Bridge crane operation state safety early warning method and system

Abstract

The invention discloses a bridge crane operation state safety early warning method and system, and relates to the technical field of bridge crane operation monitoring, and the method comprises the following steps: monitoring an operation area of a bridge crane, collecting image information of suspended cargoes in real time when the bridge crane operates, and obtaining a cargo suspension state diagram; establishing a plane-coordinate system on the acquired cargo suspension state diagram by taking a suspension connection node of the bridge crane as an original point, and acquiring a current cargo angular point coordinate; and importing an ideal cargo suspension state diagram into the plane coordinate system, and calculating cargo swing deviation angular point coordinates based on the current cargo center lifting rope linear correlation ideal cargo suspension state diagram. According to the method, the swing deviation value and the inclination deviation value are respectively obtained based on the current cargo suspension state, and the risk coefficient is integrally calculated for evaluation, so that the risk early warning effect is remarkably improved, the operation safety of the bridge crane is improved, the actual operation deviation condition is determined, and emergency treatment during early warning is facilitated.

Description

Technical Field

[0001] The present invention relates to the technical field of bridge crane operation monitoring, and in particular to a bridge crane operation status safety early warning method and system. Background Art

[0002] A bridge crane is a type of lifting equipment that is horizontally mounted above workshops, warehouses and material yards to lift materials. The bridge of the bridge crane runs longitudinally along the tracks laid on the elevated structures on both sides, making full use of the space below the bridge to lift materials without being hindered by ground equipment. It is the most widely used and largest type of lifting machinery. The bridge crane operation status safety early warning method and system are used to monitor the crane's operation status in real time and issue timely early warnings when potential risks are found.

[0003] For example, the application publication number is CN112061992A, the application publication date is 2020.12.11, and the name is "A gantry crane cable storage basket monitoring system", which specifically includes an image collector, a control processor, a memory, and a display and warning device. The control processor performs grayscale processing on the image of the gantry crane cable and the cable storage basket collected and transmitted back by the image collector, and determines the image of the cable exceeding the set boundary of the cable storage basket as an abnormal scene. The image collector includes but is not limited to a trolley frame, a driver's cab, a beam, a ladder and a walking mechanism. One or more groups of corresponding image collectors are installed. The image collector is used to collect image information of the operating status of the gantry crane cable and the cable storage basket, and send the image information to the control processor. The control processor is communicatively connected with multiple image collectors, and is used to forward the image information to the memory, process the received image information, compare it with the plan in the system, and send the abnormal scene information of the cable escaping from the cable storage basket marked in the plan to the display and warning device.

[0004] The shortcoming of the existing technology including the above-mentioned application is that, when monitoring and warning of the operating status of a crane, the image of the objects suspended by the crane is collected, and then the monitoring and warning are carried out based on the comparative analysis of the position deviation of the object image and the preset situation. The objects suspended by the crane are prone to shaking when moving. At this time, the deviation of the position of the object is caused by two reasons. One is that the deviation is caused by the swing of the object, and the other is that the deviation of the position of the object is caused by the tilt of the suspended object. In actual monitoring, risk warning is only based on the position deviation of the suspended object, and the specific risk impact of the two situations is not distinguished. The security of risk monitoring is poor, and it is impossible to determine the actual situation for emergency handling. Summary of the invention

[0005] The purpose of the present invention is to provide a bridge crane operating status safety early warning method and system to solve the above-mentioned deficiencies in the prior art.

[0006] In order to achieve the above object, the present invention provides the following technical solution: a bridge crane operation status safety early warning method, comprising the following steps:

[0007] S1: Monitor the operation area of ​​the bridge crane, collect image information of the suspended cargo when the bridge crane is running in real time, and obtain the cargo suspension status diagram;

[0008] S2: Establish a plane coordinate system with the bridge crane suspension connection node as the origin on the collected cargo suspension state diagram to obtain the coordinates of the current cargo corner point;

[0009] S3: Import the ideal cargo suspension state diagram into the plane coordinate system, and calculate the coordinates of the cargo swing deviation corner point based on the current cargo center suspension rope straight line associated with the ideal cargo suspension state diagram;

[0010] S4: Based on the current cargo corner point coordinates, the swing deviation corner point coordinates and the ideal corner point coordinates, the swing deviation value and the tilt deviation value of the cargo hoisted by the bridge crane are calculated, and the swing deviation value and the tilt deviation value obtained historically are stored;

[0011] S5: The operation risk coefficient of the bridge crane is calculated based on the swing deviation value and the tilt deviation value, and the operation status of the bridge crane is evaluated and warned based on the operation risk coefficient of the bridge crane.

[0012] As a further description of the above technical solution: the monitoring of the operating area of ​​the bridge crane in step S1 also includes:

[0013] The collected surveillance video data is intelligently analyzed using AI recognition technology to identify personnel in the video content. When it is detected that someone has entered the operating area of ​​the bridge crane, the early warning mechanism is immediately triggered.

[0014] As a further description of the above technical solution: In step S3, the coordinates of the cargo swing deviation corner point are calculated based on the current cargo center suspension rope straight line associated with the ideal cargo suspension state diagram as follows:

[0015] S3.1: Calculate the deviation angle P between the current cargo center sling straight line and the Y axis in the plane coordinate system;

[0016] S3.2: Obtain the straight line between the plane coordinate origin and the cargo corner point of the ideal cargo suspension state diagram and mark it as the reference straight line, and calculate the distance between the plane coordinate origin and the corresponding corner point of the cargo;

[0017] S3.3: The reference straight line deflection angle P is used to obtain the swing straight line constraint formula, and a circle is drawn with the plane coordinate origin of the ideal cargo suspension state diagram as the center and the distance between the plane coordinate origin of the ideal cargo suspension state diagram and the corresponding corner point of the cargo as the radius to obtain the swing circle constraint formula;

[0018] S3.4: Calculate the intersection of the swing straight line constraint formula and the swing circle constraint formula, which is the cargo swing deviation corner point, and obtain the coordinates of the deviation corner point.

[0019] As a further description of the above technical solution: In step S4, based on the current cargo corner point coordinates, the swing deviation corner point coordinates and the ideal corner point coordinates, the swing deviation value and the tilt deviation value of the cargo hoisted by the bridge crane are calculated as follows:

[0020] Calculate the distance between the swing deviation corner point and the ideal corner point to obtain the swing deviation value;

[0021] Swing deviation value L d The calculation logic is Where X b , Y b are the X-axis coordinates and Y-axis coordinates of the swing deviation corner point in the two-dimensional coordinate system, where X O , Y O are the X-axis coordinate and Y-axis coordinate of the ideal corner point in the two-dimensional coordinate system respectively;

[0022] Calculate the distance between the current cargo corner point and the swing deviation corner point to obtain the tilt deviation value;

[0023] Tilt deviation value L q The calculation logic is Where X z , Y z They are respectively the X-axis coordinate and Y-axis coordinate of the current cargo corner point in the two-dimensional coordinate system.

[0024] As a further description of the above technical solution: In step S5, the operation risk coefficient of the bridge crane is calculated based on the swing deviation value and the tilt deviation value by joint integration as follows:

[0025] Calculate the independent risk coefficient of the swing deviation of the bridge crane operation;

[0026] Calculate the independent risk factor of tilt deviation in operation of bridge crane;

[0027] Calculate the risk factor of the superimposed influence of the swing deviation value and the tilt deviation value on the operation of the bridge crane;

[0028] The independent risk coefficient of swing deviation, the independent risk coefficient of tilt deviation and the superimposed influence risk coefficient are summed to obtain the bridge crane operation risk coefficient.

[0029] As a further description of the above technical solution: the independent risk coefficient of the swing deviation of the bridge crane is calculated as follows:

[0030] Based on the time series, multiple historical parameters of swing deviation values ​​are retrieved to obtain a swing deviation parameter set (L d1 , L d2 , L d3 ...L dn ), where L dn is the current swing deviation value;

[0031] The swing deviation value parameter set is used to make a swing deviation value scatter plot based on the time series, and each data point in the swing deviation value scatter plot is sequentially connected to obtain a swing deviation value trend plot;

[0032] Using the data points corresponding to the current swing deviation value as grouping marking lines on the swing deviation value trend graph, wherein the grouping marking lines and the horizontal coordinates of the swing deviation value trend graph are parallel to each other, collecting the third adjacent intersection point between the grouping marking line and the deviation value trend graph, and obtaining the horizontal axis coordinate corresponding to the third intersection point;

[0033] The correction interval of the swing deviation value is determined based on the horizontal axis coordinate corresponding to the third intersection point, the swing deviation revision value is obtained based on the correction interval, and the independent risk coefficient of the swing deviation is calculated and integrated.

[0034] As a further description of the above technical solution: based on the horizontal axis coordinate corresponding to the third intersection point, the swing deviation value correction interval is determined, based on the correction interval, the swing deviation revision value is obtained and the swing deviation independent risk coefficient is integrated and calculated as follows:

[0035] The horizontal axis coordinate corresponding to the third intersection point on the swing deviation value trend graph and the horizontal axis coordinate interval corresponding to the current swing deviation value on the swing deviation value trend graph are marked as the swing deviation value correction interval;

[0036] Based on the swing deviation correction interval, the corresponding data points on the swing deviation value scatter plot are collected and marked as: L xd1 , L xd2 , L xd3 ...L xdm ;

[0037] Swing deviation independent risk factor F b The calculation formula is: δ1 represents the weight of the impact of the object suspension swing on safe operation;

[0038] The specific calculation of independent risk coefficient of tilt deviation of bridge crane operation is:

[0039] The independent risk factor F of the tilt bias q The calculation formula is: q=L q *δ2, δ2 represents the weight of the object suspension inclination on safe operation, where δ2>δ1>0.

[0040] As a further description of the above technical solution: the risk coefficient of the superimposed influence of the swing deviation value and the tilt deviation value on the operation of the bridge crane is calculated as follows:

[0041] The calculation logic of the superposition impact risk coefficient is: Where j represents the weight of the combined impact of the swing deviation value and the tilt deviation value on the crane operation risk.

[0042] As a further description of the above technical solution: the evaluation and early warning of the operation status of the bridge crane based on the bridge crane operation risk coefficient is specifically as follows:

[0043] Set risk factor thresholds;

[0044] The current bridge crane operation risk coefficient is compared with the risk coefficient threshold. When the current bridge crane operation risk coefficient is greater than the risk coefficient threshold, an alarm is issued, and the swing deviation value and tilt deviation value corresponding to the current bridge crane operation risk coefficient are displayed.

[0045] A bridge crane operation status early warning system, which is used to implement the above-mentioned bridge crane operation status safety early warning method, comprises:

[0046] An operation monitoring module is arranged in the operation area of ​​the bridge crane to monitor the operation area of ​​the bridge crane and collect image information of the suspended cargo when the bridge crane is running in real time to obtain a cargo suspension state diagram;

[0047] The video analysis module is used to intelligently analyze the collected surveillance video data using AI recognition technology to identify personnel in the video content, and trigger an early warning when someone enters the operating area of ​​the bridge crane;

[0048] An image processing module is connected to the operation monitoring module for communication. The image processing module is used to retrieve a cargo suspension state diagram, establish a plane coordinate system with the bridge crane suspension connection node as the origin on the cargo suspension state diagram, and obtain the coordinates of the current cargo corner point;

[0049] An image analysis module, which is used to import the ideal cargo suspension state diagram into the plane coordinate system of the cargo suspension state diagram and calculate the coordinates of the cargo swing deviation corner points;

[0050] An integrated processing module, which is used to calculate the swing deviation value and the tilt deviation value of the cargo hoisted by the bridge crane based on the current cargo corner point coordinates, the swing deviation corner point coordinates and the ideal corner point coordinates;

[0051] The early warning processing module is used to retrieve the swing deviation value and the tilt deviation value to jointly integrate and calculate the operation risk coefficient of the bridge crane, and evaluate and warn the operation status of the bridge crane based on the operation risk coefficient of the bridge crane.

[0052] In the above technical scheme, the present invention provides a bridge crane operation status safety warning method and system. When the bridge crane operation status safety warning method and system monitor and warn the bridge crane operation status, it is obvious that when the bridge crane is suspended and lifting cargo, the safety risk of cargo swing and the safety risk of cargo suspension tilt have different effects. The prior art only conducts risk assessment through a single cargo position deviation, and has poor accuracy and safety. The present application obtains the swing deviation value and the tilt deviation value based on the current cargo suspension state and integrates and calculates the risk coefficient for assessment, which significantly improves the effect of risk warning, improves the safety of bridge crane operation, and determines the actual operation deviation at the same time, which is convenient for emergency processing during warning. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0054] Figure 1 A schematic diagram of a bridge crane operation status safety early warning method provided by an embodiment of the present invention;

[0055] Figure 2 A schematic diagram of a bridge crane operating status safety warning system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0056] In order to enable those skilled in the art to better understand the technical solution of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings.

[0057] Embodiment 1

[0058] See also Figure 1 The embodiment of the present invention provides a technical solution: a bridge crane operation status safety early warning method, comprising the following steps:

[0059] S1: Monitor the operation area of ​​the bridge crane, and collect image information of the suspended cargo when the bridge crane is running in real time to obtain a cargo suspension state diagram. Collecting image information of the suspended cargo when the bridge crane is running is an existing technology. Currently, all monitoring equipment has a screenshot function. The user sets the screenshot frequency and save path, and then captures the image of the monitoring video to obtain the cargo suspension state diagram. The specific process is not repeated here.

[0060] S2: On the collected cargo suspension state diagram, a plane coordinate system is established with the bridge crane suspension connection node as the origin, and the coordinates of the current cargo corner point are obtained, where the cargo corner point is the location point where the cargo edge corner is located, and the bridge crane suspension connection node is the origin, which is the rigid node where the suspension rope connected to the suspended object is connected to the bridge crane;

[0061] S3: Importing an ideal cargo suspension state diagram into the plane coordinate system, wherein the ideal cargo suspension state diagram is a cargo suspension state diagram in which the cargo does not swing or tilt under the current suspension state, and calculating the coordinates of the cargo swing deviation corner point based on the association of the ideal cargo suspension state diagram with the current cargo center suspension rope straight line;

[0062] S4: Based on the current cargo corner point coordinates, the swing deviation corner point coordinates and the ideal corner point coordinates, the swing deviation value and the tilt deviation value of the cargo hoisted by the bridge crane are calculated, and the swing deviation value and the tilt deviation value obtained historically are stored;

[0063] S5: The operation risk coefficient of the bridge crane is calculated based on the swing deviation value and the tilt deviation value, and the operation status of the bridge crane is evaluated and warned based on the operation risk coefficient of the bridge crane.

[0064] When monitoring and warning the operating status of a bridge crane, it is obvious that when a bridge crane is suspended and lifting cargo, the safety risk of cargo swinging is different from the safety risk of cargo tilting. The prior art only conducts risk assessment through a single cargo position deviation, which has poor accuracy and safety. This application obtains the swing deviation value and the tilt deviation value based on the current cargo suspension status, respectively, and integrates them to calculate the operating risk coefficient of the bridge crane, so as to evaluate and analyze the operating safety of the calculated bridge crane, thereby significantly improving the effect of risk warning, improving the safety of bridge crane operation, and determining the actual operating deviation at the same time, so as to facilitate emergency handling during warning.

[0065] Furthermore, the monitoring of the operating area of ​​the bridge crane in step S1 also includes: using AI recognition technology to intelligently analyze the video content of the collected monitoring video data to identify personnel, and immediately triggering an early warning mechanism when a person enters the operating area of ​​the bridge crane. Real-time monitoring of the operating area of ​​the bridge crane and detection of personnel intrusion are achieved, which significantly improves the safety of the workplace and reduces the probability of accidents.

[0066] In step S3, the coordinates of the corner points of the cargo swing deviation are calculated based on the current cargo center suspension rope straight line associated with the ideal cargo suspension state diagram:

[0067] S3.1: Calculate the deviation angle P between the current cargo center rope straight line and the Y axis in the plane coordinate system; it should be noted that the center rope in the ideal cargo suspension state diagram coincides with the Y axis in the plane coordinate system. When calculating the deviation angle P between the current cargo center rope and the Y axis in the plane coordinate system, the deviation angle between the current cargo center rope and the center rope in the ideal cargo suspension state diagram is obtained, that is, the cargo swing deviation angle in the current bridge crane operation state is obtained;

[0068] S3.2: Obtain the straight line between the plane coordinate origin and the cargo corner point of the ideal cargo suspension state diagram and mark it as the reference straight line, and calculate the distance between the plane coordinate origin and the corresponding corner point of the cargo;

[0069] S3.3: The reference straight line deflection angle P is used to obtain the swing straight line constraint formula, and a circle is drawn with the plane coordinate origin of the ideal cargo suspension state diagram as the center and the distance between the plane coordinate origin of the ideal cargo suspension state diagram and the corresponding corner point of the cargo as the radius to obtain the swing circle constraint formula;

[0070] S3.4: Calculate the intersection of the swing straight line constraint formula and the swing circle constraint formula, which is the cargo swing deviation corner point, and obtain the coordinates of the swing deviation corner point. The swing deviation corner point is the coordinate of the cargo corner point when the cargo only swings. When the suspended cargo tilts during the operation of the bridge crane, the coordinates of the swing deviation corner point are the same as the coordinates of the current cargo intersection.

[0071] In step S4, based on the current cargo corner coordinates, the swing deviation corner coordinates and the ideal corner coordinates, the swing deviation value and the tilt deviation value of the cargo hoisted by the bridge crane are calculated as follows:

[0072] Calculate the distance between the swing deviation corner point and the ideal corner point to obtain the swing deviation value;

[0073] Swing deviation value L d The calculation logic is Where X b , Y bare the X-axis coordinates and Y-axis coordinates of the swing deviation corner point in the two-dimensional coordinate system, where X O , Y O are the X-axis coordinate and Y-axis coordinate of the ideal corner point in the two-dimensional coordinate system respectively;

[0074] Calculate the distance between the current cargo corner point and the swing deviation corner point to obtain the tilt deviation value;

[0075] Tilt deviation value L q The calculation logic is Where X z , Y z They are respectively the X-axis coordinate and Y-axis coordinate of the current cargo corner point in the two-dimensional coordinate system.

[0076] In step S5, the operation risk coefficient of the bridge crane is calculated based on the swing deviation value and the tilt deviation value by joint integration as follows:

[0077] Calculate the independent risk coefficient of the swing deviation of the bridge crane operation;

[0078] Calculate the independent risk factor of tilt deviation in operation of bridge crane;

[0079] Calculate the risk factor of the superimposed influence of the swing deviation value and the tilt deviation value on the operation of the bridge crane;

[0080] The independent risk coefficient of swing deviation, the independent risk coefficient of tilt deviation and the superimposed influence risk coefficient are summed to obtain the bridge crane operation risk coefficient.

[0081] The independent risk coefficient of the swing deviation of the bridge crane is calculated as follows:

[0082] Based on the time series, multiple historical parameters of swing deviation values ​​are retrieved to obtain a swing deviation parameter set (L d1 , L d2 , L d3 ...L dn ), where L dn is the current swing deviation value;

[0083] The swing deviation value parameter set is used to make a swing deviation value scatter plot based on the time series, and each data point in the swing deviation value scatter plot is sequentially connected to obtain a swing deviation value trend plot;

[0084] Using the data points corresponding to the current swing deviation value as grouping marking lines on the swing deviation value trend graph, wherein the grouping marking lines and the horizontal coordinates of the swing deviation value trend graph are parallel to each other, collecting the third adjacent intersection point between the grouping marking line and the deviation value trend graph, and obtaining the horizontal axis coordinate corresponding to the third intersection point;

[0085] The correction interval of the swing deviation value is determined based on the horizontal axis coordinate corresponding to the third intersection point, the swing deviation revision value is obtained based on the correction interval, and the independent risk coefficient of the swing deviation is calculated and integrated.

[0086] When the bridge crane is in operation, the suspended cargo swings. At this time, the swing deviation value calculated based on the cargo suspension status diagram collected in real time has a large difference due to the different swing cycles. That is, it is impossible to accurately evaluate the independent risk coefficient of the swing deviation based on the swing deviation value obtained by calculating the cargo swing at the current single moment. The present application prepares a swing deviation value trend graph by retrieving the historically associated swing deviation values, determines the swing deviation value correction interval by grouping marking lines, and obtains the swing deviation revised value based on the integration of the swing deviation value data points corresponding to the determined swing deviation value correction interval, and integrates and calculates the independent risk coefficient of the swing deviation, thereby significantly improving the accuracy and rationality of the evaluation of the independent risk coefficient of the swing deviation, and improving the effect of the safety early warning of the operating status of the bridge crane.

[0087] The swing deviation correction interval is determined based on the horizontal axis coordinate corresponding to the third intersection point. The swing deviation revision value is obtained based on the correction interval and the swing deviation independent risk coefficient is calculated and integrated as follows:

[0088] The horizontal axis coordinate corresponding to the third intersection point on the swing deviation value trend graph and the horizontal axis coordinate interval corresponding to the current swing deviation value on the swing deviation value trend graph are marked as the swing deviation value correction interval;

[0089] Based on the swing deviation correction interval, the corresponding data points on the swing deviation value scatter plot are collected and marked as: L xd1 , L xd2 , L xd3 ...L xdm ;

[0090] Swing deviation independent risk factor F b The calculation formula is: δ1 represents the weight of the impact of the object suspension swing on safe operation;

[0091] The specific calculation of independent risk coefficient of tilt deviation of bridge crane operation is:

[0092] The independent risk factor F of the tilt bias q The calculation formula is: q =L q *δ2, δ2 represent the weight of the hanging tilt of the object on the safe operation, where δ2>δ1>0. δ1 and δ2 are determined according to the actual situation, such as through expert scoring, historical data analysis or experimental measurement. These weight values ​​reflect the actual impact of the swing deviation and tilt deviation on the safe operation of the bridge crane.

[0093] The specific risk factors of the superimposed influence of the swing deviation value and the tilt deviation value on the operation of the bridge crane are calculated as follows:

[0094] The calculation logic of the superposition impact risk coefficient is: Where j represents the weight of the combined impact of the swing deviation value and the tilt deviation value on the crane operation risk.

[0095] The specific evaluation and early warning of the operation status of the bridge crane based on the bridge crane operation risk coefficient are as follows:

[0096] Set risk factor thresholds;

[0097] The current bridge crane operation risk coefficient is compared with the risk coefficient threshold. When the current bridge crane operation risk coefficient is greater than the risk coefficient threshold, an alarm is issued, and the swing deviation value and tilt deviation value corresponding to the current bridge crane operation risk coefficient are displayed.

[0098] The present embodiment provides a method for early warning of the operating status of a bridge crane. By independently analyzing the current cargo suspension status to obtain an independent risk coefficient for swing deviation, an independent risk coefficient for tilt deviation and a superimposed impact risk coefficient, and integrating and evaluating the operating risk coefficient of the bridge crane, the effect of risk early warning is significantly improved, the safety of the operation of the bridge crane is improved, and the actual operating deviation is determined at the same time, which is convenient for emergency handling during early warning.

[0099] Embodiment 2:

[0100] See also Figure 2 The embodiment of the present invention provides another technical solution, a bridge crane operation status early warning system, which is used to implement the above-mentioned bridge crane operation status safety early warning method, wherein the bridge crane operation status early warning system includes:

[0101] An operation monitoring module is arranged in the operation area of ​​the bridge crane to monitor the operation area of ​​the bridge crane and collect image information of the suspended cargo when the bridge crane is running in real time to obtain a cargo suspension state diagram;

[0102] The video analysis module is used to intelligently analyze the collected surveillance video data using AI recognition technology to identify personnel in the video content, and trigger an early warning when someone enters the operating area of ​​the bridge crane;

[0103] An image processing module is connected to the operation monitoring module for communication. The image processing module is used to retrieve a cargo suspension state diagram, establish a plane coordinate system with the bridge crane suspension connection node as the origin on the cargo suspension state diagram, and obtain the coordinates of the current cargo corner point;

[0104] An image analysis module, which is used to import the ideal cargo suspension state diagram into the plane coordinate system of the cargo suspension state diagram and calculate the coordinates of the cargo swing deviation corner points;

[0105] An integrated processing module, which is used to calculate the swing deviation value and the tilt deviation value of the cargo hoisted by the bridge crane based on the current cargo corner point coordinates, the swing deviation corner point coordinates and the ideal corner point coordinates;

[0106] The early warning processing module is used to retrieve the swing deviation value and the tilt deviation value to jointly integrate and calculate the bridge crane operation risk coefficient, and evaluate and warn the bridge crane operation status based on the bridge crane operation risk coefficient. The specific early warning processing modules include: a distributed risk calculation module, which is used to distribute and calculate the independent risk coefficient of the bridge crane operation swing deviation, the independent risk coefficient of the bridge crane operation tilt deviation, and the risk coefficient of the superimposed influence of the swing deviation value and the tilt deviation value on the bridge crane operation, and sum them up to obtain the bridge crane operation risk coefficient; a comparison alarm module, which is used to compare the bridge crane operation risk coefficient with the risk coefficient threshold, and alarm when the bridge crane operation risk coefficient is greater than the risk coefficient threshold.

[0107] The above description is only by way of illustration of certain exemplary embodiments of the present invention. It is undoubted that those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the above drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. A bridge crane operation status safety early warning method, characterized in that: The following steps are involved: S1: Monitor the operation area of ​​the bridge crane, collect image information of the suspended cargo when the bridge crane is running in real time, and obtain the cargo suspension status diagram; S2: Establish a plane coordinate system with the bridge crane suspension connection node as the origin on the collected cargo suspension state diagram to obtain the coordinates of the current cargo corner point; S3: Import the ideal cargo suspension state diagram into the plane coordinate system, and calculate the coordinates of the cargo swing deviation corner point based on the current cargo center suspension rope straight line associated with the ideal cargo suspension state diagram; S4: Based on the current cargo corner point coordinates, the swing deviation corner point coordinates and the ideal corner point coordinates, the swing deviation value and the tilt deviation value of the cargo hoisted by the bridge crane are calculated, and the swing deviation value and the tilt deviation value obtained historically are stored; S5: The operation risk coefficient of the bridge crane is calculated based on the swing deviation value and the tilt deviation value, and the operation status of the bridge crane is evaluated and warned based on the operation risk coefficient of the bridge crane.

2. A bridge crane operation status safety early warning method according to claim 1, characterized in that: The monitoring of the operating area of ​​the bridge crane in step S1 further includes: The collected surveillance video data is intelligently analyzed using AI recognition technology to identify personnel in the video content. When it is detected that someone has entered the operating area of ​​the bridge crane, the early warning mechanism is immediately triggered.

3. A bridge crane operation status safety early warning method according to claim 1, characterized in that: In step S3, the coordinates of the corner points of the cargo swing deviation are calculated based on the current cargo center suspension rope straight line associated with the ideal cargo suspension state diagram: S3.1: Calculate the deviation angle P between the current cargo center sling straight line and the Y axis in the plane coordinate system; S3.2: Obtain the straight line between the plane coordinate origin and the cargo corner point of the ideal cargo suspension state diagram and mark it as the reference straight line, and calculate the distance between the plane coordinate origin and the corresponding corner point of the cargo; S3.3: The reference straight line deflection angle P is used to obtain the swing straight line constraint formula, and a circle is drawn with the plane coordinate origin of the ideal cargo suspension state diagram as the center and the distance between the plane coordinate origin of the ideal cargo suspension state diagram and the corresponding corner point of the cargo as the radius to obtain the swing circle constraint formula; S3.4: Calculate the intersection of the swing straight line constraint formula and the swing circle constraint formula, which is the cargo swing deviation corner point, and obtain the coordinates of the deviation corner point.

4. A bridge crane operation status safety early warning method according to claim 3, characterized in that: In step S4, based on the current cargo corner coordinates, the swing deviation corner coordinates and the ideal corner coordinates, the swing deviation value and the tilt deviation value of the cargo hoisted by the bridge crane are calculated as follows: Calculate the distance between the swing deviation corner point and the ideal corner point to obtain the swing deviation value; Swing deviation value L d The calculation logic is Where X b , Y b are the X-axis coordinates and Y-axis coordinates of the swing deviation corner point in the two-dimensional coordinate system, where X O , Y O are the X-axis coordinate and Y-axis coordinate of the ideal corner point in the two-dimensional coordinate system respectively; Calculate the distance between the current cargo corner point and the swing deviation corner point to obtain the tilt deviation value; Tilt deviation value L q The calculation logic is Where X z , Y z They are respectively the X-axis coordinate and Y-axis coordinate of the current cargo corner point in the two-dimensional coordinate system.

5. A bridge crane operation status safety early warning method according to claim 4, characterized in that: In step S5, the operation risk coefficient of the bridge crane is calculated based on the swing deviation value and the tilt deviation value by joint integration as follows: Calculate the independent risk coefficient of the swing deviation of the bridge crane operation; Calculate the independent risk factor of tilt deviation in operation of bridge crane; Calculate the risk factor of the superimposed influence of the swing deviation value and the tilt deviation value on the operation of the bridge crane; The independent risk coefficient of swing deviation, the independent risk coefficient of tilt deviation and the superimposed influence risk coefficient are summed to obtain the bridge crane operation risk coefficient.

6. A bridge crane operation status safety early warning method according to claim 5, characterized in that: The independent risk coefficient of the swing deviation of the bridge crane is calculated as follows: Based on the time series, multiple historical parameters of swing deviation values ​​are retrieved to obtain a swing deviation parameter set (L d1 , L d2 , L d3 ...L dn ), where L dn is the current swing deviation value; The swing deviation value parameter set is used to create a swing deviation value scatter plot based on the time series, and each data point in the swing deviation value scatter plot is sequentially connected to obtain a swing deviation value trend plot; Using the data points corresponding to the current swing deviation value as grouping marking lines on the swing deviation value trend graph, wherein the grouping marking lines and the horizontal coordinates of the swing deviation value trend graph are parallel to each other, collecting the third adjacent intersection point between the grouping marking line and the deviation value trend graph, and obtaining the horizontal axis coordinate corresponding to the third intersection point; The swing deviation value correction interval is determined based on the horizontal axis coordinate corresponding to the third intersection point, the swing deviation revision value is obtained based on the correction interval, and the swing deviation independent risk coefficient is calculated and integrated.

7. A method for early warning of operating status safety of a bridge crane according to claim 6, characterized in that: The swing deviation correction interval is determined based on the horizontal axis coordinate corresponding to the third intersection point. The swing deviation revision value is obtained based on the correction interval and the swing deviation independent risk coefficient is calculated and integrated as follows: The horizontal axis coordinate corresponding to the third intersection point on the swing deviation value trend graph and the horizontal axis coordinate interval corresponding to the current swing deviation value on the swing deviation value trend graph are marked as the swing deviation value correction interval; Based on the swing deviation correction interval, the corresponding data points on the swing deviation value scatter plot are collected and marked as: L xd1 , L xd2 , L xd3 ...L xdm ; Swing deviation independent risk factor F b The calculation formula is: δ1 represents the weight of the impact of the object suspension swing on safe operation; The specific calculation of independent risk coefficient of tilt deviation of bridge crane operation is: The independent risk factor F of the tilt bias q The calculation formula is: q =L q *δ2, δ2 represents the weight of the object suspension inclination on safe operation, where δ2>δ1>0.

8. A method for early warning of operating status safety of a bridge crane according to claim 7, characterized in that: The specific risk factors of the superimposed influence of the swing deviation value and the tilt deviation value on the operation of the bridge crane are calculated as follows: The calculation logic of the superposition impact risk coefficient is: Where j represents the weight of the combined impact of the swing deviation value and the tilt deviation value on the crane operation risk.

9. The method for early warning of operating status safety of a bridge crane according to claim 1, characterized in that: The specific evaluation and early warning of the operation status of the bridge crane based on the bridge crane operation risk coefficient are as follows: Set risk factor thresholds; The current bridge crane operation risk coefficient is compared with the risk coefficient threshold. When the current bridge crane operation risk coefficient is greater than the risk coefficient threshold, an alarm is issued, and the swing deviation value and tilt deviation value corresponding to the current bridge crane operation risk coefficient are displayed.

10. A bridge crane operation status early warning system, which is used to implement the bridge crane operation status safety early warning method according to any one of claims 1 to 9, characterized in that: include: An operation monitoring module is arranged in the operation area of ​​the bridge crane to monitor the operation area of ​​the bridge crane and collect image information of the suspended cargo when the bridge crane is running in real time to obtain a cargo suspension state diagram; The video analysis module is used to intelligently analyze the collected surveillance video data using AI recognition technology to identify personnel in the video content, and trigger an early warning when someone enters the operating area of ​​the bridge crane; An image processing module is connected to the operation monitoring module for communication. The image processing module is used to retrieve a cargo suspension state diagram, establish a plane coordinate system with the bridge crane suspension connection node as the origin on the cargo suspension state diagram, and obtain the coordinates of the current cargo corner point; An image analysis module, which is used to import the ideal cargo suspension state diagram into the plane coordinate system of the cargo suspension state diagram and calculate the coordinates of the cargo swing deviation corner points; An integrated processing module, which is used to calculate the swing deviation value and the tilt deviation value of the cargo hoisted by the bridge crane based on the current cargo corner point coordinates, the swing deviation corner point coordinates and the ideal corner point coordinates; The early warning processing module is used to retrieve the swing deviation value and the tilt deviation value to jointly integrate and calculate the operation risk coefficient of the bridge crane, and evaluate and warn the operation status of the bridge crane based on the operation risk coefficient of the bridge crane.

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