CN117862263A - Copper pipe coil pulling vibration reduction method and system special for heating ventilation - Google Patents
Copper pipe coil pulling vibration reduction method and system special for heating ventilation Download PDFInfo
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- RYGMFSIKBFXOCR-UHFFFAOYSA-N Copper Chemical compound [Cu] RYGMFSIKBFXOCR-UHFFFAOYSA-N 0.000 title claims abstract description 169
- 229910052802 copper Inorganic materials 0.000 title claims abstract description 169
- 239000010949 copper Substances 0.000 title claims abstract description 169
- 230000009467 reduction Effects 0.000 title claims abstract description 79
- 238000009423 ventilation Methods 0.000 title claims abstract description 35
- 238000010438 heat treatment Methods 0.000 title claims abstract description 33
- 238000000034 method Methods 0.000 title claims abstract description 30
- 238000012544 monitoring process Methods 0.000 claims abstract description 38
- 230000003044 adaptive effect Effects 0.000 claims abstract description 36
- 238000013135 deep learning Methods 0.000 claims abstract description 17
- 239000000463 material Substances 0.000 claims abstract description 8
- 238000007781 pre-processing Methods 0.000 claims abstract description 7
- 238000013016 damping Methods 0.000 claims description 56
- 230000005540 biological transmission Effects 0.000 claims description 21
- 238000012795 verification Methods 0.000 claims description 17
- 238000004458 analytical method Methods 0.000 claims description 11
- 238000004804 winding Methods 0.000 claims description 8
- 230000006978 adaptation Effects 0.000 claims description 7
- 238000012549 training Methods 0.000 claims description 7
- 238000011144 upstream manufacturing Methods 0.000 claims description 6
- 238000011156 evaluation Methods 0.000 claims description 4
- 238000013075 data extraction Methods 0.000 claims description 3
- 238000001125 extrusion Methods 0.000 claims description 3
- 238000004519 manufacturing process Methods 0.000 abstract description 6
- 238000005096 rolling process Methods 0.000 abstract description 2
- 230000000694 effects Effects 0.000 description 10
- 238000012986 modification Methods 0.000 description 5
- 230000004048 modification Effects 0.000 description 5
- 238000001514 detection method Methods 0.000 description 4
- 230000008569 process Effects 0.000 description 4
- 230000002159 abnormal effect Effects 0.000 description 2
- 238000013528 artificial neural network Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000010801 machine learning Methods 0.000 description 2
- 238000005457 optimization Methods 0.000 description 2
- 230000009471 action Effects 0.000 description 1
- 238000004378 air conditioning Methods 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 238000012806 monitoring device Methods 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 238000007619 statistical method Methods 0.000 description 1
- 238000005482 strain hardening Methods 0.000 description 1
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Abstract
The invention relates to the technical field of copper pipe rolling production, in particular to a copper pipe coiling vibration reduction method and a copper pipe coiling vibration reduction system special for heating ventilation, wherein the method comprises the following steps: acquiring parameter information before copper tube coiling, wherein the parameter information comprises material information and pre-processing size information of a copper tube; the disc drawing amplitude prediction model carries out deep learning on historical disc drawing data, carries out amplitude prediction on the copper pipe of the disc drawing die opening according to a learning result, and determines the initial position of the vibration damper according to a prediction result; the method comprises the steps of monitoring the real-time amplitude of a copper pipe of a disc drawing die opening, inputting a monitoring result into a vibration reduction adaptive control model, and carrying out self-adaptive adjustment on the initial position of a vibration reduction device by the vibration reduction adaptive control model according to the real-time amplitude monitoring result. The invention effectively solves the problems of large high-speed drawing vibration of the coil drawing die opening and unstable coil drawing quality of the copper tube special for heating ventilation, and the coil drawing vibration reduction of the heating ventilation copper tube is adaptively adjusted through the monitoring result and the quality feedback of the copper tube, so that the coil drawing quality of the heating ventilation copper tube is improved.
Description
Technical Field
The invention relates to the technical field of copper pipe rolling production, in particular to a copper pipe coiling vibration reduction method and system special for heating ventilation.
Background
Disc drawing is one of the copper tube processing and production steps, and is usually carried out at normal temperature, so that the copper tube is called cold working, and in the disc drawing process, the copper tube is stretched under the action of a die, so that plastic deformation is generated, and finally, a thinner and longer tube is obtained.
At a coil drawing die opening, high-speed drawing vibration is larger, and because the copper pipe special for heating ventilation is usually matched with other parts in a heating ventilation air conditioning system accurately, the copper pipe special for heating ventilation has stricter size and accuracy control when being coiled and drawn, and the vibration reduction wheel is arranged at the die opening under the normal condition to ensure the coil drawing and wire winding quality, however, the vibration reduction position of the vibration reduction wheel on the copper pipe is required to be continuously adjusted when the copper pipe with continuous and longer period is produced, and at present, the vibration of the copper pipe of the coil drawing die opening and whether the copper pipe is in a straightening state are monitored.
The information disclosed in this background section is only for enhancement of understanding of the general background of the disclosure and is not to be taken as an admission or any form of suggestion that this information forms the prior art that is well known to a person skilled in the art.
Disclosure of Invention
The invention provides a copper pipe coil pulling vibration reduction method and a copper pipe coil pulling vibration reduction system special for heating ventilation, which can effectively solve the problems in the background technology.
In order to achieve the above purpose, the technical scheme adopted by the invention is as follows:
a method of adapting to copper tube coil tension vibration damping special for heating ventilation, the method comprising:
acquiring parameter information before copper tube coiling, wherein the parameter information comprises material information and pre-processing size information of the copper tube;
establishing a disc drawing amplitude prediction model, performing deep learning on historical disc drawing data by the disc drawing amplitude prediction model, performing amplitude prediction on the copper pipe of the disc drawing die opening according to a learning result, and determining the initial position of the vibration damper according to a prediction result;
and (3) carrying out real-time amplitude monitoring on the copper pipe of the disc drawing die opening, inputting a monitoring result into a vibration reduction adaptive control model, and carrying out self-adaptive adjustment on the initial position of the vibration reduction device by the vibration reduction adaptive control model according to the real-time amplitude monitoring result.
Further, performing real-time amplitude monitoring of the copper tubing of the disc pull-out die, comprising:
dividing the area of the copper pipe from the die outlet to the wire collecting end according to the coil drawing extrusion speed of the copper pipe;
and arranging the vibration reduction device on the copper pipe in the corresponding area, wherein the vibration reduction device is connected with a vibration transmission device, and the vibration transmission device transmits the vibration of the vibration reduction device to the vibration reduction adaptive control model.
Further, a main vibration reduction wheel is arranged in the middle of the dividing area, the copper pipe close to one side of the disc drawing die opening is the upstream, the copper pipe close to one side of the wire collecting end is the downstream, auxiliary vibration reduction wheels and the vibration transmission device are respectively arranged at the upstream and downstream positions, and the main vibration reduction wheels and the auxiliary vibration reduction wheels limit the shape of the copper pipe of the die opening, so that the copper pipe of the die opening is in a straight line shape.
Further, the vibration transmission device is connected with a vibration adaption device, the vibration adaption device collects the vibration amplitude of the vibration transmission device in real time, learns the vibration amplitude data of the copper pipe of the die outlet, and transmits the learning result to the vibration reduction adaption control model.
Further, the adaptive vibration damping control model adaptively adjusts the initial position of the vibration damping device according to the real-time amplitude monitoring result, and the adaptive vibration damping control model comprises the following steps:
acquiring an initial position of the vibration damper and the monitoring result;
extracting vibration characteristics according to the monitoring result, and analyzing the vibration characteristics;
and determining the length of the copper pipe from the copper pipe of the die opening to the winding end, and adaptively adjusting the initial position according to the length of the copper pipe and the vibration characteristic analysis result.
Further, establishing a disc pull amplitude prediction model, including:
collecting historical data information of the copper pipe in a coiling stage, and extracting data information related to copper pipe vibration of a die outlet;
constructing a history learning queue, setting time length according to time sequence, and setting the capacity of the history learning queue according to the time length;
assigning weights to the data information in the history learning queue according to a time sequence, wherein the weights are larger when the distance from the current time is closer, setting a time step, and updating the data of the history learning queue according to the time step;
and performing deep learning on the data information related to the copper pipe vibration according to the assigned weight, and correspondingly obtaining the set position of the vibration damper through a learning result.
Further, constructing a training set and a verification set to train and evaluate the disk pull amplitude prediction model includes:
selecting the historical data information to construct n subsets, and carrying out sequence identification on the n subsets;
selecting one subset as the verification set according to the sequence identifier, using the remaining n-1 subsets as the training set, and recording the current subset as the performance parameter of the verification set;
repeating this step until each of the subsets acts as a verification set;
and calculating and obtaining the comprehensive evaluation result of the disc pull amplitude prediction model by taking each subset as the performance parameter of the verification set.
Further, the vibration reduction adaptive control model collects the copper pipe coil pulling quality, and adjusts the position of the vibration reduction device according to feedback of the copper pipe coil pulling quality.
Adapt to heating and ventilation special copper pipe coil and draw vibration damping system, the system includes:
the copper pipe parameter acquisition module acquires parameter information before copper pipe coiling, wherein the parameter information comprises material information and pre-processing size information of the copper pipe;
the disc pulling amplitude prediction module is used for establishing a disc pulling amplitude prediction model, performing deep learning on historical disc pulling data by the disc pulling amplitude prediction model, performing amplitude prediction on the copper pipe of the disc pulling die opening according to a learning result, and determining the initial position of the vibration damper according to a prediction result;
the vibration reduction adaptation adjustment module is used for monitoring the real-time amplitude of the copper pipe of the disc drawing die, inputting the monitoring result into the vibration reduction adaptation control model, and carrying out self-adaptive adjustment on the initial position of the vibration reduction device according to the real-time amplitude monitoring result.
Further, the disc pull amplitude prediction module includes:
the historical data extraction unit is used for collecting historical data information of the copper pipe in a coiling stage and extracting data information related to copper pipe vibration of the die outlet;
a learning queue unit is constructed, a history learning queue is constructed, the time length is set according to the time sequence, and the capacity of the history learning queue is set according to the time length;
the queue data updating unit is used for assigning weights to the data information in the history learning queue according to the time sequence, wherein the weights are larger when the distance from the current time is closer, the time step is set, and the data of the history learning queue is updated according to the time step;
and the vibration reduction position setting unit is used for performing deep learning on the data information related to the copper pipe vibration according to the assigned weight, and correspondingly obtaining the position set by the vibration reduction device through a learning result.
By the technical scheme of the invention, the following technical effects can be realized:
the problem that the coil pulling vibration of the coil pulling die opening is large at a high speed and the coil pulling quality of the copper tube special for heating ventilation is unstable is effectively solved, the vibration damping device is arranged, the vibration and the vibration damping effect are monitored in real time, the coil pulling vibration damping of the heating ventilation copper tube is adaptively adjusted through the monitoring result and the quality feedback of the copper tube, and the coil pulling quality of the heating ventilation copper tube is improved.
The foregoing description is only an overview of the technical solutions of the present application, and may be implemented according to the content of the specification in order to make the technical means of the present application more clearly understood, and in order to make the above-mentioned and other objects, features and advantages of the present application more clearly understood, the following detailed description of the present application will be given.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments described in the present invention, and other drawings may be obtained according to the drawings without inventive effort to those skilled in the art.
FIG. 1 is a schematic flow chart of a method for reducing vibration of copper pipe coil for heating ventilation;
FIG. 2 is a flow chart for creating a disk pull amplitude prediction model;
FIG. 3 is a schematic diagram of a system for accommodating heat ventilation dedicated copper coil pull vibration damping;
FIG. 4 is a schematic view of the structure of the vibration damper and copper tube mounting locations;
reference numerals: 1. copper pipe of the die outlet; 2. a main vibration reduction wheel; 3. an auxiliary vibration reduction wheel; 4. a vibration transmission device; 5. a vibration adaption device; 6. a power device.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and/or" as used herein includes any and all combinations of one or more of the associated listed items.
Example 1
As shown in fig. 1, the application provides a copper pipe coil pulling vibration reduction method suitable for heating ventilation, which comprises the following steps:
s10: acquiring parameter information before copper tube coiling, wherein the parameter information comprises material information and pre-processing size information of a copper tube;
s20: establishing a disc drawing amplitude prediction model, performing deep learning on historical disc drawing data by the disc drawing amplitude prediction model, performing amplitude prediction on a copper pipe of a disc drawing die opening according to a learning result, and determining an initial position of a vibration damper according to a prediction result;
s30: the method comprises the steps of monitoring the real-time amplitude of a copper pipe of a disc drawing die opening, inputting a monitoring result into a vibration reduction adaptive control model, and carrying out self-adaptive adjustment on the initial position of a vibration reduction device by the vibration reduction adaptive control model according to the real-time amplitude monitoring result.
Specifically, the material property of the copper pipe can seriously affect the vibration amplitude of the coil-pulled copper pipe, the vibration amplitude comprises the elastic modulus and hardness, density and heat conduction performance of the copper pipe, and the wall thickness and diameter ratio before and after coil pulling are obtained, the parameter information of the copper pipe is obtained, the amplitude result corresponding to the current coil-pulled copper pipe parameter information is matched through a coil-pulled amplitude prediction model, a deep learning technology such as a neural network is adopted by the coil-pulled amplitude prediction model, historical coil-pulled data are learned, the matching relation between the historical copper pipe parameter information and the vibration amplitude is obtained, the monitoring result is input into a vibration reduction adaptive control model and the initial position of a vibration reduction device is set, the real-time monitoring of the copper pipe of a coil-pulled die opening can adopt a vibration sensor and transmit real-time vibration information to the vibration reduction adaptive model, the vibration reduction adaptive model adaptively adjusts the vibration reduction device according to the initial position of the vibration reduction device and the vibration information received in real time, manual intervention can be reduced, the automation degree and production efficiency of the production line can be improved, and meanwhile, potential problems can be found in advance by the application of the prediction model, and the downtime in production can be reduced.
According to the technical scheme, the problems that the coil drawing die opening is large in high-speed drawing vibration and unstable in coil drawing quality of the copper tube special for heating ventilation are effectively solved, the vibration reduction device is arranged, the vibration and the vibration reduction effect are monitored in real time, the coil drawing vibration reduction of the heating ventilation copper tube is adaptively adjusted through the monitoring result and the quality feedback of the copper tube, and the coil drawing quality of the heating ventilation copper tube is improved.
Further, as shown in fig. 4, the real-time amplitude monitoring of the copper tube of the disc drawing die comprises:
dividing the area of the copper pipe from the die outlet to the wire collecting end according to the coil drawing extrusion speed of the copper pipe;
and a vibration damper is arranged on the copper pipe in the corresponding area, and is connected with a vibration transmission device 4, and the vibration transmission device 4 transmits the vibration of the vibration damper to a vibration damping adaptive control model.
As the preferable mode of the above embodiment, the vibration from the copper tube 1 of the die outlet to the wire winding end is changed to different degrees, the copper tube can be divided into a plurality of areas according to the length, a plurality of vibration reduction devices are arranged to realize the step-by-step vibration reduction effect, a vibration transmission device 4 is arranged on a part of the vibration reduction devices, the vibration generated by the copper tube at the position is collected, the vibration information is transmitted to a vibration reduction adaptive control model for the model to carry out subsequent adaptive adjustment, wherein the vibration reduction device can be externally connected with a power device 6, the power device 6 is commanded through the vibration reduction adaptive control model, and then the adaptive adjustment of the vibration reduction device is completed.
Further, as shown in fig. 4, a main vibration damping wheel 2 is provided in the middle of the divided area, the copper pipe near the die opening of the disc is upstream, the copper pipe near the wire winding end is downstream, and an auxiliary vibration damping wheel 3 and a vibration transmission device 4 are respectively provided at the upstream and downstream positions, wherein the main vibration damping wheel 2 and the auxiliary vibration damping wheel 3 limit the shape of the copper pipe 1 of the die opening, so that the copper pipe 1 of the die opening is in a straight line shape.
On the basis of the above embodiment, the main vibration-damping wheel 2 plays a main vibration-damping role, while the other auxiliary vibration-damping wheels 3 assist the main vibration-damping wheel 2, in this embodiment, the copper pipe is divided into three areas, each area is provided with a vibration-damping device, and the main vibration-damping wheel 2 and the auxiliary vibration-damping wheel 3 together make the copper pipe form a straight line state, so that the copper pipe just after being pulled by the disc can be reduced to deform again, secondly, the copper pipe just after being pulled by the disc can smoothly enter a winding end without winding, and other conditions can be avoided, corresponding detection equipment can be installed for detecting the copper pipe limited by the main vibration-damping wheel 2 and the auxiliary vibration-damping wheel 3 in the straight line state of the copper pipe, and the positions of the main vibration-damping wheel 2 and the auxiliary vibration-damping wheel 3 can be adjusted according to the detection results, wherein the vibration transmission device 4 can use devices capable of collecting vibration data such as vibration sensors.
Further, as shown in fig. 4, the vibration transmission device 4 is connected with a vibration adaptive device 5, and the vibration adaptive device 5 collects the vibration amplitude of the vibration transmission device 4 in real time, learns the vibration amplitude data of the copper pipe 1 of the die outlet, and transmits the learning result to the vibration damping adaptive control model.
As a preferred embodiment, the vibration transmission device 4 transmits vibration data in real time through the connected vibration adapter 5, the vibration data may include information such as amplitude, frequency and the like of vibration, the data may be continuous time series data, the vibration condition of the copper pipe die outlet is recorded, the vibration data collected by the vibration adapter 5 is input into a learning model, the learning model is used for learning and analyzing the vibration data through a machine learning algorithm, after analyzing the vibration data, a learning result is generated, for example, a prediction or abnormal detection result of the vibration amplitude is generated, the vibration damping adaptive control model performs adaptive adjustment according to the learning result, and the position and the force of the vibration damping device are adjusted according to the prediction or abnormal detection result of the vibration amplitude, so as to realize the optimal control effect on the vibration of the copper pipe.
Further, the adaptive vibration damping control model adaptively adjusts an initial position of the vibration damping device according to a real-time amplitude monitoring result, and the adaptive vibration damping control model comprises the following steps:
acquiring an initial position and a monitoring result of the vibration damper;
extracting vibration characteristics according to the monitoring result, and analyzing the vibration characteristics;
determining the length of the copper pipe from the copper pipe 1 of the die opening to the copper pipe at the winding end, and adaptively adjusting the initial position according to the length of the copper pipe and the vibration characteristic analysis result.
Based on the above embodiment, firstly, the initial position of the vibration damping device is obtained, which is the position when the vibration damping device starts to work, then, vibration data transmitted by the vibration transmission device 4 is monitored in real time, including information such as amplitude, frequency and the like of vibration, vibration data transmitted by the vibration transmission device 4 are utilized to extract vibration characteristics, the characteristics can include information such as amplitude, frequency, period and the like of vibration, a common characteristic extraction method includes analysis of time domain characteristics and frequency domain characteristics, the extracted vibration characteristics are analyzed, various algorithms and methods such as machine learning models, statistical analysis and the like can be adopted in the analysis process, the aim is to judge the vibration condition and change trend of a copper pipe according to the vibration characteristics, whether the working state of the vibration damping device meets the requirements or not, the length of the copper pipe from a die orifice to a receiving end is determined, the copper pipe length and the vibration characteristic analysis result are combined, the initial position of the vibration damping device is adjusted adaptively, the adjustment possibly involves operations such as position movement, the adjustment of the vibration characteristics, some parameters of vibration can be set with the analysis of the vibration characteristics according to the analysis of the vibration characteristics, the threshold value can be obtained, the acquisition mode of the threshold can be obtained through the analysis of the pulling amplitude prediction model, if the vibration amplitude is studied data is detected, the vibration condition exceeds the corresponding threshold value, or the vibration condition can be improved, and the vibration condition is set to be improved if the vibration condition exceeds the initial adjustment condition is greatly.
Further, as shown in fig. 2, the disc pull amplitude prediction model is built, including:
s21: collecting historical data information of the copper pipe in a coiling stage, and extracting data information related to vibration of the copper pipe 1 of the die outlet;
s22: constructing a history learning queue, setting time length according to time sequence, and setting the capacity of the history learning queue according to the time length;
s23: assigning weights to the data information in the history learning queue according to the time sequence, wherein the weights are larger when the distance from the current time is smaller, setting time step, and updating the data of the history learning queue according to the time step;
s24: and carrying out deep learning on data information related to copper pipe vibration according to the assigned weight, and correspondingly obtaining the set position of the vibration damper through a learning result.
In this embodiment, a history learning queue is constructed according to a time sequence, the extracted vibration related data information is arranged according to the time sequence, the history learning queue is used for storing history vibration data so as to facilitate subsequent learning and analysis, the capacity and the time length of the history learning queue are set according to specific requirements and actual conditions, the capacity can represent the number of history data items stored in the queue, the time length represents the time span of each data item, the data information in the history learning queue is assigned with weight according to the time sequence, the data closer to the current time is, the assigned weight is larger, the weight can be assigned according to modes such as exponential decay, the data information in the history learning queue is updated according to the set time step, the data in the history learning queue is kept to be certain timeliness according to the set time step, the vibration related data information in the history learning queue is subjected to deep learning according to the assigned weight, the deep learning algorithm such as a neural network, the history data is learned and trained according to the mode and the time span of the history vibration data, a prediction model is established, the data is obtained by the deep learning algorithm, the predicted model is set, the optimal vibration position is controlled according to the predicted, the vibration position is predicted, and the vibration damping effect is controlled according to the vibration position, and the vibration damping effect is controlled.
Further, constructing a training set and a verification set to train and evaluate the disk pull amplitude prediction model includes:
selecting historical data information to construct n subsets, and carrying out sequence identification on the n subsets;
selecting one subset as a verification set according to the sequence identification, using the remaining n-1 subsets as training sets, and recording the current subset as performance parameters of the verification set;
repeating this step until each subset acts as a verification set;
and calculating the performance parameters by taking each subset as a verification set to obtain the comprehensive evaluation result of the disc pull amplitude prediction model.
On the basis of the embodiment, the historical data is divided into a plurality of subsets, each subset serves as a verification set, the historical data can be fully utilized for model training and evaluation, the generalization capability of the model can be verified through taking different subsets as the verification sets, namely whether the model has good prediction capability for data in different time periods or under different conditions, and the risk of model overfitting is reduced.
In this embodiment, the coil pulling quality of the copper tube is monitored in real time through various sensors and monitoring devices in the process of coil pulling of the copper tube, the coil pulling quality can include parameters such as shape, diameter and wall thickness of the copper tube, monitored copper tube coil pulling quality data are collected into the vibration damping adaptive control model, the data can be continuous time series data, various parameters in the process of coil pulling of the copper tube are recorded, the vibration damping adaptive control model analyzes the current coil pulling state and quality according to the feedback of the coil pulling quality, if the parameters such as shape, diameter and the like of the copper tube are monitored to have deviation from preset standard, the vibration control of the copper tube is described as possibly having problems, the position of the vibration damping device is required to be adjusted, the position of the vibration damping device is adaptively adjusted according to the analysis result of the vibration damping adaptive control model, the adjustment can be the strength of the vibration damping device is increased or reduced, or the position of the vibration damping device is changed, after adjustment, the coil pulling quality of the copper tube is continuously monitored, and the vibration adaptive control model is fed back to the adaptive control model, if the vibration damping device is effectively adjusted; if the disc pulling quality is not improved or deteriorated, it is necessary to further adjust the position of the vibration damping device.
Example two
Based on the same inventive concept as the copper pipe coil pulling vibration reduction method for adapting to heating and ventilation in the foregoing embodiment, the invention also provides a copper pipe coil pulling vibration reduction system for adapting to heating and ventilation, as shown in fig. 3, the system comprises:
the copper pipe parameter acquisition module acquires parameter information before copper pipe coiling, wherein the parameter information comprises material information and pre-processing size information of a copper pipe;
the disc pulling amplitude prediction module is used for establishing a disc pulling amplitude prediction model, performing deep learning on historical disc pulling data by the disc pulling amplitude prediction model, performing amplitude prediction on the copper pipe of the disc pulling die opening according to a learning result, and determining the initial position of the vibration damper according to a prediction result;
the vibration reduction adaptive adjustment module is used for monitoring the real-time amplitude of the copper pipe of the disc drawing die opening, inputting the monitoring result into the vibration reduction adaptive control model, and carrying out self-adaptive adjustment on the initial position of the vibration reduction device according to the real-time amplitude monitoring result.
The adjusting system can effectively realize the technical effects of adapting to the special copper pipe coil pulling vibration reduction method for heating ventilation, and the technical effects are described in the embodiment and are not repeated here.
Further, the disc pull amplitude prediction module includes:
the historical data extraction unit is used for collecting historical data information of the copper pipe in a coil drawing stage and extracting data information related to copper pipe vibration of the die outlet;
a learning queue unit is constructed, a history learning queue is constructed, the time length is set according to the time sequence, and the capacity of the history learning queue is set according to the time length;
the queue data updating unit is used for assigning weights to the data information in the history learning queue according to the time sequence, wherein the weights are larger when the distance from the current time is closer, the time step is set, and the data of the history learning queue is updated according to the time step;
and the vibration reduction position setting unit is used for performing deep learning on data information related to copper pipe vibration according to the assigned weight, and correspondingly obtaining the position set by the vibration reduction device through a learning result.
Similarly, the above-mentioned optimization schemes of the system may also respectively correspond to the optimization effects corresponding to the methods in the first embodiment, which are not described herein again.
Although the present application has been described in connection with specific features and embodiments thereof, it will be apparent that various modifications and combinations can be made without departing from the spirit and scope of the application. Accordingly, the specification and figures are merely exemplary illustrations of the application as defined in the appended claims and are to be construed as covering any and all modifications, variations, combinations, or equivalents that are within the scope of the application. It will be apparent to those skilled in the art that various modifications and variations can be made in the present application without departing from the scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the present application and the equivalents thereof, the present application is intended to cover such modifications and variations.
Claims (10)
1. The utility model provides a special copper pipe dish of adaptation heating and ventilation draws damping method which characterized in that, the method includes:
acquiring parameter information before copper tube coiling, wherein the parameter information comprises material information and pre-processing size information of the copper tube;
establishing a disc drawing amplitude prediction model, performing deep learning on historical disc drawing data by the disc drawing amplitude prediction model, performing amplitude prediction on the copper pipe of the disc drawing die opening according to a learning result, and determining the initial position of the vibration damper according to a prediction result;
and (3) carrying out real-time amplitude monitoring on the copper pipe of the disc drawing die opening, inputting a monitoring result into a vibration reduction adaptive control model, and carrying out self-adaptive adjustment on the initial position of the vibration reduction device by the vibration reduction adaptive control model according to the real-time amplitude monitoring result.
2. The method for reducing vibration of a copper tube coil dedicated for heating and ventilation according to claim 1, wherein the monitoring of the amplitude of the copper tube of the coil drawing die in real time comprises:
dividing the area of the copper pipe from the die outlet to the wire collecting end according to the coil drawing extrusion speed of the copper pipe;
and arranging the vibration reduction device on the copper pipe in the corresponding area, wherein the vibration reduction device is connected with a vibration transmission device, and the vibration transmission device transmits the vibration of the vibration reduction device to the vibration reduction adaptive control model.
3. The method for drawing and damping the copper pipe coiled specially for heating and ventilation according to claim 2, wherein a main damping wheel is arranged in the middle of the dividing area, the copper pipe on one side close to the drawing die opening of the coiled pipe is upstream, the copper pipe on one side close to the wire collecting end is downstream, auxiliary damping wheels and the vibration transmission device are respectively arranged at the upstream and downstream positions, and the main damping wheel and the auxiliary damping wheels limit the shape of the copper pipe of the die opening, so that the copper pipe of the die opening is in a straight line shape.
4. The method for reducing vibration of copper pipe coiled specially for adapting heating and ventilation according to claim 3, wherein the vibration transmission device is connected with a vibration adapting device, the vibration adapting device collects vibration amplitude of the vibration transmission device in real time, learns vibration amplitude data of the copper pipe of the die outlet, and transmits learning results to the vibration reduction adaptation control model.
5. The method for adaptively adjusting the vibration damping of copper pipe coiling special for heating and ventilation according to claim 1 or 4, wherein the vibration damping adaptive control model adaptively adjusts the initial position of the vibration damping device according to a real-time amplitude monitoring result, and the method comprises the following steps:
acquiring an initial position of the vibration damper and the monitoring result;
extracting vibration characteristics according to the monitoring result, and analyzing the vibration characteristics;
and determining the length of the copper pipe from the copper pipe of the die opening to the winding end, and adaptively adjusting the initial position according to the length of the copper pipe and the vibration characteristic analysis result.
6. The method for reducing vibration of copper pipe coil specially adapted for heating ventilation according to claim 1, wherein the step of establishing a coil amplitude prediction model comprises the steps of:
collecting historical data information of the copper pipe in a coiling stage, and extracting data information related to copper pipe vibration of a die outlet;
constructing a history learning queue, setting time length according to time sequence, and setting the capacity of the history learning queue according to the time length;
assigning weights to the data information in the history learning queue according to a time sequence, wherein the weights are larger when the distance from the current time is closer, setting a time step, and updating the data of the history learning queue according to the time step;
and performing deep learning on the data information related to the copper pipe vibration according to the assigned weight, and correspondingly obtaining the set position of the vibration damper through a learning result.
7. The method for adapting to heat and ventilation special copper pipe coil pull vibration reduction according to claim 6, wherein constructing a training set and a verification set to train and evaluate the coil pull amplitude prediction model comprises:
selecting the historical data information to construct n subsets, and carrying out sequence identification on the n subsets;
selecting one subset as the verification set according to the sequence identifier, using the remaining n-1 subsets as the training set, and recording the current subset as the performance parameter of the verification set;
repeating this step until each of the subsets acts as a verification set;
and calculating and obtaining the comprehensive evaluation result of the disc pull amplitude prediction model by taking each subset as the performance parameter of the verification set.
8. The method for reducing vibration of copper pipe coil special for heating ventilation according to claim 1, wherein the vibration reduction adaptation control model collects the copper pipe coil drawing quality and adjusts the position of the vibration reduction device according to feedback of the copper pipe coil drawing quality.
9. Adapt to heating and ventilation special copper pipe coil and draw vibration damping system, its characterized in that, the system includes:
the copper pipe parameter acquisition module acquires parameter information before copper pipe coiling, wherein the parameter information comprises material information and pre-processing size information of the copper pipe;
the disc pulling amplitude prediction module is used for establishing a disc pulling amplitude prediction model, performing deep learning on historical disc pulling data by the disc pulling amplitude prediction model, performing amplitude prediction on the copper pipe of the disc pulling die opening according to a learning result, and determining the initial position of the vibration damper according to a prediction result;
the vibration reduction adaptation adjustment module is used for monitoring the real-time amplitude of the copper pipe of the disc drawing die, inputting the monitoring result into the vibration reduction adaptation control model, and carrying out self-adaptive adjustment on the initial position of the vibration reduction device according to the real-time amplitude monitoring result.
10. The system for reducing vibration in a copper coil dedicated for heating and ventilation according to claim 9, wherein the coil amplitude prediction module comprises:
the historical data extraction unit is used for collecting historical data information of the copper pipe in a coiling stage and extracting data information related to copper pipe vibration of the die outlet;
a learning queue unit is constructed, a history learning queue is constructed, the time length is set according to the time sequence, and the capacity of the history learning queue is set according to the time length;
the queue data updating unit is used for assigning weights to the data information in the history learning queue according to the time sequence, wherein the weights are larger when the distance from the current time is closer, the time step is set, and the data of the history learning queue is updated according to the time step;
and the vibration reduction position setting unit is used for performing deep learning on the data information related to the copper pipe vibration according to the assigned weight, and correspondingly obtaining the position set by the vibration reduction device through a learning result.
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