the road surface type and sleepers are not tested when testing the safety of outrigger support.

[0006] This invention provides a method for outrigger safety testing, comprising:

[0007] Acquire an image to be processed, wherein the image to be processed is an image containing a preset region, wherein the preset region is the area included after extending outwards from the contact point between the target outrigger and the road surface by a first preset distance;

[0008] Based on the image to be processed, determine whether the overall road surface type of the preset area belongs to the target road surface type. The target road surface type includes all road surface types that require sleepers to support the target outrigger.

[0009] If it is determined that the overall road surface type belongs to the target road surface type, then based on the image to be processed, it is determined whether the sleeper exists in the preset area;

[0010] If the sleeper is not present within the preset area, then the support of the target outrigger is deemed to be at risk.

[0011] If the sleeper exists within the preset area, then based on the image to be processed, determine whether the positional relationship between the sleeper and the target leg meets the sleeper placement requirements;

[0012] If the sleeper placement requirements are not met, then the support of the target outrigger is deemed to be at risk.

[0013] According to the outrigger safety detection method of the present invention, determining whether the overall road surface type of the preset area belongs to the target road surface type based on the image to be processed includes:

[0014] Based on the image to be processed, determine the proportion of road surface areas belonging to the target road surface type within the preset area to all road surface areas in the image to be processed;

[0015] If the percentage is greater than the first preset percentage, then the overall road surface type of the preset area is determined to belong to the target road surface type.

[0016] According to the outrigger safety detection method of the present invention, the step of determining whether the positional relationship between the sleeper and the target outrigger meets the sleeper placement requirements based on the image to be processed includes:

[0017] Based on semantic segmentation, the preset region is determined to contain the target leg and the sleeper region.

[0018] The sleeper area is divided into blocks, and the blocks are sorted according to the number of pixels contained in each block.

[0019] Determine the proportion of pixels contained in the first block among the pixels contained in the sleeper area, wherein the first block is the block containing the most pixels among all the blocks.

[0020] If the proportion of pixels in the first block to pixels in the sleeper area is greater than a second preset proportion, and the minimum distance between pixels in the first block and pixels in the leg area is less than a second preset distance, then the positional relationship is determined to meet the sleeper placement requirements.

[0021] The outrigger safety detection method according to the present invention further includes:

[0022] If it is determined that the proportion of pixels contained in the first block in the total number of pixels contained in the sleeper area is less than or equal to the second preset proportion, then it is determined whether the maximum angle of the triangle formed by the centroid of the first block, the centroid of the second block, and the lowest point of the target leg is greater than the preset angle, and the second block is the block with the second most pixels among all the blocks.

[0023] If so, then the positional relationship is determined to meet the sleeper placement requirements;

[0024] If not, then the positional relationship does not meet the requirements for sleeper placement.

[0025] According to the outrigger safety detection method of the present invention, after determining that the positional relationship meets the sleeper placement requirements, the method further includes:

[0026] Based on the image to be processed, determine the material characteristics of the sleeper;

[0027] Based on the material characteristics, it is determined whether the material of the sleeper meets the safety requirements.

[0028] The outrigger safety detection method according to the present invention further includes:

[0029] Within a preset detection time, each image acquisition module acquires the image to be processed according to a preset frequency;

[0030] Based on each of the images to be processed corresponding to the target outrigger, it is determined whether the support of the target outrigger poses a risk.

[0031] If the number of images to be processed that indicate a risk to the support of the target outrigger is determined to be greater than a third preset ratio in all images to be processed acquired by the corresponding image acquisition module, an alarm is triggered.

[0032] The outrigger safety detection method according to the present invention further includes:

[0033] Save the image to be processed that indicates the target outrigger's support is at risk.

[0034] The present invention also provides an outrigger safety detection system, comprising: a camera and a processing module;

[0035] The camera is used to capture an image to be processed. The image to be processed is an image containing a preset area. The preset area is the area included after extending a first preset distance in all directions from the contact point between the target leg and the road surface.

[0036] The processing module is used to acquire the image to be processed, and based on the image to be processed, determine whether the overall road surface type of the preset area belongs to the target road surface type. If the overall road surface type belongs to the target road surface type, and based on the image to be processed, determine whether the sleeper exists in the preset area. If the sleeper does not exist in the preset area, determine that the support of the target outrigger is at risk. If the sleeper exists in the preset area, based on the image to be processed, determine whether the positional relationship between the sleeper and the target outrigger meets the sleeper placement requirements. If the sleeper does not meet the sleeper placement requirements, determine that the support of the target outrigger is at risk. The target road surface type includes all road surface types that require sleepers to support the target outrigger.

[0037] The present invention also provides a working machine, which includes a main body and outriggers. The main body operates under the support of the outriggers. The working machine also includes the outrigger safety detection system described above.

[0038] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the outrigger safety detection method as described above.

[0039] This invention provides a method, system, operating machinery, and electronic equipment for outrigger safety detection. It acquires an image of a pre-defined area extending outwards from the contact point between the target outrigger and the road surface at a first predetermined distance. Based on this image, it determines whether the overall road surface type of the pre-defined area belongs to the target road surface type. The target road surface type includes all road surface types that require sleepers to support the target outrigger. Therefore, it can determine whether sleepers are needed for the target outrigger's support based on the overall road surface type of the pre-defined area. If sleepers are required, the system further determines whether sleepers exist within the pre-defined area based on the image. If sleepers are absent, the system considers the support of the target outrigger to be at risk. If sleepers are present, the system determines whether the positional relationship between the sleepers and the target outrigger meets the sleeper placement requirements. If the sleeper placement does not meet the requirements, the system considers the support of the target outrigger to be at risk. Thus, by detecting the road surface type, sleepers, and sleeper placement status of the road surface in contact with the outrigger, accurate detection of outrigger support stability is achieved, effectively ensuring the safety of the outrigger's support for the operating machinery. Attached Figure Description

[0040] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0041] Figure 1 This is a flowchart illustrating a method for outrigger safety testing provided in an embodiment of the present invention;

[0042] Figure 2 This is a schematic flowchart of a method for detecting whether sleepers are correctly placed according to an embodiment of the present invention;

[0043] Figure 3 This is a schematic diagram of the structure of an outrigger safety detection system provided in an embodiment of the present invention;

[0044] Figure 4 This is a schematic diagram of the structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0045] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0046] The following is combined with Figure 1 and Figure 2 This invention describes a method for outrigger safety testing, which is applied to working machinery that uses outriggers to support the main body of the machinery, such as pump trucks and cranes.

[0047] The outrigger safety detection method provided in this embodiment of the invention is executed in the processor of the working machinery. Furthermore, the processor can utilize a controller or central control screen to complete the outrigger safety detection method, such as... Figure 1 As shown, the method includes the following steps:

[0048] 101. Obtain the image to be processed, wherein the image to be processed is an image containing a preset area, wherein the preset area is the area included after extending outwards from the contact point between the target outrigger and the road surface by a first preset distance;

[0049] Specifically, the processor can acquire images from the camera of the operating machinery. Meanwhile, considering that the function of the sleepers is to support the outriggers of the operating machinery, and that it is necessary to determine whether sleepers need to be placed and whether their placement is correct based on the road surface type and the positional relationship between the sleepers and the outriggers, a preset area is defined by extending a first preset distance outwards from the contact point between the outriggers and the road surface. This ensures that the image to be processed includes not only the outriggers but also the area where sleepers need to be placed, as well as the road surface in that area.

[0050] More specifically, the preset area can be set according to actual needs, such as 2m, 2.5m, etc., so that the preset area is a circular, square, or other shaped area centered on the contact point between the target outrigger and the road surface.

[0051] Furthermore, taking a concrete pump truck as an example, when the boom is detected to have extended, it means that the operator has confirmed that the outriggers are fully supported. At this point, the image to be processed is acquired and then fed into a neural network model such as target detection and / or semantic segmentation for image recognition, in order to further detect the road surface type and the presence of sleepers in the area where the target outriggers are located.

[0052] 102. Based on the image to be processed, determine whether the overall road surface type of the preset area belongs to the target road surface type, wherein the target road surface type includes all road surface types that require sleepers to support the target outrigger;

[0053] Understandably, for softer surfaces such as gravel roads, loess roads, and mud roads, simply placing a base plate cannot guarantee the bearing area when the outriggers are supporting the load, which can easily cause the machinery to tip over or overturn during construction. Therefore, for the above types of roads, in addition to placing a base plate, it is necessary to place sleepers under the base plate to increase the bearing area.

[0054] Specifically, the processor can pre-set the correspondence between different road surface types and sleepers. For example, gravel roads, loess roads, mud roads and other soft road surface types are associated with sleeper support legs, while cement roads, asphalt roads and other hard road surface types are associated with sleeper support legs.

[0055] More specifically, by performing target recognition on the image to be processed, the overall road surface type of the preset area can be determined.

[0056] In one specific embodiment, a semantic segmentation model can be used to perform semantic segmentation on the image to be processed to determine the road surface type within a preset region. That is, various road surface types are pre-defined as regions of interest for the semantic segmentation model, and then semantic segmentation is performed on the image to be processed to obtain a specific road surface type mask image. Then, based on the correspondence between road surface types and sleepers, it can be determined whether the overall road surface type of the preset region belongs to the target road surface type that requires sleepers to support the target outrigger.

[0057] 103. If it is determined that the overall road surface type belongs to the target road surface type, then based on the image to be processed, determine whether the sleeper exists in the preset area;

[0058] It is understood that the outrigger safety detection method provided in the embodiments of the present invention may also include a step of providing a safety reminder to the user regarding the support of the target outrigger if it is determined that the support of the target outrigger does not require sleepers.

[0059] In one specific embodiment, to determine whether the image to be processed includes sleepers, the sleepers can be set as the region of interest in the semantic segmentation model, and then the semantic segmentation model can be used to determine whether a sleeper mask image exists in the image to be processed. Alternatively, object detection can be used to determine whether the image to be processed includes sleepers.

[0060] 104. If the sleeper is not present in the preset area, then the support of the target outrigger is deemed to be at risk.

[0061] Specifically, when the overall road surface type of the preset area is determined to be the target road surface type, but the actual support of the target outrigger does not have sleepers, it indicates that the support stability of the target outrigger cannot be guaranteed. Therefore, it can be determined that the support of the target outrigger is at risk.

[0062] In one specific embodiment, when it is determined that the support of the target outrigger poses a risk, a prompt can be made to the user so that the user can take timely action, thereby improving the construction safety of the machinery. The prompt can be made in the following ways: triggering an audible and visual alarm on the machinery, displaying a risk warning on the machinery's central control screen, or displaying a risk warning on the user's mobile phone or other smart terminal.

[0063] 105. If the sleeper exists within the preset area, then based on the image to be processed, determine whether the positional relationship between the sleeper and the target leg meets the sleeper placement requirements;

[0064] Specifically, when there are sleepers in the preset area, it is also necessary to determine whether the sleepers are located below the bottom of the target outrigger in order to determine whether the sleepers effectively support the target outrigger. Therefore, by analyzing the positional relationship between the sleepers and the target outrigger, it can be determined whether the sleeper placement meets the placement requirements, thereby further improving the safety of the operating machinery.

[0065] 106. If the sleeper placement requirements are not met, the support of the target outrigger is deemed to be at risk.

[0066] It is understood that the outrigger safety detection method provided in the embodiments of the present invention may also include a step of providing the user with a safety reminder for the target outrigger support if it is determined that the sleeper placement meets the sleeper placement requirements.

[0067] The outrigger safety detection method provided in this embodiment of the invention is based on image recognition of an image of a preset area at the target outrigger. On the one hand, by combining road surface type detection, sleeper detection, and sleeper placement position detection, it effectively improves the accuracy of determining the safety of the outrigger, thereby improving the safety of the operating machinery. On the other hand, by reusing the camera on the operating machinery, the outrigger safety detection method provided in this embodiment of the invention can be used on the operating machinery, effectively reducing the cost of use.

[0068] Based on the above embodiments, determining whether the overall road surface type of the preset area belongs to the target road surface type based on the image to be processed includes:

[0069] Based on the image to be processed, determine the proportion of road surface areas belonging to the target road surface type within the preset area to all road surface areas in the image to be processed;

[0070] If the percentage is greater than the first preset percentage, then the overall road surface type of the preset area is determined to belong to the target road surface type.

[0071] It is understandable that construction machinery refers to equipment used for construction operations, which generally operate in harsh environments and involve multiple road surface types. For example, loess mud roads may intersect with cement-soil roads, sand and gravel may cover cement roads, and loess roads may be covered with cement. Therefore, when using a semantic segmentation model to classify road surface types, multiple road surface types will emerge.

[0072] Furthermore, for situations where the preset area includes multiple road surface types, since it is necessary to consider whether the road surface types in the preset area affect the stability of the target outrigger support, all road surface types that require sleepers to support the target outrigger can be classified as target road surface types. Then, based on the proportion of each road surface type in the preset area, it can be determined whether the overall road surface type of the preset area belongs to the target road surface type. That is, when the proportion of the road surface area corresponding to the road surface type that requires sleepers to be placed in the total road surface area of ​​the preset area reaches a certain level, it indicates that sleepers need to be placed to improve the support stability of the target outrigger.

[0073] Specifically, the higher the first preset ratio is set, the lower the probability that the target outrigger needs sleeper support; conversely, the lower the first preset ratio is set, the higher the probability that the target outrigger needs sleeper support. Therefore, by reasonably setting the first preset ratio, it is possible to accurately determine whether the overall road surface type of the preset area belongs to the target road surface type, that is, whether the target outrigger in the preset area needs sleeper support. Preferably, the first preset ratio can be set to 50%.

[0074] In a specific embodiment, the processor first determines the road surface area within the preset area using Formula 1. Then, it determines whether the proportion of the road surface type mask that requires sleepers to be placed within the preset area is greater than a first preset proportion. For example, if more than 50% of the area within the preset area is a cement road surface mask, the overall classification is Category 1, which does not require sleepers. If more than 50% of the area within the preset area is a mud, loess, and / or gravel mask, the overall classification is Category 2, which requires sleepers to be placed. In other words, the overall road surface type of the preset area belongs to the target road surface type.

[0075] A interest =A ellipse ∩A seg (1)

[0076] Among them, A interest A is the region where the preset region and the semantic segmentation region intersect; ellipse For the preset area; Aseg This represents the semantic segmentation reasoning mask graph region.

[0077] Based on the above embodiments, determining whether the positional relationship between the sleeper and the target outrigger meets the sleeper placement requirements based on the image to be processed includes:

[0078] Based on semantic segmentation, the preset region is determined to contain the target leg and the sleeper region.

[0079] The sleeper area is divided into blocks, and the blocks are sorted according to the number of pixels contained in each block.

[0080] Determine the proportion of pixels contained in the first block among the pixels contained in the sleeper area, wherein the first block is the block containing the most pixels among all the blocks.

[0081] If the proportion of pixels in the first block to pixels in the sleeper area is greater than a second preset proportion, and the minimum distance between pixels in the first block and pixels in the leg area is less than a second preset distance, then the positional relationship is determined to meet the sleeper placement requirements.

[0082] Understandably, due to the camera's perspective, the positional relationship between the target leg and the sleeper displayed in the image to be processed acquired by the processor can include three scenarios: the sleeper completely envelops the target leg, the target leg cuts the sleeper into two sections, and the sleeper and the target leg are not in contact.

[0083] Specifically, the sleeper mask image obtained based on semantic segmentation is composed of pixels. By dividing the sleeper region into blocks based on the distribution of pixels, clustered pixels can be divided into a block. Therefore, when the sleeper mask completely covers the lower part of the target leg, or when the sleeper is located on one side of the target leg but not in contact with it, most of the pixels in the sleeper mask will cluster together and be divided into a large block. This involves dividing the sleeper mask image into blocks, sorting them by pixel count, and then determining the percentage of pixels in the block with the most pixels out of all blocks. This can be achieved by ensuring that the number of pixels in the block with the most pixels significantly exceeds the number of pixels in the remaining blocks. First, a distinction is made between two scenarios: the sleeper wrapping around the target leg and the sleeper not touching the target leg, and the scenario where the sleeper is cut in two by the target leg. Then, by determining whether the distance between the pixels in the block with the most pixels in the sleeper area and the pixels in the leg area is less than a second preset distance, it is determined whether the block with the most pixels is adjacent to the pixels in the leg area. This further distinguishes between the two scenarios: the sleeper wrapping around the target leg and the sleeper not touching the target leg, ultimately determining whether the image being processed shows the scenario where the sleeper wraps around the lower end of the target leg.

[0084] More specifically, the second preset ratio is data set based on experimentation or experience, such as 90%, 95%, etc.

[0085] Based on the above embodiments, the outrigger safety detection method further includes:

[0086] If it is determined that the proportion of pixels contained in the first block in the total number of pixels contained in the sleeper area is less than or equal to the second preset proportion, then it is determined whether the value of the maximum angle of the triangle with the centroid of the first block, the centroid of the second block, and the lowest point of the target leg as endpoints is greater than the preset angle, and the second block is the block with the second most pixels among all the blocks.

[0087] If so, then the positional relationship is determined to meet the sleeper placement requirements;

[0088] If not, then the positional relationship does not meet the requirements for sleeper placement.

[0089] Specifically, when the image to be processed depicts a sleeper divided into two sections by the target leg, since most of the pixels in the sleeper area are clustered on both sides of the target leg, the two blocks containing the most and second most pixels will be located on either side of the leg area when dividing the sleeper area into blocks. At this point, by determining whether the maximum angle of the triangle formed by the centroid of the first block containing the most pixels, the centroid of the second block containing the second most pixels, and the lowest point of the target leg is greater than a preset angle set based on the angle at which the camera captures the image of the preset area at the leg, it can be further determined whether the actual positional relationship between the target leg and the sleeper, where the sleeper is divided into two sections by the target leg, is that the sleeper is located below the target leg. This accurately determines whether the sleeper is correctly placed.

[0090] More specifically, the lowest point of the target outrigger can be obtained through target detection.

[0091] In one specific embodiment, the `findcontours` function in OpenCV is used to divide the sleeper mask image obtained from the semantic segmentation model into blocks and sort them according to the number of pixels, thereby determining whether the sleeper placement meets the sleeper placement requirements. The specific process is as follows: Figure 2 As shown, it includes the following steps:

[0092] 201. Determine the sleeper mask diagram;

[0093] 202. Block partitioning based on sleeper mask graph using the findcontours function;

[0094] 203. Sort the results returned by the findcontours function;

[0095] 204. Determine whether the percentage of pixels in the first block exceeds the second preset percentage; if yes, proceed to step 205; if no, proceed to step 206.

[0096] 205. Ensure that the sleepers are placed in accordance with the sleeper placement requirements;

[0097] 206. Determine whether the maximum angle of the triangle formed by the centroid of the first block, the centroid of the second block, and the lowest point of the target leg is greater than the preset angle; if yes, return to step 205; if no, proceed to step 207.

[0098] 207. It was determined that the sleeper placement did not meet the sleeper placement requirements.

[0099] Based on the above embodiments, after determining that the positional relationship meets the sleeper placement requirements, the method further includes:

[0100] Based on the image to be processed, determine the material characteristics of the sleeper;

[0101] Based on the material characteristics, it is determined whether the material of the sleeper meets the safety requirements.

[0102] Specifically, by determining whether the sleeper material meets the support requirements of the target outrigger, that is, whether the sleeper material meets the safety requirements, the stability of the sleeper's support for the target outrigger can be further guaranteed.

[0103] Furthermore, the determination of the material of the sleeper can include the determination of materials such as metal, wood, and foam plastic. For example, if the sleeper is determined to be made of foam plastic, it can be determined that the material does not meet the safety requirements. If the sleeper is determined to be made of wood or metal, it can be determined that the material meets the safety requirements.

[0104] Based on the above embodiments, the outrigger safety detection method further includes:

[0105] Within a preset detection time, each image acquisition module acquires the image to be processed according to a preset frequency;

[0106] Based on each of the images to be processed corresponding to the target outrigger, it is determined whether the support of the target outrigger poses a risk.

[0107] If the number of images to be processed that indicate a risk to the support of the target outrigger is determined to be greater than a third preset ratio in all images to be processed acquired by the corresponding image acquisition module, an alarm is triggered.

[0108] Specifically, within a preset detection period, each image acquisition module acquires images to be processed at a preset frequency to determine whether the support of the target leg poses a risk. An alarm is triggered only when the proportion of images indicating that the support of the target leg poses a risk is greater than a third preset proportion among all images to be processed. The risk of the target leg's support can be comprehensively determined by combining the results of multiple image acquisition modules and multiple confirmations of the results of a single image acquisition module, thereby improving the accuracy of detection and avoiding false alarms.

[0109] More specifically, the image acquisition module can be a camera installed on the operating machinery.

[0110] In one specific embodiment, a preset detection duration of 30 seconds is set, with 2 frames of detection images captured per second. Simultaneously, a third preset ratio is set to 80%, meaning an alarm is triggered when the detection results of more than 80% of the image frames acquired by each image acquisition module are alarm signals. Taking a concrete pump truck as an example, a pump truck with a 360° surround view system typically has 6 cameras. The final result can be determined by taking the intersection of multiple camera data. For instance, if the left front outrigger has two cameras with complete fields of view, an alarm is triggered when the calculation results of 80% of the images acquired by each camera indicate incorrect placement.

[0111] Specifically, for the same target outrigger, when n cameras can capture images of that target outrigger, the processor determines whether to trigger an alarm based on Formula 2:

[0112] S final =S1∩S2∩…∩S n (2)

[0113] Among them, S final The overall decision signal for whether to trigger an alarm; S1, S2 and S n These are the judgment signals for whether an alarm is triggered, obtained from the images to be processed acquired by cameras 1, 2, and n targeting the outrigger.

[0114] Furthermore, since operating machinery typically includes multiple outriggers, alarm triggering strategies can be further optimized. For example, for a pump truck with four outriggers, when one or two target outriggers are identified as having a support risk, only the image to be processed is saved without triggering an alarm. When three or four target outriggers are identified as having a support risk, an on-site alarm is triggered directly, thereby further reducing the probability of false alarms. Another example is that when any target outrigger is identified as having a support risk, the center of gravity of the operating machinery can be obtained, and the offset between the machine's center of gravity and a pre-stored center of gravity can be calculated to determine whether to trigger an alarm. This can further reduce the probability of false alarms and prevent false alarms from affecting operational efficiency.

[0115] Based on the above embodiments, the outrigger safety detection method further includes:

[0116] Save the image to be processed that indicates the target outrigger's support is at risk.

[0117] Specifically, by saving images of outriggers that indicate a risk of damage to their support, liability for accidents can be determined based on these images in the event of an operational accident, thereby preventing disputes.

[0118] The following describes a leg safety detection system provided by the present invention. The leg safety detection system described below can be referred to in correspondence with the leg safety detection method described above.

[0119] The outrigger safety detection system provided in this embodiment of the invention, such as Figure 3 As shown, it includes: a camera 310 and a processing module 320; wherein,

[0120] The camera 310 is used to acquire an image to be processed. The image to be processed is an image containing a preset area. The preset area is the area included after extending a first preset distance in all directions from the contact point between the target outrigger and the road surface.

[0121] The processing module 320 is used to acquire the image to be processed, and based on the image to be processed, determine whether the overall road surface type of the preset area belongs to the target road surface type. If the overall road surface type belongs to the target road surface type, and based on the image to be processed, determine whether the sleeper exists in the preset area, and if the sleeper does not exist in the preset area, determine that the support of the target outrigger is at risk. If the sleeper exists in the preset area, based on the image to be processed, determine whether the positional relationship between the sleeper and the target outrigger meets the sleeper placement requirements, and if the sleeper does not meet the sleeper placement requirements, determine that the support of the target outrigger is at risk. The target road surface type includes all road surface types that require sleepers to support the target outrigger.

[0122] The outrigger safety detection system provided in this invention acquires an image of a preset area formed by extending a first preset distance outward from the contact point between the target outrigger and the road surface. Based on this image, it determines whether the overall road surface type of the preset area belongs to the target road surface type. The target road surface type includes all road surface types that require sleepers to support the target outrigger. Therefore, it can determine whether sleepers are needed for the target outrigger's support based on the overall road surface type of the preset area. If sleepers are required, the system further determines whether sleepers exist within the preset area based on the image. If sleepers are not present, the system considers the support of the target outrigger to be at risk. If sleepers are present, the system determines whether the positional relationship between the sleepers and the target outrigger meets the sleeper placement requirements based on the image. If the sleeper placement does not meet the requirements, the system considers the support of the target outrigger to be at risk. Thus, by detecting the road surface type, sleepers, and sleeper placement status of the road surface in contact with the outrigger, accurate detection of outrigger support stability is achieved, effectively ensuring the safety of the outrigger's support for the working machinery.

[0123] Optionally, the processing module 320 is specifically used for:

[0124] Based on the image to be processed, determine the proportion of road surface areas belonging to the target road surface type within the preset area to all road surface areas in the image to be processed;

[0125] If the percentage is greater than the first preset percentage, then the overall road surface type of the preset area is determined to belong to the target road surface type.

[0126] Optionally, the processing module 320 is also specifically used for:

[0127] Based on semantic segmentation, the preset region is determined to contain the target leg and the sleeper region.

[0128] The sleeper area is divided into blocks, and the blocks are sorted according to the number of pixels contained in each block.

[0129] Determine the proportion of pixels contained in the first block among the pixels contained in the sleeper area, wherein the first block is the block containing the most pixels among all the blocks.

[0130] If the proportion of pixels in the first block to pixels in the sleeper area is greater than a second preset proportion, and the minimum distance between pixels in the first block and pixels in the leg area is less than a second preset distance, then the positional relationship is determined to meet the sleeper placement requirements.

[0131] Optionally, the processing module 320 is further configured to:

[0132] When the proportion of pixels contained in the first block in the total number of pixels contained in the sleeper area is less than or equal to the second preset proportion, it is determined whether the maximum angle of the triangle formed by the centroid of the first block, the centroid of the second block, and the lowest point of the target leg is greater than the preset angle. The second block is the block with the second most pixels among all the blocks.

[0133] If so, then the positional relationship is determined to meet the sleeper placement requirements;

[0134] If not, then the positional relationship does not meet the requirements for sleeper placement.

[0135] Optionally, the processing module 320 is further configured to:

[0136] After determining that the positional relationship meets the sleeper placement requirements, the material characteristics of the sleeper are determined based on the image to be processed;

[0137] Based on the material characteristics, it is determined whether the material of the sleeper meets the safety requirements.

[0138] Optionally, the processing module 320 is further configured to:

[0139] Within a preset detection time, each image acquisition module acquires the image to be processed according to a preset frequency;

[0140] Based on each of the images to be processed corresponding to the target outrigger, it is determined whether the support of the target outrigger poses a risk.

[0141] If the number of images to be processed that indicate a risk to the support of the target outrigger is determined to be greater than a third preset ratio in all images to be processed acquired by the corresponding image acquisition module, an alarm is triggered.

[0142] Optionally, the processing module 320 is further configured to:

[0143] Save the image to be processed that indicates the target outrigger's support is at risk.

[0144] This invention also provides a working machine including a fuselage and outriggers, wherein the fuselage operates under the support of the outriggers, and the working machine further includes an outrigger safety detection system as described in any of the above embodiments.

[0145] It is understood that the working machinery including the outrigger safety detection system as described in any of the above embodiments has all the advantages and technical effects of the outrigger safety detection system provided in any of the above embodiments, and will not be repeated here.

[0146] Specifically, the operating machinery can be any type of operating machinery that uses outriggers for support, such as pump trucks, cranes, etc.

[0147] Figure 4 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 4As shown, the electronic device may include: a processor 410 and a communication bus 440, wherein the processor 410, the communication interface 420, and the memory 430 communicate with each other through the communication bus 440. The processor 410 can call logical instructions in the memory 430 to execute a leg safety detection method, the method comprising: acquiring an image to be processed, the image to be processed being an image containing a preset region, the preset region being the area included after extending outwards from the contact point between the target leg and the road surface by a first preset distance; based on the image to be processed, determining whether the overall road surface type of the preset region belongs to a target road surface type, the target road surface type including all road surface types that require sleepers to support the target leg; if the overall road surface type is determined to belong to the target road surface type, then based on the image to be processed, determining whether the sleeper exists in the preset region; if the sleeper does not exist in the preset region, then determining that the support of the target leg is at risk; if the sleeper exists in the preset region, then based on the image to be processed, determining whether the positional relationship between the sleeper and the target leg meets the sleeper placement requirements; if it does not meet the sleeper placement requirements, then determining that the support of the target leg is at risk.

[0148] Furthermore, the logical instructions in the aforementioned memory 430 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0149] On the other hand, the present invention also provides a computer program product, the computer program product including a computer program stored on a non-transitory computer-readable storage medium, the computer program including program instructions, when the program instructions are executed by a computer, the computer is able to execute the outrigger safety detection method provided by the above methods, the method including: acquiring an image to be processed, the image to be processed being an image containing a preset area, the preset area being an area included after extending outwards from the contact point between the target outrigger and the road surface by a first preset distance; based on the image to be processed, determining whether the overall road surface type of the preset area belongs to a target road surface type, the target road surface type including all road surface types that require sleepers to support the target outrigger; if it is determined that the overall road surface type belongs to the target road surface type, then based on the image to be processed, determining whether the sleeper exists in the preset area; if the sleeper does not exist in the preset area, then determining that the support of the target outrigger is at risk; if the sleeper exists in the preset area, then based on the image to be processed, determining whether the positional relationship between the sleeper and the target outrigger meets the sleeper placement requirements; if it does not meet the sleeper placement requirements, then determining that the support of the target outrigger is at risk.

[0150] In another aspect, the present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon. When executed by a processor, the computer program implements a method for outrigger safety detection. The method includes: acquiring an image to be processed, the image to be processed being an image containing a preset region, the preset region being the area included after extending outwards from the contact point between the target outrigger and the road surface by a first preset distance; based on the image to be processed, determining whether the overall road surface type of the preset region belongs to a target road surface type, the target road surface type including all road surface types that require sleepers to support the target outrigger; if the overall road surface type is determined to belong to the target road surface type, then based on the image to be processed, determining whether the sleeper exists within the preset region; if the sleeper does not exist within the preset region, then determining that the support of the target outrigger is at risk; if the sleeper exists within the preset region, then based on the image to be processed, determining whether the positional relationship between the sleeper and the target outrigger meets the sleeper placement requirements; if it does not meet the sleeper placement requirements, then determining that the support of the target outrigger is at risk.

[0151] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0152] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0153] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for testing the safety of outriggers, characterized in that, include: Acquire an image to be processed, wherein the image to be processed is an image containing a preset region, wherein the preset region is the area included after extending outwards from the contact point between the target outrigger and the road surface by a first preset distance; Based on the image to be processed, determine whether the overall road surface type of the preset area belongs to the target road surface type. The target road surface type includes all road surface types that require sleepers to support the target outrigger. If it is determined that the overall road surface type belongs to the target road surface type, then based on the image to be processed, it is determined whether the sleeper exists in the preset area; If the sleeper is not present within the preset area, then the support of the target outrigger is deemed to be at risk. If the sleeper exists within the preset area, then based on the image to be processed, determine whether the positional relationship between the sleeper and the target leg meets the sleeper placement requirements; If the sleeper placement requirements are not met, then the support of the target outrigger is deemed to be at risk.

2. The outrigger safety detection method according to claim 1, characterized in that, The step of determining whether the overall road surface type of the preset area belongs to the target road surface type based on the image to be processed includes: Based on the image to be processed, determine the proportion of road surface areas belonging to the target road surface type within the preset area to all road surface areas in the image to be processed; If the percentage is greater than the first preset percentage, then the overall road surface type of the preset area is determined to belong to the target road surface type.

3. The outrigger safety detection method according to claim 1, characterized in that, The step of determining whether the positional relationship between the sleeper and the target outrigger meets the sleeper placement requirements based on the image to be processed includes: Based on semantic segmentation, the preset region is determined to contain the target leg and the sleeper region. The sleeper area is divided into blocks, and the blocks are sorted according to the number of pixels contained in each block. Determine the proportion of pixels contained in the first block among the pixels contained in the sleeper area, wherein the first block is the block containing the most pixels among all the blocks. If the proportion of pixels in the first block to pixels in the sleeper area is greater than a second preset proportion, and the minimum distance between pixels in the first block and pixels in the leg area is less than a second preset distance, then the positional relationship is determined to meet the sleeper placement requirements.

4. The outrigger safety detection method according to claim 3, characterized in that, Also includes: If it is determined that the proportion of pixels contained in the first block in the total number of pixels contained in the sleeper area is less than or equal to the second preset proportion, then it is determined whether the value of the maximum angle of the triangle with the centroid of the first block, the centroid of the second block, and the lowest point of the target leg as endpoints is greater than the preset angle, and the second block is the block with the second most pixels among all the blocks. If so, then the positional relationship is determined to meet the sleeper placement requirements; If not, then the positional relationship does not meet the requirements for sleeper placement.

5. The outrigger safety detection method according to claim 3 or 4, characterized in that, After determining that the positional relationship meets the sleeper placement requirements, the method further includes: Based on the image to be processed, determine the material characteristics of the sleeper; Based on the material characteristics, it is determined whether the material of the sleeper meets the safety requirements.

6. The outrigger safety detection method according to claim 1, characterized in that, Also includes: Within a preset detection time, each image acquisition module acquires the image to be processed according to a preset frequency; Based on each of the images to be processed corresponding to the target outrigger, it is determined whether the support of the target outrigger poses a risk. If the number of images to be processed that indicate a risk to the support of the target outrigger is determined to be greater than a third preset ratio in all images to be processed acquired by the corresponding image acquisition module, an alarm is triggered.

7. The outrigger safety testing method according to claim 1, characterized in that, Also includes: Save the image to be processed that indicates the target outrigger's support is at risk.

8. A leg safety detection system, characterized in that, include: Camera and processing module; The camera is used to capture an image to be processed. The image to be processed is an image containing a preset area. The preset area is the area included after extending a first preset distance in all directions from the contact point between the target leg and the road surface. The processing module is used to acquire the image to be processed, and based on the image to be processed, determine whether the overall road surface type of the preset area belongs to the target road surface type. If the overall road surface type belongs to the target road surface type, and based on the image to be processed, determine whether there are sleepers in the preset area, and if there are no sleepers in the preset area, determine that the support of the target outrigger is at risk. If there are sleepers in the preset area, based on the image to be processed, determine whether the positional relationship between the sleepers and the target outrigger meets the sleeper placement requirements, and if it does not meet the sleeper placement requirements, determine that the support of the target outrigger is at risk. The target road surface type includes all road surface types that require sleepers to support the target outrigger.

9. A working machine, comprising a main body and outriggers, wherein the main body operates under the support of the outriggers, characterized in that, The operating machinery also includes the outrigger safety detection system as described in claim 8.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the outrigger safety detection method as described in any one of claims 1 to 7.

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