CN114476959B - Tower crane luffing mechanism early warning system - Google Patents
Tower crane luffing mechanism early warning system Download PDFInfo
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- CN114476959B CN114476959B CN202210360874.2A CN202210360874A CN114476959B CN 114476959 B CN114476959 B CN 114476959B CN 202210360874 A CN202210360874 A CN 202210360874A CN 114476959 B CN114476959 B CN 114476959B
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66C—CRANES; LOAD-ENGAGING ELEMENTS OR DEVICES FOR CRANES, CAPSTANS, WINCHES, OR TACKLES
- B66C15/00—Safety gear
- B66C15/06—Arrangements or use of warning devices
Abstract
A tower crane luffing mechanism early warning system comprises a steel wire rope image acquisition processing unit and a control unit, steel wire rope image information is acquired in real time and is subjected to image processing and parallelism recognition, more than two parallelism reference threshold values and more than two early warning levels are set, a plurality of frames of steel wire rope images acquired within a fixed time period T are continuously analyzed through the steel wire rope image acquisition processing unit, the parallelism of each frame of steel wire rope image is recognized and compared with a preset parallelism reference threshold value, the early warning levels are determined according to the proportion of the parallelism data reaching the preset parallelism reference threshold value in all the parallelism data within the fixed time period T, the proportion of the parallelism data reaching the preset parallelism reference threshold value within two or more than two adjacent fixed time periods T is continuously compared by combining the steel wire rope image acquisition processing unit, and adjusting the early warning level according to the comparison result, identifying and processing abnormal fluctuation in the rope disorder risk early warning program, and stabilizing the early warning level.
Description
Technical Field
The invention relates to the technical field of crane safety control, in particular to an early warning system for a luffing mechanism of a tower crane.
Background
The tower crane luffing mechanism transmission chain comprises a motor, a speed reducer, a winding drum, a pulley and a steel wire rope, the steel wire rope is disordered (the outermost circle of the steel wire rope is disordered) in use, in order to prevent accidents, early identification measures are provided in the prior art, intervention processing is prompted in a mode of early warning for an operator, the disorder rope problem is mostly generated in an indirect judgment mode, so that the misjudgment rate is high, parallelism judgment is a direct judgment mode for the disorder rope problem developed in recent years, the technology identifies the parallelism of the steel wire rope based on image analysis, correlation analysis is not needed, and early warning is directly carried out according to a threshold value, so that the tower crane luffing mechanism transmission chain is a more accurate early warning mode. The problem that easily appears when the tower crane luffing mechanism transmission chain uses parallelism recognition early warning is that because luffing mechanism during operation transmission system's unstability often leads to wire rope parallelism abnormal fluctuation, when this kind of fluctuation involves a plurality of early warning threshold intervals, just leads to alarm signal's unstability easily, and the credibility worsens, and in the long term, operating personnel will be intentionally neglected the early warning of specific rank.
Disclosure of Invention
The invention provides a tower crane luffing mechanism early warning system based on solving the problems provided by the background technology, which identifies and processes abnormal fluctuation in an early warning program of a wire rope disorder risk, stabilizes early warning level and improves early warning accuracy.
The technical scheme of the invention is as follows:
a tower crane luffing mechanism early warning system comprises a steel wire rope image acquisition and processing unit and a control unit, wherein the steel wire rope image acquisition and processing unit acquires steel wire rope image information in real time, performs image processing and parallelism recognition on the acquired steel wire rope image information, the control unit is provided with more than two parallelism reference thresholds and more than two early warning levels, the steel wire rope image acquisition and processing unit continuously analyzes multi-frame steel wire rope images acquired in a fixed time period T, recognizes the parallelism of each frame of steel wire rope image, compares the parallelism with a preset parallelism reference threshold, determines the early warning levels according to the proportion of the parallelism data reaching the preset parallelism reference threshold in all the parallelism data in the fixed time period T, and continuously compares the parallelism data reaching the preset parallelism reference threshold in two or more than two adjacent fixed time periods T by the steel wire rope image acquisition and processing unit And (4) comparing, and adjusting the early warning level according to the comparison result.
In a further embodiment, the steel wire rope image acquisition and processing unit adopts processing software to perform image denoising, segmentation, feature extraction, linear processing and parallelism recognition.
In a further embodiment, the parallelism identification is defined by angle of the linearly processed wire rope data.
In a further embodiment, the parallelism reference threshold comprises at least a first threshold, a second threshold and a third threshold from low to high, and the early warning level comprises at least a first early warning level, a second early warning level and a third early warning level from low to high.
In a further embodiment, data associations are established for each parallelism reference threshold and each pre-warning level, and under the following conditions:
f1, the proportion of the parallelism data reaching the third threshold value in all the parallelism data in the fixed time period T is equal to or larger than a preset proportion value;
f2, the proportion of the parallelism data reaching the second threshold value in all the parallelism data in the fixed time period T is equal to or larger than a preset proportion value;
f3, the proportion of the parallelism data reaching the first threshold value in all the parallelism data in the fixed time period T is equal to or larger than a preset proportion value;
when the condition f1 is met, the control unit sends out early warning according to a third early warning level;
when the condition f2 is met but the condition f1 is not met, the control unit sends out early warning according to a second early warning level;
when the condition f3 is satisfied but the condition f2 is not satisfied, the control unit issues an early warning at a first early warning level.
In a further embodiment, the wire rope image acquisition processing unit continuously compares the data occupancy ratio of the parallel degrees reaching the preset parallel reference threshold value in two or more adjacent fixed time periods T, and when the data occupancy increment difference value Δ a between the data occupancy ratios of the parallel degrees reaching the preset parallel reference threshold value in two or more adjacent fixed time periods T reaches the preset data occupancy increment difference value threshold value Δ Ay, the wire rope image acquisition processing unit adjusts the current early warning level to a higher early warning level.
In a further embodiment, the wire rope image acquisition processing unit continuously compares the data occupancy ratio of the parallel degrees reaching the preset parallel reference threshold value in two or more adjacent fixed time periods T, and when the data occupancy decrement difference value Δ a 'between the data occupancy ratios of the parallel degrees reaching the preset parallel reference threshold value in two or more adjacent fixed time periods T reaches the preset data occupancy decrement difference value threshold value Δ a' y, the wire rope image acquisition processing unit adjusts the current early warning level to a lower early warning level.
In a further embodiment, different early warning levels are distinguished by different degrees of sound warning or combined sound and light warning in the cab of the tower crane.
The invention can obtain the following technical effects:
the tower crane luffing mechanism early warning system provided by the invention sets early warning levels based on parallelism recognition, continuously analyzing a plurality of frames of steel wire rope images collected within a fixed time period T through a steel wire rope image collecting and processing unit, identifying the parallelism of each frame of steel wire rope image, comparing with a preset parallelism reference threshold value, determining the early warning level according to the proportion of the parallelism data reaching the preset parallelism reference threshold in all the parallelism data in the fixed time period T, continuously comparing the proportion of the parallelism data reaching the preset parallelism reference threshold in two or more adjacent fixed time periods T by combining the steel wire rope image acquisition processing unit, adjusting the early warning level according to the comparison result, abnormal fluctuation is identified and processed in an early warning program of the wire rope disorder risk, early warning level is stabilized, and early warning accuracy is improved.
Drawings
The aspects and advantages of the present application will become apparent to those skilled in the art from a reading of the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. In the drawings:
fig. 1 is a schematic diagram of an early warning principle of an early warning system of a luffing mechanism of a tower crane according to an embodiment of the present invention.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. It should be noted that these embodiments are provided so that this disclosure can be more completely understood and fully conveyed to those skilled in the art, and the present disclosure may be implemented in various forms without being limited to the embodiments set forth herein.
Example 1
The early warning system for the luffing mechanism of the tower crane comprises a steel wire rope image acquisition and processing unit and a control unit, wherein the steel wire rope image acquisition and processing unit acquires steel wire rope image information in real time and performs image processing and parallelism recognition on the acquired steel wire rope image information.
According to the implemented technology, the steel wire rope image acquisition processing unit adopts processing software to perform noise reduction, segmentation, feature extraction, linear processing and parallelism recognition on an image, namely, the functional configuration of the steel wire rope image acquisition processing unit comprises image acquisition hardware (a camera) and an image processing program. In addition, in the parallelism identification in this embodiment, angle definition is performed on the wire rope data subjected to linear processing, and the angle value definition is preferably adopted in the angle value and the trigonometric function value.
Further, according to the early warning requirement, the control unit is provided with more than two parallelism reference threshold values and more than two early warning levels, and different early warning levels are distinguished through sound warning or acousto-optic combined warning of different degrees in the cab of the tower crane, which is the same as the prior art.
As an improvement of this embodiment, in order to identify and process abnormal fluctuations in an early warning program of a rope disorder risk of a steel wire rope and stabilize an early warning level, the steel wire rope image acquisition and processing unit continuously analyzes multiple frames of steel wire rope images acquired within a fixed time period T, identifies the parallelism of each frame of steel wire rope image, compares the parallelism with a preset parallelism reference threshold, and determines the early warning level according to the proportion of the parallelism data reaching the preset parallelism reference threshold in all the parallelism data within the fixed time period T.
The preset fixed time period T can here be selected and adjusted in conjunction with the rate of movement of the horn from a range of seconds to tens of seconds.
Before introducing the above determination method, the parallelism reference threshold is first defined into at least a first threshold, a second threshold and a third threshold from low to high, and the early warning level is defined into at least a first early warning level, a second early warning level and a third early warning level from low to high.
Next, establishing data association between each parallelism reference threshold and each early warning level, and under the following conditions:
f1, the proportion of the parallelism data reaching the third threshold value in all the parallelism data in the fixed time period T is equal to or larger than a preset proportion value;
f2, the proportion of the parallelism data reaching the second threshold value in all the parallelism data in the fixed time period T is equal to or larger than a preset proportion value;
f3, the proportion of the parallelism data reaching the first threshold value in all the parallelism data in the fixed time period T is equal to or larger than a preset proportion value;
when the condition f1 is met, the control unit sends out early warning according to a third early warning level;
when the condition f2 is met but the condition f1 is not met, the control unit sends out early warning according to a second early warning level;
when the condition f3 is satisfied but the condition f2 is not satisfied, the control unit issues an early warning at a first early warning level.
According to the mode for determining the early warning level, scientific interval processing and probability statistics are carried out on the reference threshold value of the program, so that the method has good adaptability to the fluctuation influence of the steel wire rope of the tower crane luffing mechanism in the working process, the early warning level can be stabilized, and the stability of the early warning level represents higher early warning accuracy. In defining the parallelism reference threshold from low to high, the effect should be optimized in combination with empirical values and program verification, the maximum threshold also generally not exceeding the range of 10 ° when defined with the aforementioned angle values.
As an improved correlation for determining the early warning level, the wire rope image acquisition processing unit also continuously compares the parallelism data ratio of two or more adjacent steel wire rope images reaching a preset parallelism reference threshold within two or more fixed time periods T, and adjusts the early warning level according to the comparison result.
Specifically, the wire rope image acquisition processing unit continuously compares the data occupancy ratio of the parallelism data reaching the preset parallelism reference threshold value in two or more adjacent fixed time periods T, and when the data occupancy ratio increment difference value Δ a between the data occupancy ratios of the parallelism data reaching the preset parallelism reference threshold value in two or more adjacent fixed time periods T reaches the preset data occupancy ratio increment difference value threshold value Δ Ay, the wire rope image acquisition processing unit adjusts the current early warning level to a higher early warning level. Similarly, the wire rope image acquisition processing unit may continuously compare the occupation ratio of the parallel data reaching the preset parallel reference threshold in two or more adjacent fixed time periods T, and when the data occupation ratio decrement difference value Δ a 'between the occupation ratios of the parallel data reaching the preset parallel reference threshold in two or more adjacent fixed time periods T reaches the preset data occupation ratio decrement difference value threshold Δ a' y, adjust the current early warning level to a lower early warning level. The adjustment mode well identifies and judges the action trend of the steel wire rope, so that the prevention effect on the rope disorder risk is further improved.
It will be readily understood that the term "achieve" as used herein is to be understood as meaning "equal to or exceeding" which can be directly determined by the essence of the technical solution.
In summary, the embodiment of the invention sets the early warning level based on the parallelism recognition, continuously analyzes the multi-frame steel wire rope images collected in a fixed time period T through the steel wire rope image collecting and processing unit, recognizes the parallelism of each frame of steel wire rope image, compares the parallelism with the preset parallelism reference threshold, determines the early warning level according to the proportion of the parallelism data reaching the preset parallelism reference threshold in all the parallelism data in the fixed time period T, carries out scientific interval processing and probability statistics on the reference threshold of the program, has good adaptability to the fluctuation influence of the steel wire rope of the luffing mechanism of the tower crane in the working process, and can stabilize the early warning level. Furthermore, the parallelism data ratio reaching the preset parallelism reference threshold value in two or more than two adjacent fixed time periods T is continuously compared by combining the steel wire rope image acquisition and processing unit, the early warning level is adjusted according to the comparison result, the action trend of the steel wire rope is well identified and judged, and the effect is further improved.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention.
Claims (8)
1. A tower crane luffing mechanism early warning system comprises a steel wire rope image acquisition and processing unit and a control unit, wherein the steel wire rope image acquisition and processing unit acquires steel wire rope image information in real time, performs image processing and parallelism recognition on the acquired steel wire rope image information, and the control unit is provided with more than two parallelism reference thresholds and more than two early warning levels And (4) comparing the parallelism data of the threshold value, and adjusting the early warning level according to the comparison result.
2. The tower crane luffing mechanism early warning system of claim 1, wherein the wire rope image acquisition processing unit adopts processing software to perform image denoising, segmentation, feature extraction, linear processing and parallelism recognition.
3. The tower crane luffing mechanism warning system of claim 2, wherein the parallelism identification is defined by an angle of the linearly processed wire rope data.
4. The tower crane luffing mechanism early warning system of claim 1, wherein the parallelism reference threshold comprises at least a first threshold, a second threshold, and a third threshold from low to high, and the early warning levels comprise at least a first early warning level, a second early warning level, and a third early warning level from low to high.
5. The tower crane luffing mechanism warning system of claim 4, wherein data associations of respective parallelism reference thresholds and respective warning levels are established, and wherein:
f1, the proportion of the parallelism data reaching the third threshold value in all the parallelism data in the fixed time period T is equal to or larger than a preset proportion value;
f2, the proportion of the parallelism data reaching the second threshold value in all the parallelism data in the fixed time period T is equal to or larger than a preset proportion value;
f3, the proportion of the parallelism data reaching the first threshold value in all the parallelism data in the fixed time period T is equal to or larger than a preset proportion value;
when the condition f1 is met, the control unit sends out early warning according to a third early warning level;
when the condition f2 is met but the condition f1 is not met, the control unit sends out early warning according to a second early warning level;
when the condition f3 is satisfied but the condition f2 is not satisfied, the control unit issues an early warning at a first early warning level.
6. The tower crane luffing mechanism early warning system according to claim 1, wherein the wire rope image acquisition processing unit continuously compares the data occupancy ratio of the parallelism data reaching the preset parallelism reference threshold in two or more adjacent fixed time periods T, and adjusts the current early warning level to a higher early warning level when the data occupancy increment difference Δ a between the data occupancy ratios of the parallelism data reaching the preset parallelism reference threshold in two or more adjacent fixed time periods T reaches the preset data occupancy increment difference threshold Δ Ay.
7. The tower crane luffing mechanism early warning system according to claim 1, wherein the wire rope image acquisition processing unit continuously compares the data occupancy of the parallelism data reaching the preset parallelism reference threshold within two or more adjacent fixed time periods T, and adjusts from the current early warning level to a lower early warning level when the data occupancy decrement difference Δ a 'between the data occupancies of the parallelism data reaching the preset parallelism reference threshold within two or more adjacent fixed time periods T reaches the preset data occupancy decrement difference threshold Δ a' y.
8. The tower crane luffing mechanism early warning system of claim 1, wherein different early warning levels are distinguished by different degrees of audible or combined audible and visual alarms within a tower crane cab.
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Denomination of invention: An early warning system for luffing mechanism of tower crane Effective date of registration: 20230222 Granted publication date: 20220805 Pledgee: Zhejiang Xiaoshan rural commercial bank Limited by Share Ltd. Jingjiang branch Pledgor: HANGZHOU JIE DRIVE TECHNOLOGY Co.,Ltd. Registration number: Y2023980033135 |
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