CN115092838B

CN115092838B - Tower crane operation parameter control method, system, device and storage medium

Info

Publication number: CN115092838B
Application number: CN202210703179.1A
Authority: CN
Inventors: 印卫东; 杨亿; 张纯超
Original assignee: Zhangjiagang Shenlian Construction Machinery Co ltd
Current assignee: Zhangjiagang Shenlian Construction Machinery Co ltd
Priority date: 2022-06-21
Filing date: 2022-06-21
Publication date: 2023-09-15
Anticipated expiration: 2042-06-21
Also published as: CN115092838A; CN117361359A; CN117361359B

Abstract

The embodiment of the specification provides a method, a system, a device and a storage medium for controlling operation parameters of a tower crane, wherein the method comprises the following steps: determining lifting parameters, wherein the lifting parameters comprise the position of a lifting hook and the corresponding lifting speed of the lifting hook in the lifting process of the tower crane; presetting operation target parameters of the tower crane based on hoisting parameters, and controlling the operation of the tower crane based on the operation target parameters; and acquiring the running real-time parameters of the tower crane, and sending out alarm information in response to the difference between the running real-time parameters and the running target parameters exceeding the preset conditions.

Description

Tower crane operation parameter control method, system, device and storage medium

Technical Field

The present disclosure relates to the field of engineering machine control, and in particular, to a method, a system, an apparatus, and a storage medium for controlling operating parameters of a tower crane.

Background

The existing tower crane operation control generally needs to manually continuously adjust the lifting hook position and the lifting speed corresponding to the lifting hook position of the tower crane, so that the stability and the position accuracy in the lifting process are not ensured, and meanwhile, the time for completing one operation period of the tower crane is uncontrollable.

It is therefore desirable to provide an efficient, reliable, automatically controllable method and system for controlling the operational parameters of a tower crane.

Disclosure of Invention

One of the embodiments of the present disclosure provides a method for controlling an operating parameter of a tower crane. The method comprises the following steps: determining lifting parameters, wherein the lifting parameters comprise the position of a lifting hook and the corresponding lifting speed of the lifting hook in the lifting process of the tower crane; presetting operation target parameters of the tower crane based on the hoisting parameters, and controlling the tower crane to operate based on the operation target parameters; and acquiring the running real-time parameters of the tower crane, and sending out alarm information in response to the difference between the running real-time parameters and the running target parameters exceeding a preset condition.

One of the embodiments of the present disclosure provides a tower crane operating parameter control system, the system comprising: the lifting parameter determining module is used for determining lifting parameters, wherein the lifting parameters comprise the position of a lifting hook and the corresponding lifting speed in the lifting process of the tower crane; the control module is used for presetting operation target parameters of the tower crane based on the hoisting parameters and controlling the operation of the tower crane based on the operation target parameters; and the alarm module is used for acquiring the operation real-time parameters of the tower crane, and sending alarm information in response to the difference between the operation real-time parameters and the operation target parameters exceeding a preset condition.

One of the embodiments of the present disclosure provides an apparatus for controlling an operating parameter of a tower crane, including a processor and a memory; the memory is used for storing computer instructions which when executed by the processor implement the tower crane operating parameter control method.

One of the embodiments of the present specification provides a computer-readable storage medium storing computer instructions that, when read by a computer in the storage medium, the computer performs a method of controlling operational parameters of a tower crane.

Drawings

The present specification will be further elucidated by way of example embodiments, which will be described in detail by means of the accompanying drawings. The embodiments are not limiting, in which like numerals represent like structures, wherein:

FIG. 1 is a schematic illustration of an application scenario of a tower crane operating parameter control system according to some embodiments of the present disclosure;

FIG. 2 is a block diagram of a tower machine operating parameter control system according to some embodiments of the present disclosure;

FIG. 3 is an exemplary flow chart of a method of controlling operational parameters of a tower crane according to some embodiments of the present disclosure;

FIG. 4 is a flow chart illustrating determination of lifting parameters according to some embodiments of the present disclosure;

Fig. 5 is a schematic illustration of determining lifting parameters according to some embodiments of the present description.

Detailed Description

In order to more clearly illustrate the technical solutions of the embodiments of the present specification, the drawings that are required to be used in the description of the embodiments will be briefly described below. It is apparent that the drawings in the following description are only some examples or embodiments of the present specification, and it is possible for those of ordinary skill in the art to apply the present specification to other similar situations according to the drawings without inventive effort. Unless otherwise apparent from the context of the language or otherwise specified, like reference numerals in the figures refer to like structures or operations.

It will be appreciated that "system," "apparatus," "unit" and/or "module" as used herein is one method for distinguishing between different components, elements, parts, portions or assemblies at different levels. However, if other words can achieve the same purpose, the words can be replaced by other expressions.

As used in this specification and the claims, the terms "a," "an," "the," and/or "the" are not specific to a singular, but may include a plurality, unless the context clearly dictates otherwise. In general, the terms "comprises" and "comprising" merely indicate that the steps and elements are explicitly identified, and they do not constitute an exclusive list, as other steps or elements may be included in a method or apparatus.

A flowchart is used in this specification to describe the operations performed by the system according to embodiments of the present specification. It should be appreciated that the preceding or following operations are not necessarily performed in order precisely. Rather, the steps may be processed in reverse order or simultaneously. Also, other operations may be added to or removed from these processes.

Fig. 1 is a schematic view of an application scenario of a tower crane operating parameter control system according to some embodiments of the present disclosure.

As shown in fig. 1, an application scenario 100 of a tower crane operating parameter control system may include a processing device 110, a storage device 120, a terminal 130, a tower crane device 140, and a network 150. The components in the application scenario 100 of the tower crane operating parameter control system may be connected in one or more of a variety of ways.

The processing device 110 may process data and/or information obtained from the tower apparatus 140, the storage device 120, and/or the terminal 130. The processing device 110 may obtain the operation target parameters of the tower crane by using the received basic parameters of the tower crane through preset processing, so as to control the operation of the tower crane. For example, the processing device 110 may process data generated by the tower apparatus 140. In some embodiments, the processing device 110 may be a single server or a group of servers.

Storage device 120 may store data, instructions, and/or any other information, for example, storage device 120 may store information or data obtained from processing device 110 and/or tower apparatus 140. As another example, the storage device 120 may store data and/or instructions that are used by the processing device 110 to perform or use the exemplary methods described in this specification.

In some embodiments, the storage device 120 may be connected to the network 150 to enable communication with one or more components (e.g., the processing device 110, the terminal 130, etc.) in the application scenario 100 of the tower crane operating parameter control system. One or more components in the application scenario 100 of the tower crane operating parameter control system may read data or instructions in the storage device 120 over the network 150.

Terminal 130 may refer to one or more terminal devices or software used by a user. In some embodiments, the terminal 130 may include a smart phone 130-1, a tablet computer 130-2, a notebook computer 130-3, a desktop computer 130-4, or the like, or any combination thereof. In some embodiments, the terminal 130 may interact with other components in the application scenario 100 of the tower crane operating parameter control system over a network. In some embodiments, the terminal 130 may be integral with the processing device 110 as an operator console for the tower apparatus 140.

In some embodiments, the terminal may be fixed and/or mobile. For example, the terminal 130 may be fixed to the tower apparatus 140 or may be a mobile terminal. In some embodiments, terminal 130 may be configured to input tower foundation parameters to facilitate the associated processing of subsequent processing devices 110. In some embodiments, the terminal 130 may be configured to display an alarm message to alert an administrator of the tower crane apparatus. The above examples are only intended to illustrate the breadth of the scope of the terminal 130 and not to limit its scope.

The tower crane device 140 may provide the processing device 110 with the basic parameters of the tower crane, and the tower crane device 140 may receive the operation target parameters of the tower crane obtained by performing specific processing on the basic parameters of the tower crane by the processing device 110, so as to perform operation of the tower crane based on the operation target parameters.

Network 150 may provide any suitable network for information and/or data exchange in application scenario 100 of the tower crane operating parameter control system. In some embodiments, one or more components of the application scenario 100 of the tower crane operating parameter control system (e.g., the processing device 110, the storage device 120, the terminal 130, the tower crane device 140, etc.) may exchange information and/or data with one or more components of the application scenario 100 of the tower crane operating parameter control system over the network 150.

For example, the processing device 110 may obtain tower crane base parameters of the tower crane device 140 via the network 150. For another example, the tower crane apparatus 140 may obtain tower crane operating target parameters obtained by the processing apparatus 110 via the network 150. As another example, processing device 110 may access data and/or instructions stored by storage device 120 via network 150. Network 150 may include a Local Area Network (LAN), wide Area Network (WAN), wired network, wireless network, etc., or any combination thereof.

It should be noted that the application scenario 100 of the tower crane operating parameter control system is provided for illustrative purposes only and is not intended to limit the scope of the present description. Many modifications and variations will be apparent to those of ordinary skill in the art in light of the present description. For example, the application scenario may also include a database. As another example, the application scenario 100 may be implemented on other devices to implement similar or different functionality. However, variations and modifications do not depart from the scope of the present description.

FIG. 2 is a block diagram of a tower machine operating parameter control system, according to some embodiments of the present disclosure. In some embodiments, the tower crane operating parameter control system 200 may include a hoist parameter determination module 210, a control module 220, and an alarm module 230.

In some embodiments, the lifting parameter determination module 210 may be used to determine lifting parameters. The hoisting parameters comprise the position of a lifting hook and the corresponding hoisting speed in the hoisting process of the tower crane.

In some embodiments, the control module 220 may be configured to preset an operational target parameter for the tower crane based on the hoisting parameter determined by the hoisting parameter determination module 210, and control the operation of the tower crane based on the operational target parameter.

In some embodiments, the alarm module 230 may be configured to obtain an operational real-time parameter of the tower crane, and send out alarm information in response to the operational real-time parameter differing from the operational target parameter by more than a preset condition.

See fig. 3-5 for more details regarding the lifting parameter determination module 210, the control module 220, and the alert module 230.

It should be understood that the system shown in fig. 2 and its modules may be implemented in a variety of ways.

It should be noted that the above description of the tower crane operating parameter control system and its modules is for convenience only and is not intended to limit the present disclosure to the scope of the illustrated embodiments. It will be appreciated by those skilled in the art that, given the principles of the system, various modules may be combined arbitrarily or a subsystem may be constructed in connection with other modules without departing from such principles. In some embodiments, the lifting parameter determination module 210, the control module 220, and the alarm module 230 disclosed in fig. 1 may be different modules in one system, or may be one module to implement the functions of two or more modules described above. For example, each module may share one memory module, or each module may have a respective memory module. Such variations are within the scope of the present description.

FIG. 3 is an exemplary flow chart of a method of controlling operational parameters of a tower crane according to some embodiments of the present description. As shown in fig. 3, the process 300 includes the following steps. In some embodiments, the process 300 may be performed by the processing device 110.

Step 310, determining hoisting parameters, wherein the hoisting parameters comprise the position of a lifting hook and the corresponding hoisting speed in the hoisting process of the tower crane. In some embodiments, step 310 may be performed by the lifting parameter determination module 210.

The hoisting parameters may be parameter information related to the hoisting process of the tower crane. For example, the lifting parameters may include the position of the lifting hook and its corresponding lifting speed during lifting of the tower crane. The hoisting parameters may be determined based on basic parameters of the tower crane.

The basic parameters of the tower crane comprise the parameters of the crane weight, the multiplying power of a lifting hook pulley block, the standard section specification and the like of the tower crane. The hoisting weight is the hoisting mass, which can be obtained by a hoisting weight sensor. The multiplying power of the lifting hook pulley block can be input by a user through a terminal. The initial lifting speed of the tower crane lifting hook can be determined based on the lifting weight and the multiplying power of the lifting hook pulley block. The standard knot specification comprises standard knot size and number, and the standard knot size influences the firmness and stability of the tower crane. The lifting height of each specification is generally marked when leaving the factory, the specifications are different, and the lifting heights have corresponding differences. The lifting height of the tower crane hook can be determined by the product of the standard knot size and the standard knot number.

In some embodiments, the lifting parameter determining module 210 may directly obtain the lifting parameter information of the tower crane apparatus, or may obtain the lifting parameter information of the tower crane apparatus from the storage device. In some embodiments, the lifting parameter determination module 210 may also obtain lifting parameter information of the tower crane apparatus from the terminal.

See fig. 4-5 for more details regarding the determination of lifting parameters.

Step 320, presetting operation target parameters of the tower crane based on the hoisting parameters, and controlling the tower crane to operate based on the operation target parameters. In some embodiments, step 320 may be performed by the control module 220.

The operational target parameter of the tower crane may be a target parameter related to the operation of the tower crane equipment. For example, the operational target parameters may include a target hook position and its corresponding target lifting speed.

In some embodiments, the control module 220 may preset the tower crane operating target parameters of the tower crane apparatus based on the hoisting parameters. In some embodiments, the preset tower crane operation target parameter of the tower crane equipment based on the hoisting parameter may be a preset value of the tower crane operation target parameter of the tower crane equipment based on the hoisting parameter by querying a preset relation comparison table. The preset relation comparison table can comprise the positions of all lifting hooks of the tower crane and the corresponding lifting speeds in the lifting process of the tower crane, as shown in the following table:

Hook position 1	Hook position 2	…	Hook position N
				Lifting speed 1 of lifting hook	Lifting speed 2 of lifting hook	…	Lifting speed N of lifting hook

In some embodiments, the hoisting parameters may be directly used as the target parameters of the tower crane operation, that is, the preset relationship comparison table may be the hoisting parameters themselves. In some embodiments, the hoisting parameters may be subjected to an increasing or decreasing process within a preset range, that is, the preset relationship table is obtained by performing a preset increasing or decreasing process on the hoisting parameters within the preset range. In some embodiments, a combination of the two embodiments is also possible, for example, the lifting parameter is directly used as a part of the tower crane operation target parameter at the initial position of the lifting hook, and the processed parameter is used as the rest part of the tower crane operation target parameter at the other position.

In some embodiments, the control module 220 may control the operation of the tower crane apparatus based on preset tower crane operation target parameters. For example, the control module 220 may control the lifting speed of the crane equipment hook when in the corresponding position based on the target position of the preset hook and its corresponding target lifting speed in the preset crane operation target parameters.

In some embodiments, the control of the operation of the tower crane based on the operation target parameter of the tower crane may be performed by determining a motor frequency corresponding to the lifting speed in the lifting parameters based on the relation between the rotation speed and the frequency of the lifting motor, and controlling the frequency change of the lifting motor according to the motor frequency based on the variable frequency governor so as to control the lifting speed.

The lifting motor refers to a motor used for lifting the lifting hook in tower crane equipment.

The speed of the lifting motor refers to the rotation speed of the lifting motor, and is often called the rotation speed of the lifting motor for short, which is an important parameter of the lifting motor. For example, the rotational speed of the hoist motor may be 3000 rpm or 5000 rpm.

The frequency of the lifting motor refers to the frequency of a lifting motor power supply. For example, the frequency of a lifting motor driven by a 50Hz power frequency power supply is 50Hz. For another example, the frequency of the lifting motor is changed by a lifting motor driven by a variable frequency power supply.

The variable frequency speed regulator can be an important component of the lifting motor, and can convert a power frequency power supply into an alternating current power supply with various frequencies so as to realize variable speed operation of the lifting motor.

The full name of the lifting speed is the lifting speed of the lifting hook, which is the lifting speed corresponding to the lifting hook of the tower crane when the lifting hook is positioned at a specific lifting hook position. In some embodiments, the lifting speed of the lifting hook may be the rotational speed of the corresponding lifting motor. For example, the lifting speed of the hook may be a variable speed value between 1000 rpm and 5000 rpm.

In some embodiments, controlling the lifting speed based on the motor frequency of the lifting motor means that the lifting speed of the lifting hook can be correspondingly controlled by increasing or decreasing the frequency of the lifting motor. In some embodiments, the variable frequency governor may convert the mains frequency power to an ac power of 0-50 Hz, where the frequency of the ac power may be proportional to the lifting speed of the hook. For example, a 1Hz AC power signal may correspond to a hook lifting speed of 100 revolutions per second and a 50Hz AC power signal may correspond to a hook lifting speed of 5000 revolutions per second.

In some embodiments, the control module 220 may determine a hoist motor frequency corresponding to a hoist speed based on a relationship of a hoist motor rotational speed and a hoist motor frequency.

In some embodiments, the rotational speed of the hoist motor may be obtained by the hoist speed of the hook. For example, the rotational speed of the hoist motor may be equal to the hoist speed of the hook.

In some embodiments, the frequency of the lifting motor corresponding to the lifting speed is determined based on the relation between the rotation speed of the lifting motor and the frequency of the lifting motor, and can be determined by a lookup table. For example, the preset lookup table may include rotational speeds of a plurality of lifting motors and frequencies of the corresponding lifting motors. In some embodiments, the relationship between the rotational speed of the hoist motor and the frequency of the hoist motor may be determined by the rotational speed formula n=60 f (1-s)/p of the ac motor, where n is the rotational speed of the motor, f is the frequency of the motor, s is the slip of the motor, and p is the pole pair number of the motor.

In some embodiments, the positioning device, the speed detection device and the variable frequency speed regulator can be connected through the controller, the controller determines the corresponding lifting hook lifting speed based on the lifting hook position acquired by the positioning device, the lifting hook lifting speed is transmitted to the variable frequency speed regulator, and the variable frequency speed regulator adjusts the lifting motor frequency of the corresponding lifting motor based on the lifting hook lifting speed, so that the lifting speed of the lifting hook reaches the target lifting hook lifting speed.

For example, when the lifting hook is at a certain lifting hook position, the controller acquires a specific lifting hook position through a positioning device arranged in the tower crane equipment, the controller determines a corresponding lifting hook lifting speed through a speed detection device arranged in the tower crane equipment, then the controller transmits the lifting hook lifting speed to the variable-frequency speed regulator, and the variable-frequency speed regulator adjusts the lifting motor frequency of a corresponding lifting motor based on the real-time lifting hook lifting speed and the target lifting hook lifting speed, so that the lifting speed of the lifting hook reaches the target speed.

According to the tower crane operation parameter control method, the variable frequency speed regulation based on the real-time operation parameters of the tower crane and the operation target parameters of the tower crane can be realized, and therefore the efficiency of the operation control of the tower crane and the accuracy in the lifting process are improved.

And 330, acquiring the operation real-time parameters of the tower crane, and sending out alarm information in response to the difference between the operation real-time parameters and the operation target parameters exceeding the preset conditions. In some embodiments, step 330 may be performed by alert module 230.

The real-time parameters of operation of the tower crane may be real-time parameters related to operation of the tower crane equipment. For example, the real-time operational parameters of the tower crane may include real-time hook positions and their corresponding real-time lifting speeds.

In some embodiments, the alarm module 230 may obtain real-time operating parameters of the tower crane in real-time through a detection device built in the tower crane equipment. For example, the position of the real-time lifting hook and the corresponding real-time lifting speed thereof can be obtained in real time through a positioning device and a speed detection device which are arranged in the tower crane equipment.

In some embodiments, the preset conditions may include a plurality of preset values or a plurality of preset ranges. For example, the preset conditions may include a preset hook position difference value and a preset lifting speed difference value.

In some embodiments, the preset conditions may be determined based on empirical values or a library of experts.

The alarm information can be used for prompting that the real-time parameters of the operation of the tower crane and the target parameters of the operation of the tower crane are too different. In some embodiments, the alarm information may include alarm information of an operating parameter of the tower crane. For example, the alarm information may be "hook position too different +.! Or the difference of the lifting speed is too large-! ". In some embodiments, the alert information may also include potential hazards and corresponding processing methods that are too different in the tower crane operating parameters. For example, when the difference of the hook positions is too large, the alarm information may be "the difference of the hook positions is too large, which may cause instability, please immediately adjust the hook parameters".

In some embodiments, the alert module 230 may determine whether alert information needs to be sent by monitoring the tower crane operating parameter variance values. In some embodiments, monitoring the tower crane operating parameter differential value may be determined by comparing the magnitude of the tower crane operating parameter differential value to a preset value. For example, the alarm module 230 issues an alarm message when the tower crane operating parameter variance value is greater than a preset value.

By the tower crane operation parameter control method, the operation control of the tower crane can be more targeted, and the efficiency and the automation level of the operation control of the tower crane are improved.

Fig. 4 is a flow chart illustrating determination of lifting parameters according to some embodiments of the present description. In some embodiments, the process 400 may be performed by the processing device 110. As shown in fig. 4, the process 400 includes the steps of:

step 410, constructing a basic feature vector based on basic parameters of the current tower crane.

The basic parameters refer to parameters reflecting basic properties of the operation of the tower crane. For example, the base parameters may include at least one of a sling weight, a hook block magnification, a standard knot specification that makes up the tower crane, and the like.

In some embodiments, the tower crane base parameters may be obtained in a variety of ways. For example, the crane weight, i.e. the crane lifting mass, of the crane can be acquired by means of a lifting sensor. For another example, the hook pulley block magnification may be obtained based on user input, and the hook pulley block magnification may be determined based on the number of wires of the pulley block, e.g., 2 magnification means that the wires are two strands, and 4 magnification means that the wires are four strands. For another example, the standard section specification of the tower crane can be obtained by reading the tower crane product information, and the standard section specification refers to the length, the width and the height of the standard section.

The basic feature vector refers to a vector capable of reflecting the basic parameter features of the tower crane. For example, the tower crane base parameters may be reflected by each element position and element value in the vector. In some embodiments, the feature vector may be constructed based on tower crane base parameters. For example, the feature vector is constructed (10,4,2,15) based on the tower crane foundation parameters of 10 tons in hanging weight, 4 times of multiplying power of a hanging pulley block, 2 meters in standard knot height and 15 knots in standard knot number.

Step 420, retrieving at least one reference feature vector satisfying a preset relationship with the base feature vector based on the database.

The database refers to a collection of vectors that contain a plurality of features that reflect various tower crane base parameters. For example, the database may include a plurality of feature vectors corresponding to the tower cranes with different hoisting weights, different pulley block multiplying powers of the lifting hooks, different standard sections of specifications, different lifting heights, and at least one set of tower crane operation parameters corresponding to each feature vector.

In some embodiments, the feature vector constructed by the plurality of tower crane parameters can be used as a database, and the database can be further updated based on the parameters of each operation of each tower crane.

The preset relationship refers to a relationship between preset feature vectors. For example, the preset relationship may include that the distance, similarity, etc. of the vectors satisfy a certain relationship. The smaller the vector distance is, the larger the vector similarity is, for example, the preset relationship may be that the vector distance does not exceed a preset value or the vector similarity is not lower than a preset value, etc. The preset relationship can be determined by a preset vector distance threshold or a similarity threshold. For example, a predetermined relationship may be determined that the euclidean distance of the vector is 0.2 or less.

The reference feature vector is a feature vector in the database, wherein the basic feature vector corresponding to the basic parameter of the current tower crane meets the preset relation, and the tower crane operation parameter corresponding to the reference feature vector can be used for determining the tower crane operation parameter corresponding to the current tower crane.

In some embodiments, at least one reference feature vector satisfying a preset relationship with the base feature vector may be retrieved based on a database. For example, a feature vector satisfying the euclidean distance from the base feature vector to a threshold value (e.g., 0.2) or less may be determined as the reference feature vector based on database retrieval.

Step 430, determining the tower crane operation parameter corresponding to each reference feature vector in the at least one reference feature vector as a first candidate parameter.

The operation parameters can comprise the lifting hook positions in the lifting process of the tower crane and the lifting speed corresponding to each lifting hook position. For example, at different hook positions, the lifting speed is 8m/min, 10m/min, 15m/min, etc. The operating parameter may be sequence data based on a change in position.

The first candidate parameters refer to tower crane operation parameters corresponding to each reference feature vector retrieved based on the database. The operation parameters are parameters meeting the standard in the historical operation parameters of the tower crane in the database, for example, the optimal parameters in the historical operation parameters, and the parameters meeting the standard in the operation stability and the position accuracy of the tower crane in the historical operation parameters. In some embodiments, the criteria may be preset based on actual demand. For example, the predetermined criteria is a tower crane operational stability and position accuracy score greater than 95 points. In some embodiments, the first candidate parameter includes at least one set of operating parameters.

In some embodiments, a tower crane operating parameter corresponding to each of the at least one reference feature vector may be determined as a first candidate parameter. For example, 3 reference feature vectors are retrieved based on the database, and the operation parameters of 3 towers corresponding to the 3 reference feature vectors are determined as first candidate parameters. In some embodiments, 1 tower machine may include multiple sets of corresponding operating parameters. For example, there are 5 sets of parameters satisfying the criteria in a certain tower crane historical operating parameter, and the tower crane may include 5 sets of corresponding operating parameters.

Step 440, composing the simulation data based on the base parameters of the current tower crane and the first candidate parameters.

The simulation data refers to data for simulation including tower crane base parameters and operating parameters. For example, the simulation data may be 10 tons of tower crane weight, 4 times the lifting hook pulley block multiplying power, 2 meters of standard section height, 15 sections in number, 30 meters of tower crane lifting height, 0 meters, 1 meter, 2 meters, … …, 30 meters of lifting hook position, 8 meters per minute, 8.2 meters per minute, 8.4 meters per minute, … …, 15 meters per minute, … …, 0 meters per minute.

In some embodiments, the simulation data may be composed based on the base parameter and the first candidate parameter of the current tower crane. In some embodiments, the base parameters of the current tower crane may be combined with each set of operating parameters in the first candidate parameters to form the simulation data. For example, if the first candidate parameter includes 5 sets of operation parameters, the base parameter of the current tower crane and the 5 sets of operation parameters are respectively combined to form 5 sets of simulation data.

Step 450, performing simulation on the simulation data, and determining hoisting parameters based on the simulation result.

In some embodiments, the lifting parameters may be determined based on simulation results by performing a simulation on the simulation data. For example, multiple sets of simulation data may be simulated by simulation software, and corresponding operating parameters are selected as hoisting parameters based on simulation results.

The simulation result can comprise data reflecting the lifting stability of the tower crane, the accuracy of the lifting hook position and the primary working period of the tower crane. For example, the simulation results may include a tower crane lifting stability score, a hook position accuracy score, a tower crane one-time duty cycle score, and the like.

In some embodiments, determining the lifting parameter based on the simulation results includes: simulating at least one group of simulation data through simulation software to obtain at least one group of simulation results, wherein the simulation results reflect the stability and the position accuracy in the lifting process of the tower crane; and selecting the historical operation parameters corresponding to the simulation results meeting the preset conditions as hoisting parameters.

Stability refers to the stability of start/stop operation and speed regulation transition in the lifting process of the tower crane.

The position accuracy refers to the accuracy of the height of the lifting hook in the lifting process of the tower crane. Such as the minimum height, maximum height, etc. of the hook when lifting.

The preset condition refers to a condition that a preset simulation result needs to satisfy. For example, the preset condition may be that the simulation result meets the requirements of stability and position accuracy. For example, the stability and the position accuracy may be quantified to obtain a stability score and a position accuracy score, and the preset condition may be that the stability score and the position accuracy score are greater than or equal to 95 scores, respectively.

In some embodiments, at least one group of simulation data can be simulated by simulation software to obtain at least one group of simulation results, wherein the simulation results reflect the stability and the position accuracy in the lifting process of the tower crane; and selecting the historical operation parameters corresponding to the simulation results meeting the preset conditions as hoisting parameters. For example, the historical operation parameters corresponding to the optimal result may be selected as the hoisting parameters based on the simulation results, and the optimal result may refer to the simulation result with the highest scores or the average scores of the scores in the simulation results. For another example, based on the simulation result, a historical operation parameter corresponding to a result satisfying a stability score and a position accuracy score of 95 score or more, respectively, may be selected as the hoisting parameter.

The stability and the position accuracy are used as indexes for determining the lifting parameters of the current tower crane, so that the determined lifting parameters are more accurate, and the stability and the position accuracy of the tower crane in actual operation are improved.

In some embodiments, the simulation result satisfying the preset condition may be determined by determining a simulation result score.

The scoring of the simulation results refers to scoring stability and position accuracy in the simulation results. For example, the simulation results may be scored based on an evaluation function or the like. For the determination of the score of the simulation result, see fig. 5 and its related description.

In some embodiments, the simulation results may be determined based on the simulation result scores. For example, a simulation result with an optimal score may be selected as a simulation result satisfying a preset condition. For another example, a scoring threshold may be preset, and a result with a score greater than the threshold may be used as a simulation result satisfying the preset condition.

Other tower cranes with basic parameters basically the same as the current tower crane can be determined based on vector retrieval, and then the historical operation parameters of other tower cranes are used as reference data for simulation, so that the simulation data sources are simple and reliable; meanwhile, simulation data are formed by combining the basic parameters of the current tower crane to perform simulation, so that the simulation result is more in line with the actual situation of the current tower crane, and the simulation data are more accurate.

It should be noted that the above description of the process 400 is for purposes of illustration and description only, and is not intended to limit the scope of applicability of the present disclosure. Various modifications and changes to flow 400 will be apparent to those skilled in the art in light of the present description. However, such modifications and variations are still within the scope of the present description. For example, the process 400 may also include sending the hoisting parameters to the user.

Fig. 5 is a schematic illustration of determining lifting parameters according to some embodiments of the present description. In some embodiments, the process 500 may determine the tower crane lifting parameters through multiple iterations. In some embodiments, the process 500 may be performed by the processing device 110. As shown in fig. 5, the process 500 includes the steps of:

step 510, presetting initial hoisting parameters.

The initial hoisting parameters refer to the hoisting parameters before iterative updating.

In some embodiments, initial lifting parameters may be preset. For example, by manual setting based on computational requirements. In some embodiments, the initial lifting parameters may be preset based on the first candidate parameters determined in step 430 of fig. 4. For example, at least one set of tower crane operating parameters in the first candidate parameters may be determined directly as the initial hoisting parameters. In some embodiments, the initial lifting parameters may be preset based on the lifting parameters determined in step 450 of fig. 4. For example, the hoisting parameter may be determined directly as the initial hoisting parameter.

The initial hoisting parameters are preset based on the first candidate parameters retrieved in fig. 4 or the hoisting parameters determined through simulation, the obtained initial hoisting parameters are the operation parameters relatively close to the current tower crane, and then iterative optimization is performed based on the initial hoisting parameters, so that the calculated amount of an algorithm is reduced, and meanwhile, the subsequent iterative result is more accurate.

Step 520, performing at least one round of iterative updating on the initial hoisting parameter based on the preset algorithm to obtain at least one second candidate parameter.

The preset algorithm refers to a preset algorithm for iteratively updating the initial hoisting parameters. In some embodiments, the preset algorithm may be designed manually based on computational requirements. For example, a preset algorithm may be set based on hook position and corresponding lifting speed. In some embodiments, the preset algorithm may be implemented as follows:

step one: a population of N particles is constructed, each particle having a dimension D. Wherein each particle represents one possible solution; n is the particle group size, and the value range of N is [20,1000]. The particle dimension D represents the spatial dimension of the particle search, i.e., the number of variables that need to be solved. In some embodiments, the variable to be solved is a velocity sequence based on hook position, and the particle dimension D is determined by the number of hook positions. For example, the number of the lifting hook positions is 30, and each position corresponds to one lifting speed, so that the dimension D of the particles is 30.

In some embodiments, the candidate solution for the ith particle may be set to X _id ，X _id ＝(X _i1 ，X _i2 ，X _i3 ……)，X _id Representing the lifting speed at each hook position. For example, X _i1 Represents the lifting speed, X of the lifting hook position 1 _i2 Representing the lifting speed, X of the lifting hook position 2 _i3 Indicating the lifting speed of the hook position 3.

In some embodiments, the rate of change of the ith particle may be set to V _id ，V _id ＝(V _i1 ,，V _i2 ，V _i3 … …) indicates the direction and size of the movement of the particles. In some embodiments, the particle change rate V _id Representing candidate solution X _id Wherein V is _id And X _id Is in one-to-one correspondence. For example, V _i1 X represents _i1 Is V _i2 X represents _i2 Is V _i3 X represents _i3 Is used for adjusting the amplitude of the adjustment.

Step two: and designing an iteration formula based on particle swarm parameters such as particle swarm scale, particle dimension, iteration times, inertia weight, learning factors and the like. In some embodiments, the particle change rate V may be based on _id And candidate solution V _id And designing a particle swarm variation rate updating formula and a candidate solution updating formula.

In some embodiments, the particle swarm variation rate update formula may be designed as follows:

wherein the particle dimension is N, i represents the particle number, i=1, 2,3, … …, N; the particle dimension is D, D represents the particle dimension number, d=1, 2,3, … …, D; k is the iteration number; omega is the inertial weight; c ₁ Learning factors for an individual; c ₂ Is a group learning factor; r is (r) ₁ ，r ₂ Is interval [0,1 ]]Random numbers in the search module are used for increasing the randomness of the search;a variation amplitude vector representing the d-th dimension of the particle i in the kth iteration; />A candidate solution vector representing the d-th dimension of the particle i in the kth iteration; />The historical optimal position of the particle i in the d dimension in the kth iteration is represented, namely, after the kth iteration, the optimal solution obtained by searching the ith particle (individual); />And (3) representing the historical optimal position of the population in the d-th dimension in the kth iteration, namely, after the kth iteration, searching the optimal solution by the population.

In some embodiments, a candidate solution update formula may be designed as follows:

equation (2) indicates that the candidate solution updated for the next iteration is determined by the current candidate solution and the particle change rate updated for the next iteration.

The second candidate parameter is a parameter obtained by iteratively updating the initial hoisting parameter. For example, the second candidate parameter may be an updated hoisting parameter obtained by iterating a preset iteration number based on a candidate solution iteration formula.

In some embodiments, at least one iteration update may be performed on the initial lifting parameter based on a preset algorithm, resulting in at least one second candidate parameter. For example, the initial hoisting parameters may be iteratively updated in a round based on equation (2) to obtain As a second candidate parameter.

In some embodiments, at least one round of iterations includes: updating the adjustment amplitude to be updated to obtain an updated adjustment amplitude; updating the hoisting parameters to be updated based on the updated adjustment amplitude to obtain second candidate parameters; the lifting parameter obtained after updating is used as a lifting parameter to be updated of the next round, the updated adjustment amplitude is used as an adjustment amplitude to be updated of the next round, wherein the lifting parameter to be updated of the first round is a preset initial lifting parameter, and the adjustment amplitude to be updated is a preset value; and ending the iterative updating until the preset condition is met.

Adjusting amplitude refers to candidate solution X _id Is a variable amplitude of (a). The adjustment amplitude to be updated refers to the adjustment amplitude to be updated in the next iteration. For example, by performing k rounds of iteration, the adjustment amplitude to be updated may be And the like.

In some embodiments, the adjustment amplitude to be updated may be updated based on equation (1), resulting in an updated adjustment amplitude. In some embodiments, the adjustment amplitude to be updated may be iteratively updated in k rounds based on formula (1) to obtain an updated adjustment amplitudeWhere k may be set based on actual algorithm requirements, for example, k=300 times may be set. For example, one round of iteration can be performed on the adjustment amplitude to be updated based on formula (1), resulting in an updated adjustment amplitude +. >For another example, two iterations of the adjustment amplitude to be updated may be performed based on formula (1) to obtain the updated adjustment amplitude +.>

In some embodiments, the updated adjustment amplitude may be used as the adjustment amplitude to be updated for the next iteration update, where the adjustment amplitude to be updated for the first iteration is a preset value, and may be set based on artificial random or based on experience. Can be obtained by updating the first round of iterationThe preset amplitude to be updated is updated as a second round of iterative updating. As another example, the k-1 th round of iterative update may be followed by +.>The adjustment amplitude to be updated is updated as the k-th round of iterative update.

The hoisting parameters to be updated refer to the hoisting parameters waiting for the next iteration to be updated. For example, by performing k rounds of iterations, the lifting parameters to be updated may beAny of the followingMeaning one.

In some embodiments, at least one round of iterative updating may be performed on the hoisting parameters to be updated based on the updated adjustment amplitude, so as to obtain updated hoisting parameters. In some embodiments, the hoisting parameter to be updated may be iteratively updated according to the formula (2) based on the updated adjustment amplitude and the hoisting parameter to be updated, to obtain the updated hoisting parameter. For example, the adjustment amplitude after the iterative update can be based on And hoisting parameters to be updated->The second iteration update is carried out through the formula (2) to obtain updated hoisting parameters +.>

In some embodiments, the updated lifting parameter may be used as a lifting parameter to be updated for the next iteration, where the lifting parameter to be updated for the first iteration is a preset initial lifting parameter. For example, the first iteration may be updatedAnd as a second round of iterative updating, the hoisting parameters to be updated are updated. As another example, the k-1 th round of iterative update may be followed by +.>And as the hoisting parameters to be updated of the kth round of iterative updating.

In some embodiments, when the iteration is terminated, the updated lifting parameter resulting from the last iteration is determined to be a second candidate parameter. For example, the number of iterations performed at the end of the iteration is 200, and the updated hoisting parameters obtained from the 200 th iteration can be obtainedIs determined as the secondCandidate parameters.

The preset condition refers to a preset maximum number of updates or an evaluation score index of the updated hoisting parameter. For example, the preset condition may be that the maximum number of iterations is 300, that the updated lifting parameter evaluation score index is 95 or more, and the like. In some embodiments, the simulation result may be obtained through simulation, and the evaluation score index of the updated hoisting parameter may be obtained based on the simulation result score. For more on the acquisition of the evaluation score index based on the simulation result score, see step 530 and its description.

In some embodiments, the iteration stops when a preset condition is met. For example, when the iteratively updated lifting parameters meet the evaluation score, the iteration is stopped. And determining the hoisting parameters meeting the evaluation index as second candidate parameters. For another example, the iteration stops when the iteration reaches a maximum number k of iterations.

The hoisting parameters are repeatedly updated based on the adjustment amplitude obtained by each iteration, so that the hoisting parameters updated by each iteration are used as second candidate parameters, the second candidate parameters obtained by each iteration are conveniently simulated, and the simulation accuracy is improved; meanwhile, the evaluation value of the simulation result is used as one of iteration stop conditions, so that the iteration times can be reduced, and the calculation efficiency is improved.

In some embodiments, the adjustment amplitude comprises a plurality of increment elements, and each position in the hoisting parameter to be updated has a one-to-one correspondence with each increment element. In some embodiments, the updating of the delta element to be updated in one of the adjustment amplitudes to be updated includes: based on the current loss of the previous round, updating the increment element to be updated, wherein the updated increment element is used as the increment element to be updated of the next round, and the current loss of the previous round is determined based on the action difference between the second candidate parameter obtained in the previous round and the history optimal second candidate parameter.

Incremental elements refer to elements of each dimension in a vector constructed based on the adjustment amplitude. For example, the increment element may include an adjustment of the amplitude V _id V in (1) _i1 ，V _i2 ，V _i3 ，……，V _id At least one of (a)One. In some embodiments, the adjustment amplitude comprises a plurality of increment elements, and each hook position in the lifting parameter to be updated has a one-to-one correspondence with each increment element. For example, delta element V _i1 ，V _i2 ，V _i3 ，……，V _id Respectively corresponds to the lifting hook position 1, the lifting hook position 2, the lifting hook positions 3 and … … and the lifting hook position d one by one.

The current loss of the previous round refers to the difference between the second candidate parameter obtained by the previous round of iterative updating and the historical optimal candidate parameter. In some embodiments, the current loss of the previous round may be determined based on the difference between the second candidate parameter and the historical optimal candidate parameter resulting from the previous round of updating, as well as the interval random number and the learning factor. The current loss of the previous round may be expressed as follows:

wherein c ₁ Learning factors for an individual; c ₂ Is a group learning factor; r is (r) ₁ ，r ₂ Is interval [0,1 ]]Random numbers in the search module are used for increasing the randomness of the search;representing a second candidate parameter based on k rounds of updating,/for>The individual history optimal candidate parameters and the group optimal history candidate parameters are respectively represented.

In some embodiments, updating the adjustment amplitude to be updated includes: and updating each increment element to be updated in the adjustment amplitude to be updated. In some embodiments, the delta element to be updated may be updated based on the current penalty of the previous round. For example, delta element V may be updated based on the current penalty of the previous round _i1 Updating, wherein the updating formula is as follows:

wherein, the liquid crystal display device comprises a liquid crystal display device,representing delta elements after k+1 rounds of updating,/o>Indicating that the incremental elements to be updated for the present round,indicating the current penalty of the previous round (k-th round). In some embodiments, other delta elements to be updated (e.g., V _i2 ，V _i3 ，……，V _id ) And updating.

In some embodiments, the updated delta element may be used as the delta element to be updated for the next iteration. For example, the increment element obtained by the first iteration may beThe delta element to be updated as the second round of iteration. As another example, the k-1 th round of iteration may be taken as +.>As the delta element to be updated for the kth round of iteration.

The adjustment amplitude to be updated comprises a plurality of increment elements to be updated, and the adjustment amplitude to be updated is updated by respectively carrying out multiple rounds of iteration on the increment elements to be updated, so that the accuracy of the updating result can be improved.

In some embodiments, when the updated increment element is not within the preset range, the updated increment element may be adjusted to a boundary value of the preset range.

The preset range refers to the maximum change rate of the adjustment amplitude set in advance and can be expressed as V _max . In some embodiments, the variable (V) may be based on each dimension _id ) The preset range V is determined by 10 to 20 percent of the variation range _max . In some embodiments, it may be based onDifferent conditions of each dimension variable for each V _id Different maximum rates of change are set. For example, V may be set _i1 ＜V _1max ，V _i2 ＜V _2max Etc. In some embodiments, when the updated increment element exceeds the preset range, the updated increment element may be adjusted to a boundary value of the preset range. For example, when updated delta elementsWhen in use, will->Is adjusted to V _1max 。

By setting a reasonable variation range and limiting the maximum variation rate of particles, the exploring capability and the developing capability of the algorithm can be balanced.

And step 530, performing simulation based on at least one second candidate parameter to obtain at least one simulation result.

The simulation result is a result which is obtained through simulation and can reflect the operation stability of the tower crane, the position accuracy of the lifting hook and the primary operation period of the tower crane. In some embodiments, the simulation results may be numerical values representing the aforementioned 3 different properties. For example, operational stability 98, hook position accuracy 96, tower crane one-time duty cycle score 97.

In some embodiments, a simulation may be performed based on the at least one second candidate parameter to obtain at least one simulation result. In some embodiments, at least one simulation result may be obtained by performing a simulation based on the current tower crane base parameter and at least one second candidate parameter to form at least one set of simulation data. For example, the current tower crane base parameter and the 3 second candidate parameters may be respectively combined to form 3 groups of simulation data, and the 3 groups of simulation data are simulated to obtain 3 simulation results.

And step 540, scoring each simulation result in the at least one simulation result, and taking the second candidate parameter corresponding to the simulation result with the score meeting the preset condition as the hoisting parameter.

The preset condition refers to a simulation result scoring criterion set in advance, which can be used to determine whether the second candidate parameter is an optimal solution. For example, the preset condition may be set such that the score of the simulation result is 95 points or more.

In some embodiments, each of the at least one simulation result may be scored, and the second candidate parameter corresponding to the simulation result whose score satisfies the preset condition is determined as the hoisting parameter. In some embodiments, scoring each of the at least one simulation result comprises: scoring the lifting stability, the lifting hook position accuracy and the primary operation period of the tower crane in each simulation result respectively; and then carrying out weighted summation on the 3 scores to obtain a comprehensive score of each simulation result, wherein the weight can be set based on experience.

In some embodiments, a second candidate parameter corresponding to a simulation result for which the composite score of each simulation result satisfies a preset condition may be determined as the lifting parameter. For example, the composite scores for the 3 simulation results are respectively: and the first simulation result comprehensive score is 98 points, the second is 94 points, and the third is 90 points, and the second candidate parameter corresponding to the first simulation result is determined as the hoisting parameter.

In some embodiments, the determination of the simulation result score comprises: constructing an evaluation function for judging whether the candidate solution is an optimal solution, wherein the evaluation function G (Yi) is a weighting function, and G represents weighted summation of different performance evaluation scores; yi comprises: stability, position accuracy and time for completing one operation period of the tower crane in the lifting process of the tower crane.

In some embodiments, an evaluation function may be constructed for determining whether the second candidate parameter is an optimal solution.

In some embodiments, the evaluation function may be constructed based on stability during lifting of the tower crane, accuracy of hook position, and one-time operation cycle of the tower crane. In some embodiments, the evaluation function G (Y _i ) For a weighted function, G represents the weighted summation of the scores of the different performance evaluations, Y _i Comprises evaluation of 3 different performances of stability, accuracy of lifting hook position and one operation period of a tower craneThe score is estimated. For example, Y _i1 Representing a stability assessment score, Y _i1 Representing the evaluation score, Y, of the accuracy of the hook position _i3 Representing the evaluation score of one working cycle of the tower crane. In some embodiments, the weights of the evaluation scores for 3 different performances may be set based on actual requirements, with the sum of the 3 weights being 1. For example, weights may be set based on the importance of 3 different performances to the operation of the tower crane.

In some embodiments, the simulation results may be scored based on an evaluation function. In some embodiments, the simulation result score may be obtained by weighted summation of the evaluation scores of the different performances.

In some embodiments, it may be determined whether the at least one second candidate parameter is an optimal solution based on the simulation result score. For example, each simulation result may be scored, and the corresponding second candidate parameter with the highest score is selected as the optimal solution, i.e. as the hoisting parameter.

And searching optimal candidate parameters through multiple rounds of iteration based on a preset algorithm, simulating each round of optimal candidate parameters, and selecting candidate parameters with optimal scores of simulation results as hoisting parameters, so that accuracy of determining the hoisting parameters is improved.

In some embodiments of the present disclosure, a tower crane operating parameter control apparatus is provided, including a processor and a memory, where the memory is configured to store computer instructions, and the processor is configured to perform a tower crane operating parameter control method.

Some embodiments of the present disclosure also provide a computer-readable storage medium storing computer instructions that, when read by a computer in the storage medium, perform a method for controlling operational parameters of a tower crane.

According to the foregoing, the method, the system, the device and the computer medium for controlling the operation parameters of the tower crane according to some embodiments of the present disclosure can perform the operation control of the tower crane more efficiently, reliably, automatically and controllably.

While the basic concepts have been described above, it will be apparent to those skilled in the art that the foregoing detailed disclosure is by way of example only and is not intended to be limiting. Although not explicitly described herein, various modifications, improvements, and adaptations to the present disclosure may occur to one skilled in the art. Such modifications, improvements, and modifications are intended to be suggested within this specification, and therefore, such modifications, improvements, and modifications are intended to be included within the spirit and scope of the exemplary embodiments of the present invention.

Meanwhile, the specification uses specific words to describe the embodiments of the specification. Reference to "one embodiment," "an embodiment," and/or "some embodiments" means that a particular feature, structure, or characteristic is associated with at least one embodiment of the present description. Thus, it should be emphasized and should be appreciated that two or more references to "an embodiment" or "one embodiment" or "an alternative embodiment" in various positions in this specification are not necessarily referring to the same embodiment. Furthermore, certain features, structures, or characteristics of one or more embodiments of the present description may be combined as suitable.

Furthermore, the order in which the elements and sequences are processed, the use of numerical letters, or other designations in the description are not intended to limit the order in which the processes and methods of the description are performed unless explicitly recited in the claims. While certain presently useful inventive embodiments have been discussed in the foregoing disclosure, by way of various examples, it is to be understood that such details are merely illustrative and that the appended claims are not limited to the disclosed embodiments, but, on the contrary, are intended to cover all modifications and equivalent arrangements included within the spirit and scope of the embodiments of the present disclosure. For example, while the system components described above may be implemented by hardware devices, they may also be implemented solely by software solutions, such as installing the described system on an existing server or mobile device.

Likewise, it should be noted that in order to simplify the presentation disclosed in this specification and thereby aid in understanding one or more inventive embodiments, various features are sometimes grouped together in a single embodiment, figure, or description thereof. This method of disclosure, however, is not intended to imply that more features than are presented in the claims are required for the present description. Indeed, less than all of the features of a single embodiment disclosed above.

In some embodiments, numbers describing the components, number of attributes are used, it being understood that such numbers being used in the description of embodiments are modified in some examples by the modifier "about," approximately, "or" substantially. Unless otherwise indicated, "about," "approximately," or "substantially" indicate that the number allows for a 20% variation. Accordingly, in some embodiments, numerical parameters set forth in the specification and claims are approximations that may vary depending upon the desired properties sought to be obtained by the individual embodiments. In some embodiments, the numerical parameters should take into account the specified significant digits and employ a method for preserving the general number of digits. Although the numerical ranges and parameters set forth herein are approximations that may be employed in some embodiments to confirm the breadth of the range, in particular embodiments, the setting of such numerical values is as precise as possible.

Each patent, patent application publication, and other material, such as articles, books, specifications, publications, documents, etc., referred to in this specification is incorporated herein by reference in its entirety. Except for application history documents that are inconsistent or conflicting with the content of this specification, documents that are currently or later attached to this specification in which the broadest scope of the claims to this specification is limited are also. It is noted that, if the description, definition, and/or use of a term in an attached material in this specification does not conform to or conflict with what is described in this specification, the description, definition, and/or use of the term in this specification controls.

Finally, it should be understood that the embodiments described in this specification are merely illustrative of the principles of the embodiments of this specification. Other variations are possible within the scope of this description. Thus, by way of example, and not limitation, alternative configurations of embodiments of the present specification may be considered as consistent with the teachings of the present specification. Accordingly, the embodiments of the present specification are not limited to only the embodiments explicitly described and depicted in the present specification.

Claims

1. A method for controlling operational parameters of a tower crane, comprising:

determining lifting parameters, wherein the lifting parameters comprise the position of a lifting hook and the corresponding lifting speed of the lifting hook in the lifting process of the tower crane;

presetting operation target parameters of the tower crane based on the hoisting parameters, and controlling the tower crane to operate based on the operation target parameters;

and acquiring the running real-time parameters of the tower crane, and sending out alarm information in response to the difference between the running real-time parameters and the running target parameters exceeding a preset condition.

2. The method of claim 1, the lifting parameter being obtained based on a search database, the determining the lifting parameter comprising:

constructing a basic feature vector based on the basic parameters of the current tower crane;

retrieving at least one reference feature vector satisfying a preset relationship with the base feature vector based on the database;

Determining the tower crane operation parameter corresponding to each reference feature vector in the at least one reference feature vector as a first candidate parameter;

forming simulation data based on the basic parameters and the first candidate parameters of the tower crane;

and performing simulation on the simulation data, and determining the hoisting parameters based on simulation results.

3. The method of claim 1, the determining lifting parameters comprising:

presetting initial hoisting parameters;

performing at least one round of iterative updating on the initial hoisting parameters based on a preset algorithm to obtain at least one second candidate parameter;

performing simulation based on the at least one second candidate parameter to obtain at least one simulation result;

and scoring each simulation result in the at least one simulation result, and taking a second candidate parameter corresponding to the simulation result, the scoring of which meets a preset condition, as the hoisting parameter.

4. The method of claim 1, the presetting of operational target parameters for the tower crane based on the hoisting parameters, and controlling the tower crane operation based on the operational target parameters comprising:

determining the motor frequency corresponding to the lifting speed in the lifting parameters based on the relation between the speed and the frequency of the lifting motor;

And controlling the frequency change of the lifting motor according to the motor frequency based on the variable frequency speed regulator so as to control the lifting speed.

5. A tower crane operating parameter control system comprising:

the lifting parameter determining module is used for determining lifting parameters, wherein the lifting parameters comprise the position of a lifting hook and the corresponding lifting speed in the lifting process of the tower crane;

the control module is used for presetting operation target parameters of the tower crane based on the hoisting parameters and controlling the operation of the tower crane based on the operation target parameters;

and the alarm module is used for acquiring the operation real-time parameters of the tower crane, and sending alarm information in response to the difference between the operation real-time parameters and the operation target parameters exceeding a preset condition.

6. The system of claim 5, the hoist parameter determination module further to:

retrieving at least one reference feature vector satisfying a preset relationship with the base feature vector based on a database;

7. The system of claim 5, the hoist parameter determination module further to:

presetting initial hoisting parameters;

8. The system of claim 5, the control module further to:

9. A tower crane operating parameter control apparatus, said apparatus comprising at least one processor and at least one memory;

The at least one memory is configured to store computer instructions;

the at least one processor is configured to execute at least some of the computer instructions to implement the method of any one of claims 1-4.

10. A computer readable storage medium storing computer instructions which, when read by a computer in the storage medium, perform the method of any one of claims 1 to 4.