Intelligent detection system for wire breakage of elevator steel wire rope

Abstract

The invention relates to the technical field of elevator safety monitoring, in particular to an intelligent detection system for wire breakage of an elevator steel wire rope, and the system comprises a data collection module which is used for obtaining real-time operation data of an elevator at a preset collection frequency; the prior judgment module is used for determining a judgment time interval and a corresponding operation condition category according to the real-time operation direction, the actual load and the floor stopping information; the frame selection module is used for selecting key picture frames from the judgment time interval; the steel wire rope form analysis module is used for detecting fracture characteristics of the steel wire rope in the first picture area and the second picture area covered by the multiple cameras; and the adjusting module is used for calculating an adjusting value according to the fracture characteristic quantity and dynamically correcting the acquisition frequency. Through real-time acquisition, working condition judgment, multi-area image analysis and dynamic frequency adjustment, comprehensive, accurate and continuous monitoring of wire breakage of the elevator steel wire rope is achieved, and the reliability and early warning capacity of wire breakage detection are effectively improved.

Description

Technical Field

[0001] This invention relates to the field of elevator safety monitoring technology, and in particular to an intelligent detection system for broken wires in elevator steel wire ropes. Background Technology

[0002] Elevators, as frequently used vertical transportation equipment in urban buildings, are directly related to the safety of passengers' lives and property. As a critical load-bearing component of elevators, broken wires or abnormal wear in the steel wire rope can severely affect the elevator's operational stability and safety. With the increasing use of high-rise buildings and elevators in cities, real-time monitoring and early warning of steel wire ropes are particularly necessary.

[0003] Currently, safety inspection of elevator wire ropes mainly relies on manual inspection or single-point sensor detection, which has problems such as long inspection cycle, limited coverage, slow response and high risk of missed detection, making it difficult to meet the safety monitoring requirements of modern elevators for real-time, comprehensive and reliable safety monitoring.

[0004] Therefore, developing an intelligent detection system capable of dynamically collecting, comprehensively analyzing, and providing real-time early warning of broken wires in steel wire ropes has become an urgent need for the development of elevator safety monitoring technology.

[0005] Chinese Patent Publication No. CN118205982A discloses an elevator wire rope detection device, including an opening and closing mechanism, an input / output interface, and a sensor assembly. The wire rope detection device is arranged near the wire rope on the counterweight side of the traction sheave or below the car side. The sensor assembly is used to detect the state of the wire rope. The input / output interface is used to communicate with the elevator and receive elevator operating status information, including the car position. The opening and closing mechanism adjusts the distance between the sensor assembly and the wire rope according to the car position, so that interference between the wire rope and the wire rope detection device can be avoided during elevator operation.

[0006] Existing elevator safety monitoring technologies rely on sensor components that are fixed or adjusted with the car position. These can only detect the local condition of the wire rope, making it difficult to achieve continuous and comprehensive wire breakage monitoring. At the same time, since the spacing is adjusted only based on the car position, there is a lag in detection, and abnormalities in the wire rope may be missed or the response may be delayed. Summary of the Invention

[0007] To address this, the present invention provides an intelligent detection system for broken wires in elevator steel wire ropes. This system determines the judgment time interval based on the elevator's running direction and load, selects judgment frames, performs multi-region analysis of broken wire characteristics, and dynamically corrects the acquisition frequency to overcome the problems of missed detection and delayed feedback in existing technologies for elevator steel wire ropes.

[0008] To achieve the above objectives, the present invention provides an intelligent detection system for broken wires in elevator steel wire ropes, comprising: The data acquisition module is used to collect elevator operating data at a preset acquisition frequency; The prior judgment module is used to determine the first judgment time interval based on the real-time running direction, actual load weight and stop information in the running data, and to obtain the corresponding operating condition category of the elevator based on the stop information within the time interval. A frame selection module is used to select a judgment frame in the first judgment time interval according to the operating condition category. The wire rope morphology analysis module is used to update the judgment frame to the current image frame and determine whether there are wire rope breakage features in the current image frame. The adjustment module is used to calculate an adjustment value based on the wire rope breakage characteristics when such characteristics are present, so as to adjust the preset acquisition frequency to a corrected acquisition frequency.

[0009] Furthermore, the prior judgment module includes a running load intensity judgment unit; The load intensity judgment unit is used to obtain the real-time running direction and actual load weight, and to determine the corresponding running load result based on the comparison result of the actual load weight and the load comparison threshold.

[0010] Furthermore, the prior judgment module also includes a stop-floor behavior analysis unit; The stoppage behavior analysis unit is used to obtain the corresponding operating condition category based on the stoppage information within the first judgment time interval when the second operating load result is obtained.

[0011] Furthermore, the stopping behavior analysis unit includes an interval determination subunit and an operating condition determination subunit; An interval determination sub-unit is used to determine the first judgment time interval based on the load comparison threshold, the actual load weight, and the real-time timestamp; The operating condition determination subunit is used to obtain the stop information of the first determination time interval and the comparison result of the stop information and the corresponding preset threshold to obtain the corresponding operating condition category.

[0012] Furthermore, the frame selection module includes a direction-related frame selection unit and a running condition-related frame selection unit; The direction-related frame selection unit is used to select the current image frame at the location associated with the real-time running direction based on the real-time running direction when the first running condition category is obtained. The operating condition associated frame selection unit is used to select the current image frame at the midpoint of the complete start-stop cycle closest to the real-time timestamp within the first judgment time interval when other operating condition categories besides the first operating condition category are obtained.

[0013] Furthermore, the wire rope morphology analysis module includes a fracture identification unit and a re-verification unit; A fracture detection unit is used to determine whether there are wire rope fracture features in the first image region of the current image frame; The re-verification unit is used to obtain adjacent image frames and verify whether the wire rope breakage feature exists in the current image frame when there is no wire rope breakage feature in the first image area.

[0014] Furthermore, the fracture identification unit includes a device quantity statistics unit and a region delineation unit; The device count unit is used to obtain the number of acquisition devices corresponding to the current image frame; The region delineation unit is used to divide the image into the first image region and the second image region based on the number of acquisition devices.

[0015] Furthermore, the re-verification unit includes an adjacent image frame selection subunit and a feature verification subunit; The adjacent image frame selection sub-unit is used to select adjacent image frames when there is no wire rope breakage feature in the first image area; The feature verification subunit is used to determine whether there is a wire rope breakage feature in the second image region of the current image frame based on the adjacent image frames.

[0016] Furthermore, the adjustment module includes an adjustment value calculation unit and an adjustment unit; The adjustment module includes an adjustment value calculation unit and an adjustment unit; The adjustment value calculation unit is used to calculate the adjustment value of the preset acquisition frequency when it is determined that there are characteristics of wire rope breakage. The adjustment unit is used to adjust the preset acquisition frequency to a corrected acquisition frequency according to the adjustment value.

[0017] Furthermore, the adjustment value calculation unit includes a difference calculation subunit and a frequency mapping calculation subunit; The difference calculation subunit is used to calculate the difference in the number of fracture features based on the number of wire rope fracture features in the current image frame and the adjacent image frames; The frequency mapping calculation subunit calculates the adjustment value based on the difference in the number of fracture features.

[0018] Compared with existing technologies, the advantages of this invention are as follows: A data acquisition module acquires elevator operation data at a preset frequency, and a priori judgment module analyzes real-time operating direction, actual load, and stop information to determine the first judgment time interval and corresponding operating condition category. A frame selection module selects judgment frames during critical start-stop cycles and operating states, ensuring that wire rope breakage analysis is implemented during high-risk periods. A wire rope morphology analysis module uses a first image area covered by multiple cameras to judge the main fracture features and verifies the fracture features through a second image area, improving the accuracy and robustness of detection. An adjustment module dynamically calculates adjustment values ​​and corrects the acquisition frequency based on the number of fracture features, achieving real-time response and continuous tracking of fracture features. This invention significantly reduces the missed detection rate of wire rope breaks, shortens the detection response time, and achieves continuous, comprehensive, and accurate monitoring of wire rope breaks. Simultaneously, frame selection and multi-region analysis driven by critical time intervals and operating conditions reduce redundant data acquisition in non-critical states, improving system efficiency. This invention achieves dynamic and intelligent wire rope breakage detection in elevator safety monitoring, enhances early warning capabilities, and provides reliable protection for elevator operation safety.

[0019] Furthermore, by using the load intensity judgment unit to obtain the real-time running direction and actual load, and combining it with the load comparison threshold to determine the running load result, the system can distinguish between high load and low load conditions, providing targeted judgment for subsequent wire breakage detection, improving detection accuracy and reducing false alarms.

[0020] Furthermore, by analyzing the stopping information within the first judgment time interval under low-load operation by the stopping behavior analysis unit, the operating condition category is obtained, which realizes the accurate capture of the car's intermittent stopping behavior, provides an effective reference for frame selection and wire breakage identification, and improves the system's adaptability. Attached Figure Description

[0021] Figure 1 This is a schematic diagram of the intelligent detection system for broken wires in elevator steel wire ropes according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the prior judgment module in an embodiment of the present invention; Figure 3 This is a logic decision diagram of the frame selection module in an embodiment of the present invention; Figure 4 This is a logic decision diagram of the verification unit in an embodiment of the present invention. Detailed Implementation

[0022] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0023] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0024] It should be noted that in the description of this invention, the terms "upper", "lower", "left", "right", "inner", "outer", etc., which indicate directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and is not intended to indicate or imply that the device or element must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation of this invention.

[0025] Furthermore, it should be noted that, in the description of this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0026] Please see Figure 1 As shown, this is a structural schematic diagram of an intelligent detection system for broken wires in elevator steel wire ropes according to an embodiment of the present invention. The present invention provides an intelligent detection system for broken wires in elevator steel wire ropes, comprising: The data acquisition module is used to collect elevator operating data at a preset acquisition frequency; The prior judgment module is used to determine the first judgment time interval based on the real-time running direction, actual load weight and stop information in the running data, and to obtain the corresponding operating condition category of the elevator based on the stop information within the time interval. A frame selection module is used to select a judgment frame in the first judgment time interval according to the operating condition category. The wire rope morphology analysis module is used to update the judgment frame to the current image frame and determine whether there are wire rope breakage features in the current image frame. The adjustment module is used to calculate an adjustment value based on the wire rope breakage characteristics when such characteristics are present, so as to adjust the preset acquisition frequency to a corrected acquisition frequency.

[0027] In this embodiment, the first judgment time interval is a key time period determined based on the real-time running direction, actual load and stop floor information, which is used to select judgment frames and determine the running condition category. The operating condition category is the elevator operating status type obtained from the analysis of elevator load and floor stop information, which is used to guide frame selection and wire breakage judgment; The first image area is the key observation area used for judgment in the multi-camera images; The second image area is an auxiliary observation area used for fracture feature verification in multi-camera images; The adjustment value is a parameter calculated based on the difference in the number of fracture features and the preset fracture number threshold, which is used to dynamically correct the acquisition frequency. The corrected acquisition frequency is the image acquisition cycle after the preset acquisition frequency is increased or decreased by the adjustment module when a fracture feature is detected or an adjustment value is calculated.

[0028] The data acquisition module acquires elevator operation data at a preset frequency, and the prior judgment module analyzes real-time operating direction, actual load, and stop information to determine the first judgment time interval and corresponding operating condition category. The frame selection module selects judgment frames during key start-stop cycles and operating states to ensure that wire rope breakage analysis is performed during high-risk periods. The wire rope morphology analysis module uses the first image area covered by multiple cameras to judge the main fracture features and verifies the fracture features through the second image area, improving the accuracy and robustness of detection. The adjustment module dynamically calculates adjustment values ​​and corrects the acquisition frequency based on the number of fracture features, realizing real-time response and continuous tracking of fracture features. This invention can significantly reduce the missed detection rate of wire rope breaks, shorten the detection response time, and achieve continuous, comprehensive, and accurate monitoring of wire rope breaks. At the same time, through frame selection and multi-region analysis driven by key time intervals and operating conditions, redundant data acquisition in non-critical states is reduced, improving system efficiency. This invention realizes dynamic and intelligent wire rope breakage detection in elevator safety monitoring, enhances early warning capabilities, and provides reliable protection for elevator operation safety.

[0029] Specifically, the prior judgment module includes a running load intensity judgment unit; The load intensity judgment unit is used to obtain the real-time running direction and actual load weight, and to determine the corresponding running load result based on the comparison result of the actual load weight and the load comparison threshold.

[0030] In this embodiment, the real-time running direction of the elevator is obtained; If it is the upward direction, the load comparison threshold is calculated based on the elevator's rated load weight and a preset empirical coefficient; The preset empirical coefficient is in the range of 0 to 1 and is used to characterize the reduction ratio of the rated load during the uplink operation. In this embodiment, it is taken as 0.85. If the direction is downward, the elevator's rated load weight is directly used as the load comparison threshold; The actual load weight is compared with the load comparison threshold; If the actual load weight is greater than the load comparison threshold, the first operating load result is obtained, corresponding to the first operating condition category. At this time, the elevator is in a state of operation close to or reaching the rated load in the real-time operating direction. There are a large number of passengers in the car, and the wire rope stress level is in a high range. At this time, the time interval formed by extending the basic time length from the real-time timestamp to the past is directly selected as the first judgment time interval, and the wire rope broken wire visual detection process based on image acquisition and recognition is directly started. If the actual load weight is less than or equal to the load comparison threshold, a second operating load result is obtained. At this time, the car load level of the corresponding elevator in the real-time running direction is lower than the rated load, the wire rope stress level is in the normal operating range, and the subsequent operating condition analysis process based on the second operating load result is executed.

[0031] By using the load intensity judgment unit to obtain the real-time running direction and actual load, and combining the load comparison threshold to determine the running load result, the system can distinguish between high load and low load conditions, providing targeted judgment for subsequent wire breakage detection, improving detection accuracy and reducing false alarms.

[0032] See Figure 2 As shown, it is a structural schematic diagram of the prior judgment module in an embodiment of the present invention; Specifically, the prior judgment module also includes a stop-floor behavior analysis unit; The stoppage behavior analysis unit is used to obtain the corresponding operating condition category based on the stoppage information within the first judgment time interval when the second operating load result is obtained.

[0033] In this embodiment, the floor stopping information refers to the data of floor stopping events that occurred in the car within the first judgment time interval, including but not limited to: the number of floors stopped, the total number of times the car stopped at each floor within the time interval; and the duration of continuous floor stopping, the number of consecutive floor stopping events that occurred in the car, which is used to reflect the concentration or dispersion of floor stopping behavior.

[0034] By analyzing the stopping information within the first judgment time interval under low load operation by the stopping behavior analysis unit, the operating condition category is obtained, and the intermittent stopping behavior of the car is accurately captured, providing an effective reference for frame selection and wire breakage identification, and improving the system adaptability.

[0035] Specifically, the stop behavior analysis unit includes an interval determination subunit and an operating condition determination subunit; An interval determination sub-unit is used to determine the first judgment time interval based on the load comparison threshold, the actual load weight, and the real-time timestamp; The operating condition determination subunit is used to obtain the stop information of the first determination time interval and the comparison result of the stop information and the corresponding preset threshold to obtain the corresponding operating condition category.

[0036] In this embodiment, the load difference is calculated based on the load comparison threshold and the actual load weight. The load difference is the difference between the load comparison threshold and the actual load weight. Based on the load difference, the duration of the first judgment time interval is calculated; ; in: T represents the duration of the first judgment time interval; The base time length is a preset empirical parameter used to ensure the minimum length of the time interval; The maximum possible time length can be determined based on historical system data, which sets the upper limit for the extension of the time interval. is the time adjustment coefficient, and is the empirical coefficient, which adjusts the sensitivity of the load difference to the increase of the interval length; This is the load difference, which is the difference between the load comparison threshold and the actual load weight. In this embodiment, , as well as The value of is related to the actual operating parameters of the elevator, for example: An elevator has a door opening time of approximately 4 seconds and a closing time of approximately 5 seconds. The elevator's rated operating speed is 1.5 m / s. The operation includes an acceleration phase of approximately 1.0 second, a constant speed phase with an average inter-floor travel time of approximately 3 seconds, and a deceleration phase of approximately 1.0 second. The average dwell time for passengers on each floor is approximately 6 to 8 seconds, and the average number of passengers going up and down is 1 to 3 per floor. The base time length ranges from 15 to 25 seconds, with 20 seconds being the optimal choice. The maximum possible duration can be increased, with a value ranging from 30 to 60 seconds, and 40 seconds being the optimal choice. This is the time adjustment coefficient, with a value ranging from 0.02 to 0.08, and 0.05 is optimally selected. The time interval obtained by extending the duration forward from the real-time timestamp is the first judgment time interval; The forward extension refers to using the real-time timestamp as the end point of the interval and backtracking to obtain the time interval corresponding to the duration. The stopping information includes the number of stopping levels and the duration of consecutive stopping levels; Compare the number of stopping levels with the preset threshold number of stopping levels; If the number of stops exceeds the preset threshold, the elevator's operating condition category is determined based on the duration of the consecutive stops. The duration of the continuous stop layer is compared with a preset duration threshold. If the duration of the continuous stop is greater than the preset duration threshold, a second operating condition category is obtained. At this time, the elevator will continuously experience multiple stop events within the first judgment time interval. The stop behavior is concentrated and the elevator is in a state of frequent stop and frequent start-stop. If the duration of the continuous stop is less than or equal to the preset duration threshold, a third operating condition category is obtained. At this time, the elevator has multiple stop events within the first judgment time interval, but the continuity is insufficient. The stop behavior is discretely distributed, and the elevator is in an intermittent stop and intermittent start-stop operating state. If the number of stops is less than or equal to the preset number of stops threshold, the fourth operating condition category is obtained. At this time, the elevator has fewer stops in the first judgment time interval and mainly runs through the floors continuously. The elevator is in a low-frequency stop operation state. The values ​​of the number of stops and the duration threshold are related to the elevator's rated operating parameters, historical operating statistics, and actual operating parameters. In this embodiment, the threshold number of stopping levels is the critical number of stopping levels for the elevator to transition from normal operation to high-frequency start-stop state within a unit judgment time interval. Its value ranges from 3 to 6 times, and preferably 4 times. The duration of continuous stop is the length of the number of consecutive stop events, used to characterize the concentration of repeated stop behaviors of the elevator in adjacent operating cycles, and the value ranges from 3 to 10 times, preferably 5 times.

[0037] By calculating the load difference through the interval determination sub-unit and adjusting the duration of the first judgment time interval, and combining the analysis of the number of stopping floors and the duration of continuous stopping floors by the operating condition judgment sub-unit, the characteristics of elevator operation behavior can be accurately reflected, and dynamic operating condition division under different stopping modes can be realized, thereby improving the pertinence and reliability of monitoring.

[0038] See Figure 3 As shown, it is a logic decision diagram of the frame selection module in an embodiment of the present invention; Specifically, the frame selection module includes a direction-related frame selection unit and a running condition-related frame selection unit; The direction-related frame selection unit is used to select the current image frame at the location associated with the real-time running direction based on the real-time running direction when the first running condition category is obtained. The operating condition associated frame selection unit is used to select the current image frame at the midpoint of the complete start-stop cycle closest to the real-time timestamp within the first judgment time interval when other operating condition categories besides the first operating condition category are obtained.

[0039] In this embodiment, when the first operating condition category is obtained, the start and stop direction of the elevator is acquired; If it is in the upward direction, obtain the current image frame at the moment the car starts, at which time the traction force caused by the car load reaches its maximum value; If it is in the downward direction, obtain the current image frame at the moment the car stops, at which time the wire rope tension reaches its peak. When other operating condition categories besides the first operating condition category are obtained, the first judgment time interval is evenly divided into several time periods, and the image frame is directly acquired at the instant corresponding to the midpoint time of each time period. When other operating condition categories besides the first operating condition category are obtained, the complete start-stop cycle within the first judgment time interval is identified, and the image frame corresponding to the midpoint of the complete start-stop cycle closest to the real-time timestamp is obtained. In this embodiment, the start-stop cycle is divided by whether the car speed is zero and the door status information. The start point of each start-stop cycle is the instant the car starts and the end point is the instant the car comes to a complete stop. In the complete start-stop cycle closest to the current real-time timestamp, the image frame corresponding to the midpoint is directly obtained.

[0040] The direction-related frame selection unit obtains the midpoint frame of the start-stop moment or the complete start-stop cycle, and the operating condition-related frame selection unit selects key frames in combination with the operating condition category, so as to achieve accurate capture of key image information, improve the timeliness and effectiveness of wire rope fracture identification, and reduce the risk of missed detection.

[0041] Specifically, the wire rope morphology analysis module includes a fracture identification unit and a re-verification unit; A fracture detection unit is used to determine whether there are wire rope fracture features in the first image region of the current image frame; The re-verification unit is used to obtain adjacent image frames and verify whether the wire rope breakage feature exists in the current image frame when there is no wire rope breakage feature in the first image area.

[0042] The first image region and the second image region are defined by the region division unit. The fracture recognition unit determines the fracture characteristics of the steel wire rope in the first image region. The verification unit verifies the characteristics of the second image region through adjacent frames, realizing multi-region and multi-frame linkage recognition, and improving the accuracy and robustness of wire breakage detection.

[0043] Specifically, the fracture identification unit includes a device quantity statistics unit and a region delineation unit; The device count unit is used to obtain the number of acquisition devices corresponding to the current image frame; The region delineation unit is used to divide the image into the first image region and the second image region based on the number of acquisition devices.

[0044] In this embodiment, the number of acquisition devices is related to the field of view of the acquisition devices; In this embodiment, the number of acquisition devices is 3, that is, 3 image acquisition devices are arranged around the steel wire rope, each with a field of view of 120°, and are evenly distributed to cover the entire circumference of the steel wire rope; adjacent groups of acquisition devices are staggered along the circumference of the steel wire rope, so that the angle between the perpendicular line of the camera optical axis of the adjacent groups of acquisition devices and the line connecting the axis of the steel wire rope is 30°, so that the complete circumferential surface of the steel wire rope can be fully covered by multiple staggered perspectives without the steel wire rope rotating actively. At any given moment, the unit images synchronously acquired by the plurality of cameras are time-aligned to form the corresponding current image frame, which contains the imaging results of the steel wire rope under multiple field of view angles. Let the image acquired by a single acquisition device be a unit image, and the resolution of the unit image be W×H. The imaging sensor of the acquisition device has a nominal effective imaging coverage η, which is used to characterize the proportion of effective pixels in the image that can be used for stable analysis. Based on the effective imaging coverage η, the region scaling factor k is calculated using the following formula: ; Based on the unit image, the image frame is cropped proportionally in both the horizontal and vertical directions according to the scaling factor to obtain a size of The central region is defined as the first unit image region; in: ; Determine the first unit image region of all unit images, and the region other than the unit image region as the second unit image region; The first unit image regions of all unit images are combined to form the first image region; The second image region is a set of two regions enclosed by the top and bottom line segments of each of the three image regions and the region sandwiched between them. Edge detection is performed on the outline of the steel wire rope within the second image area; Calculate the curvature along the longitudinal direction of the wire rope; Obtain the total width of the wire rope in the first image area. ; Set width threshold The width of the elevator roller groove Diameter of a single steel wire rope The number of wire ropes, x, is related to the number of wire ropes, and the calculation formula is: ; in, This is an empirical adjustment coefficient for the width, used to ensure that the threshold covers the actual variation in the width of the slack wire rope. Its value range is 0.05≤α≤0.2. The threshold of 0.05 ensures that the wire rope width exceeding the threshold under the minimum slack state can be identified, thus avoiding missed detections. The upper limit of 0.2 prevents the threshold from being too large, which could lead to the normal tensioned wire rope being mistakenly identified as a broken wire. If there is a non-zero curvature in the first image area or the total width of the wire rope is greater than the width threshold, it is determined that there is a wire rope breakage feature. If there is no non-zero curvature in the first image area and the total width of the wire rope is less than or equal to the width threshold, it is determined that there is no wire rope breakage feature.

[0045] The number of acquisition devices is obtained through the device quantity statistics unit, and the area delineation unit divides the image area based on the field of view of the acquisition devices to achieve complete coverage of the circumference of the wire rope. By staggered deployment and synchronous acquisition of multiple cameras, the integrity of images of the wire rope from various perspectives is ensured, thereby improving the comprehensiveness and reliability of broken wire identification.

[0046] See Figure 4 As shown, it is a logic decision diagram of the verification unit in an embodiment of the invention; Specifically, the re-verification unit includes an adjacent image frame selection subunit and a feature verification subunit; The adjacent image frame selection sub-unit is used to select adjacent image frames when there is no wire rope breakage feature in the first image area; The feature verification subunit is used to determine whether there is a wire rope breakage feature in the second image region of the current image frame based on the adjacent image frames.

[0047] In this embodiment, in the uplink direction, it is preferred to select the frame adjacent to the frame after the temporal relationship is determined; In the downlink direction, the frame adjacent to the frame before the frame timing relationship is determined is preferred; To ensure that the presence of wire rope breakage features in the second image region of the current image frame can be verified through adjacent image frames, and to satisfy... To ensure reliable coverage of the verification area, the lower limit of k can be obtained as follows: At the same time, k cannot exceed the original region size, i.e. ; At the same time, the value of k should also satisfy: ; in, To ensure reliable coverage of the verification area, the minimum proportion of effective pixels, This represents the upper limit of the effective pixel ratio in the actual acquired image, and the upper limit is ≤1; In summary, the final range of values ​​for k is: ; The adjacent image frame selection subunit selects the neighboring frame where no breakage feature is detected in the first image region, and the verification unit judges the breakage feature in the second image region to realize dynamic inter-frame verification, ensuring that the breakage feature is not missed due to single-frame occlusion or noise.

[0048] Specifically, the adjustment module includes an adjustment value calculation unit and an adjustment unit; The adjustment module includes an adjustment value calculation unit and an adjustment unit; The adjustment value calculation unit is used to calculate the adjustment value of the preset acquisition frequency when it is determined that there are characteristics of wire rope breakage. The adjustment unit is used to adjust the preset acquisition frequency to a corrected acquisition frequency according to the adjustment value.

[0049] In this embodiment, the preset acquisition frequency is the image acquisition cycle frequency under normal operation without triggering adjustment. It is a fixed value and can be set according to the elevator running speed and wire rope monitoring requirements. The corrected acquisition frequency is the acquisition cycle frequency after increasing or decreasing the preset acquisition frequency when the number of detected wire rope breakage features exceeds the preset threshold or an adjustment value is calculated. The adjustment value is a parameter calculated based on the ratio of the difference in the number of fracture features to the preset fracture number threshold, and is used to correct the acquisition frequency. The difference in the number of fracture features is the difference between the number of fracture features of the wire rope in the current image frame and the preset fracture number threshold. The range of values ​​can be determined empirically based on the actual fracture situation of the wire rope. The presence of wire rope breakage features is determined by detecting wire rope breakage features in either the first image area or the second image area.

[0050] When the wire rope fracture feature is determined to exist, the adjustment value calculation unit calculates the adjustment value based on the difference in the number of fracture features and the preset threshold. The adjustment unit corrects the preset acquisition frequency to the corrected acquisition frequency, thereby achieving dynamic optimization of the acquisition cycle. By responding to the density of broken wire features, the detection efficiency and response speed are improved.

[0051] Specifically, the adjustment value calculation unit includes a difference calculation subunit and a frequency mapping calculation subunit; The difference calculation subunit is used to calculate the difference in the number of fracture features based on the number of wire rope fracture features in the current image frame and the adjacent image frames; The frequency mapping calculation subunit calculates the adjustment value based on the difference in the number of fracture features.

[0052] In this embodiment, the quantity is determined when it is determined that there are signs of wire rope breakage; The number of the wire rope fracture characteristics is compared with the preset fracture limit value; If the number of fracture features is greater than the preset fracture number threshold, calculate the difference in the number of fracture features. Wherein, the difference in the number of fracture features is the difference between the number of fracture features and a preset fracture number threshold; If the number of fracture features is less than or equal to the preset fracture number threshold, the preset acquisition frequency remains unchanged; The ratio of the difference in the number of fracture features to the preset fracture number threshold is calculated to obtain the adjustment value; The preset threshold for the number of fractures is a fixed integer value determined by adding a safety margin to the statistical average of the number of fracture characteristics of the same type of wire rope in each collection cycle under normal operating conditions. In this embodiment, the value range is 0 to 5, and 3 is used in this embodiment.

[0053] The difference calculation subunit calculates the difference in the number of broken features between the current image frame and the adjacent image frames. The frequency mapping calculation subunit maps the difference to the ratio of the preset broken threshold as an adjustment value, thereby realizing dynamic acquisition frequency correction. This ensures that the acquisition frequency is increased in time when the number of broken wire features increases abnormally, thus enhancing the system's sensitivity and timeliness to sudden broken wire events.

[0054] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles 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 all fall within the scope of protection of the present invention.

[0055] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. An intelligent detection system for broken wires in elevator steel wire ropes, characterized in that, include: The data acquisition module is used to collect elevator operating data at a preset acquisition frequency; The prior judgment module is used to determine the first judgment time interval based on the real-time running direction, actual load weight and stop information in the running data, and to obtain the corresponding operating condition category of the elevator based on the stop information within the time interval. A frame selection module is used to select a judgment frame in the first judgment time interval according to the operating condition category. The wire rope morphology analysis module is used to update the judgment frame to the current image frame and determine whether there are wire rope breakage features in the current image frame. The adjustment module is used to calculate an adjustment value based on the wire rope breakage characteristics when such characteristics are present, so as to adjust the preset acquisition frequency to a corrected acquisition frequency.

2. The intelligent detection system for broken wires in elevator steel wire ropes according to claim 1, characterized in that, The prior judgment module includes a running load intensity judgment unit; The load intensity judgment unit is used to obtain the real-time running direction and actual load weight, and to determine the corresponding running load result based on the comparison result of the actual load weight and the load comparison threshold.

3. The intelligent detection system for broken wires in elevator steel wire ropes according to claim 2, characterized in that, The prior judgment module also includes a stop-floor behavior analysis unit; The stoppage behavior analysis unit is used to obtain the corresponding operating condition category based on the stoppage information within the first judgment time interval when the second operating load result is obtained.

4. The intelligent detection system for broken wires in elevator steel wire ropes according to claim 3, characterized in that, The stop behavior analysis unit includes an interval determination subunit and an operating condition determination subunit; An interval determination sub-unit is used to determine the first judgment time interval based on the load comparison threshold, the actual load weight, and the real-time timestamp; The operating condition determination subunit is used to obtain the stop information of the first determination time interval and the comparison result of the stop information and the corresponding preset threshold to obtain the corresponding operating condition category.

5. The intelligent detection system for broken wires in elevator steel wire ropes according to claim 4, characterized in that, The frame selection module includes a direction-related frame selection unit and a running condition-related frame selection unit. The direction-related frame selection unit is used to select the current image frame at the location associated with the real-time running direction based on the real-time running direction when the first running condition category is obtained. The operating condition associated frame selection unit is used to select the current image frame at the midpoint of the complete start-stop cycle closest to the real-time timestamp within the first judgment time interval when other operating condition categories besides the first operating condition category are obtained.

6. The intelligent detection system for broken wires in elevator steel wire ropes according to claim 5, characterized in that, The wire rope morphology analysis module includes a fracture identification unit and a re-verification unit; A fracture detection unit is used to determine whether there are wire rope fracture features in the first image region of the current image frame; The re-verification unit is used to obtain adjacent image frames and verify whether the wire rope breakage feature exists in the current image frame when there is no wire rope breakage feature in the first image area.

7. The intelligent detection system for broken wires in elevator steel wire ropes according to claim 6, characterized in that, The fracture identification unit includes an equipment quantity statistics unit and an area delineation unit; The device count unit is used to obtain the number of acquisition devices corresponding to the current image frame; The region delineation unit is used to divide the image into the first image region and the second image region based on the number of acquisition devices.

8. The intelligent detection system for broken wires in elevator steel wire ropes according to claim 6, characterized in that, The re-verification unit includes an adjacent image frame selection subunit and a feature verification subunit; The adjacent image frame selection sub-unit is used to select adjacent image frames when there is no wire rope breakage feature in the first image area; The feature verification subunit is used to determine whether there is a wire rope breakage feature in the second image region of the current image frame based on the adjacent image frames.

9. The intelligent detection system for broken wires in elevator steel wire ropes according to claim 8, characterized in that, The adjustment module includes an adjustment value calculation unit and an adjustment unit; The adjustment module includes an adjustment value calculation unit and an adjustment unit; The adjustment value calculation unit is used to calculate the adjustment value of the preset acquisition frequency when it is determined that there are characteristics of wire rope breakage. The adjustment unit is used to adjust the preset acquisition frequency to a corrected acquisition frequency according to the adjustment value.

10. The intelligent detection system for broken wires in elevator steel wire ropes according to claim 9, characterized in that, The adjustment value calculation unit includes a difference calculation subunit and a frequency mapping calculation subunit; The difference calculation subunit is used to calculate the difference in the number of fracture features based on the number of wire rope fracture features in the current image frame and the adjacent image frames; The frequency mapping calculation subunit calculates the adjustment value based on the difference in the number of fracture features.

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