CN117049379A - Tower crane work monitoring system based on digital twin - Google Patents
Tower crane work monitoring system based on digital twin Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D21/00—Measuring or testing not otherwise provided for
- G01D21/02—Measuring two or more variables by means not covered by a single other subclass
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66C—CRANES; LOAD-ENGAGING ELEMENTS OR DEVICES FOR CRANES, CAPSTANS, WINCHES, OR TACKLES
- B66C15/00—Safety gear
- B66C15/06—Arrangements or use of warning devices
- B66C15/065—Arrangements or use of warning devices electrical
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66C—CRANES; LOAD-ENGAGING ELEMENTS OR DEVICES FOR CRANES, CAPSTANS, WINCHES, OR TACKLES
- B66C23/00—Cranes comprising essentially a beam, boom, or triangular structure acting as a cantilever and mounted for translatory of swinging movements in vertical or horizontal planes or a combination of such movements, e.g. jib-cranes, derricks, tower cranes
- B66C23/88—Safety gear
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
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Abstract
The invention relates to the technical field of cranes, and provides a digital twin-based tower crane operation monitoring system which comprises a server, a tower crane, a sensor module, a digital twin module and an evaluation module, wherein the sensor module collects obstacle data on a travelling path of the tower crane, the digital twin module calls historical operation data of the same type of the tower crane, builds a working state monitoring mathematical model according to the historical operation data, and the evaluation module evaluates the working state of the tower crane according to the obstacle data of the sensor module and the working state monitoring mathematical model to form an evaluation result and prompts an operator according to the evaluation result. According to the invention, through the mutual coordination of the evaluation module, the digital twin module and the sensor module, the safety and the reliability of the whole system are effectively improved, so that the whole system has the advantages of wide operation range, high interaction comfort with an operator and capability of monitoring the hoisting state of the crane.
Description
Technical Field
The invention relates to the technical field of cranes, in particular to a digital twinning-based tower crane operation monitoring system.
Background
The traditional tower crane work monitoring method mainly depends on manual inspection and experience judgment, and has the problems of low monitoring precision, low efficiency, high safety risk and the like. The digital twin technology is a technology combining an actual physical system with a digital model, and can realize real-time monitoring, prediction and optimization of the physical system. However, a digital twin-based tower crane operation monitoring system is not yet available.
As the prior art CN115303946B discloses a method and a system for monitoring the operation of a digital twin-based tower crane, along with the wide application of the tower crane, the corresponding use limitation is also found by more and more people, for example, the operating state of an operator in high-altitude operation is difficult to monitor, suspended matters interfere with building or equipment at a construction site in the lifting process, the abrasion of crane equipment cannot be predicted in time, and the suspended matters can be found only when overhauling and maintenance are often needed or can be found only when faults occur.
Another typical online monitoring system for a tower crane disclosed in the prior art, such as CN106081911B, is generally used for safety monitoring of the tower crane, in which a plurality of cameras are installed on the tower crane and in the operating range of the tower crane, the cameras are connected with a computer in a monitoring room through a data line, and a worker judges whether the operating environment is dangerous by observing the operating condition on the computer, so that the hidden danger of the tower crane during operation cannot be monitored accurately, comprehensively and timely.
The invention is designed for solving the problems that the operation detection range is small, interaction is lacked, the surrounding environment cannot be controlled in real time, the working state of a crane cannot be controlled and the like in the prior art.
Disclosure of Invention
The invention aims to provide a digital twin-based tower crane operation monitoring system aiming at the defects existing at present.
In order to overcome the defects in the prior art, the invention adopts the following technical scheme:
the tower crane operation monitoring system comprises a server and a tower crane, and further comprises a sensor module, a digital twin module and an evaluation module, wherein the server is respectively connected with the sensor module, the digital twin module and the evaluation module;
the sensor module collects obstacle data on the tower crane travel route,
the digital twin module calls the same type of historical operation data of the tower crane, builds a working state monitoring mathematical model according to the historical operation data, and the evaluation module evaluates the working state of the tower crane according to the obstacle data and the working state monitoring mathematical model of the sensor module to form an evaluation result and prompts an operator according to the evaluation result;
the digital twin module comprises a data calling unit and a digital twin unit, wherein the data call historical operation data of the tower crane, and the digital twin unit acquires the historical operation data of the tower crane and constructs a working state monitoring mathematical model;
the digital twin unit calls historical operation data of the same type as the tower crane according to the verification code, builds a working state monitoring mathematical model of the tower crane according to the historical operation data, and the base database is used for storing data of the data calling unit.
Optionally, the sensor module is arranged on the tower crane, the sensor module comprises a supporting unit, a distance detecting unit and a sound detecting unit, the supporting unit supports the distance detecting unit, the distance detecting unit collects distance data between the tower crane and an obstacle on a travelling route, and the sound detecting unit detects sound of a working mechanism of the tower crane;
the distance detection unit is arranged on a lifting rope of the tower crane.
Optionally, the distance detection unit includes a detection radar and a data transmitter, the detection radar is disposed on the support unit and collects distance data between itself and an obstacle on a travelling route of the tower crane as obstacle distance data, and the data transmitter transmits data detected by the detection radar to the evaluation module.
Optionally, the sound detection unit is arranged in the tower-type middle connected lifting mechanism to collect sound amplitude corresponding to sound data of the lifting mechanism when lifting and lowering the lifted object;
the sound detection unit comprises a detection cavity and a sound pickup member, the detection cavity supports the sound pickup member, and the sound pickup member collects sound amplitude of the lifting mechanism when lifting and lowering a lifted object;
the detection cavity is provided with a sound receiving groove for transmitting sound, and the sound pickup component is arranged in the inner wall of the sound receiving groove of the detection cavity.
Optionally, the digital twin unit constructs the working state monitoring mathematical model according to the following steps:
s1, collecting same-type operation data of the tower crane within a specified time range, wherein the operation data comprise the weight of the tower crane, the operation time of the tower crane and the traction force of a lifting rope of the tower crane;
s2, preprocessing the collected operation data, wherein the preprocessing comprises abnormal value removal and data standardization;
s3, establishing a working state monitoring mathematical model, wherein the following linear working state monitoring mathematical model is established based on a multiple regression analysis method,
Abnormal＝a·x 1 +b·x 2 +c·x 3 +ε；
wherein a, b, c are parameters to be estimated of the model, x 1 、x 2 、x 3 The method is characterized in that the method comprises the steps of respectively obtaining a weight independent variable of the hoisting of the tower crane, a time length independent variable of the operation of the tower crane and a pulling force independent variable of a hoisting rope of the tower crane, wherein epsilon is an error item;
s4, estimating the parameters to be estimated in the mathematical model by using a least square method, and bringing the estimated parameters to be estimated into the mathematical model to obtain a final form of the working state monitoring mathematical model;
s5, verifying the established working state monitoring mathematical model by using part of qualified data which are already examined, and evaluating deviation index displacement of the established working state monitoring mathematical model;
s6, if the deviation index is positive, the working state monitoring mathematical model meets the requirements, and if the deviation index is negative, the mean square error of the prediction result is higher than a set deviation threshold range, and the working state monitoring mathematical model does not meet the requirements;
s7, applying a working state monitoring mathematical model meeting the requirements to actual tower crane running state monitoring, and recording a real-time state abnormality index Abnormal of the tower crane, wherein the working state monitoring mathematical model meets the following requirements:
where y-y ' is the absolute difference between the actual value y and the predicted value y ', std_dev (y ') is the standard deviation of the predicted value, the value of which is calculated from the training data.
Optionally, the evaluation module includes an early warning unit and an evaluation unit, the evaluation unit evaluates the work of the tower crane according to the analysis results of the sensor module and the digital twin module to form an evaluation result, and the early warning unit prompts the evaluation result to the operator;
the evaluation unit acquires obstacle distance data of the distance detection unit, sound amplitude acquired by the sound detection unit and an analysis result of the digital twin module, and calculates a State index State of the hoisting operation of the tower crane according to the following formula:
State＝λ 1 ·Sound+λ 2 ·Distance+λ 3 ·Abnormal；
wherein lambda is 1 Is the sound weight coefficient lambda 2 Is the boundary weight coefficient lambda 3 As a state abnormality weight coefficient, sound is a Sound index obtained by Sound amplitude processing, distance is a Distance index obtained by obstacle Distance data processing, and Abnormal is a state abnormality index;
if the State index State of the lifting operation of the tower crane exceeds a set monitoring value Monitor, the abnormality of the tower crane can be judged, and a prompt is triggered to the operator so as to replace corresponding parts or maintain the parts of the tower crane.
Optionally, the Sound index Sound obtained by the obstacle distance data processing is calculated according to the following formula:
wherein Noise is the real-time sound amplitude acquired by the sound pickup component, min_sound is the minimum amplitude in the normal running state, and max_sound is the maximum amplitude in the normal running state.
Optionally, the early warning unit includes controlling the display screen and controlling the pilot lamp, control the display screen according to the evaluation result of evaluation unit and show the operating condition of tower crane, control the pilot lamp according to the evaluation result of evaluation unit triggers the instruction of different kinds of colours.
Optionally, the deviation index determination for evaluating and building the working state monitoring mathematical model is calculated according to the following formula:
deviation＝range-MSE；
wherein range is a set deviation threshold, and MSE is the mean square error of the established working state monitoring mathematical model.
The beneficial effects obtained by the invention are as follows:
1. the state of the tower crane is monitored through the mutual coordination of the evaluation module, the digital twin module and the sensor module, so that the safety and the reliability of the whole system are effectively improved, and the whole system has the advantages of wide operation range, high interaction comfort with operators and capability of monitoring the hoisting state of the crane;
2. the working state of the tower crane in the lifting process is detected through the sensor module, so that the whole lifting process is safer;
3. the digital twin module is used for analyzing according to the service environment of the tower crane, so that the operation safety of the tower crane is improved, and the reliability and efficiency of the lifted articles are also ensured to the maximum extent;
4. the sound signal generated in the hoisting process of the tower crane is collected through the sound detection unit, and the sound signal is analyzed according to the collection, so that the working process of the whole tower crane is accurately monitored.
Drawings
The invention will be further understood from the following description taken in conjunction with the accompanying drawings. The components in the figures are not necessarily to scale, emphasis instead being placed upon illustrating the principles of the embodiments. Like reference numerals designate like parts in the different views.
Fig. 1 is a schematic block diagram of the overall structure of the present invention.
Fig. 2 is a block diagram of a distance detecting unit, a sound detecting unit and an evaluation module according to the present invention.
FIG. 3 is a schematic diagram of an evaluation flow of the evaluation unit of the present invention.
Fig. 4 is a schematic side view of the tower crane of the present invention with an obstacle, fixed obstacle.
Fig. 5 is a schematic structural view of the supporting unit and the distance detecting unit provided on the lifting rope.
Fig. 6 is a schematic cross-sectional view of the support unit and the lifting rope of the present invention.
Fig. 7 is a schematic structural view of the distance detecting unit and the supporting unit of the present invention.
Fig. 8 is a partially cut-away schematic illustration of the sound detection unit of the present invention.
Fig. 9 is a schematic top view of the tower crane and fixed barrier of the present invention.
Reference numerals illustrate: 1. a tower crane; 2. fixing the obstacle; 3. a hanging rope; 4. a lifting mechanism; 5. a sound detection unit; 6. a distance detection unit; 7. a first support base; 8. a second support base; 9. a hinge; 10. a clamping joint; 11. a reciprocating spring; 12. a sound pickup member; 13. and a detection cavity.
Detailed Description
The following embodiments of the present invention are described in terms of specific examples, and those skilled in the art will appreciate the advantages and effects of the present invention from the disclosure herein. The invention is capable of other and different embodiments and its several details are capable of modification and variation in various respects, all without departing from the spirit of the present invention. The drawings of the present invention are merely schematic illustrations, and are not intended to be drawn to actual dimensions. The following embodiments will further illustrate the related art content of the present invention in detail, but the disclosure is not intended to limit the scope of the present invention.
Embodiment one: according to fig. 1, 2, 3, 4, 5, 6, 7, 8 and 9, the present embodiment provides a digital-twinning-based tower crane operation monitoring system, which includes a server, and a tower crane, the tower crane operation monitoring system further includes a sensor module, a digital twinning module and an evaluation module, the server is respectively connected with the sensor module, the digital twinning module and the evaluation module, and stores process data of the sensor module, the digital twinning module and the evaluation module for query and call;
the sensor module collects the distance between the sensor module and the obstacle on the travelling route of the tower crane as obstacle data,
the digital twin module calls the same type of historical operation data of the tower crane, builds a working state monitoring mathematical model according to the historical operation data, and the evaluation module evaluates the working state of the tower crane according to the obstacle data and the working state monitoring mathematical model of the sensor module to form an evaluation result and prompts an operator according to the evaluation result;
the digital twin module comprises a data calling unit and a digital twin unit, wherein the data call historical operation data of the tower crane, and the digital twin unit acquires the historical operation data of the tower crane and constructs a working state monitoring mathematical model;
the digital twin unit calls historical operation data of the same type as the tower crane according to the verification code, builds a working state monitoring mathematical model of the tower crane according to the historical operation data, and the base database is used for storing data of the data calling unit.
The tower crane work monitoring system further comprises a central processor, wherein the central processor is respectively connected with the sensor module, the digital twin module, the evaluation module and the tower crane in a control manner, and the central processor is used for carrying out centralized control on the sensor module, the digital twin module, the evaluation module and the tower crane so as to enable the whole system to run more intelligently and coordinately;
if the identity verification of the server on the tower crane is not passed, the data calling unit is not allowed to call data;
if the identity verification of the tower crane by the server passes, transmitting the tower crane identity coding sequence to the identity verification generator;
the identity verification generator acquires the tower crane identity coding sequence of the corresponding position which is verified by the server, and grants a verification authorization code according to the following steps:
in the formula, code (v) is a value corresponding to the v th bit of the verification code, time is the number of times of the data calling unit calling on the same day, date is the grade of the tower crane, and ID (v) is a value corresponding to the v th bit of the identity coding sequence of the tower crane;
after the verification authorization code is generated, the authorization code is sent to a server for verification. This is typically done through HTTP requests (such as POST or GET requests);
and verifying the received authorization code at the server side. The server performs the same operation of generating and verifying the authorization code on the tower crane in a local self-running mode, then compares whether the authorization code generated by the server and the received authorization code are consistent, and if so, the verification is successful; otherwise, the verification fails;
in addition, the server checks to pass, and then allows to call the historical operation data of the same type as the tower crane;
optionally, the sensor module is arranged on the tower crane, the sensor module comprises a supporting unit, a distance detecting unit and a sound detecting unit, the supporting unit supports the distance detecting unit, the distance detecting unit collects the distance between the tower crane and an obstacle on a travelling route, and the sound detecting unit detects the sound of a working mechanism of the tower crane;
the distance detection unit is arranged on a lifting rope of the tower crane;
the supporting unit comprises a first supporting seat, a second supporting seat and a hinging piece, wherein one side walls of the first supporting seat and the second supporting seat are mutually hinged through the hinging piece and are nested at the periphery of the lifting rope, the first supporting seat and the second supporting seat are respectively provided with a storage cavity for limiting and clamping the distance detecting unit,
in addition, the supporting unit further comprises a clamping member and a placing groove arranged on the side wall of the storage cavity, wherein the clamping member is used for limiting the distance detection unit so that the distance detection unit can be detachably clamped in the storage cavity; the clamping component is arranged on the side wall of the storage cavity and limits the distance detection unit;
as shown in fig. 7, the clamping member includes a clamping head and a reciprocating spring, one end of the reciprocating spring is connected with the bottom wall of the placement groove, the other end of the reciprocating spring is connected with one side end surface of the clamping head and makes the clamping head protrude out of the side wall of the storage cavity to form a clamping part, and the clamping part is in limit clamping connection with the side wall of the distance detection unit;
the two side walls of the clamping connector in the inserting and pulling direction are arc-shaped or semicircular contact surfaces, so that the distance detection unit can be conveniently inserted and pulled;
the sound detection unit is used for collecting sound signals generated in the hoisting process of the tower crane and analyzing the sound signals according to the collected sound signals so as to accurately monitor the whole working process of the tower crane;
optionally, the distance detection unit includes a detection radar and a data transmitter, the detection radar is arranged on the support unit and collects the obstacle distance data of the travelling route of the tower crane, and the data transmitter transmits the data detected by the detection radar to the evaluation module;
optionally, the sound detection unit is arranged in the tower-type middle connected lifting mechanism to collect sound amplitude corresponding to sound data of the lifting mechanism when lifting and lowering the lifted object;
as shown in fig. 8, the sound detection unit includes a detection chamber that supports the sound pickup member that collects sound amplitudes of the lifting mechanism when lifting and lowering a lifted article;
the detection cavity is provided with a sound receiving groove for transmitting sound, and the sound pickup component is arranged in the inner wall of the sound receiving groove of the detection cavity;
the sound pickup member comprises a sound pickup, a signal processor and a memory, wherein the sound pickup is used for collecting the sound of the lifting mechanism when lifting and lowering a lifted object, the signal processor is used for processing the collected sound so as to convert the collected sound into standard sound amplitude, and the memory is used for storing the sound amplitude processed by the signal processor;
the signal processor is a known technology for processing the sound signal, which can be known by those skilled in the art by querying the related technical manual, so that the details are not repeated in this embodiment;
in the implementation, the working state of the tower crane in the lifting process is detected through the sensor module, so that the whole lifting process is safer;
the digital twin unit builds a working state monitoring mathematical model according to the following steps:
s1, collecting same-type operation data of the tower crane within a specified time range, wherein the operation data comprise the weight of the tower crane, the operation time of the tower crane and the traction force of a lifting rope of the tower crane;
s2, preprocessing the collected operation data, wherein the preprocessing comprises abnormal value removal and data standardization;
s3, establishing a working state monitoring mathematical model, wherein the following linear working state monitoring mathematical model is established based on a multiple regression analysis method,
Abnormal＝a·x 1 +b·x 2 +c·x 3 +ε；
wherein a, b, c are parameters to be estimated of the model, x 1 、x 2 、x 3 The independent weight independent variable, the independent operation time independent variable and the independent crane lifting weight are respectively calculatedThe traction independent variable of the rope, epsilon is an error term;
s4, estimating the parameters to be estimated in the mathematical model by using a least square method, and bringing the estimated parameters to be estimated into the mathematical model to obtain a final form of the working state monitoring mathematical model;
s5, verifying the established working state monitoring mathematical model by using part of qualified data which are already examined, and evaluating deviation index displacement of the established working state monitoring mathematical model;
s6, if the deviation index is positive, the working state monitoring mathematical model meets the requirements, and if the deviation index is negative, the mean square error of the prediction result is higher than a set deviation threshold range, and the working state monitoring mathematical model does not meet the requirements;
s7, applying a working state monitoring mathematical model meeting the requirements to actual tower crane running state monitoring, and recording a real-time state abnormality index Abnormal of the tower crane, wherein the working state monitoring mathematical model meets the following requirements:
where y-y ' is the absolute difference between the actual value y and the predicted value y ', std_dev (y ') is the standard deviation of the predicted value, the value of which is calculated from the training data, in this embodiment, the step of providing a standard deviation of the predicted value is also provided:
1) And predicting a group of data by using a working state monitoring mathematical model to obtain a group of prediction results y'.
2) Calculating an average (mean (y')) of the set of predictions:
wherein y is j ' is the result of each prediction, M is the total number of predictions;
3) For each prediction result y j 'its difference from the mean (y') is calculatedThe average of the squares of these differences, i.e. variance (y'), is calculated:
4) Taking the square root of the variance, the standard deviation std_dev (y') is obtained:
of course, those skilled in the art may also calculate the standard deviation of the predicted value in other manners, so that the description is omitted in this example;
wherein, the deviation index deviation for evaluating and establishing the working state monitoring mathematical model is calculated according to the following formula:
deviation＝range-MSE；
wherein range is a set deviation threshold, the value of which is set by a manager or a system according to the actual situation, MSE is the mean square error of the established working state monitoring mathematical model, and the following conditions are satisfied:
where N is the number of sampled tower crane data, abnormal i Is obtained from the data of the tower crane in actual operation, and comprises the information such as the lifting weight and the running time of the tower crane (in actual operation, abnormal i Is real-time data recorded by various sensors and measuring devices), abnormal i ' is a predicted value obtained by an established digital twin model, and the model calculates a predicted state index according to input crane operation parameters (such as hoisting weight and running time).
Analyzing according to the service environment of the tower crane through the digital twin module, improving the operation safety of the tower crane, and guaranteeing the reliability and efficiency of the lifted articles to the maximum extent;
optionally, the evaluation module includes an early warning unit and an evaluation unit, the evaluation unit evaluates the work of the tower crane according to the analysis results of the sensor module and the digital twin module to form an evaluation result, and the early warning unit prompts the evaluation result to the operator;
the evaluation unit acquires obstacle distance data of the distance detection unit, sound amplitude acquired by the sound detection unit and an analysis result of the digital twin module, and calculates a State index State of the hoisting operation of the tower crane according to the following formula:
State＝λ 1 ·Sound+λ 2 ·Distance+λ 3 ·Abnormal；
wherein lambda is 1 Is a sound weight coefficient, the value of which is set by a system or an operator according to actual conditions, lambda 2 Is the obstacle distance weight coefficient, the value of which is set by the system or the operator according to the actual situation, lambda 3 The value of the state abnormality weight coefficient is set by a system or an operator according to actual conditions, sound is a Sound index obtained by Sound amplitude processing, distance is a Distance index obtained by obstacle Distance data processing, and Abnormal is a state abnormality index;
if the State index State of the lifting operation of the tower crane exceeds a set monitoring value Monitor, triggering a prompt to the operator;
if the State index State of the hoisting operation of the tower crane is smaller than a set monitoring value Monitor, allowing the operator to control the tower crane to hoist the object;
in addition, the Monitor value Monitor is set by the operator or the system, which is a technical means well known to those skilled in the art, and those skilled in the art can query the related technical manual to obtain the technology, so that the description is omitted in this embodiment;
in the process of setting the weight coefficient, the system or the operator can be used for controlling the weight coefficient according to the actual situationSetting and setting the sound weight coefficient lambda 1 Obstacle distance weighting coefficient lambda 2 And boundary weight coefficient lambda 3 The following are satisfied: lambda (lambda) 1 +λ 2 +λ 3 ＝1；
The set Monitor value Monitor is set by the system according to the actual use condition of the tower crane and the activity range of the crane, which is a technical means known to those skilled in the art, and those skilled in the art can inquire about the related technical manual to obtain the technology, so that the technology is not repeated in the embodiment;
optionally, the Sound index Sound obtained by the Sound amplitude processing is calculated according to the following formula:
wherein Noise is the real-time sound amplitude acquired by the sound pickup component, min_sound is the minimum amplitude in the normal running state, and max_sound is the maximum amplitude in the normal running state;
and calculating a Distance index Distance obtained by processing the obstacle Distance data according to the following formula:
wherein, the obstand is the obstacle distance data obtained by the detection of the detection radar, the min_distance is the minimum safety distance between the tower crane and the obstacle in the lifting process, the max_distance is the maximum safety distance between the tower crane and the obstacle in the lifting process, and the value of the max_distance is determined according to the space of the construction area;
optionally, the early warning unit includes a control display screen and a control indicator, the control display screen displays the working state of the tower crane according to the evaluation result of the evaluation unit, and the control indicator triggers the indication of different colors according to the evaluation result of the evaluation unit;
the early warning unit is arranged in an operation room of the tower crane so as to carry out interactive prompt with the operator;
in this embodiment, through the cooperation of the evaluation module, the digital twin module and the sensor module, the state of the tower crane is monitored according to the data of surrounding obstacles and fixed obstacles in the running process of the tower crane, so that the safety and reliability of the whole system are effectively improved, and the whole system has the advantages of wide operation range, high interaction comfort with operators and capability of monitoring the hoisting state of the crane.
Embodiment two: this embodiment should be understood to include all the features of any one of the foregoing embodiments and be further modified on the basis thereof, as shown in fig. 1, 2, 3, 4, 5, 6, 7, 8, and 9, in that the tower crane operation monitoring system further includes a swing monitoring module for monitoring a swing range of the tower crane;
the swing monitoring module determines the swing range of the tower crane according to the following steps:
s11, acquiring position data of a rotation center point and a fixed obstacle of the tower crane from the digital twin module;
s12, calculating a horizontal distance between the tower crane and the fixed obstacle;
s13, if the position of the article lifted by the tower crane and the extended arm length L are smaller than the horizontal distance, allowing the tower crane to swing in the range of the obstacle, otherwise, jumping to the step S14;
s14, obtaining an obstacle distance D between two adjacent fixed obstacles on the left and right in the working range of the tower crane and horizontal distances D1 and D2 from the two fixed obstacles to the tower crane, and calculating a swing angle range ran of the tower crane between the two adjacent fixed obstacles on the left and right according to the following formula:
when the swing monitoring module calculates the swing range in the scene, the swing range is prompted to the operator so as to ensure the safe rotation of the tower crane and ensure the safety and the reliability of the work to the maximum extent.
Embodiment two: this embodiment should be understood to include all the features of any one of the foregoing embodiments, and further improve thereon, as shown in fig. 1, 2, 3, 4, 5, 6, 7, 8, and 9, and in that the tower crane operation monitoring system further includes a manipulation interaction module that obtains boundary data of surrounding buildings in the tower crane usage scenario, and analyzes the boundary data to form an analysis result,
the control interaction module comprises a data setting unit and a position analysis unit, wherein the data setting unit is used for collecting boundary data of surrounding buildings of the tower crane set by an operator, the boundary data are set by an administrator according to the relation between the tower crane and the surrounding buildings (the boundary data comprise maps, layout diagrams, coordinates and the like of the tower crane and the surrounding buildings), and the position analysis unit is used for analyzing the control boundary range of the tower crane according to the boundary data around the tower crane;
the position analysis unit acquires the position of the tower crane, establishes a space rectangular coordinate system XYZ, and calculates the key distance P between the position of the tower crane and a fixed obstacle according to the following formula:
in (x) 1 ,y 1 ,z 1 ) Is the position coordinate of the tower crane, (x) 2 ,y 2 ,z 2 ) Position coordinates for the surrounding building;
the position analysis unit obtains the key distance P between the position of the tower crane and surrounding buildings and calculates a control Boundary range index bound of the tower crane according to the following formula:
wherein D is min For the minimum safe distance that the tower crane required, k is the length coefficient of the lifting article, satisfies:
wherein L is the actual length of the lifted object, and is directly obtained by the lifting material required in the lifting process, L min A minimum length value of a lifting object set for lifting the tower crane, a value set by a system (corresponding to a known value), L max A maximum length value of the lifted object set for the tower crane to be lifted, a value set by a system (corresponding to a known value), a being an adjustment factor, the value of which is obtained empirically;
transmitting the calculated control Boundary range index Boundary of the tower crane to an operator of the tower crane, and prompting the operator;
meanwhile, comparing the control Boundary range index bound with a set control range threshold Scope, and if the control Boundary range index bound meets the following conditions: boundary < Scope), then allow the operator to hoist the item;
if the Boundary > Scope, not allowing the operator to lift the article and prompting the operator;
through control interactive module with operating personnel carries out interactive suggestion for operating personnel can more graceful operation when lifting by crane article, greatly reduced operating personnel's intensity of labour prevents the operation in-process distraction, promotes tower crane operation's security and reliability.
The foregoing disclosure is only a preferred embodiment of the present invention and is not intended to limit the scope of the invention, so that all equivalent technical changes made by applying the description of the present invention and the accompanying drawings are included in the scope of the present invention, and in addition, elements in the present invention can be updated as the technology develops.
Claims (9)
1. The tower crane operation monitoring system based on the digital twin comprises a server and a tower crane, and is characterized by further comprising a sensor module, a digital twin module and an evaluation module, wherein the server is respectively connected with the sensor module, the digital twin module and the evaluation module;
the sensor module collects obstacle data on the travelling route of the tower crane, the digital twin module calls the same type of historical operation data of the tower crane, a working state monitoring mathematical model is built according to the historical operation data, and the evaluation module evaluates the working state of the tower crane according to the obstacle data of the sensor module and the working state monitoring mathematical model to form an evaluation result and prompts an operator according to the evaluation result;
the digital twin module comprises a data calling unit and a digital twin unit, wherein the data calling unit calls historical operation data of the tower crane, and the digital twin unit acquires the historical operation data of the tower crane and constructs a working state monitoring mathematical model;
the digital twin unit calls historical operation data of the same type as the tower crane according to the verification code, builds a working state monitoring mathematical model of the tower crane according to the historical operation data, and the base database is used for storing data of the data calling unit.
2. The digital twin-based tower crane operation monitoring system according to claim 1, wherein the sensor module is arranged on the tower crane, the sensor module comprises a supporting unit, a distance detecting unit and a sound detecting unit, the supporting unit supports the distance detecting unit, the distance detecting unit collects the distance between the tower crane and an obstacle on a travelling route, and the sound detecting unit detects the sound of a working mechanism of the tower crane;
the distance detection unit is arranged on a lifting rope of the tower crane.
3. The digital twin based tower crane operation monitoring system according to claim 2, wherein the distance detection unit comprises a detection radar which is provided on the support unit and collects the distance between itself and an obstacle on the traveling route of the tower crane as obstacle distance data, and a data transmitter which transmits the data detected by the detection radar to the evaluation module.
4. The digital twin-based tower crane operation monitoring system according to claim 3, wherein the sound detection unit is arranged in a lifting mechanism connected with the tower crane to collect sound amplitude corresponding to sound data of the lifting mechanism when lifting and lowering a lifted object;
the sound detection unit comprises a detection cavity and a sound pickup member, the detection cavity supports the sound pickup member, and the sound pickup member collects sound amplitude of the lifting mechanism when lifting and lowering a lifted object;
the detection cavity is provided with a sound receiving groove for transmitting sound, and the sound pickup component is arranged in the inner wall of the sound receiving groove of the detection cavity.
5. The digital twin based tower crane operation monitoring system according to claim 4, wherein the digital twin unit builds an operation state monitoring mathematical model according to the steps of:
s1, collecting same-type operation data of the tower crane within a specified time range, wherein the operation data comprise the weight of the tower crane, the operation time of the tower crane and the traction force of a lifting rope of the tower crane;
s2, preprocessing the collected operation data, wherein the preprocessing comprises abnormal value removal and data standardization
S3, establishing a working state monitoring mathematical model, wherein the following linear working state monitoring mathematical model is established based on a multiple regression analysis method,
y＝a·x 1 +b·x 2 +c·x 3 +ε；
wherein a, b, c are parameters to be estimated of the model, x 1 、x 2 、x 3 The method is characterized in that the method comprises the steps of respectively obtaining a weight independent variable of the hoisting of the tower crane, a time length independent variable of the operation of the tower crane and a pulling force independent variable of a hoisting rope of the tower crane, wherein epsilon is an error item;
s4, estimating the parameters to be estimated in the mathematical model by using a least square method, and bringing the estimated parameters to be estimated into the mathematical model to obtain a final form of the working state monitoring mathematical model;
s5, verifying the established working state monitoring mathematical model by using part of qualified data which are already examined, and evaluating deviation index displacement of the established working state monitoring mathematical model;
s6, if the deviation index is positive, the working state monitoring mathematical model meets the requirements, and if the deviation index is negative, the mean square error of the prediction result is higher than a set deviation threshold range, and the working state monitoring mathematical model does not meet the requirements;
s7, applying a working state monitoring mathematical model meeting the requirements to actual tower crane running state monitoring, and recording a real-time state abnormality index Abnormal of the tower crane, wherein the working state monitoring mathematical model meets the following requirements:
where y-y ' is the absolute difference between the actual value y and the predicted value y ', std_dev (y ') is the standard deviation of the predicted value, the value of which is calculated from the training data.
6. The digital twin-based tower crane operation monitoring system according to claim 5, wherein the evaluation module comprises an early warning unit and an evaluation unit, the evaluation unit evaluates the operation of the tower crane according to the analysis results of the sensor module and the digital twin module to form an evaluation result, and the early warning unit prompts the evaluation result to the operator;
the evaluation unit acquires obstacle distance data of the distance detection unit, sound amplitude acquired by the sound detection unit and an analysis result of the digital twin module, and calculates a State index State of the hoisting operation of the tower crane according to the following formula:
State＝λ 1 ·Sound+λ 2 ·Distance+λ 3 ·Abnormal；
wherein lambda is 1 Is the sound weight coefficient lambda 2 Is the boundary weight coefficient lambda 3 As a state abnormality weight coefficient, sound is a Sound index obtained by Sound amplitude processing, distance is a Distance index obtained by processing according to the obstacle Distance data, and Abnormal is a state abnormality index;
if the State index State of the lifting operation of the tower crane exceeds a set monitoring value Monitor, the abnormality of the tower crane can be judged, and a prompt is triggered to the operator so as to replace corresponding parts or maintain the parts of the tower crane.
7. The digital twinning-based tower crane operation monitoring system according to claim 6, wherein the Sound index Sound obtained by the obstacle distance data processing is calculated according to the following formula:
wherein Noise is the real-time sound amplitude acquired by the sound pickup component, min_sound is the minimum amplitude in the normal running state, and max_sound is the maximum amplitude in the normal running state.
8. The digital twin-based tower crane operation monitoring system according to claim 7, wherein the early warning unit comprises a control display screen and a control indicator lamp, the control display screen displays the operating state of the tower crane according to the evaluation result of the evaluation unit, and the control indicator lamp triggers the indication of different colors according to the evaluation result of the evaluation unit.
9. The digital twin based tower crane operation monitoring system according to claim 8, wherein the evaluation establishes a deviation index expression of the operation state monitoring mathematical model calculated according to the following formula:
deviation＝range-MSE；
wherein range is a set deviation threshold, and MSE is the mean square error of the established working state monitoring mathematical model.
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