Intelligent detection system for fire hose

Abstract

The invention relates to the technical field of fire hose detection, in particular to an intelligent detection system for a fire hose, the intelligent detection system is provided with a processing module, a contour recognition module, a feature extraction module and a defect analysis module, the fire hose is preprocessed through a heating extrusion unit, and defect detection is performed on the fire hose through an execution unit; a contour image is acquired through an image acquisition unit, a contour representation value of each sub-region is determined through an identification unit so as to screen feature sub-regions, contour feature points are determined through a contour tendency coefficient of a feature extraction module, and fluorescence labeling is performed on the contour feature points. And the defect analysis module determines the comparison condition of the collapse characterization vectors before and after the local defect detection to judge whether the fire hose has the defect, so that the region with the knitting angle difference in the hose can be quickly identified, the adaptive adjustment detection mode of the region with the difference is realized, and the detection reliability of the fire hose is improved.

Description

Technical Field

[0001] The invention relates to the technical field of fire hose detection, and in particular to an intelligent detection system for fire hoses. Background Art

[0002] Fire hose is a key equipment in firefighting operations. Its quality is directly related to the firefighting effect and the life safety of firefighters. During the firefighting process, the fire hose needs to withstand the impact of high-pressure water flow and various tensile forces that may be encountered during laying and use. Its quality and performance must comply with national and industry-related standards and regulations. However, in actual application scenarios, the weaving angles of the hoses will vary. The difference in weaving angles makes the internal fiber arrangement structure of the hoses different, and the degree of resistance to tensile force is also different. The traditional fire hose detection method is relatively single and fixed, and cannot keenly capture the differences in weaving angles in the hoses, and cannot flexibly and accurately make adaptive adjustments to the detection method. Therefore, improving the reliability of fire hose detection is a technical problem that needs to be solved urgently.

[0003] For example, the Chinese patent authorization announcement number is: CN118067525B, which discloses a fire hose tensile strength detection device for fire detection, which relates to the field of fire hose detection technology, including a mounting frame, and also includes: a moving mechanism, which is installed on the mounting frame; a water filling mechanism, which is installed below the moving mechanism, and the water filling mechanism includes two piston water tanks installed in a mirror-like manner; a connecting mechanism, which is installed on the top of the moving mechanism; an anti-residue mechanism, which is installed on the mounting frame; a driving mechanism, which is installed on one side of the anti-residue mechanism, and a detection mechanism, which is installed on the anti-residue mechanism; the mounting frame includes two connecting plates, and a U-shaped mounting frame is fixed on the top of the two connecting plates to perform water pressure test and tensile test on the fire hose at the same time.

[0004] The prior art still has the following problems:

[0005] The existing technology does not take into account that the braiding angles of fire hoses will be different in actual application scenarios, resulting in different hoses' ability to withstand tension. The existing technology cannot quickly identify areas in the hose where there are differences in braiding angles, and cannot adaptively adjust the detection method for areas with differences, affecting the reliability of fire hose detection. Summary of the invention

[0006] To this end, the present invention provides an intelligent detection system for fire hoses to overcome the problems that the prior art cannot quickly identify areas with different weaving angles in the hose and cannot adaptively adjust the detection method to the areas with differences, thus affecting the reliability of fire hose detection.

[0007] To achieve the above object, the present invention provides an intelligent detection system for a fire hose, comprising:

[0008] A processing module, which includes a heating and extrusion unit for preprocessing the fire hose and an execution unit for detecting defects of the fire hose;

[0009] Wherein, the preprocessing includes preheating and pre-extrusion;

[0010] A contour recognition module, which is connected to the processing module and includes an image acquisition unit and a recognition unit. The image acquisition unit is used to acquire the contour images of several sub-regions on the fire hose after preprocessing;

[0011] The recognition unit is used to determine the contour characterization value of each sub-region according to the contour image, and screen the characteristic sub-regions based on the comparison of the contour characterization values;

[0012] A feature extraction module, which is respectively connected to the processing module and the contour recognition module, and is used to identify the contour edges of the characteristic sub-regions in the length direction of the fire hose, determine the contour feature points according to the contour tendency coefficients of several points on the contour edges, and perform fluorescent marking on the contour feature points;

[0013] Wherein, the contour edge includes a first contour edge and a second contour edge;

[0014] A defect analysis module, which is respectively connected to the processing module and the feature acquisition module, and is used to control the execution unit to perform local defect detection on the characteristic sub-regions, determine the collapse characterization vectors of each contour feature point, and judge whether there are defects in the fire hose according to the comparison of the collapse characterization vectors of the contour feature points on the first contour edge and the collapse characterization vectors of the contour feature points on the second contour edge.

[0015] Further, the recognition unit is used to determine the contour characterization value of each sub-region, wherein,

[0016] The recognition unit acquires the width value of the contour image in the width direction of the fire hose, calculates the difference between the maximum width value and the minimum width value in the sub-region, and determines the difference as the contour characterization value of the sub-region.

[0017] Further, the recognition unit is also used to screen the characteristic sub-regions, wherein,

[0018] If the contour characterization value of the sub-region meets the characteristic contour determination condition, the sub-region is screened as a characteristic sub-region;

[0019] The characteristic contour determination condition is that the contour characterization value exceeds a preset contour characterization reference value.

[0020] Furthermore, the feature extraction module is used to determine the contour tendency coefficients of several points on the contour edge, where

[0021] the feature extraction module obtains any point other than the endpoints and two adjacent points of the point on the contour edge, and determines the included angle formed by the tangent directions of the two adjacent points, and determines the included angle as the contour tendency coefficient of the point.

[0022] Furthermore, the feature extraction module is also used to determine the contour feature points, where

[0023] the feature extraction module obtains the contour tendency coefficients corresponding to several points in the feature sub-region;

[0024] if the contour tendency coefficient meets the contour mutation condition, the feature extraction module determines the point corresponding to the contour tendency coefficient as the contour feature point;

[0025] the contour mutation condition is that the contour tendency coefficient exceeds a preset contour tendency threshold.

[0026] Furthermore, the defect analysis module is used to determine the collapse characterization vector, where

[0027] the defect analysis module is used to obtain the positions of the contour feature points before and after the local defect detection respectively;

[0028] Taking the position of the contour feature point after the local defect detection as the vector starting point and the position of the contour feature point before the local defect detection as the vector end point to construct a vector, and determining the vector as the collapse characterization vector of the contour feature point.

[0029] Furthermore, the defect analysis module is used to determine the first characterization vector and the second characterization vector, where

[0030] the contour edge is the edge contour of the feature sub-region in the length direction of the fire hose, and the contour edges of each feature sub-region include the first contour edge and the second contour edge;

[0031] the defect analysis module is used to determine the vector sum of the collapse characterization vectors of each contour feature point on the first contour edge as the first characterization vector;

[0032] Determine the vector sum of the collapse characterization vectors of each contour feature point on the second contour edge as the second characterization vector.

[0033] Furthermore, the defect analysis module is used to determine the first characterization parameter, where

[0034] The defect analysis module constructs a reference unit vector along the length direction of the fire hose, calculates the vector angle between the first characterization vector and the reference unit vector, and determines the vector angle as the first characterization parameter.

[0035] Further, the defect analysis module is used to determine a second characterization parameter, where

[0036] The defect analysis module calculates the vector angle between the second characterization vector and the reference unit vector, and determines the vector angle as the second characterization parameter.

[0037] Further, the defect analysis module is also used to determine whether there is a defect in the fire hose, where

[0038] If the first characterization parameter and the second characterization parameter in the characteristic sub-region do not meet the normal conditions of the hose, the defect analysis module determines that there is a defect in the fire hose;

[0039] The normal conditions of the hose are that the difference between the first characterization parameter and the second characterization parameter does not exceed a preset difference threshold.

[0040] Compared with the prior art, the beneficial effects of the present invention are as follows. The present invention sets a processing module, a contour recognition module, a feature extraction module, and a defect analysis module. The fire hose is pre-heated and pre-extruded by a heating and extrusion unit, the fire hose is defect-detected by an execution unit, the contour images of several sub-regions on the fire hose after pre-heating and pre-extrusion are obtained by an image acquisition unit, the contour characterization values of each sub-region are determined by an identification unit according to the contour images, and the characteristic sub-regions are screened based on the comparison of the contour characterization values. The contour edges of the characteristic sub-regions are identified by the feature extraction module, the contour feature points are determined according to the contour tendency coefficients of several points on the contour edges, and the contour feature points are fluorescently marked. The defect analysis module performs local defect detection on the characteristic sub-regions, and determines whether there is a defect in the fire hose according to the vector angle between the collapse characterization vectors of the first contour edge and the second contour edge. Furthermore, the region with a difference in the weaving angle in the hose is quickly identified, the detection method is adaptively adjusted for the different regions, and the reliability of the fire hose detection is improved.

[0041] In particular, the present invention pre-heats and pre-extrudes the fire hose through the processing module. It can be understood that for the sub-regions with different weaving angles, their performance changes after pre-heating will form a contrast with other sub-regions. The performance change amount can be amplified through pre-extrusion, enabling the detector to more intuitively obtain the sub-regions with different weaving angles in the hose, helping the detector accurately locate the problem sub-regions. The present invention pre-heats and pre-extrudes the fire hose through the processing module, and further, the region with a difference in the weaving angle in the hose is quickly identified, and the reliability of the fire hose detection is improved.

[0042] In particular, in the present invention, the recognition unit screens the characteristic sub-regions based on the comparison of the contour characterization values. It can be understood that by calculating the difference between the maximum and minimum values of the sub-region width values as the contour characterization value, and screening the characteristic sub-regions according to the average value comparison, it is possible to capture the local deformation anomalies caused by factors such as the difference in the weaving angle of the water hose. After preheating and pre-extrusion, the width change in the region with a special weaving angle may be different from that in other regions, and its contour characterization value will deviate significantly from the average value, so it can be accurately positioned as a characteristic sub-region, helping the inspectors quickly lock the potential quality hazards of the water hose. Screening the characteristic sub-regions from a large number of sub-regions can make the subsequent detection work more targeted. Compared with the comprehensive and undifferentiated detection of the entire water hose, concentrating on studying these characteristic sub-regions can greatly improve the detection efficiency, and at the same time, more deeply analyze the impact of these key regions on the overall performance of the water hose, avoiding ignoring local important problems due to the overly large detection range. In the present invention, the recognition unit screens the characteristic sub-regions based on the comparison of the contour characterization values, and furthermore, it realizes the rapid identification of the regions with different weaving angles in the water hose, improving the reliability of the fire hose detection.

[0043] In particular, in the present invention, the feature extraction module determines the contour feature points according to the contour tendency coefficients of several points on the contour edge and performs fluorescence marking on the contour feature points. It can be understood that by calculating the contour tendency coefficients to determine the contour feature points, it is possible to accurately find the positions where the contour changes violently in the characteristic sub-regions, and these positions correspond to the regions where the weaving angles of the water hose are different. Fluorescence marking these key parts enables the inspectors to visually observe the problem regions of the water hose, facilitating more detailed analysis in the follow-up. The contour tendency coefficient provides a quantitative standard for the determination of the contour feature points. By setting the contour tendency threshold, it is possible to accurately screen out the points with significant contour changes according to the specific water hose detection requirements. This quantitative analysis method makes the detection results more objective and reliable, which is conducive to improving the accuracy and repeatability of the detection. Furthermore, it realizes the rapid identification of the regions with different weaving angles in the water hose, improving the reliability of the fire hose detection.

[0044] In particular, the present invention determines whether there are defects in the fire hose through the defect analysis module based on the collapse characterization vectors of the first contour edge and the second contour edge. It can be understood that by analyzing the position changes of the contour feature points before and after local defect detection to construct the collapse characterization vectors, the deformation of the feature sub-region during the defect detection process can be accurately reflected. Since it is a local analysis of the feature sub-region, the specific area where defects may exist can be accurately located, avoiding the blindness of comprehensively detecting the entire fire hose, improving the accuracy and efficiency of detection. Calculate the vector sum of the collapse characterization vectors of each contour feature point on the first contour edge and the second contour edge, and use the included angle between it and the reference unit vector as the characterization parameter, converting the determination of defects into a quantifiable numerical analysis, making the detection results more objective and reliable, reducing the subjectivity and error of human judgment. The present invention determines whether there are defects in the fire hose through the defect analysis module based on the collapse characterization vectors of the first contour edge and the second contour edge. Furthermore, it realizes the rapid identification of the area with different braiding angles in the hose, adaptively adjusts the detection method for the different areas, and improves the reliability of fire hose detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 is the functional block diagram of the intelligent detection system for fire hoses according to an embodiment of the present invention;

[0046] Figure 2 is the logical flowchart of the identification unit for screening feature sub-regions according to an embodiment of the present invention;

[0047] Figure 3 is the logical flowchart of the feature extraction module for determining contour feature points according to an embodiment of the present invention;

[0048] Figure 4 is the logical flowchart of the defect analysis module for determining whether there are defects in the fire hose according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0049] In order to make the objectives and advantages of the present invention clearer, the present invention will be further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0050] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are only used to explain the technical principles of the present invention and do not limit the protection scope of the present invention.

[0051] It should be noted that in the description of the present invention, the terms indicating the direction or positional relationship such as "upper", "lower", "inner", "outer", etc. are based on the direction or positional relationship shown in the drawings. This is only for convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as a limitation to the present invention.

[0052] In addition, it should also be noted that in the description of the present invention, unless otherwise clearly specified and defined, the terms "installation" and "connection" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, and it can be the communication inside two elements. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0053] Please refer to Figure 1 As shown, it is a functional block diagram of the intelligent detection system for fire hoses according to an embodiment of the present invention. An intelligent detection system for fire hoses of the present invention includes:

[0054] A processing module, which includes a heating and extrusion unit for preprocessing the fire hose and an execution unit for defect detection of the fire hose;

[0055] Among them, the preprocessing includes preheating and pre-extrusion;

[0056] Specifically, please refer to Table 1. The heating temperature, extrusion force, and moving speed of the hot press roller for preheating and pre-extruding the fire hose can be set by those skilled in the art according to several historical experimental data. Preferably, according to the experimental data in Table 1, the heating temperature can be set to 60 °C, the extrusion force can be set to 100 N, and the moving speed of the hot press roller can be set to 6 mm / s, so as to obtain a fire hose that is convenient for subsequent profile analysis during the detection process.

[0057] Table 1

[0058]

[0059]

[0060] Specifically, the present invention does not limit the specific structure of the heating and extrusion unit. Preferably, it can be a hot press roller. Two relatively arranged hot press rollers are adopted. A heating element, such as a resistance wire, is arranged inside one of the hot press rollers, and the surface of the hot press roller reaches the set temperature through heating. The other hot press roller can be an ordinary pressure roller. The two hot press rollers rotate towards each other through the drive of a motor and a gear to realize preheating and pre-extrusion of the fire hose, which will not be elaborated here.

[0061] Specifically, the present invention does not limit the specific structure of the execution unit. Preferably, it can be a lead screw drive stretching mechanism. Two lead screws are respectively located on both sides of the fire hose. One end of the lead screw is connected to the output shaft of the motor through a coupling, and the other end is installed on a fixed bracket. A slider is installed on the lead screw, and the slider is fixed to both ends of the fire hose through a fixture. When the motor drives the lead screw to rotate, the slider moves on the lead screw, thereby stretching the fire hose to realize the defect detection of the fire hose. By controlling the rotation speed and the number of rotation turns of the motor, the stretching speed and length can be accurately controlled, which will not be elaborated here.

[0062] Specifically, the present invention pre-heats and pre-extrudes the fire hose through a processing module. It can be understood that for sub-regions with different weaving angles, their performance changes after pre-heating will form a contrast with other sub-regions. Through pre-extrusion, this performance change amount can be amplified, enabling the inspectors to more intuitively obtain the sub-regions of the hose with different weaving angles, helping the inspectors accurately locate the problem sub-regions. The present invention pre-heats and pre-extrudes the fire hose through a processing module, and further, realizes the rapid identification of the regions in the hose with different weaving angles, improving the reliability of fire hose detection.

[0063] Specifically, for sub-regions with different weaving angles, their thermal expansion and deformation behaviors after being squeezed are different. When heating, due to the different fiber arrangement directions, the region with a larger weaving angle has more obvious thermal expansion and a larger width change, while the region with a smaller weaving angle has relatively smaller thermal expansion. Heating and squeezing the fire hose can amplify the subtle differences caused by different weaving angles, making them easier to detect. The present invention pre-heats and pre-extrudes the fire hose through a processing module, and further, realizes the rapid identification of the regions in the hose with different weaving angles, improving the reliability of fire hose detection.

[0064] A contour recognition module, which is connected to the processing module, includes an image acquisition unit and a recognition unit. The image acquisition unit is used to acquire the contour images of several sub-regions on the fire hose after preprocessing;

[0065] Specifically, the interval distance between several sub-regions on the fire hose can be set by those skilled in the art according to the detection accuracy requirements of the fire hose. The higher the accuracy requirement, the smaller the set interval distance. The preferred interval distance can be 20 cm.

[0066] The recognition unit is used to determine the contour characterization values of each sub-region according to the contour images, and screen out the characteristic sub-regions based on the comparison of the contour characterization values;

[0067] Specifically, the present invention does not limit the specific structure of the image acquisition unit. Preferably, it can be an industrial camera for acquiring the contour images of several sub-regions on the fire hose, which will not be elaborated here.

[0068] Specifically, the present invention does not limit the specific structure of the recognition unit. Preferably, it can be an image processor. The image processor uses an edge algorithm to determine the contour characterization values of each sub-region, and filters out the characteristic sub-regions based on the comparison of the contour characterization values, which will not be elaborated here.

[0069] A feature extraction module, which is respectively connected to the processing module and the contour recognition module, is used to identify the contour edges of the characteristic sub-region in the length direction of the fire hose, determine the contour feature points according to the contour tendency coefficients of several points on the contour edge, and perform fluorescent marking on the contour feature points;

[0070] Among them, the contour edge includes a first contour edge and a second contour edge;

[0071] Specifically, the present invention does not limit the specific structure of the feature extraction module. Preferably, it can be a processor used in a computer, which is used to identify the contour edges of the characteristic sub-region in the length direction of the fire hose, determine the contour feature points according to the contour tendency coefficients of several points on the contour edge, and control a micro-sprinkler head to apply a fluorescent substance to the contour feature points through the processor. The fluorescent substance is selected as an erasable fluorescent component, which can be a fluorescent polymer containing redox groups such as disulfide bonds, and the fluorescence is erased by using the redox property without affecting the subsequent use of the fire hose, which will not be elaborated here.

[0072] A defect analysis module, which is respectively connected to the processing module and the feature acquisition module, is used to control the execution unit to perform local defect detection on the characteristic sub-region, determine the collapse characterization vectors of each contour feature point, and determine whether there are defects in the fire hose according to the comparison of the collapse characterization vectors of the contour feature points on the first contour edge and the collapse characterization vectors of the contour feature points on the second contour edge.

[0073] Specifically, the present invention does not limit the specific structure of the defect analysis module. Preferably, it can be a microprocessor, which is used to control the execution unit to perform local defect detection on the characteristic sub-region, determine the collapse characterization vectors, and determine whether there are defects in the fire hose, which will not be elaborated here.

[0074] Specifically, the recognition unit is used to determine the contour characterization values of each sub-region, where,

[0075] The recognition unit obtains the width value of the contour image in the width direction of the fire hose, calculates the difference between the maximum width value and the minimum width value in the sub-region, and determines the difference as the contour characterization value of the sub-region.

[0076] Exemplarily, a specific method for determining the contour characterization value of a sub-region is given here. The width values obtained in the width direction of the fire hose are 44.2 mm, 46.8 mm, 48 mm, 45.1 mm, 50.2 mm, 47 mm, 46.7 mm, 49.1 mm, 45 mm, and 47 mm respectively. The maximum width value in the sub-region is 50.2 mm, the minimum width value in the sub-region is 44.2 mm, and the difference is 6 mm. Therefore, the contour characterization value of the sub-region is 6 mm.

[0077] Specifically, please refer to Figure 2 As shown, it is the logic flowchart of the recognition unit for screening characteristic sub-regions in the embodiment of the present invention. The recognition unit is also used to screen characteristic sub-regions, where

[0078] If the contour characterization value of the sub-region meets the characteristic contour determination condition, the sub-region is screened as a characteristic sub-region;

[0079] If the contour characterization value of the sub-region does not meet the characteristic contour determination condition, the sub-region is not screened;

[0080] The characteristic contour determination condition is that the contour characterization value exceeds a preset contour characterization reference value.

[0081] Specifically, the preset contour characterization reference value can be set by those skilled in the art according to the average value of the contour characterization values of several sub-regions. The contour characterization reference value is the product of the average value and the contour characterization factor. The value range of the contour characterization factor can be [0.8, 0.9]. Preferably, the contour characterization factor can be 0.85.

[0082] Specifically, in the present invention, the recognition unit screens the characteristic sub-regions based on the comparison of the contour characterization values. It can be understood that by calculating the difference between the maximum and minimum values of the sub-region width values as the contour characterization value and screening the characteristic sub-regions according to the average value comparison, the local deformation anomalies caused by factors such as the difference in the weaving angle of the water hose can be captured. After preheating and pre-extrusion, the width change of the region with a special weaving angle may be different from that of other regions, and its contour characterization value will deviate significantly from the average value, so it can be accurately positioned as a characteristic sub-region, helping the inspectors quickly lock the potential quality hazards of the water hose. Screening the characteristic sub-regions from a large number of sub-regions can make the subsequent detection work more targeted. Compared with the comprehensive and undifferentiated detection of the entire water hose, concentrating on studying these characteristic sub-regions can greatly improve the detection efficiency. At the same time, it can more deeply analyze the influence of these key regions on the overall performance of the water hose and avoid ignoring important local problems due to the too large detection range. In the present invention, the recognition unit screens the characteristic sub-regions based on the comparison of the contour characterization values. Furthermore, it realizes the rapid identification of the regions with different weaving angles in the water hose and improves the reliability of the fire hose detection.

[0083] Specifically, different weaving angles of the water hose will result in differences in its structure. During the preheating and pre-extrusion processes, this structural difference will cause different deformation situations in each sub-region of the water hose. The contour characterization value can quantify this degree of deformation by calculating the difference between the maximum and minimum values of the width values of the sub-region in the width direction of the fire hose. For regions with different weaving angles, due to different fiber arrangements and stress modes, their width change laws are also different, so the contour characterization values will be different, and thus the difference in the internal structure of the water hose can be reflected by this value. Under normal circumstances, for the region with a uniform water hose structure, after preheating and pre-extrusion, its width change is relatively stable and consistent, and the contour characterization value will also fluctuate within a certain range. When the contour characterization value of a certain sub-region exceeds the average value of several contour characterization values to a large extent, it indicates that the width change of this region exceeds the normal range and there is a problem with the weaving angle anomaly. Setting the characteristic contour determination condition by calculating the average value is a method based on statistical laws. Among a large number of sub-regions, the contour characterization values of normal sub-regions will be distributed around the average value, while for the sub-regions with anomalies, their contour characterization values will deviate from the average value. Using this statistical characteristic, the characteristic sub-regions that are different from most sub-regions can be screened out, so as to effectively identify the problematic regions in the water hose. Furthermore, it realizes the rapid identification of the regions with different weaving angles in the water hose and improves the reliability of the fire hose detection.

[0084] Specifically, the feature extraction module is used to determine the contour tendency coefficients of several points on the contour edge, where

[0085] The feature extraction module obtains any point other than the endpoint on the contour edge and two adjacent points of the point, and determines the included angle formed by the tangent directions of the two adjacent points, and determines the included angle as the contour tendency coefficient of the point.

[0086] Specifically, please refer to Figure 3 As shown, it is a logic flowchart for the feature extraction module of the embodiment of the present invention to determine the contour feature points. The feature extraction module is also used to determine the contour feature points, wherein,

[0087] The feature extraction module obtains the contour tendency coefficients corresponding to several points in the feature sub-region;

[0088] If the contour tendency coefficient meets the contour mutation condition, the feature extraction module determines the point corresponding to the contour tendency coefficient as the contour feature point;

[0089] If the contour tendency coefficient does not meet the contour mutation condition, the feature extraction module does not screen the point corresponding to the contour tendency coefficient;

[0090] The contour mutation condition is that the contour tendency coefficient exceeds a preset contour tendency threshold.

[0091] Specifically, the preset contour tendency threshold can be set by those skilled in the art according to the detection accuracy requirements of the fire hose. The higher the accuracy requirement, the smaller the preset contour tendency threshold. The value range of the preset contour tendency threshold can be [15, 30], and the interval unit is °. Preferably, the contour tendency threshold can be 20°.

[0092] Specifically, the present invention determines the contour feature points according to the contour tendency coefficients of several points on the contour edge through the feature extraction module, and performs fluorescence marking on the contour feature points. It can be understood that by calculating the contour tendency coefficients to determine the contour feature points, the positions where the contour changes violently in the feature sub-region can be accurately found. These positions correspond to the regions where the weaving angles of the hose are different. Fluorescence marking these key parts enables the inspectors to visually observe the problem areas of the hose, facilitating more detailed analysis later. The contour tendency coefficient provides a quantitative standard for the determination of contour feature points. By setting the contour tendency threshold, the points with significant contour changes can be accurately screened according to the specific hose detection requirements. This quantitative analysis method makes the detection results more objective and reliable, which is conducive to improving the accuracy and repeatability of the detection. Furthermore, it realizes the rapid identification of the regions with different weaving angles in the hose, improving the reliability of the fire hose detection.

[0093] Specifically, the contour tendency coefficient is determined by calculating the angle between a point on the contour edge and the tangent directions of its two adjacent points. The magnitude of the angle can intuitively reflect the degree of change of the contour at that point. Where the contour changes gently, the tangent directions of adjacent points are relatively close, the angle is small, and the contour tendency coefficient is also small. While where the contour undergoes sudden changes or has a large bending degree, the difference in the tangent directions of adjacent points is large, the angle is large, and the contour tendency coefficient is also large. Therefore, the contour tendency coefficient can be used as a quantitative index to measure whether there is a sudden change in the change amount of the water hose width, thereby helping to determine the contour feature points. The present invention determines the contour feature points according to the contour tendency coefficients of several points on the contour edge through the feature extraction module. Furthermore, the region with different braiding angles in the water hose is quickly identified, improving the reliability of fire hose detection.

[0094] Specifically, the defect analysis module is used to determine the collapse characterization vectors of each contour feature point of the fluorescence marker before and after local defect detection, where

[0095] the defect analysis module is used to respectively obtain the positions of the contour feature points before and after local defect detection;

[0096] Taking the position of the contour feature point after local defect detection as the vector starting point and the position of the contour feature point before local defect detection as the vector ending point to construct a vector, and determining the vector as the collapse characterization vector of the contour feature point.

[0097] Specifically, the defect analysis module is used to determine the first characterization vector and the second characterization vector, where

[0098] the contour edge is the edge contour of the feature sub-region in the length direction of the fire hose, and the contour edges of each feature sub-region include a first contour edge and a second contour edge;

[0099] the defect analysis module is used to determine the vector sum of the collapse characterization vectors of each contour feature point on the first contour edge as the first characterization vector;

[0100] Determine the vector sum of the collapse characterization vectors of each contour feature point on the second contour edge as the second characterization vector.

[0101] Specifically, taking the vector starting point of any collapse characterization vector on the first contour edge as the vector starting point of the first characterization vector and the vector starting point of any collapse characterization vector on the second contour edge as the vector starting point of the second characterization vector.

[0102] Specifically, the defect analysis module is used to determine the first characterization parameter, where

[0103] The defect analysis module constructs a reference unit vector along the length direction of the fire hose, calculates the vector angle between the first characterization vector and the reference unit vector, and determines the vector angle as the first characterization parameter.

[0104] Specifically, the defect analysis module is used to determine a second characterization parameter, where

[0105] the defect analysis module calculates the vector angle between the second characterization vector and the reference unit vector, and determines the vector angle as the second characterization parameter.

[0106] Specifically, please refer to Figure 4 as shown, which is a logic flowchart for the defect analysis module of the embodiment of the present invention to determine whether there is a defect in the fire hose. The defect analysis module is also used to determine whether there is a defect in the fire hose, where

[0107] If the first characterization parameter and the second characterization parameter in the characteristic sub-region do not meet the normal conditions of the hose, the defect analysis module determines that there is a defect in the fire hose;

[0108] If the first characterization parameter and the second characterization parameter in the characteristic sub-region meet the normal conditions of the hose, the defect analysis module determines that there is no defect in the fire hose;

[0109] The normal conditions of the hose are that the difference between the first characterization parameter and the second characterization parameter does not exceed a preset difference threshold.

[0110] Specifically, the preset difference threshold can be set by those skilled in the art according to the detection accuracy requirements of the fire hose. The higher the accuracy requirement, the smaller the preset difference threshold. The value range of the difference threshold can be [2, 5], and the interval unit is °. Preferably, the difference threshold can be 3°.

[0111] Specifically, in the present invention, the defect analysis module determines whether there is a defect in the fire hose according to the comparison of the first contour edge and the collapse characterization vector of the second contour edge. It can be understood that by analyzing the position change of the contour feature points before and after local defect detection to construct the collapse characterization vector, the deformation of the feature sub-region during the defect detection process can be accurately reflected. Since it is a local analysis of the feature sub-region, the specific area where a defect may exist can be accurately located, avoiding the blindness of comprehensively detecting the entire fire hose, improving the accuracy and efficiency of detection. Calculate the vector sum of the collapse characterization vectors of each contour feature point on the first contour edge and the second contour edge, and use the included angle between it and the reference unit vector as the characterization parameter, converting the determination of the defect into a quantifiable numerical analysis, making the detection result more objective and reliable, reducing the subjectivity and error of human judgment. The present invention determines whether there is a defect in the fire hose according to the comparison of the first contour edge and the collapse characterization vector of the second contour edge. Furthermore, it realizes the rapid identification of the area with different braiding angles in the hose, adaptively adjusts the detection method for the different area, and improves the reliability of the fire hose detection.

[0112] Specifically, it can be understood that the collapse characterization vector is constructed based on the position change of the contour feature points before and after local defect detection. During the defect detection process, by converting these position changes into vectors, the local deformation can be quantitatively described. Calculating the vector sum of the collapse characterization vectors of each contour feature point on the first contour edge and the second contour edge can comprehensively integrate the deformation information of all contour feature points on this edge. The vector sum represents the overall deformation trend and degree of the same edge during the defect detection process. If the stretching effect of the feature sub-region is uniform, the vector sums corresponding to the first contour edge and the second contour edge should have similar characteristics. Construct a reference unit vector along the length direction of the fire hose, and calculate the vector included angles between the first characterization vector and the second characterization vector and this reference unit vector respectively. This included angle reflects the deformation direction of the edge relative to the length direction of the hose during the defect detection process. Under normal conditions of the fire hose, the deformation directions of the first contour edge and the second contour edge should be relatively consistent, that is, the difference between the two vector included angles is small. If there is a defect, the deformation of the defective part will cause the deformation direction of the edge to change, making the difference between the two vector included angles exceed the normal range. Furthermore, it realizes the rapid identification of the area with different braiding angles in the hose, adaptively adjusts the detection method for the different area, and improves the reliability of the fire hose detection.

[0113] So far, the technical solution of the present invention has been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0114] The above are only the preferred embodiments of the present invention and are not used to limit the present invention. For those skilled in the art, the present invention can have various changes and modifications. Any modification, equivalent substitution, improvement, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. An intelligent detection system for fire hoses, characterized in that: include: A processing module, comprising a heating and extruding unit for pre-processing a fire hose, and an execution unit for performing defect detection on the fire hose; Wherein, the pretreatment includes preheating and pre-extrusion; A contour recognition module, which is connected to the processing module and includes an image acquisition unit and a recognition unit, wherein the image acquisition unit is used to acquire contour images of several sub-areas on the fire hose that have completed the preprocessing; The recognition unit is used to determine the contour characterization value of each sub-region according to the contour image, and to select the characteristic sub-region based on the comparison of the contour characterization value; A feature extraction module, which is connected to the processing module and the contour recognition module respectively, and is used to identify the contour edge of the feature sub-region in the length direction of the fire hose, determine the contour feature points according to the contour tendency coefficients of several points on the contour edge, and perform fluorescent marking on the contour feature points; Wherein, the contour edge includes a first contour edge and a second contour edge; A defect analysis module, which is respectively connected to the processing module and the feature acquisition module, is used to control the execution unit to perform local defect detection on the feature sub-area and determine the collapse characterization vector of each contour feature point, and determine whether the fire hose has defects based on the comparison between the collapse characterization vector of the contour feature point on the first contour edge and the collapse characterization vector of the contour feature point on the second contour edge.

2. The intelligent detection system for fire hose according to claim 1, characterized in that: The recognition unit is used to determine the contour characterization value of each sub-region, wherein: The recognition unit obtains the width value of the contour image in the width direction of the fire hose, calculates the difference between the maximum width value and the minimum width value in the sub-area, and determines the difference as the contour characterization value of the sub-area.

3. The intelligent detection system for fire hose according to claim 2, characterized in that: The recognition unit is also used to screen characteristic sub-regions, wherein: If the contour representation value of the sub-region meets the characteristic contour determination condition, the sub-region is screened as a characteristic sub-region; The characteristic profile determination condition is that the profile characterization value exceeds a preset profile characterization reference value.

4. The intelligent detection system for fire hose according to claim 3, characterized in that: The feature extraction module is used to determine the contour tendency coefficients of several points on the contour edge, where: The feature extraction module obtains any point other than the endpoint and two adjacent points of the point on the contour edge, determines the angle formed by the tangent directions of the two adjacent points, and determines the angle as the contour inclination coefficient of the point.

5. The intelligent detection system for fire hoses according to claim 4, characterized in that: The feature extraction module is also used to determine contour feature points, wherein: The feature extraction module obtains contour tendency coefficients corresponding to a number of points in the feature sub-area; If the contour tendency coefficient meets the contour mutation condition, the feature extraction module determines the point corresponding to the contour tendency coefficient as a contour feature point; The profile mutation condition is that the profile tendency coefficient exceeds a preset profile tendency threshold.

6. The intelligent detection system for fire hoses according to claim 5, characterized in that: The defect analysis module is used to determine the collapse characterization vector, wherein: The defect analysis module is used to respectively obtain the positions of the contour feature points before and after the local defect detection; A vector is constructed with the position of the contour feature point after local defect detection as the starting point of the vector and the position of the contour feature point before local defect detection as the end point of the vector, and the vector is determined as the collapse characterization vector of the contour feature point.

7. The intelligent detection system for fire hoses according to claim 6, characterized in that: The defect analysis module is used to determine a first characterization vector and a second characterization vector, wherein: The contour edge is the edge contour of the characteristic sub-region in the length direction of the fire hose, and the contour edge of each characteristic sub-region includes a first contour edge and a second contour edge; The defect analysis module is used to determine the vector sum of the collapse characterization vectors of each contour feature point on the first contour edge as the first characterization vector; The vector sum of the collapse characterization vectors of each contour feature point on the second contour edge is determined as the second characterization vector.

8. The intelligent detection system for fire hoses according to claim 7, characterized in that: The defect analysis module is used to determine a first characterization parameter, wherein: The defect analysis module constructs a reference unit vector along the length direction of the fire hose, calculates a vector angle between a first characterization vector and the reference unit vector, and determines the vector angle as a first characterization parameter.

9. The intelligent detection system for fire hoses according to claim 8, characterized in that: The defect analysis module is used to determine a second characterization parameter, wherein: The defect analysis module calculates a vector angle between a second characterization vector and the reference unit vector, and determines the vector angle as a second characterization parameter.

10. The intelligent detection system for fire hoses according to claim 9, characterized in that: The defect analysis module is also used to determine whether the fire hose has defects, wherein: If the first characterization parameter and the second characterization parameter in the characteristic sub-region do not meet the normal conditions of the fire hose, the defect analysis module determines that the fire hose has defects; The normal condition of the water hose is that the difference between the first characterization parameter and the second characterization parameter does not exceed a preset difference threshold.

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