阅读说明：本技术 一种基于5g网络的自行式起重机远程控制系统 (Self-propelled crane remote control system based on 5g network ) 是由 梁大伟 于 2021-08-24 设计创作，主要内容包括：本发明公开了一种基于5g网络的自行式起重机远程控制系统,包括采集模块、标记处理模块、分析模块、匹配模块和控制模块；采集模块采集起重机的运行信息以及吊装的货物信息；标记处理模块包含第一处理单元和第二处理单元,第一处理单元用于对运行信息进行标记处理,得到第一处理信息；第二处理单元用于对货物信息进行标记处理,得到第二处理信息；分析模块用于对第一处理信息和第二处理信息进行计算分析,得到包含设匹值和货匹值的分析集；匹配模块根据分析集中的设匹值和货匹值进行匹配,得到结果集；本发明解决了不能对不同类型的吊装物进行针对性的调控,导致起重机的吊装效果不佳的技术问题。(The invention discloses a self-propelled crane remote control system based on a 5g network, which comprises an acquisition module, a marking processing module, an analysis module, a matching module and a control module, wherein the acquisition module is used for acquiring a mark of a crane; the collecting module collects the running information of the crane and the hoisted cargo information; the marking processing module comprises a first processing unit and a second processing unit, and the first processing unit is used for marking the running information to obtain first processing information; the second processing unit is used for marking the cargo information to obtain second processing information; the analysis module is used for calculating and analyzing the first processing information and the second processing information to obtain an analysis set containing a set matching value and a goods matching value; the matching module matches the goods matching value according to the set matching value in the analysis set to obtain a result set; the invention solves the technical problem that the lifting effect of the crane is poor because different types of hoisted objects cannot be controlled in a targeted manner.)

1. A self-propelled crane remote control system based on a 5g network is characterized by comprising an acquisition module, a marking processing module, an analysis module, a matching module and a control module; the collecting module collects the running information of the crane and the hoisted cargo information; the marking processing module comprises a first processing unit and a second processing unit, and the first processing unit is used for marking the running information to obtain first processing information; the second processing unit is used for marking the cargo information to obtain second processing information; the analysis module is used for calculating and analyzing the first processing information and the second processing information to obtain an analysis set containing a set matching value and a goods matching value; the matching module matches the goods matching value according to the set matching value in the analysis set to obtain a result set; and the control module controls the operation of the crane according to the result set.

2. The remote control system for the self-propelled crane based on the 5g network as claimed in claim 1, wherein the specific steps for marking the operation information are as follows:

the method comprises the steps of obtaining type data, hydraulic data and hoisting data in operation information, marking the crane type in the type data and obtaining corresponding type correlation values, and respectively carrying out value taking and marking on the hydraulic speed in the hydraulic data and the maximum hoisting quality in the hoisting data to obtain first processing information.

3. A self-propelled crane remote control system based on 5g network as claimed in claim 2, wherein the specific steps of marking the cargo information are as follows:

the method comprises the steps of obtaining quality data, model data and grade data in goods information, conducting value taking and marking on the quality data, marking the goods model in the model data and obtaining a corresponding model correlation value, marking the goods grade in the grade data and obtaining a corresponding grade preset value, and conducting classification combination on all marked data to obtain second processing information.

4. A self-propelled crane remote control system based on 5g network as claimed in claim 3 wherein the specific steps of calculating and analyzing the first processed information and the second processed information are:

normalizing the marked data items in the first processing information and the second processing information by using a formulaCalculating to obtain a set matching value of the crane; wherein mu is represented as an operation correction factor, the value is 0.512873, a1 and a2 are represented as different proportionality coefficients, QLG is represented as a type correlation value corresponding to the type of the crane, YS is represented as a hydraulic speed, and DZ is represented as the maximum hoisting quality;

calculating the goods matching value by using a formula HP ═ ZX × (b1 × HXG + b2 × HDG); wherein b1 and b2 are expressed as different proportionality coefficients, HXG is expressed as a model related value corresponding to a cargo model, HDG is expressed as a grade preset value corresponding to a cargo grade, ZX is expressed as a mass proportion coefficient, and the set matching value and the cargo matching value are classified and combined to obtain an analysis set.

5. A self-propelled crane remote control system based on 5g network as claimed in claim 4Is characterized in that the mass proportion coefficient is obtained by calculation, and the formula of the calculation is as follows:wherein HZ is expressed as the cargo quality, eta is expressed as the matching correction factor, and the value is 1.465832.

6. A self-propelled crane remote control system based on 5g network as claimed in claim 5 wherein, the specific steps of matching according to the design and goods values in the analysis set are: calculating the set value and the goods value simultaneously by using a formulaAnd calculating to obtain a correlation value, and matching the correlation value with a preset correlation range to obtain a result set.

7. A self-propelled crane remote control system based on a 5g network as claimed in claim 6 wherein the specific steps of matching the correlation value with the preset correlation range are:

if the correlation value is not larger than the minimum value of the correlation range, generating a first matching signal; if the correlation value is greater than the minimum value of the correlation range and not greater than the maximum value of the correlation range, generating a second matching signal; if the correlation value is greater than the maximum value of the correlation range, generating a third matching signal; and combining the first matching signal, the second matching signal and the third matching signal to obtain a result set.

8. A self-propelled crane remote control system based on 5g network as claimed in claim 7 wherein the concrete steps of controlling the crane operation according to the result set are:

and acquiring the running speed corresponding to each matching signal in the result set, and controlling the crane to run according to the corresponding running speed.

Technical Field

The invention relates to the technical field of cranes, in particular to a self-propelled crane remote control system based on a 5g network.

Background

The 5G network refers to a fifth generation network in the development of mobile communication networks, and compared with the previous four generation mobile networks, the 5G network shows more enhanced functions in the practical application process. The self-propelled crane is a cantilever crane which is self-powered and moves along a rail or trackless channel by a self running mechanism, and the running efficiency of the crane can be improved based on a 5G network.

When the existing self-propelled crane is used, the targeted control can not be carried out on the basis of different hoisted objects, so that some important hoisted objects can not be timely and effectively processed, and the hoisting effect of the crane is poor.

Disclosure of Invention

The invention aims to provide a self-propelled crane remote control system based on a 5g network, and mainly aims to solve the technical problem that lifting effects of cranes are poor due to the fact that different types of hoisted objects cannot be controlled in a targeted mode in the existing scheme.

The purpose of the invention can be realized by the following technical scheme:

a self-propelled crane remote control system based on a 5g network comprises an acquisition module, a marking processing module, an analysis module, a matching module and a control module; the collecting module collects the running information of the crane and the hoisted cargo information; the marking processing module comprises a first processing unit and a second processing unit, and the first processing unit is used for marking the running information to obtain first processing information; the second processing unit is used for marking the cargo information to obtain second processing information; the analysis module is used for calculating and analyzing the first processing information and the second processing information to obtain an analysis set containing a set matching value and a goods matching value; the matching module matches the goods matching value according to the set matching value in the analysis set to obtain a result set; and the control module controls the operation of the crane according to the result set.

Further, the specific steps of marking the operation information are as follows:

the method comprises the steps of obtaining type data, hydraulic data and hoisting data in operation information, marking crane types in the type data and obtaining corresponding type correlation values, marking the crane types as QL, setting different crane types to correspond to one different type correlation value, matching the crane types in the type data with all the crane types to obtain corresponding type correlation values and marking the type correlation values as QLG, respectively carrying out value taking and marking on hydraulic speed in the hydraulic data and maximum hoisting quality in the hoisting data, marking the hydraulic speed as YS, and marking the maximum hoisting quality as DZ to obtain first processing information.

Further, the specific steps of marking the cargo information are as follows:

acquiring quality data, model data and grade data in the cargo information, dereferencing and marking the quality data, marking the cargo quality in the quality data as HZ, marking the cargo model in the model data and acquiring a corresponding model related value, marking the cargo model as HX, setting different cargo models to correspond to different model related values, matching the cargo model in the model data with all the cargo models to acquire a corresponding model related value and marking the model related value as HXG, marking the cargo grade in the grade data and acquiring a corresponding grade preset value, marking the cargo grade as HD, matching the cargo grade with a preset grade related table to acquire a corresponding grade preset value and marking the grade preset value as HDG, and classifying and combining the marked data to acquire second processing information.

Further, the specific steps of performing calculation analysis on the first processing information and the second processing information are as follows:

normalizing the marked data items in the first processing information and the second processing information by using a formulaCalculating to obtain a set matching value of the crane; wherein mu is represented as an operation correction factor, the value is 0.512873, a1 and a2 are represented as different proportionality coefficients, QLG is represented as a type correlation value corresponding to the type of the crane, YS is represented as a hydraulic speed, and DZ is represented as the maximum hoisting quality;

calculating the goods matching value by using a formula HP ═ ZX × (b1 × HXG + b2 × HDG); wherein b1 and b2 are expressed as different proportionality coefficients, HXG is expressed as a model related value corresponding to a cargo model, HDG is expressed as a grade preset value corresponding to a cargo grade, ZX is expressed as a mass proportion coefficient, and the set matching value and the cargo matching value are classified and combined to obtain an analysis set.

Further, the mass specific gravity coefficient is obtained by calculation, and the formula of the calculation is as follows:wherein HZ is expressed as the cargo quality, eta is expressed as the matching correction factor, and the value is 1.465832.

Further, the specific steps of matching according to the matching value and the goods matching value in the analysis set are as follows: calculating the set value and the goods value simultaneously by using a formulaAnd calculating to obtain a correlation value, and matching the correlation value with a preset correlation range to obtain a result set.

Further, the specific step of matching the correlation value with the preset correlation range is as follows:

if the correlation value is not larger than the minimum value of the correlation range, generating a first matching signal; if the correlation value is greater than the minimum value of the correlation range and not greater than the maximum value of the correlation range, generating a second matching signal; if the correlation value is greater than the maximum value of the correlation range, generating a third matching signal; and combining the first matching signal, the second matching signal and the third matching signal to obtain a result set.

Further, the specific steps of controlling the operation of the crane according to the result set are as follows:

and acquiring the running speed corresponding to each matching signal in the result set, and controlling the crane to run according to the corresponding running speed.

The invention has the beneficial effects that:

according to the invention, through the matching use of the acquisition module, the marking processing module, the analysis module, the matching module and the control module, the lifting effect of the crane can be improved by performing targeted regulation and control on different types of lifting objects, effective data support is provided for remote control of the crane from two aspects by acquiring the operation information of the crane and the information of the lifted cargos, each acquired data is standardized and normalized to facilitate calculation by marking and counting, the crane and the cargos are analyzed and matched by establishing a connection among the data through calculation, and the crane performs targeted remote control on different types of cargos by further performing simultaneous and analysis on the calculated results.

Drawings

The invention will be further described with reference to the accompanying drawings.

FIG. 1 is a block diagram of a self-propelled crane remote control system based on a 5g network.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

Referring to fig. 1, the invention relates to a self-propelled crane remote control system based on a 5g network, which comprises an acquisition module, a marking processing module, an analysis module, a matching module and a control module; the collecting module collects the running information of the crane and the hoisted cargo information;

in this embodiment, can realize more high-efficient stable control based on 5g network, and then can improve the control effect of hoist, through the operation information of gathering the hoist and the goods information of hoist and mount, match the analysis from two aspects for the hoist carries out different remote control to different hoist and mount thing, thereby can reach the purpose that improves goods hoist and mount effect.

The marking processing module comprises a first processing unit and a second processing unit, and the first processing unit is used for marking the running information to obtain first processing information; the method comprises the following specific steps:

obtaining type data, hydraulic data and hoisting data in the operation information, marking the crane type in the type data and obtaining a corresponding type correlation value, marking the crane type as QL, setting different crane types to correspond to one different type correlation value, matching the crane type in the type data with all the crane types to obtain a corresponding type correlation value and marking the type correlation value as QLG, respectively carrying out value taking and marking on the hydraulic speed in the hydraulic data and the maximum hoisting quality in the hoisting data, marking the hydraulic speed as YS, and marking the maximum hoisting quality as DZ to obtain first processing information;

the second processing unit is used for marking the cargo information to obtain second processing information; the method comprises the following specific steps:

acquiring quality data, model data and grade data in the cargo information, taking and marking the quality data, marking the cargo quality in the quality data as HZ, marking the cargo model in the model data and acquiring a corresponding model correlation value, marking the cargo model as HX, setting different cargo models to correspond to different model correlation values, matching the cargo model in the model data with all the cargo models to acquire a corresponding model correlation value and marking the model correlation value as HXG, marking the cargo grade in the grade data and acquiring a corresponding grade preset value, marking the cargo grade as HD, matching the cargo grade with a preset grade correlation table to acquire a corresponding grade preset value and marking the grade preset value as HDG, and classifying and combining the marked data to acquire second processing information;

in this embodiment, mark and statistics through the mark processing module to each item data of gathering, carry out the valuization to the data of text and handle, be convenient for calculate between each item data of hoist and goods, wherein, draw pictures to the hoist in the aspect of from aspects such as hoist type, hydraulic speed and the biggest hoist and mount quality, draw pictures to the goods in the aspect of goods quality, goods model and goods grade, be convenient for subsequent computational analysis.

The analysis module is used for calculating and analyzing the first processing information and the second processing information to obtain an analysis set containing a set matching value and a goods matching value; the method comprises the following specific steps:

normalizing the marked data items in the first processing information and the second processing informationProcessing by means of formulaeCalculating to obtain a set matching value of the crane; wherein mu is represented as an operation correction factor, the value is 0.512873, a1 and a2 are represented as different proportionality coefficients, QLG is represented as a type correlation value corresponding to the type of the crane, YS is represented as a hydraulic speed, and DZ is represented as the maximum hoisting quality;

calculating the goods matching value by using a formula HP ═ ZX × (b1 × HXG + b2 × HDG); wherein b1 and b2 are expressed as different proportionality coefficients, HXG is expressed as a model related value corresponding to a cargo model, HDG is expressed as a grade preset value corresponding to a cargo grade, ZX is expressed as a mass proportion coefficient, and the set matching value and the cargo matching value are classified and combined to obtain an analysis set.

The mass specific gravity coefficient is obtained by calculation, and the formula of the calculation is as follows:wherein HZ is expressed as the quality of the goods, eta is expressed as a matching correction factor, and the value is 1.465832;

the matching module matches the goods matching value according to the set matching value in the analysis set to obtain a result set; the method comprises the following specific steps: calculating the set value and the goods value simultaneously by using a formulaCalculating to obtain a correlation value, matching the correlation value with a preset correlation range, and if the correlation value is not greater than the minimum value of the correlation range, generating a first matching signal; if the correlation value is greater than the minimum value of the correlation range and not greater than the maximum value of the correlation range, generating a second matching signal; if the correlation value is greater than the maximum value of the correlation range, generating a third matching signal; combining the first matching signal, the second matching signal and the third matching signal to obtain a result set;

in this embodiment, through carrying out simultaneous calculation with each item data of gathering and processing, through setting for the value and goods matching value respectively to hoist and goods carry out the analysis to can provide data support for the remote control of hoist through the correlation value.

The control module controls the operation of the crane according to the result set, and the specific steps are as follows:

acquiring the running speed corresponding to each matching signal in the result set, and controlling the crane to run according to the corresponding running speed; when the result set contains a first matching signal, controlling the crane to keep low speed for hoisting and running, wherein the cargo level corresponding to the first matching signal is high; when the result set contains a second matching signal, controlling the crane to keep normal speed for hoisting and running, wherein the grade of the goods corresponding to the second matching signal is medium; when the result set contains a third matching signal, controlling the crane to keep fast hoisting operation, wherein the grade of the goods corresponding to the third matching signal is low; the specific low and high speed values may be preset based on the existing normal speed.

The formulas in the invention are all a formula which is obtained by removing dimensions and taking numerical value calculation, and software simulation is carried out by collecting a large amount of data to obtain the formula closest to the real condition, and the preset proportionality coefficient and the threshold value in the formula are set by the technical personnel in the field according to the actual condition or are obtained by simulating a large amount of data.

In the description of the present invention, it is to be understood that the terms "upper", "lower", "left", "right", and the like, indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, are only for convenience in describing the present invention and simplifying the description, and do not indicate or imply that the referred device or element must have a specific orientation and a specific orientation configuration and operation, and thus, should not be construed as limiting the present invention. Furthermore, "first" and "second" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present invention, "a plurality" means two or more unless otherwise specified.

In the description of the present invention, it should be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and the like are to be construed broadly and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be directly connected or indirectly connected through an intermediate member, or they may be connected through two or more elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.

While one embodiment of the present invention has been described in detail, the description is only a preferred embodiment of the present invention and should not be taken as limiting the scope of the invention. All equivalent changes and modifications made within the scope of the present invention shall fall within the scope of the present invention.