CN115535854B - Intelligent maintenance control system for tower crane - Google Patents
Intelligent maintenance control system for tower crane Download PDFInfo
- Publication number
- CN115535854B CN115535854B CN202211020323.8A CN202211020323A CN115535854B CN 115535854 B CN115535854 B CN 115535854B CN 202211020323 A CN202211020323 A CN 202211020323A CN 115535854 B CN115535854 B CN 115535854B
- Authority
- CN
- China
- Prior art keywords
- tower crane
- data
- working
- working state
- state
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000012423 maintenance Methods 0.000 title claims abstract description 39
- 230000003993 interaction Effects 0.000 claims abstract description 14
- 230000005281 excited state Effects 0.000 claims description 15
- 239000003795 chemical substances by application Substances 0.000 claims description 12
- 238000006243 chemical reaction Methods 0.000 claims description 8
- 230000006870 function Effects 0.000 claims description 8
- 230000003068 static effect Effects 0.000 claims description 7
- 238000007405 data analysis Methods 0.000 claims description 6
- 230000006266 hibernation Effects 0.000 claims description 6
- 230000002159 abnormal effect Effects 0.000 claims description 4
- 238000004458 analytical method Methods 0.000 claims description 4
- 238000012512 characterization method Methods 0.000 claims description 3
- 230000005764 inhibitory process Effects 0.000 claims description 3
- 230000006855 networking Effects 0.000 claims description 3
- 238000012545 processing Methods 0.000 abstract description 4
- 230000002829 reductive effect Effects 0.000 abstract description 4
- 238000004364 calculation method Methods 0.000 abstract description 3
- 238000012544 monitoring process Methods 0.000 abstract description 3
- 238000000034 method Methods 0.000 description 10
- 238000011156 evaluation Methods 0.000 description 6
- 230000008569 process Effects 0.000 description 6
- 238000012986 modification Methods 0.000 description 5
- 230000004048 modification Effects 0.000 description 5
- 238000010276 construction Methods 0.000 description 4
- 230000007613 environmental effect Effects 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 3
- 238000007726 management method Methods 0.000 description 3
- 238000004088 simulation Methods 0.000 description 3
- 230000008859 change Effects 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 230000018109 developmental process Effects 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 230000007704 transition Effects 0.000 description 2
- 230000005540 biological transmission Effects 0.000 description 1
- 238000004140 cleaning Methods 0.000 description 1
- 238000009430 construction management Methods 0.000 description 1
- 230000008094 contradictory effect Effects 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 230000000670 limiting effect Effects 0.000 description 1
- 238000007781 pre-processing Methods 0.000 description 1
- 230000002441 reversible effect Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66C—CRANES; LOAD-ENGAGING ELEMENTS OR DEVICES FOR CRANES, CAPSTANS, WINCHES, OR TACKLES
- B66C13/00—Other constructional features or details
- B66C13/16—Applications of indicating, registering, or weighing devices
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66C—CRANES; LOAD-ENGAGING ELEMENTS OR DEVICES FOR CRANES, CAPSTANS, WINCHES, OR TACKLES
- B66C13/00—Other constructional features or details
- B66C13/18—Control systems or devices
- B66C13/48—Automatic control of crane drives for producing a single or repeated working cycle; Programme control
-
- 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
- B66C23/62—Constructional features or details
Landscapes
- Engineering & Computer Science (AREA)
- Mechanical Engineering (AREA)
- Automation & Control Theory (AREA)
- Control And Safety Of Cranes (AREA)
Abstract
The invention requests to protect a maintenance control system of an intelligent tower crane, which acquires working state data of the tower crane; analyzing the working state data of the tower crane, sending the analyzed working state data to an operator for data interaction, and when the working state control data meet a first condition, performing state control on the tower crane by the operator according to the interacted state data; when the working state control data meet the second condition, the operator performs state maintenance on the tower crane according to the interacted state data, and the state control and maintenance data are sent to the background server. According to the technical scheme, real-time calculation and update of the service life of the tower crane component and service life management of the whole life cycle, which are in line with engineering practical application scenes, can be realized, the number of required tower crane data monitoring sensors can be reduced, classification processing is carried out according to multi-working state data, and control and maintenance processing costs are reasonably distributed.
Description
Technical Field
The invention relates to the technical field of building machinery, in particular to an intelligent maintenance control system of a tower crane.
Background
As key equipment of modern construction, the tower crane increases the full load rate along with the development of PC construction buildings, and most of the tower crane works under alternating high stress. Research shows that the structural failure mode of the tower crane is fatigue failure more than 80%. Therefore, the structural service working state of the tower crane becomes an important evaluation index for safe and reliable operation. Corresponding technologies exist at home and abroad to study the structural service working state of the tower crane, but most of the technologies belong to theoretical researches, are mainly used for evaluating theoretical working state values under standard experimental conditions, and have larger individual differences on the structural working state of a specific tower crane due to complex and changeable conditions such as super moment, super weight, environmental factors and the like in the actual hoisting process. Therefore, the theoretical working state value has guiding significance for the structural working state evaluation of the actual tower crane, and the actual safety boundary is difficult to evaluate accurately. The development of industry puts higher and higher evaluation demands on the safe use of the tower crane structure, so that the real-time accurate evaluation of the residual working state of the tower crane structure is becoming one focus of attention in the industry.
The main flow of the existing actual tower crane working state assessment theory is to utilize finite element simulation and fatigue damage theory, take the environmental load acquired in real time on site as boundary conditions, check the working state of the tower crane in real time, and then utilize stress strain information acquired in site to calculate the residual working state according to the damage theory. Although the theoretical mode can accurately calculate the residual working state of the tower crane, the following defects exist: (1) The finite element simulation technology is utilized to carry out working state calibration, so that the accuracy of boundary conditions of the simulation model is required to be very high, the load and the cost for collecting environmental load are increased, and the difficulty in obtaining environmental and working condition information data for a long time and the high implementation cost are caused by the characteristic. In addition, the reliability and economy of the prior art of part of the types of sensors lead to low reliability of field complex load information acquisition, and excessive installation and monitoring cost and maintenance cost. (2) The accurate description of environment and working condition information can enable the on-site real-time acquisition data volume to be large, the data preprocessing consumes a long time, the terminal computing resources and memory resources are occupied, the terminal performance of the tower crane is affected, and the terminal economy of the tower crane is reduced. Meanwhile, a large amount of data transmission has high requirements on network environment and hardware. The construction environment is complex, the network signal is poor, and the infrastructure is not sound, so that the timeliness and feasibility of the working state evaluation system are greatly reduced. (3) The existing residual working state management system only focuses on the residual working state description of the tower crane, but does not relate the residual working state evaluation of the tower crane to actual construction management, remanufacturing, scrapping and the like of a user, and the management function of the system in the whole life cycle process of the tower crane is omitted. Therefore, there is an urgent need to propose a technical solution to solve the above technical problems in the prior art.
Disclosure of Invention
The embodiment of the invention aims to provide an intelligent maintenance control system for a tower crane, which solves the technical problems in the prior art.
The invention discloses an intelligent tower crane maintenance control system, which is characterized by comprising:
the acquisition module is used for acquiring the working state data of the tower crane;
the analysis module is used for carrying out data analysis on the working state data of the tower crane;
the interaction module is used for sending the analyzed working state data to an operator for data interaction;
the first state module is used for controlling the state of the tower crane according to the interacted state data by an operator when the working state control data of the tower crane meets a first condition;
the second state module is used for carrying out state maintenance on the tower crane according to the interacted state data by an operator when the working state control data of the tower crane meets a second condition;
and the backup module is used for sending the data of the state control and maintenance to a background server.
Specifically, the obtaining the working state data of the tower crane specifically includes:
classifying the tower crane according to the working state and the working mode;
the working states of the tower crane comprise a working state and a static state;
the working mode of the tower crane comprises stretching, rotating and supporting of elements of the tower crane;
and the working state data of the tower crane is obtained by at least a first sensor, a second sensor and a third sensor.
Specifically, the classifying the tower crane according to the working state and the working mode further comprises:
when the working state of the tower crane is a working state, setting the working state data of the tower crane to be an excited state;
when the working state of the tower crane is a static state, setting the working state data of the tower crane to be a hibernation state;
when the working mode of the tower crane is the stretching work of elements of the tower crane, setting the working state data of the tower crane as first sensor data priority weight;
when the working mode of the tower crane is rotary working of elements of the tower crane, setting the working state data of the tower crane as second sensor data priority weight;
when the working mode of the tower crane is the supporting work of the elements of the tower crane, the working state data of the tower crane is set as the third sensor data priority weight.
Specifically, the data analysis on the working state data of the tower crane specifically includes:
performing format conversion on the working state data according to the priority weight and the setting state in the obtained working state data of the tower crane;
and sending the work state data after format conversion to an operator for data interaction.
Specifically, the format conversion of the working state data according to the obtained priority weight and the setting state in the working state data of the tower crane specifically includes:
when the working state data of the tower crane is set to be in a hibernation state, converting the working state data of all elements of the tower crane into data in a text txt format for storage for subsequent viewing;
when the working state data of the tower crane is set to be in an excited state and the working state data of the tower crane is set to be a first sensor data priority weight, converting the working state data of all elements of the tower crane into data in a picture format;
when the working state data of the tower crane is set to be in an excited state and the working state data of the tower crane is set to be the second sensor data priority weight, converting the working state data of all elements of the tower crane into data in a video format;
and when the working state data of the tower crane is set to be in an excited state and the working state data of the tower crane is set to be in a third sensor data priority weight, converting the working state data of all elements of the tower crane into data in a vector format.
Specifically, the sending the parsed working state data to an operator for data interaction specifically includes: extracting the data format of the analyzed working state data, and constructing a data state working model from the working state data under the data format;
the working model shows the working characterization index of the tower crane.
Specifically, the extracting the data format of the parsed working state data, and building a data state working model from the working state data in the data format specifically includes:
d in MEM The height of the tower crane is represented, EW represents the telescopic length of the tower crane, omega represents the rotation angle of the tower crane, lambda represents the ambient wind speed, t represents the working time of the tower crane, and n d Representing the adjustment coefficient, J ion Represents the weight of the tower crane, G represents the gravitational constant, D mw Represents the ambient temperature, S mw And representing working condition data of the tower crane.
Specifically, when the working state control data of the tower crane meets a first condition, an operator performs state control on the tower crane according to the interacted state data, and the method specifically includes:
based on the working condition data, when the working condition data value is larger than a first threshold value, the working condition data value confirms that the current working mode of the tower crane is normal, and the operator monitors the working condition of the tower crane in real time;
and the operator normally operates the tower crane.
Specifically, when the working state control data of the tower crane meets the second condition, the operator performs state maintenance on the tower crane according to the interacted state data, and specifically includes:
based on the working condition data, when the working condition data value is smaller than a first threshold value, the current working mode of the tower crane is determined to be abnormal, and the operator performs operation inhibition and fault maintenance on the working condition of the tower crane.
Specifically, the sending the data for controlling and maintaining the state to the background server specifically includes:
the server is provided with a distributed multi-Agent structure, each tower crane is provided with a sub Agent, networking is carried out among the sub agents, and each Agent has the functions of information acquisition, control decision and information exchange.
The invention discloses an intelligent tower crane maintenance control system which is claimed by the invention, and working state data of a tower crane are obtained; analyzing the working state data of the tower crane, sending the analyzed working state data to an operator for data interaction, and when the working state control data meet a first condition, performing state control on the tower crane by the operator according to the interacted state data; when the working state control data meet the second condition, the operator performs state maintenance on the tower crane according to the interacted state data, and the state control and maintenance data are sent to the background server. According to the technical scheme, real-time calculation and update of the service life of the tower crane component and service life management of the whole life cycle, which are in line with engineering practical application scenes, can be realized, the number of required tower crane data monitoring sensors can be reduced, classification processing is carried out according to multi-working state data, and control and maintenance processing costs are reasonably distributed.
Drawings
The accompanying drawings are included to provide a further understanding of embodiments of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain, without limitation, the embodiments of the invention.
FIG. 1 is a block diagram of an intelligent tower crane maintenance control system according to the present invention;
FIG. 2 is a flowchart illustrating an embodiment of a maintenance control system for an intelligent tower crane according to the present invention;
fig. 3 is a flowchart illustrating a second embodiment of a maintenance control system for an intelligent tower crane according to the present invention.
Detailed Description
The following describes the detailed implementation of the embodiments of the present invention with reference to the drawings. It should be understood that the detailed description and specific examples, while indicating and illustrating the invention, are not intended to limit the invention.
In the present embodiment, if directional indications (such as up, down, left, right, front, and rear … …) are included, the directional indications are merely used to explain the relative positional relationship, movement, and the like between the components in a specific posture (as shown in the drawings), and if the specific posture is changed, the directional indications are correspondingly changed.
In addition, if there is a description of "first", "second", etc. in the embodiments of the present application, the description of "first", "second", etc. is for descriptive purposes only and is not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. In addition, the technical solutions of the embodiments may be combined with each other, but it is necessary to base that the technical solutions can be realized by those skilled in the art, and when the technical solutions are contradictory or cannot be realized, the combination of the technical solutions should be considered to be absent and not within the protection scope of the present application.
Referring to fig. 1, the present invention is directed to an intelligent tower crane maintenance control system, comprising:
the acquisition module is used for acquiring the working state data of the tower crane;
the analysis module is used for carrying out data analysis on the working state data of the tower crane;
the interaction module is used for sending the analyzed working state data to an operator for data interaction;
the first state module is used for controlling the state of the tower crane according to the interacted state data by an operator when the working state control data of the tower crane meets a first condition;
the second state module is used for carrying out state maintenance on the tower crane according to the interacted state data by an operator when the working state control data of the tower crane meets a second condition;
and the backup module is used for sending the data of the state control and maintenance to a background server.
Specifically, the obtaining the working state data of the tower crane specifically includes:
classifying the tower crane according to the working state and the working mode;
the working states of the tower crane comprise a working state and a static state;
the working mode of the tower crane comprises stretching, rotating and supporting of elements of the tower crane;
and the working state data of the tower crane is obtained by at least a first sensor, a second sensor and a third sensor.
Specifically, referring to fig. 2, the classifying the tower crane according to the working state and the working mode further includes:
when the working state of the tower crane is a working state, setting the working state data of the tower crane to be an excited state;
when the working state of the tower crane is a static state, setting the working state data of the tower crane to be a hibernation state;
when the working mode of the tower crane is the stretching work of elements of the tower crane, setting the working state data of the tower crane as first sensor data priority weight;
when the working mode of the tower crane is rotary working of elements of the tower crane, setting the working state data of the tower crane as second sensor data priority weight;
when the working mode of the tower crane is the supporting work of the elements of the tower crane, the working state data of the tower crane is set as the third sensor data priority weight.
The elements of the tower crane at least comprise a crane boom, a crane transition section, a crane foundation section, a tower body standard section, an upper support, a lower support and a tower head.
The working states of the hoisting transition section, the hoisting foundation section and the standard tower section are stretching;
the working state of the lifting arm is rotary;
the working states of the upper support, the lower support and the tower head are supporting work.
Because the working states of different elements are different, the emphasis of the working states is different, and when the elements are in the working mode of the working states of the elements, the data collected by the corresponding sensors are given higher weight to represent the working state of the tower crane, so that the subsequent control and maintenance are convenient.
Specifically, the data analysis on the working state data of the tower crane specifically includes:
performing format conversion on the working state data according to the priority weight and the setting state in the obtained working state data of the tower crane;
and sending the work state data after format conversion to an operator for data interaction.
Specifically, referring to fig. 3, the converting the format of the working state data according to the priority weight and the setting state in the obtained working state data of the tower crane specifically includes:
when the working state data of the tower crane is set to be in a hibernation state, converting the working state data of all elements of the tower crane into data in a text txt format for storage for subsequent viewing;
when the working state data of the tower crane is set to be in an excited state and the working state data of the tower crane is set to be a first sensor data priority weight, converting the working state data of all elements of the tower crane into data in a picture format;
when the working state data of the tower crane is set to be in an excited state and the working state data of the tower crane is set to be the second sensor data priority weight, converting the working state data of all elements of the tower crane into data in a video format;
and when the working state data of the tower crane is set to be in an excited state and the working state data of the tower crane is set to be in a third sensor data priority weight, converting the working state data of all elements of the tower crane into data in a vector format.
When the working state data of the tower crane is set to be in an excited state and the working state data of the tower crane is set to be in a first sensor data priority weight, that is to say, the working state of the tower crane is in an extended working state, the static images of the current tower crane in different time periods during working are indicated to have a degree of distinction, so that whether the current tower crane works normally or not is indicated, and therefore the working state data of all elements of the tower crane are converted into data in a picture format.
When the working state data of the tower crane is set to be in an excited state and the working state data of the tower crane is set to be in a second sensor data priority weight, that is to say, the working state of the tower crane is in a rotating working state, the map change images of the current tower crane in different time periods during working are indicated to be more differentiated, so that whether the current tower crane works normally or not is indicated, and therefore the working state data of all elements of the tower crane are converted into data in a video format;
when the working state data of the tower crane is set to be in an excited state and the working state data of the tower crane is set to be in a third sensor data priority weight, that is, the working state of the tower crane is in a supporting working state, the change of the current tower crane in different time periods during working is not obvious, and data with small data volume are needed to indicate whether the current tower crane works normally or not, so that the working state data of all elements of the tower crane are converted into data in a vector format.
Specifically, the sending the parsed working state data to an operator for data interaction specifically includes: extracting the data format of the analyzed working state data, and constructing a data state working model from the working state data under the data format;
the working model shows the working characterization index of the tower crane.
Specifically, the extracting the data format of the parsed working state data, and building a data state working model from the working state data in the data format specifically includes:
d in MEM The height of the tower crane is represented, EW represents the telescopic length of the tower crane, omega represents the rotation angle of the tower crane, lambda represents the ambient wind speed, t represents the working time of the tower crane, and n d Representing the adjustment coefficient, J ion Represents the weight of the tower crane, G represents the gravitational constant, D mw Represents the ambient temperature, S mw And representing working condition data of the tower crane.
Obtaining two coordinate points A (x) of the tower head under the working state of the tower crane by utilizing a random function method 1 ,y 1 ,z 1 ),B(x 2 ,y 2 ,z 2 ) The expression is as follows:
x 1 =L·Rand_x+(L+W) (1-1)
x 2 =L·Rand_x-(L+W) (1-2)
z 1 =(L+W)tan(π·Rand_θ)+W·Rand_z (1-5)
z 2 =-(L+W)tan(π·Rand_θ)+W·Rand_z (1-6)
wherein rand_x and rand_z respectively represent values generated by a random function and used for calculating coordinates, rand_θ represents values generated by the random function and used for calculating radian (the values are required to be limited in a definition domain of the function), and i represents the rotation speed of the tower crane;
connecting the generated points A, B, discarding the part exceeding the length and the width of the theoretical rotation, carrying out cylindrical expansion on the line according to the rotation diameter of the tower crane to generate a rotating three-dimensional model block of the tower crane, randomly generating a plurality of tower crane rotating model blocks within a certain time by repeating the process, thereby obtaining a layer of tower crane rotating model block with expected rotation normal rate, and stacking the plurality of tower crane rotating model blocks which are randomly generated to obtain the tower crane rotating model with the three-dimensional porous structure.
Specifically, when the working state control data of the tower crane meets a first condition, an operator performs state control on the tower crane according to the interacted state data, and the method specifically includes:
based on the working condition data, when the working condition data value is larger than a first threshold value, the working condition data value confirms that the current working mode of the tower crane is normal, and the operator monitors the working condition of the tower crane in real time;
and the operator normally operates the tower crane.
Specifically, when the working state control data of the tower crane meets the second condition, the operator performs state maintenance on the tower crane according to the interacted state data, and specifically includes:
based on the working condition data, when the working condition data value is smaller than a first threshold value, the current working mode of the tower crane is determined to be abnormal, and the operator performs operation inhibition and fault maintenance on the working condition of the tower crane.
Further, when the working condition data value is larger than a first threshold value, the working mode of the tower crane is considered to be normal, that is, the working state of the tower crane in the current environment is in a normal range content, and the operator monitors the working condition of the tower crane in real time;
based on the working condition data, when the working condition data value is larger than a first threshold value, the working mode of the tower crane is considered to be normal, that is, the working state of the tower crane in the current environment is in abnormal range content, and the operator monitors the working condition of the tower crane in real time.
An embodiment is described below, in which the tower crane builds and inputs process data before the tower crane is constructed on site, including the time for erecting the tower, lifting, and removing the tower, and the corresponding part numbers and key part names. And uploading the data to a server through GPRS to realize data storage. When the W6017-10B tower crane is in construction, a moment sensor on a crane arm acquires real-time lifting moment in real time when the tower crane works, data is transmitted to an ECU (electronic control unit) of the tower crane through a LAN485 bus, data cleaning analysis is carried out, and information such as real-time lifting amplitude value of the tower crane is combined to obtain real-time maximum load moment percentage K in the working process of the tower crane n . The ECU calculates each tower crane in real time by using the tower crane loss life calculation modelReal-time remaining life information of the component. And displaying the service life of the calculated result at the tower crane terminal, and uploading the service life to a server through GPRS equipment to update the file information of the components of the tower crane.
Specifically, the sending the data for controlling and maintaining the state to the background server specifically includes:
the server is provided with a distributed multi-Agent structure, each tower crane is provided with a sub Agent, networking is carried out among the sub agents, and each Agent has the functions of information acquisition, control decision and information exchange.
Those skilled in the art will appreciate that various modifications and improvements can be made to the disclosure. For example, the various devices or components described above may be implemented in hardware, or may be implemented in software, firmware, or a combination of some or all of the three.
A flowchart is used in this disclosure to describe the steps of a method according to an embodiment of the present disclosure. It should be understood that the steps that follow or before do not have to be performed in exact order. Rather, the various steps may be processed in reverse order or simultaneously. Also, other operations may be added to these processes.
The foregoing is illustrative of the present disclosure and is not to be construed as limiting thereof. Although a few exemplary embodiments of this disclosure have been described, those skilled in the art will readily appreciate that many modifications are possible in the exemplary embodiments without materially departing from the novel teachings and advantages of this disclosure. Accordingly, all such modifications are intended to be included within the scope of this disclosure as defined in the claims. It is to be understood that the foregoing is illustrative of the present disclosure and is not to be construed as limited to the specific embodiments disclosed, and that modifications to the disclosed embodiments, as well as other embodiments, are intended to be included within the scope of the appended claims. The disclosure is defined by the claims and their equivalents.
In the description of the present specification, reference to the terms "one embodiment," "some embodiments," "illustrative embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present application. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
While embodiments of the present application have been shown and described, it will be understood by those of ordinary skill in the art that: many changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the application, the scope of which is defined by the claims and their equivalents.
Claims (6)
1. An intelligent tower crane maintenance control system, comprising: the acquisition module is used for acquiring the working state data of the tower crane;
the analysis module is used for carrying out data analysis on the working state data of the tower crane;
the interaction module is used for sending the analyzed working state data to an operator for data interaction;
the first state module is used for controlling the state of the tower crane according to the interacted state data by an operator when the working state control data of the tower crane meets a first condition;
the second state module is used for carrying out state maintenance on the tower crane according to the interacted state data by an operator when the working state control data of the tower crane meets a second condition;
the backup module is used for sending the data of the state control and maintenance to a background server;
the obtaining the working state data of the tower crane specifically comprises the following steps:
classifying the tower crane according to the working state and the working mode;
the working states of the tower crane comprise a working state and a static state;
the working mode of the tower crane comprises stretching, rotating and supporting of elements of the tower crane;
the working state data of the tower crane is obtained by at least a first sensor, a second sensor and a third sensor;
the classification of the tower crane according to the working state and the working mode further comprises:
when the working state of the tower crane is a working state, setting the working state data of the tower crane to be an excited state;
when the working state of the tower crane is a static state, setting the working state data of the tower crane to be a hibernation state;
when the working mode of the tower crane is the stretching work of elements of the tower crane, setting the working state data of the tower crane as first sensor data priority weight;
when the working mode of the tower crane is rotary working of elements of the tower crane, setting the working state data of the tower crane as second sensor data priority weight;
when the working mode of the tower crane is the supporting work of elements of the tower crane, setting the working state data of the tower crane as the data priority weight of a third sensor;
the data analysis of the working state data of the tower crane specifically comprises the following steps:
performing format conversion on the working state data according to the priority weight and the setting state in the obtained working state data of the tower crane;
transmitting the work state data after format conversion to an operator for data interaction;
the format conversion of the working state data is performed according to the obtained priority weight and the setting state in the working state data of the tower crane, and specifically comprises the following steps:
when the working state data of the tower crane is set to be in a hibernation state, converting the working state data of all elements of the tower crane into data in a text txt format for storage for subsequent viewing;
when the working state data of the tower crane is set to be in an excited state and the working state data of the tower crane is set to be a first sensor data priority weight, converting the working state data of all elements of the tower crane into data in a picture format;
when the working state data of the tower crane is set to be in an excited state and the working state data of the tower crane is set to be the second sensor data priority weight, converting the working state data of all elements of the tower crane into data in a video format;
and when the working state data of the tower crane is set to be in an excited state and the working state data of the tower crane is set to be in a third sensor data priority weight, converting the working state data of all elements of the tower crane into data in a vector format.
2. The maintenance control system of an intelligent tower crane according to claim 1, wherein the sending the parsed working state data to an operator for data interaction specifically comprises:
extracting the data format of the analyzed working state data, and constructing a data state working model from the working state data under the data format;
the working model shows the working characterization index of the tower crane.
3. The maintenance control system of an intelligent tower crane according to claim 2, wherein the extracting the data format of the parsed working state data builds a data state working model from the working state data in the data format, and specifically comprises:
in the middle ofRepresenting tower crane height +.>Represents the telescopic length of the tower crane, < > or>Represents the rotation angle of the tower crane->Indicating ambient wind speed>Indicating the working time of the tower crane->Representing adjustment coefficients->Representing the weight of the tower crane>Representing gravitational constant, ++>Indicating ambient temperature, ++>And representing working condition data of the tower crane.
4. The intelligent tower crane maintenance control system according to claim 3, wherein when the working state control data of the tower crane meets a first condition, an operator performs state control on the tower crane according to the interacted state data, and the intelligent tower crane maintenance control system specifically comprises:
based on the working condition data, when the working condition data value is larger than a first threshold value, the working condition data value confirms that the current working mode of the tower crane is normal, and the operator monitors the working condition of the tower crane in real time;
and the operator normally operates the tower crane.
5. The maintenance control system of claim 3, wherein when the operating state control data of the tower crane meets the second condition, the operator performs the state maintenance on the tower crane according to the interacted state data, and the maintenance control system specifically comprises:
based on the working condition data, when the working condition data value is smaller than a first threshold value, the current working mode of the tower crane is determined to be abnormal, and the operator performs operation inhibition and fault maintenance on the working condition of the tower crane.
6. The maintenance control system of an intelligent tower crane according to claim 1, wherein the data for controlling and maintaining the state is sent to a background server, and specifically comprises:
the server is provided with a distributed multi-Agent structure, each tower crane is provided with a sub Agent, networking is carried out among the sub agents, and each Agent has the functions of information acquisition, control decision and information exchange.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202211020323.8A CN115535854B (en) | 2022-08-24 | 2022-08-24 | Intelligent maintenance control system for tower crane |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202211020323.8A CN115535854B (en) | 2022-08-24 | 2022-08-24 | Intelligent maintenance control system for tower crane |
Publications (2)
Publication Number | Publication Date |
---|---|
CN115535854A CN115535854A (en) | 2022-12-30 |
CN115535854B true CN115535854B (en) | 2024-01-19 |
Family
ID=84725767
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202211020323.8A Active CN115535854B (en) | 2022-08-24 | 2022-08-24 | Intelligent maintenance control system for tower crane |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN115535854B (en) |
Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2001328792A (en) * | 2000-05-19 | 2001-11-27 | Mitsubishi Heavy Ind Ltd | Remote monitoring and maintenance system |
FI20125964A (en) * | 2012-09-19 | 2014-03-20 | Konecranes Oyj | A predictive maintenance method and system |
CN103922227A (en) * | 2013-01-11 | 2014-07-16 | 上海船厂船舶有限公司 | Crane monitoring and management system |
CN214192292U (en) * | 2020-11-30 | 2021-09-14 | 北京起重运输机械设计研究院有限公司 | Remote maintenance device for crane |
WO2021213293A1 (en) * | 2020-04-24 | 2021-10-28 | 西北工业大学 | Ubiquitous operating system oriented toward group intelligence perception |
CN114408748A (en) * | 2022-03-21 | 2022-04-29 | 杭州杰牌传动科技有限公司 | State data monitoring and transmitting system and method for remote control of intelligent tower crane |
CN114604768A (en) * | 2022-01-24 | 2022-06-10 | 杭州大杰智能传动科技有限公司 | Intelligent tower crane maintenance management method and system based on fault identification model |
-
2022
- 2022-08-24 CN CN202211020323.8A patent/CN115535854B/en active Active
Patent Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2001328792A (en) * | 2000-05-19 | 2001-11-27 | Mitsubishi Heavy Ind Ltd | Remote monitoring and maintenance system |
FI20125964A (en) * | 2012-09-19 | 2014-03-20 | Konecranes Oyj | A predictive maintenance method and system |
CN103922227A (en) * | 2013-01-11 | 2014-07-16 | 上海船厂船舶有限公司 | Crane monitoring and management system |
WO2021213293A1 (en) * | 2020-04-24 | 2021-10-28 | 西北工业大学 | Ubiquitous operating system oriented toward group intelligence perception |
CN214192292U (en) * | 2020-11-30 | 2021-09-14 | 北京起重运输机械设计研究院有限公司 | Remote maintenance device for crane |
CN114604768A (en) * | 2022-01-24 | 2022-06-10 | 杭州大杰智能传动科技有限公司 | Intelligent tower crane maintenance management method and system based on fault identification model |
CN114408748A (en) * | 2022-03-21 | 2022-04-29 | 杭州杰牌传动科技有限公司 | State data monitoring and transmitting system and method for remote control of intelligent tower crane |
Also Published As
Publication number | Publication date |
---|---|
CN115535854A (en) | 2022-12-30 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN111461405A (en) | Pollutant diffusion prediction method, device, equipment and storage medium | |
CN108376184A (en) | A kind of method and system of bridge health monitoring | |
CN111945796A (en) | Foundation pit deformation monitoring synchronous simulation analysis and real-time early warning system based on BIM technology | |
CN107687914A (en) | A kind of bridge management system and bridge management method | |
CN206627815U (en) | A kind of offshore wind power foundation structure remote monitoring system | |
KR20130094082A (en) | Telecommunication tower control system using wireless sensor network | |
CN102299948A (en) | Wireless detection system and method of building structure relative storey displacement under vibration environment | |
CN108089560A (en) | A kind of gate and headstock gear real time on-line monitoring and operational safety management system and its implementation | |
CN114689129B (en) | Underground space environment monitoring system and method | |
CN113155196A (en) | Bridge operation real-time monitoring system based on AIoT and monitoring method thereof | |
WO2020233699A1 (en) | Apparatus and method used for monitoring internal motion state of road bridge tunnel | |
Naraharisetty et al. | Cloud architecture for IoT based bridge monitoring applications | |
CN112991096A (en) | Monitoring and managing device and method for configuration type bridge cluster structure | |
Smarsly et al. | Advanced Structural Health Monitoring Based on Multiagent Technology | |
CN112770285A (en) | Digital twin factory modeling method and device based on 5G network | |
CN115049798A (en) | Metal roof health monitoring system and method based on BIM | |
CN115535854B (en) | Intelligent maintenance control system for tower crane | |
CN115535855B (en) | Control maintenance method of tower crane | |
CN111189533B (en) | External force invasion monitoring method and device, computer equipment and storage medium | |
CN204239154U (en) | Wind-driven generator tower sedimentation is tilted and vibrations safety monitoring system | |
CN215895464U (en) | Intelligent monitoring early warning analysis system in cable construction process | |
CN112525140B (en) | Beidou deformation inspection system | |
CN211906344U (en) | Construction quality supervision device based on BIM technology | |
CN109100102B (en) | Fan modal analysis method, device, terminal and computer readable storage medium based on strain continuous monitoring | |
CN113432657A (en) | Bridge safety monitoring platform based on GIS and BIM technology |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant |