A tower crane load distributed intelligent monitoring device

Abstract

The present invention discloses a tower crane load distributed intelligent monitoring device, which relates to the technical field of tower crane load monitoring. The present invention includes a load unit, a wind speed unit, a collection module, a processing unit and a monitoring platform. The load unit is composed of m load sensors, and the load sensors are arranged inside the connecting rod. The load sensors are used to obtain the load information of the connecting rod where they are located. The wind speed unit is composed of n anemometers. The m load sensors and the n anemometers form a distributed monitoring network, and the data is uniformly obtained by the collection module. The anemometers are respectively installed at both ends of the boom and the top of the attachment frame. The anemometers are used to obtain the wind speed information at both ends of the boom and the position where the attachment frame is located. By setting a distributed wind speed unit and load unit, the present invention is applicable to multiple tower cranes operating simultaneously. By setting different collection frequencies, on the one hand, it can reduce the collection of invalid data, and on the other hand, it can timely push load warnings.

Description

Technical Field

[0001] The present invention relates to the technical field of tower crane load monitoring, and specifically to a distributed intelligent monitoring device for tower crane loads. Background Art

[0002] There are generally potential safety hazards in the attachment devices of tower cranes: First, under the action of alternating loads, abnormal vibrations are likely to occur in the attachment frame. Such continuous dynamic loads will not only cause progressive loosening of the connecting bolts of the attachment frame and the tower body standard sections, but may even lead to plastic deformation or structural damage of the connecting nodes of the standard sections in severe cases. Second, when the attachment design does not meet the standard requirements, the overall stability of the tower body is insufficient, resulting in structural damage and causing tower crane collapse accidents. Third, there are design defects in the current stress checking methods, mainly manifested as over-reliance on the theoretical load data provided in the manufacturer's instructions of the tower crane. Coupled with the complexity of the spatial positioning of the attachment device at the construction site, the actual force borne by the building structure at the attachment anchoring point far exceeds the theoretical calculated value, and finally local tensile cracking and crushing damage of the building structure in the attachment anchoring area occur under overloaded conditions. Fourth, the manufacturer purchases design drawings, lacks design capabilities and technical strength, and the load at the attachment point provided in the instructions is inaccurate or even too small. The user unit uses the load data in the instructions to check the force on the building structure at the attachment point, which is much smaller than the actual force at the attachment anchoring point. During the use of the tower crane, the structure of the building structure at the attachment anchoring point is damaged, or the attachment device is damaged due to force, and in severe cases, it will lead to tower crane collapse. Fifth, the load at the attachment point provided in the manufacturer's instructions does not take the non-operating state wind load value in coastal areas according to the "Tower Crane Design Code" (GB / T 13752-2017) during design. As a result, checking the force on the attachment anchoring point according to the load in the instructions is inaccurate. When the tower crane encounters strong winds or typhoons, the force on the building structure at the attachment anchoring point does not meet the requirements, resulting in structural damage or insufficient force on the attachment rod. The attachment of the tower crane loses its acting force on the tower body, the overall stability of the tower body is insufficient, and the tower body structure twists and deforms, breaks at the waist, resulting in tower crane collapse accidents. Sixth, the wind-induced vibration effect formed by the coupling of environmental wind loads and the structural natural vibration frequency will dynamically induce out-of-plane buckling instability of ultra-long attachment rods. Such instability is sudden and the consequences of damage are serious.

[0003] Existing tower crane load monitoring systems are not applicable to load monitoring when multiple tower cranes are operating. When there are multiple tower cranes operating simultaneously at the construction site, due to the distribution positions of the fixed points of each tower crane and the reasons of wind speed and direction, they will affect each other. At this time, the load monitoring of a single tower crane will produce errors due to incomplete monitoring, which is not conducive to on-site construction safety. At the same time, a large amount of invalid data will be generated when multiple tower cranes are monitored simultaneously. It is necessary to intelligently adjust the acquisition frequency of load data according to the on-site construction environment, so as to quickly and accurately obtain load abnormal data. Therefore, designing a distributed monitoring of tower crane loads is a technical problem that needs to be solved by those skilled in the art. Summary of the Invention

[0004] Aiming at the deficiencies of the prior art, the present invention provides a distributed intelligent monitoring device for tower crane loads, which solves the problems raised in the above background technology.

[0005] To achieve the above objectives, the present invention is realized through the following technical solutions: A distributed intelligent monitoring device for tower crane loads includes a tower body. A number of attachment frames are fixedly connected to the periphery of the tower body. The top of the tower body is rotatably connected to a boom through a slewing bearing. A number of connecting rods are fixedly connected to the periphery of the attachment frames. One end of each of the number of connecting rods is fixedly connected to a connecting member, and the connecting member is fixed to the outer surface of the building by bolts. It also includes a load unit, a wind speed unit, a collection module, a processing unit, and a monitoring platform. The load unit consists of m load sensors, and the load sensors are arranged inside the connecting rods. The load sensors are used to obtain the load information of the corresponding connecting rods where they are located. The wind speed unit consists of n anemometers. The m load sensors and the n anemometers form a distributed monitoring network, and the data is uniformly obtained by the collection module. The anemometers are respectively installed at both ends of the boom and the top of the attachment frames. The anemometers are used to obtain the wind speed information of the corresponding positions at both ends of the boom and the attachment frames.

[0006] The output ends of the load unit and the wind speed unit are both connected to the input end of the collection module. The output end of the collection module is connected to the input end of the processing unit. A communication is established between the port of the processing unit and the port of the monitoring platform.

[0007] The collection module respectively obtains the load information of the load unit and the wind speed information of the wind speed unit and transmits them to the processing unit. The operator manually inputs the position information of each load sensor and anemometer to the processing unit through the monitoring platform, and at the same time inputs the engineering drawings of the building and the tower crane on the ground. The processing unit establishes a digital three-dimensional model and a wind flow model based on the position information, the engineering drawings, and the wind speed information, and at the same time marks the load monitoring points and the wind speed monitoring points and calculates the fluid distribution curve. The processing unit predicts the predicted values of each load sensor based on the wind flow model. The processing unit compares the load information and the predicted values of each load sensor to analyze the abnormal values of the load information. The processing unit automatically adjusts the collection frequency of the collection module according to the wind speed information.

[0008] Further, the specific content of establishing the digital three-dimensional model is as follows:

[0009] The processing unit establishes a spatial coordinate system in the Ansys Fluent general fluid mechanics simulation software according to the position information. The spatial coordinate system has three dimensions: the x-axis, the y-axis, and the z-axis, with the unit being meters. The processing unit establishes digital 3D models of the tower crane and the building in the spatial coordinate system according to the engineering drawings. The processing unit marks the points where the load sensors are installed in the digital 3D model as load monitoring points according to the position information of the load sensors, and marks the positions where the anemometers are installed in the digital 3D model as wind speed monitoring points according to the position information of the anemometers. When the orientation of the tower crane's boom changes, the anemometers at both ends of the boom change their positions, and the dynamic position P3 (x3, y3, z3) of the anemometer changes. The processing unit updates the digital 3D model according to the changed position of the anemometer and the orientation of the tower crane.

[0010] Furthermore, the acquisition methods of the position information and the engineering drawings are as follows:

[0011] The position information of the load sensors and the position information of the anemometers both include three dimensions: the x-axis, the y-axis, and the z-axis. The position information of the anemometers is divided into a static position and a dynamic position. The anemometer installed on the attachment frame corresponds to the static position, and the anemometers installed at both ends of the boom correspond to the dynamic position. When the orientation of the boom changes, the processing unit calculates the dynamic position after the change of the anemometer position according to the rotation angle of the boom and the engineering drawings. The processing unit can obtain the rotation angle of the tower crane's boom in the cab through the monitoring platform. The engineering drawings record the length of the boom. The operator measures the position information of each anemometer using surveying tools, and the surveying tools are a level and a laser rangefinder;

[0012] The operator marks the measured position information of the load sensors as P1 (x1, y1, z1), marks the static position measured by the anemometer on the attachment frame as P2 (x2, y2, z2), and marks the dynamic position measured by the anemometers at both ends of the boom as P3 (x3, y3, z3);

[0013] The operator manually inputs the marked position information into the monitoring platform through an input device. The input device is a general keyboard and mouse. The monitoring platform is connected to a display for video output. The operator can achieve interaction by observing the content on the display. At the same time, the operator manually inputs the engineering drawings of the building and the tower crane on the ground surface into the monitoring platform through the input device. The building in the engineering drawings includes the building body, as well as the scaffolding and safety nets surrounding the building. The monitoring platform uniformly transmits the input position information and engineering drawings to the processing unit.

[0014] Furthermore, the specific content of establishing the wind flow model is as follows:

[0015] In the digital three-dimensional model, the processing unit divides the simulation calculation area of each tower crane with the tower body of each tower crane as the center and the end of the long boom of each tower crane as the radius. If the sweeping areas of the ends of the long booms of two tower cranes overlap vertically, the simulation calculation areas of the two tower cranes are separated by the connecting line of the intersection points of the two overlapping circles.

[0016] The processing unit presets a system of equations for wind flow control and inputs the wind speed information of each wind speed monitoring point into the following system of equations:

[0017]

[0018] Calculate the fluid distribution curve. is the rate of change of a single physical quantity, where the physical quantity is air density , the wind speed information u, and the time t. The first formula of the system of equations from top to bottom is the continuity equation, based on the mass conservation of the wind fluid, that is, the mass of a given volume of fluid remains constant. is the air density. At a standard atmospheric pressure of 15°C, the air density is , t is the time collected by the anemometer, and the time t collected by the anemometer is uniformly obtained by the acquisition module along with the wind speed information. u is the wind speed information, which is specifically the wind vector in the fluid simulation calculation. The wind vector includes wind speed and wind direction. ∇ is the built-in gradient operator of the CFD simulation software, used to describe the rate of change of the fluid distribution curve in the space coordinate system. The second formula of the system of equations from top to bottom is the momentum equation, based on Newton's second law. The rate of change of momentum within a fluid volume is equal to the sum of the forces acting on it, including pressure and gravity. For an incompressible fluid with a constant viscosity, where p is the static pressure, which is specifically the atmospheric pressure data in the fluid simulation calculation and can be obtained by the processing unit through the monitoring platform to access the external network. v is the kinematic viscosity of air. Generally, the kinematic viscosity of air is at standard atmospheric pressure. is the acceleration due to gravity, generally taking the standard value . The third formula of the system of equations from top to bottom is the energy equation, based on the first law of thermodynamics. The change in the total energy of the fluid is equal to the energy added or removed from the system. Among them, is the total enthalpy, which can be calculated based on the temperature and specific heat of air. , cp is the specific heat at constant pressure of air, which is at normal temperature. λ is the thermal conductivity of air. The thermal conductivity of air is related to temperature and is at normal temperature. T is the current ambient temperature, which can be obtained by the processing unit through the monitoring platform to access the external network. is an external heat source. In the simulation calculation, there is no special heat source, and the general value is 0. It should be noted that the equations are used to set the simulation environment conditions of the fluid, and calculate the influence of the change rate of various physical quantities in the simulation environment on the wind fluid, such as wind speed, wind direction, temperature, density and pressure. The direction change of the fluid distribution curve in the digital three-dimensional model is still calculated by the simulation software according to the principles of fluid mechanics;

[0019] When the fluid distribution curves of all simulation calculation areas are all calculated, all fluid distribution curves are gathered to obtain the distribution and change trend of the wind force, which is marked as the wind force flow model. Among them, when the orientation of the tower crane's boom starts to change, the dynamic positions P3(x3, y3, z3) of the anemometers at both ends of the boom change, and the processing unit updates the digital three-dimensional model in real time. The fluid distribution curves in the simulation calculation area are updated synchronously with the digital three-dimensional model, and the simulation software recalculates the fluid distribution curves and incorporates them into the wind force flow model to replace the previous fluid distribution curves.

[0020] Furthermore, the specific content of the processing unit's calculation of the predicted value includes the following:

[0021] The processing unit associates each load monitoring point with the anemometer monitoring point closest to the position of the load monitoring point according to the position information of the load monitoring point and the anemometer monitoring point. The processing unit establishes a fitting curve graph of the predicted value based on each load monitoring point, with the abscissa being the wind speed value and the ordinate being the load value. The processing unit inputs the wind speed value in the wind speed information collected at different time points and the load value in the load information collected at the same time point into the fitting curve graph. The circular scatter points in the fitting curve graph are the wind speed values and load values obtained by the acquisition module at different time points;

[0022] In each fitting curve graph, the processing unit sequentially marks the scatter point coordinates (ui, Fi) from left to right, where i = 1, 2, 3, 4,..., g, and g is the number of scatter points in the fitting curve graph. Among them, ui is the wind speed value, and Fi is the load value corresponding to the wind speed value. The processing unit sets the fitting formula , and uses the sum of squared errors formula to calculate the specific values of a, b, and c. The processing unit assigns the calculated values of a, b, and c to the fitting formula. The u in the fitting formula is the wind speed value in the wind speed information. Of course, if the wind speed value and the load value show a linear change relationship, the fitting formula is also applicable, and the value of c in the fitting formula is 0;

[0023] The processing unit substitutes the wind speed value in the collected wind speed information into the fitting formula to calculate F(u). The processing unit marks the calculated F(u) as the predicted value of the load monitoring point at the current time point.

[0024] Furthermore, the specific content of the abnormal value analysis process of the load information is as follows:

[0025] The processing unit obtains the load information of each load monitoring point in the acquisition module in real time, calculates the error value by subtracting the predicted value corresponding to the load information value of each load monitoring point at the same time point, and the processing unit adds up and averages the error values of all load monitoring points at all time points to obtain the standard error;

[0026] The processing unit adds up and averages the error values calculated at different time points of the same load monitoring point to obtain the node error. The larger the node error value, the higher the possibility of abnormal values occurring at this load monitoring point. On the contrary, the smaller the node error, the closer the load information value of this load monitoring point is to the predicted value, and the lower the possibility of abnormal values occurring. The processing unit subtracts the error value of each load monitoring point from the error values of the two adjacent load monitoring points respectively, and then adds up the subtracted values to obtain the local error. The adjacent load monitoring points are the other two load monitoring points closest to this load monitoring point. The larger the local error value, the higher the possibility of abnormal values occurring in the area where this load monitoring point is located. On the contrary, the smaller the local error, the closer the load information values of this load monitoring point and the adjacent load monitoring points are, and the lower the possibility of abnormal values occurring;

[0027] The processing unit establishes Condition 1 and Condition 2. Condition 1 is that the value of the node error is greater than or equal to the standard error, and Condition 2 is that the value of the local error is greater than or equal to the standard error. When both Condition 1 and Condition 2 are not satisfied, it means that the load information of this load monitoring point is normal, and the processing unit does not perform any operation. When either Condition 1 or Condition 2 is satisfied, it means that the load information of this load monitoring point may be abnormal and requires manual intervention for judgment. The processing unit marks the load information that triggers Condition 1 or Condition 2 as a suspicious value, and the processing unit pushes the suspicious value to the monitoring platform for subsequent manual investigation and confirmation. When both Condition 1 and Condition 2 are satisfied, the processing unit marks the load information that triggers Condition 1 and Condition 2 as an abnormal value, and the processing unit pushes the abnormal value to the monitoring platform for the operator to view.

[0028] Furthermore, the acquisition frequency adjustment process specifically includes the following content:

[0029] The processing unit sets and initializes the dynamically changing acquisition frequencies Q1, Q2, and Q3 respectively. The acquisition frequencies Q1, Q2, and Q3 can be directly switched between each other. The dynamic change range of the acquisition frequencies Q1, Q2, and Q3 is not greater than 3 times of their own initial values and not less than 0.33 times of their own initial values. The acquisition frequency Q1 corresponds to when the tower crane is in a static state or the wind speed level is safe, the acquisition frequency Q2 corresponds to when the tower crane is in operation or the wind speed level is general, and the acquisition frequency Q3 corresponds to when the tower crane is in the wind speed warning level;

[0030] The processing unit sets the adjustment factor J, and the value range of the adjustment factor J is [0.8, 1.2]. The processing unit calculates the average load change rate qF of all load monitoring points and the average wind speed change rate qu of all wind speed monitoring points respectively. The processing unit calculates the specific value of the adjustment factor J according to the formula Since the numerical change of the load information has a greater impact on the sum and monitoring results, the distribution weight of the average load change rate qF is larger;

[0031] The processing unit multiplies the adjustment factor J by the acquisition frequencies Q1, Q2, and Q3 respectively to obtain the corresponding acquisition frequencies Q1, Q2, and Q3 of the acquisition module during the next acquisition. When the tower crane is static or the wind speed level is safe, the load intensity is weak. Therefore, in order to save the processing performance of the acquisition module and the processing unit, and at the same time avoid too many invalid acquisition data (too many invalid acquisition data is likely to reduce the probability of abnormal data being noticed), it is necessary to reduce the acquisition frequency Q1. Slightly adjusting the acquisition frequency Q1 with the adjustment factor J can meet the monitoring of the load information and the wind speed information. Similarly, when the tower crane is in operation or the wind speed level is general, the load intensity of the tower crane is average at this time, and a higher acquisition frequency Q2 is required to acquire the load information and the wind speed information. When the wind speed level is in warning, the wind force is strong at this time and it is not suitable for the tower crane to operate, and the load intensity of the tower crane is prone to overload. The highest acquisition frequency Q3 is required to monitor the load information and the wind speed information in real time, so as to improve the overall response speed of the system and issue the load warning information in time.

[0032] Furthermore, the processing unit judges the wind speed level according to the wind speed information, and the specific content is as follows:

[0033] The processing unit sends a weather acquisition request to the monitoring platform. The monitoring platform searches for the weather at the current location externally and sends it to the processing unit. The monitoring platform is specifically a network-connected Windows computer. The operator can use input devices such as a mouse and keyboard to input data to the monitoring platform, and the display screen integrated on the monitoring platform can display and push the load warning information;

[0034] The processing unit obtains the wind speed at the current location from the weather and marks it as the first reference value. The processing unit extracts the wind speed information values of each anemometer from the acquisition module and adds them up to obtain the average value as the second reference value. The processing unit adds the first reference value and the second reference value and takes the average to obtain the third reference value. The units of the first reference value, the second reference value, and the third reference value are all m / s;

[0035] The processing unit presets a first judgment threshold value and a second judgment threshold value. The first judgment threshold value is 11.8, and the second judgment threshold value is 6. When the value of the third reference value is greater than or equal to the first judgment threshold value, the processing unit marks the wind speed level as a warning. When the value of the third reference value is less than the first judgment threshold value and greater than or equal to the second judgment threshold value, the processing unit marks the wind speed level as normal. When the value of the third reference value is less than the second judgment threshold value, the processing unit marks the wind speed level as safe.

[0036] Furthermore, the calculation processes of the average load change rate qF and the average wind speed change rate qu are as follows:

[0037] The processing unit extracts the load information values of each load monitoring point, divides the currently collected load information value by the previously collected load information value to obtain the node load change rate of this load monitoring point, and the processing unit adds up and averages the node load change rates of each load monitoring point to obtain the average load change rate qF;

[0038] The processing unit extracts the wind speed information values of each wind speed monitoring point, divides the currently collected wind speed information value by the previously collected wind speed information value to obtain the node wind speed change rate of this wind speed monitoring point, and the processing unit adds up and averages the node wind speed change rates of each wind speed monitoring point to obtain the average wind speed change rate qu.

[0039] Furthermore, the specific content of the switching determination of the acquisition frequencies Q1, Q2, and Q3 is as follows:

[0040] The processing unit obtains the operating state of the tower crane cab through the monitoring platform. The monitoring platform establishes data communication with the tower crane cab. When the tower crane cab is in the operating state or the wind speed level is normal, the processing unit controls the acquisition module to use the acquisition frequency Q2 to obtain the load information and the wind speed information. When the tower crane cab is in the non-operating state or the wind speed level is safe, the processing unit controls the acquisition module to use the acquisition frequency Q1 to obtain the load information and the wind speed information. When the wind speed level is a warning, at this time the tower crane is prohibited from operating, and the processing unit controls the acquisition module to use the acquisition frequency Q3 to obtain the load information and the wind speed information.

[0041] Furthermore, the connecting rods are connected using fixing pins. Inside the fixing pins, they are fixedly connected to the load sensors through elastic metal sheets. The load received by the fixing pins causes the elastic metal sheets to deform, and the load sensors convert the deformation amount of the elastic metal sheets into load information. A transmission line is provided at the tail of the fixing pins, and the load sensors send the load information outward through the transmission line.

[0042] The present invention has the following beneficial effects:

[0043] 1. By setting up distributed wind speed units and load units, the load monitoring system can be applied to the situation where multiple tower cranes operate simultaneously, avoiding errors in load monitoring caused by mutual influence between tower cranes and improving the reliability of load monitoring data.

[0044] 2. By setting different acquisition frequencies, the acquisition frequencies of load information and wind speed information can be dynamically adjusted under different circumstances. On the one hand, it can reduce the acquisition of invalid data, and on the other hand, it can improve the response speed of the system and push load warnings in a timely manner.

[0045] Of course, it is not necessary for any product implementing the present invention to achieve all the above-mentioned advantages simultaneously. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention, and those of ordinary skill in the art can also obtain other drawings based on these drawings without creative efforts.

[0047] Figure 1 It is the system block diagram of a distributed intelligent load monitoring device for a tower crane according to the present invention;

[0048] Figure 2 It is the schematic diagram of the distribution structure of the anemometer according to the present invention;

[0049] Figure 3 It is the schematic diagram of the distribution structure of the load sensor according to the present invention;

[0050] Figure 4 It is the fitting curve graph of the predicted value according to the present invention;

[0051] Figure 5 It is the schematic diagram of the structure of the fixing pin and the connecting rod according to the present invention;

[0052] Figure 6 It is the sectional structure schematic diagram of the fixing pin according to the present invention;

[0053] Figure 7 It is the internal partial schematic diagram of the fixing pin according to the present invention;

[0054] Figure 8 It is the explosion schematic diagram of the fixing pin according to the present invention.

[0055] In the drawings, the list of components represented by each reference numeral is as follows:

[0056] In the figure: 1 - tower body, 2 - attachment frame, 3 - connecting rod, 4 - boom, 5 - anemometer, 6 - load sensor, 31 - connecting piece, 32 - fixing pin, 61 - transmission line. Specific Embodiments

[0057] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts belong to the scope of protection of the present invention.

[0058] Please refer to Figure 1-4 , the present invention provides a technical solution: a distributed intelligent monitoring device for tower crane loads, as Figure 2-3 shown, including a tower body 1, a plurality of attachment frames 2 are fixedly connected to the periphery of the tower body 1, the top of the tower body 1 is rotatably connected to a boom 4 through a slewing bearing, a plurality of connecting rods 3 are fixedly connected to the periphery of the attachment frame 2, one ends of the plurality of connecting rods 3 are fixedly connected with connecting members 31, and the connecting members 31 are fixed to the outer surface of the building by bolts, as Figure 1 shown, further including a load unit, a wind speed unit, a collection module, a processing unit and a monitoring platform. The load unit consists of m load sensors 6, and the load sensors 6 are arranged inside the connecting rods 3. The load sensors 6 are used to obtain the load information of the corresponding connecting rods 3 where they are located. The wind speed unit consists of n anemometers 5. The m load sensors 6 and the n anemometers 5 form a distributed monitoring network, and the data is uniformly obtained by the collection module. The anemometers 5 are respectively installed at both ends of the boom 4 and the top of the attachment frame 2. The anemometers 5 are used to obtain the wind speed information of the corresponding positions at both ends of the boom 4 and the attachment frame 2;

[0059] The output ends of the load unit and the wind speed unit are both connected to the input end of the collection module, the output end of the collection module is connected to the input end of the processing unit, and a communication is established between the port of the processing unit and the port of the monitoring platform;

[0060] The collection module respectively obtains the load information of the load unit and the wind speed information of the wind speed unit and transmits them to the processing unit. The operator manually inputs the position information of each load sensor 6 and anemometer 5 to the processing unit through the monitoring platform, and at the same time inputs the engineering drawings of the building and the tower crane on the ground. The processing unit establishes a digital three-dimensional model and a wind flow model based on the position information, engineering drawings and wind speed information, and at the same time marks the load monitoring points and wind speed monitoring points and calculates the fluid distribution curve. The processing unit predicts the predicted values of each load sensor 6 based on the wind flow model. The processing unit compares the load information and the predicted values of each load sensor 6 to analyze the abnormal values of the load information. The processing unit automatically adjusts the collection frequency of the collection module according to the wind speed information.

[0061] Among them, the specific content of establishing the digital three-dimensional model is as follows:

[0062] The processing unit establishes a spatial coordinate system in the Ansys Fluent general fluid mechanics simulation software according to the position information. The spatial coordinate system has three dimensions: the x-axis, the y-axis, and the z-axis, with the unit being meters. The processing unit establishes digital 3D models of the tower crane and the building in the spatial coordinate system according to the engineering drawings. The processing unit marks the points where the load sensor 6 is installed in the digital 3D model as load monitoring points according to the position information of the load sensor 6, and marks the points where the anemometer 5 is installed in the digital 3D model as wind speed monitoring points according to the position information of the anemometer 5. When the orientation of the tower crane boom 4 changes, the anemometers 5 located at both ends of the boom 4 change their positions, and the dynamic position P3 (x3, y3, z3) of the anemometer 5 changes. The processing unit updates the digital 3D model according to the changed position of the anemometer 5 and the orientation of the tower crane.

[0063] Among them, the acquisition methods of the position information and the engineering drawings are as follows:

[0064] The position information of the load sensor 6 and the position information of the anemometer 5 both include three dimensions: the x-axis, the y-axis, and the z-axis. The position information of the anemometer 5 is divided into a static position and a dynamic position. The anemometer 5 installed on the attachment frame 2 corresponds to the static position, and the anemometers 5 installed at both ends of the boom 4 correspond to the dynamic position. When the orientation of the boom 4 changes, the processing unit calculates the dynamic position of the anemometer 5 after the position change according to the rotation angle of the boom 4 and the engineering drawings. The processing unit can obtain the rotation angle of the tower crane boom 4 in the cab through the monitoring platform. The engineering drawings record the length of the boom 4. The operator measures the position information of each anemometer 5 using surveying tools, and the surveying tools are a level and a laser rangefinder;

[0065] The operator marks the measured position information of the load sensor 6 as P1 (x1, y1, z1), marks the static position measured by the anemometer 5 located on the attachment frame 2 as P2 (x2, y2, z2), and marks the dynamic position measured by the anemometers 5 located at both ends of the boom 4 as P3 (x3, y3, z3);

[0066] The operator manually inputs the marked position information into the monitoring platform through an input device. The input device is a general keyboard and mouse. The monitoring platform is connected to a display for video output. The operator can interact by observing the content on the display. At the same time, the operator manually inputs the engineering drawings of the building and the tower crane on the ground into the monitoring platform through the input device. The building in the engineering drawings includes the building body, as well as the scaffolding and protective nets surrounding the building. The monitoring platform uniformly transmits the input position information and engineering drawings to the processing unit.

[0067] Among them, the specific content of establishing the wind flow model is as follows:

[0068] In the digital three-dimensional model, the processing unit divides the simulation calculation area of each tower crane with the tower body 1 of each tower crane as the center and the end of the long arm of the boom 4 of each tower crane as the radius. If the vertical overlapping occurs in the sweeping areas of the ends of the long arms of the booms of two tower cranes, the simulation calculation areas of the two tower cranes are separated by the connecting line of the intersection points of the two overlapping circles.

[0069] The processing unit presets a system of equations for wind flow control and inputs the wind speed information of each wind speed monitoring point into the following system of equations:

[0070]

[0071] Calculate the fluid distribution curve. is the rate of change of a single physical quantity, where the physical quantity is air density 、the wind speed information u and time t. The first formula from top to bottom in the system of equations is the continuity equation, which is based on the mass conservation of wind fluid, that is, the mass of a given volume of fluid remains constant. is the air density. At 15°C under standard atmospheric pressure, the air density is , t is the time collected by the anemometer 5, and the time t collected by the anemometer 5 is uniformly obtained by the acquisition module along with the wind speed information. u is the wind speed information, which is specifically the wind vector in fluid simulation calculation. The wind vector includes wind speed and wind direction. ∇ is the gradient operator built into the CFD simulation software, which is used to describe the rate of change of the fluid distribution curve in the space coordinate system. The second formula from top to bottom in the system of equations is the momentum equation, which is based on Newton's second law. The rate of change of momentum within a fluid volume is equal to the sum of the forces acting on it, including pressure and gravity. For an incompressible fluid with constant viscosity, where p is the static pressure, which is specifically the atmospheric pressure data in fluid simulation calculation and can be obtained by the processing unit through the monitoring platform to access the external network. v is the kinematic viscosity of air. Generally, the kinematic viscosity of air under standard atmospheric pressure is , is the acceleration due to gravity, and generally the standard value is taken as . The third formula from top to bottom in the system of equations is the energy equation, which is based on the first law of thermodynamics. The change in the total energy of the fluid is equal to the energy added or removed from the system, such as through conduction or convective heat transfer. Among them, is the total enthalpy, which can be calculated according to the temperature and specific heat of air. , cp is the specific heat at constant pressure of air, which is at normal temperature. λ is the thermal conductivity of air. The thermal conductivity of air is related to temperature and is at normal temperature. T is the current ambient temperature, which can be obtained by the processing unit through the monitoring platform to access the external network. It is an external heat source. In the simulation calculation, there is no special heat source, and the general value is 0. It should be noted that the equations are used to set the simulation environment conditions of the fluid, and calculate the influence of the change rates of various physical quantities in the simulation environment on the wind fluid, such as wind speed, wind direction, temperature, density, and pressure. The direction change of the fluid distribution curve in the digital three-dimensional model is still calculated by the simulation software according to the principles of fluid mechanics;

[0072] When the fluid distribution curves of all simulation calculation areas are all calculated, all the fluid distribution curves are gathered to obtain the distribution and change trend of the wind force, which is marked as the wind force flow model. Among them, when the orientation of the tower crane boom 4 starts to change, the dynamic positions P3(x3, y3, z3) of the anemometers 5 at both ends of the boom 4 change, and the processing unit updates the digital three-dimensional model in real time. The fluid distribution curves in the simulation calculation area are updated synchronously with the digital three-dimensional model, and the simulation software recalculates the fluid distribution curves and incorporates them into the wind force flow model to replace the previous fluid distribution curves.

[0073] Among them, the specific content of the prediction value calculated by the processing unit includes the following:

[0074] As Figure 4 shown, the processing unit associates each load monitoring point with the anemometer monitoring point closest to the position of this load monitoring point according to the position information of the load monitoring point and the anemometer monitoring point. The processing unit establishes a fitting curve graph of the prediction value based on each load monitoring point, with the abscissa being the wind speed value and the ordinate being the load value. The processing unit inputs the wind speed value in the wind speed information collected at different time points and the load value in the load information collected at the same time point into the fitting curve graph. The circular scatter points in the fitting curve graph are the wind speed values and load values obtained by the acquisition module at different time points;

[0075] In each fitting curve graph, the processing unit sequentially marks the scatter point coordinates ui, Fi from left to right, where i = 1, 2, 3, 4,..., g, and g is the number of scatter points in the fitting curve graph. Among them, ui is the wind speed value, and Fi is the load value corresponding to the wind speed value. The processing unit sets the fitting formula , and uses the error sum of squares formula to calculate the specific values of a, b, and c. The processing unit assigns the calculated values of a, b, and c to the fitting formula. The u in the fitting formula is the wind speed value in the wind speed information. Of course, if the wind speed value and the load value show a linear change relationship, the fitting formula is also applicable, and the value of c in the fitting formula is 0;

[0076] The processing unit substitutes the wind speed value in the collected wind speed information into the fitting formula to calculate Fu, and the processing unit marks the calculated Fu as the prediction value of this load monitoring point at the current time point.

[0077] Among them, the specific content of the abnormal value analysis process of the load information is as follows:

[0078] The processing unit obtains the load information of each load monitoring point in the acquisition module in real time, calculates the error value by subtracting the predicted value corresponding to the load information value of each load monitoring point at the same time point, and the processing unit adds up and averages the error values of all load monitoring points at all time points to obtain the standard error;

[0079] The processing unit adds up and averages the error values calculated at different time points of the same load monitoring point to obtain the node error. The larger the node error value, the higher the possibility of abnormal values occurring at this load monitoring point. On the contrary, the smaller the node error, the closer the load information value of this load monitoring point is to the predicted value, and the lower the possibility of abnormal values occurring. The processing unit subtracts the error value of each load monitoring point from the error values of the two adjacent load monitoring points respectively, and then adds up the subtracted values to obtain the local error. The adjacent load monitoring points are the other two load monitoring points closest to this load monitoring point. The larger the local error value, the higher the possibility of abnormal values occurring in the area where this load monitoring point is located. On the contrary, the smaller the local error, the closer the load information values of this load monitoring point and the adjacent load monitoring points are, and the lower the possibility of abnormal values occurring;

[0080] The processing unit establishes Condition 1 and Condition 2. Condition 1 is that the value of the node error is greater than or equal to the standard error, and Condition 2 is that the value of the local error is greater than or equal to the standard error. When both Condition 1 and Condition 2 are not satisfied, it means that the load information of this load monitoring point is normal, and the processing unit does not perform any operation. When either Condition 1 or Condition 2 is satisfied, it means that the load information of this load monitoring point may be abnormal and requires manual intervention for judgment. The processing unit marks the load information that triggers Condition 1 or Condition 2 as a suspicious value, and the processing unit pushes the suspicious value to the monitoring platform for subsequent manual investigation and confirmation. When both Condition 1 and Condition 2 are satisfied, the processing unit marks the load information that triggers Condition 1 and Condition 2 as an abnormal value, and the processing unit pushes the abnormal value to the monitoring platform for the operator to view.

[0081] Among them, the acquisition frequency adjustment process specifically includes the following content:

[0082] The processing unit sets the acquisition frequencies Q1, Q2, and Q3 that vary dynamically. The acquisition frequencies Q1, Q2, and Q3 can be directly switched between each other. The initial value of the acquisition frequency Q1 is 0.25 Hz, the initial value of the acquisition frequency Q2 is 1 Hz, and the initial value of the acquisition frequency Q3 is 4 Hz. The dynamic change range of the acquisition frequencies Q1, Q2, and Q3 is not greater than 3 times their respective initial values and not less than 0.33 times their respective initial values. The acquisition frequency Q1 corresponds to the tower crane being in a static state or when the wind speed level is safe. The acquisition frequency Q2 corresponds to the tower crane being in operation or when the wind speed level is normal. The acquisition frequency Q3 corresponds to the tower crane being in a wind speed warning level.

[0083] The processing unit sets the adjustment factor J. The value range of the adjustment factor J is [0.8, 1.2]. The processing unit calculates the average load change rate qF of all load monitoring points and the average wind speed change rate qu of all wind speed monitoring points respectively. The processing unit calculates the specific value of the adjustment factor J according to the formula For example, if the average load change rate qF is 0.2 and the average wind speed change rate qu is 0.1, then the adjustment factor J = 0.8 + |0.2 * 0.9 + 0.1 * 0.1| = 0.99. Since the numerical change of the load information has a greater impact on the monitoring result, the distribution weight of the average load change rate qF is larger.

[0084] The processing unit multiplies the adjustment factor J by the acquisition frequencies Q1, Q2, and Q3 respectively to obtain the corresponding acquisition frequencies Q1, Q2, and Q3 of the acquisition module for the next acquisition. When the tower crane is in a static state or the wind speed level is safe, the load intensity is weak. Therefore, in order to save the processing performance of the acquisition module and the processing unit, and at the same time avoid too much invalid acquisition data (too much invalid acquisition data is likely to reduce the probability of abnormal data being noticed), it is necessary to reduce the acquisition frequency Q1. Slightly adjusting the acquisition frequency Q1 with the adjustment factor J can meet the monitoring of the load information and the wind speed information. Similarly, when the tower crane is in operation or the wind speed level is normal, the load intensity of the tower crane is average at this time, and a higher acquisition frequency Q2 is required to acquire the load information and the wind speed information. When the wind speed level is in a warning state, the wind force is strong at this time and it is not suitable for the tower crane to operate. The load intensity of the tower crane is prone to overload, and the highest acquisition frequency Q3 is required to monitor the load information and the wind speed information in real time to facilitate the timely issuance of load warning information.

[0085] Among them, the processing unit judges the wind speed level according to the wind speed information. The specific content is as follows:

[0086] The processing unit sends a weather acquisition request to the monitoring platform. The monitoring platform searches for the weather at the current location externally and sends it to the processing unit. The monitoring platform is specifically a network-connected Windows computer. The operator can use input devices such as a mouse and keyboard to input data into the monitoring platform. The display screen integrated in the monitoring platform can display push load warning information;

[0087] The processing unit obtains the wind speed at the current location from the weather and marks it as the first reference value. The processing unit extracts the wind speed information values of each anemometer 5 from the acquisition module, adds them up and takes the average to obtain the second reference value. The processing unit adds the first reference value and the second reference value and takes the average to obtain the third reference value. The units of the first reference value, the second reference value, and the third reference value are all m / s;

[0088] The processing unit presets a first judgment threshold and a second judgment threshold. The first judgment threshold is 11.8, and the second judgment threshold is 6. When the value of the third reference value is greater than or equal to the first judgment threshold, the processing unit marks the wind speed level as a warning. When the value of the third reference value is less than the first judgment threshold and greater than or equal to the second judgment threshold, the processing unit marks the wind speed level as normal. When the value of the third reference value is less than the second judgment threshold, the processing unit marks the wind speed level as safe.

[0089] Among them, the calculation processes of the average load change rate qF and the average wind speed change rate qu are as follows:

[0090] The processing unit extracts the load information values of each load monitoring point, divides the currently collected load information value by the previously collected load information value to obtain the node load change rate of this load monitoring point. The processing unit adds up the node load change rates of each load monitoring point and takes the average to obtain the average load change rate qF;

[0091] The processing unit extracts the wind speed information values of each wind speed monitoring point, divides the currently collected wind speed information value by the previously collected wind speed information value to obtain the node wind speed change rate of this wind speed monitoring point. The processing unit adds up the node wind speed change rates of each wind speed monitoring point and takes the average to obtain the average wind speed change rate qu.

[0092] Among them, the specific content of the switching determination of the acquisition frequencies Q1, Q2, and Q3 is as follows:

[0093] The processing unit obtains the operating status of the tower crane cab through the monitoring platform. The monitoring platform establishes data communication with the tower crane cab. When the tower crane cab is in the operating state or the wind speed level is normal, the processing unit controls the acquisition module to obtain the load information and wind speed information using the acquisition frequency Q2. When the tower crane cab is in the non-operating state or the wind speed level is safe, the processing unit controls the acquisition module to obtain the load information and wind speed information using the acquisition frequency Q1. When the wind speed level is in warning, at this time the tower crane is prohibited from operating, and the processing unit controls the acquisition module to obtain the load information and wind speed information using the acquisition frequency Q3.

[0094] Among them, as Figure 5-8 shown, the connecting rods 3 are connected by fixing pins 32. Inside the fixing pins 32, they are fixedly connected to the load sensors 6 through elastic metal sheets. The load received by the fixing pins 32 causes the elastic metal sheets to deform. The load sensors 6 convert the amount of deformation of the elastic metal sheets into load information. A transmission line 61 is provided at the tail of the fixing pin 32, and the load sensors 6 send the load information outward through the transmission line 61.

[0095] The above is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, according to the technical solution of the present invention and its inventive concept, makes equivalent substitutions or changes, and should be covered by the protection scope of the present invention.

Claims

1. A distributed intelligent monitoring device for tower crane loads, comprising a tower body (1), wherein a plurality of attachment frames (2) are fixedly connected to the peripheral side of the tower body (1), a boom (4) is rotatably connected to the top of the tower body (1), a plurality of connecting rods (3) are fixedly connected to the peripheral side of the attachment frame (2), one end of each of the plurality of connecting rods (3) is fixedly connected with a connecting piece (31), and the connecting piece (31) is fixed to the outer surface of the building, and is characterized in that: It further includes a load unit, a wind speed unit, a collection module, a processing unit, and a monitoring platform. The load unit consists of m load sensors (6), and the load sensors (6) are arranged inside the connecting rod (3). The load sensors (6) are used to obtain the load information of the connecting rod (3) where they are located. The wind speed unit consists of n anemometers (5). The m load sensors (6) and the n anemometers (5) form a distributed monitoring network, and data is uniformly obtained by the collection module. The anemometers (5) are respectively installed at both ends of the boom (4) and the top of the attachment frame (2), and the anemometers (5) are used to obtain the wind speed information at both ends of the boom (4) and the location of the attachment frame (2). The output ends of the load unit and the wind speed unit are both connected to the input end of the collection module. The output end of the collection module is connected to the input end of the processing unit. The ports of the processing unit and the monitoring platform establish communication. The collection module respectively obtains the load information and the wind speed information and transmits them to the processing unit. The monitoring platform inputs the position information of each load sensor (6) and anemometer (5) to the processing unit, and at the same time inputs the engineering drawings of the building and the tower crane, establishes a digital three-dimensional model and a wind flow model, marks the load monitoring points and the wind speed monitoring points at the same time and calculates the fluid distribution curve, predicts the predicted values of each load sensor (6), compares the load information with the predicted values to analyze the abnormal values, and automatically adjusts the collection frequency of the collection module according to the wind speed information. The specific content of the processing unit calculating the predicted values includes the following: Associate each load monitoring point with the nearest wind speed monitoring point to the load monitoring point. Based on each load monitoring point, establish a fitting curve graph of the predicted value, with the abscissa being the wind speed value and the ordinate being the load value. Input the wind speed values in the wind speed information collected at different time points and the load values in the load information collected at the same time points into the fitting curve graph. The scatter points in the fitting curve graph are the wind speed values and load values obtained by the collection module at different time points. Mark the scatter coordinates (ui, Fi) in sequence from left to right in each fitting curve graph, where i = 1, 2, 3, 4, ……, g, and g is the number of scatter points in the fitting curve graph. Here, ui is the wind speed value and Fi is the corresponding load value. Set the fitting formula , and use the sum of squared errors formula to calculate the specific values of a, b, and c, and assign the calculated values of a, b, and c to the fitting formula. The u in the fitting formula is the wind speed value in the wind speed information; Substitute the wind speed value in the collected wind speed information into the fitting formula to calculate F(u), and mark the calculated F(u) as the predicted value of the load monitoring point at the current time point. The specific content of the abnormal value analysis process is as follows: The processing unit obtains the load information of each load monitoring point in the collection module in real time, calculates the error value by subtracting the load information value of each load monitoring point from the predicted value corresponding to the same time point of the load monitoring point, and adds up and averages the error values of all load monitoring points at all time points to obtain the standard error. Add up and average the error values calculated at different time points of the same load monitoring point to obtain the node error. Subtract the error value of each load monitoring point from the error values of the adjacent two load monitoring points respectively, and then add up the subtracted values to obtain the local error. Set up Condition 1 and Condition 2. Condition 1 is that the value of the node error is greater than or equal to the standard error, and Condition 2 is that the value of the local error is greater than or equal to the standard error. When neither Condition 1 nor Condition 2 is satisfied, no operation is performed. When either Condition 1 or Condition 2 is satisfied, mark the load information as a suspicious value, and push the suspicious value to the monitoring platform for subsequent manual investigation and confirmation. When both Condition 1 and Condition 2 are satisfied, mark the load information as an abnormal value, and push the abnormal value to the monitoring platform.

2. The distributed intelligent monitoring device for tower crane load according to claim 1, characterized in that, The specific content of establishing a digital three-dimensional model is as follows: The processing unit establishes a spatial coordinate system in the simulation software. The spatial coordinate system has three dimensions: the x-axis, the y-axis, and the z-axis, with the unit being meters. According to the engineering drawings, a digital three-dimensional model of the tower crane and the building is established in the spatial coordinate system. The points where the load sensors (6) are installed in the digital three-dimensional model are marked as load monitoring points, and the points where the anemometers (5) are installed in the digital three-dimensional model are marked as wind speed monitoring points.

3. The distributed intelligent monitoring device for tower crane load according to claim 1, wherein, The specific methods for obtaining the position information and the engineering drawings are as follows: The position information of the load sensors (6) and the anemometers (5) both include three dimensions: the x-axis, the y-axis, and the z-axis. The position information of the anemometer (5) is divided into a static position and a dynamic position. The anemometer (5) installed on the attachment frame (2) corresponds to the static position, and the anemometers (5) installed at both ends of the boom (4) correspond to the dynamic position. When the orientation of the boom (4) changes, the dynamic position of the anemometer (5) after the position change is calculated based on the rotation angle of the boom (4) and the engineering drawings. The operator uses surveying tools to measure the position information of each anemometer (5). The operator marks the measured position information of the load sensors as P1(x1, y1, z1), marks the measured static position as P2(x2, y2, z2), and marks the measured dynamic position as P3(x3, y3, z3). The operator manually inputs the marked position information into the monitoring platform through the input device. At the same time, the operator manually inputs the engineering drawings of the building and the tower crane into the monitoring platform through the input device. The monitoring platform uniformly transmits the input position information and the engineering drawings to the processing unit.

4. The distributed intelligent monitoring device for tower crane load according to claim 1, characterized in that The specific content of establishing a wind flow model is as follows: In the digital three-dimensional model, the processing unit takes the tower body (1) of each tower crane as the center and the end of the long arm of the boom (4) of each tower crane as the radius to divide the simulation calculation area of each tower crane. If the vertical overlapping area of the sweeping areas at the ends of the long arms of the booms (4) of two tower cranes exists, the simulation calculation areas of the two tower cranes are separated by the connecting line of the intersection points of the two overlapping circles. Preset equations and input the wind speed information of each wind speed monitoring point into the equations Calculate the fluid distribution curve is the rate of change of a single physical quantity, where the physical quantity is air density , the wind speed information u, and time t. The first formula of the equations from top to bottom is the continuity equation, based on the mass conservation of the wind fluid is the air density. At a standard atmospheric pressure of 15 °C, the air density is , t is the time collected by the anemometer (5), u is the wind speed information, specifically the wind vector in the fluid simulation calculation. The wind vector includes wind speed and wind direction. ∇ is the gradient operator built into the simulation software, used to describe the rate of change of the fluid distribution curve in the spatial coordinate system. The second formula of the equations from top to bottom is the momentum equation, based on Newton's second law, where p is the static pressure, specifically the atmospheric pressure data in the fluid simulation calculation, which is obtained by the processing unit from the external network through the monitoring platform. v is the kinematic viscosity of air. The kinematic viscosity of air under standard atmospheric pressure is , is the acceleration due to gravity, generally taking the standard value . The third formula of the equations from top to bottom is the energy equation, based on the first law of thermodynamics, where is the total enthalpy, which can be calculated according to the temperature and specific heat of air , cp is the specific heat at constant pressure of air, which is at room temperature. λ is the thermal conductivity of air, which is at room temperature. T is the current ambient temperature is the external heat source, generally with a value of 0 When the fluid distribution curves of all the simulation calculation areas are all calculated, all the fluid distribution curves are gathered to obtain the distribution and change trend of the wind force, which is marked as the wind flow model.

5. The distributed intelligent monitoring device for tower crane load according to claim 1, characterized in that The process of adjusting the acquisition frequency specifically includes the following content: The processing unit sets the acquisition frequencies Q1, Q2, and Q3 that change dynamically respectively and initializes them. The acquisition frequencies Q1, Q2, and Q3 can be directly switched between each other. The dynamic change range of the acquisition frequencies Q1, Q2, and Q3 is not greater than 3 times of their own initial values and not less than 0.33 times of their own initial values. When the tower crane is in a static state or the wind speed level is safe, the acquisition frequency Q1 is corresponding; when the tower crane is in operation or the wind speed level is general, the acquisition frequency Q2 is corresponding; when the tower crane is in a wind speed level of warning, the acquisition frequency Q3 is corresponding. Set the adjustment factor J, where the value range of the adjustment factor J is [0.8, 1.2]. Calculate the average load change rate qF of all load monitoring points and the average wind speed change rate qu of all wind speed monitoring points respectively. According to the formula Calculate the specific value of the adjustment factor J; Multiply the adjustment factor J by the acquisition frequencies Q1, Q2, and Q3 respectively to obtain the acquisition frequencies Q1, Q2, and Q3 corresponding to the acquisition module during the next acquisition.

6. The distributed intelligent monitoring device for tower crane load according to claim 5, characterized in that, The specific content of judging the wind speed level is as follows: Send a weather acquisition request to the monitoring platform. The monitoring platform searches for the weather at the current location externally and sends it to the processing unit. Obtain the wind speed at the current location from the weather and mark it as the first reference value. Extract the wind speed information values of each anemometer (5) from the acquisition module and sum them up and average to obtain the second reference value. Add the first reference value and the second reference value and average to obtain the third reference value. The units of the first reference value, the second reference value, and the third reference value are all m / s. Preset a first judgment threshold and a second judgment threshold. The first judgment threshold is 11.8, and the second judgment threshold is 6. When the value of the third reference value is greater than or equal to the first judgment threshold, mark the wind speed level as warning. When the value of the third reference value is less than the first judgment threshold and greater than or equal to the second judgment threshold, mark the wind speed level as general. When the value of the third reference value is less than the second judgment threshold, mark the wind speed level as safe.

7. An intelligent monitoring device for distributed tower crane load according to claim 5, characterized in that, The calculation processes of the average load change rate qF and the average wind speed change rate qu are as follows: The processing unit extracts the load information values of each load monitoring point, divides the currently acquired load information value by the previously acquired load information value to obtain the node load change rate of the load monitoring point, and sums up and averages the node load change rates of each load monitoring point to obtain the average load change rate qF. The processing unit extracts the wind speed information values of each wind speed monitoring point, divides the currently acquired wind speed information value by the previously acquired wind speed information value to obtain the node wind speed change rate of the wind speed monitoring point, and sums up and averages the node wind speed change rates of each wind speed monitoring point to obtain the average wind speed change rate qu.

8. The distributed intelligent monitoring device for tower crane load according to claim 5, characterized in that, The specific content of the switching determination of the acquisition frequencies Q1, Q2, and Q3 is as follows: The processing unit obtains the operating state of the tower crane cab through the monitoring platform. The monitoring platform establishes data communication with the tower crane cab. When the tower crane cab is in an operating state or the wind speed level is general, control the acquisition module to use the acquisition frequency Q2 to obtain load information and wind speed information. When the tower crane cab is in a non-operating state or the wind speed level is safe, the acquisition module uses the acquisition frequency Q1 to obtain load information and wind speed information. When the wind speed level is warning, the acquisition module uses the acquisition frequency Q3 to obtain load information and wind speed information.

9. The distributed intelligent monitoring device for tower crane load according to claim 1, characterized in that, The connecting rods (3) are connected by fixing pins (32). Inside the fixing pins (32), they are fixedly connected to load sensors (6) through elastic metal sheets. The load received by the fixing pins (32) causes the elastic metal sheets to deform. The load sensors (6) convert the amount of deformation of the elastic metal sheets into load information. A transmission line (61) is provided at the tail of the fixing pins (32). The load sensors (6) send out load information through the transmission line (61).

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