CN117688492A - Perforation detection system and detection method for perforating machine - Google Patents
Perforation detection system and detection method for perforating machine Download PDFInfo
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Abstract
The invention relates to the technical field of detection equipment, in particular to a perforation detection system and a perforation detection method of a perforating machine. These feature sets will be used to construct a combined feature set and set constraint parameters for perforation detection. And then, applying the constructed combined feature set and perforation detection constraint parameters to a detection model, and combining the puncher data and the material data to be punched, so as to establish a pressure analysis model, a speed analysis model and a vibration analysis model. According to the invention, the perforation process is deeply analyzed by utilizing big data and machine learning technology, so that the perforation condition of the perforating machine in the operation process can be effectively monitored and detected, and once abnormality is found, the automatic perforating machine can be adjusted in real time, so that the accuracy of the automatic perforating machine in perforation is higher, and the quality problem caused by insufficient accuracy is reduced.
Description
Technical Field
The invention relates to the technical field of detection equipment, in particular to a perforation detection system and a perforation detection method of a perforation machine.
Background
With the popularization and improvement of automation equipment, the use of perforators is becoming more and more widespread. However, the problem of poor perforation is easily caused during perforation for various reasons, such as uneven material, long-time operation of the machine, etc. This not only affects the quality of the product, but also increases the production cost and reduces the production efficiency. For this reason, the perforating condition of the perforating machine can be detected by the detecting device, but the existing detecting device still has the problem of lower detecting precision, for example, the device may generate the phenomena of error reporting, false reporting or missing reporting, and the problems may cause the user to reduce the trust degree of the device, and affect the normal use of the device. Therefore, it is necessary to design a perforation detection system of a perforation machine and a corresponding detection method, so as to improve the detection precision, effectively reduce the occurrence of perforation defects, improve the production efficiency and reduce the cost.
Disclosure of Invention
The invention aims to overcome the defects in the prior art, and provides a perforation detection system and a perforation detection method for a perforating machine, which can improve the detection precision of perforation of the perforating machine.
The technical scheme adopted for solving the technical problems is as follows: a perforation detection system and a perforation detection method for a perforating machine.
In one aspect, the present invention provides a method for detecting perforation of a perforation machine, including:
basic data information in the perforation process is collected, wherein the basic data information comprises information such as pressure, speed, vibration and the like, and pressure characteristic analysis, speed characteristic analysis and vibration characteristic analysis are carried out on the data information to obtain a pressure characteristic set, a speed characteristic set and a vibration characteristic set;
constructing a combined feature set based on the pressure feature set, the speed feature set and the vibration feature set, and setting perforation detection constraint parameters;
transmitting the combined feature set and perforation monitoring constraint parameters to a detection model, recording puncher data and material data to be punched, and constructing a pressure analysis model, a speed analysis model and a vibration analysis model; the puncher data comprise information such as the using time of the puncher, the punching depth and the like; the material to be punched data comprise the thickness of the material to be punched and the distance between a punching mechanism of a puncher and the material to be punched;
based on a pressure analysis model, a speed analysis model and a vibration analysis model, extracting target data to be detected, carrying out matching analysis on the target data and the data of the perforating machine, and constructing a perforating comprehensive analysis model to obtain perforating comprehensive analysis results;
and judging whether the perforation of the perforating machine is stable and whether the perforation is abnormal according to the perforation comprehensive analysis result, and finishing perforation detection.
Further, the method further comprises:
real-time tracking is performed through a control system based on perforation detection constraint parameters, and parameter tracking data are established;
and according to the parameter tracking data, utilizing an optimization algorithm to adjust the optimization parameters in real time.
Further, the method further comprises:
acquiring a panoramic image of a punching mechanism of a puncher and a material to be punched through a camera;
identifying the panoramic image by an image identification technology;
judging whether the puncher successfully completes punching according to the identification result.
In another aspect, the present invention provides a perforation detection system of a perforation machine, for implementing the perforation detection method of the perforation machine, the detection system comprising:
the sensor module is used for collecting data in the perforation process, including information such as pressure, speed, vibration and the like;
the signal processing module is used for analyzing and processing the data acquired by the sensor module and extracting useful characteristic information;
the detection model module is used for training and evaluating a perforation detection model according to the characteristic information extracted by the signal processing module;
and the control system is used for controlling and optimizing the running state of the perforating machine according to the output result of the detection model.
The invention has the technical effects that:
compared with the prior art, the invention firstly analyzes basic data information such as pressure, speed, vibration and the like in the perforation process to obtain corresponding feature sets. These feature sets will be used to construct a combined feature set and set constraint parameters for perforation detection. And then, applying the constructed combined feature set and perforation detection constraint parameters to a detection model, and combining the puncher data and the material data to be punched, so as to establish a pressure analysis model, a speed analysis model and a vibration analysis model. The main purpose of these models is to provide basis for optimizing operations in order to detect and control the perforation process. The invention utilizes big data and machine learning technology to carry out deep analysis on the perforation process, can effectively monitor and detect the perforation condition of the perforating machine in the operation process, and can adjust in real time once abnormality is found, thereby avoiding production stagnation caused by equipment failure. The automatic punching machine has the advantages that the occurrence rate of poor punching is greatly reduced, the production efficiency is improved, a large amount of production cost can be saved, the accuracy of the automatic punching machine in punching is enabled to reach a higher level, and therefore quality problems caused by insufficient accuracy are reduced.
Drawings
FIG. 1 is a flowchart of a method for detecting perforation of a perforating machine according to the present invention;
fig. 2 is a block diagram of a perforation detection system of a perforation machine according to the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention are clearly and completely described below with reference to the accompanying drawings of the specification.
Example 1:
as shown in fig. 1, the method for detecting perforation by a perforation machine according to the present embodiment includes:
basic data information in the perforation process is collected, wherein the basic data information comprises information such as pressure, speed, vibration and the like, and pressure characteristic analysis, speed characteristic analysis and vibration characteristic analysis are carried out on the data information to obtain a pressure characteristic set, a speed characteristic set and a vibration characteristic set;
constructing a combined feature set based on the pressure feature set, the speed feature set and the vibration feature set, and setting perforation detection constraint parameters;
transmitting the combined feature set and perforation monitoring constraint parameters to a detection model, recording puncher data and material data to be punched, and constructing a pressure analysis model, a speed analysis model and a vibration analysis model; the puncher data comprise information such as the using time of the puncher, the punching depth and the like; the material to be punched data comprise the thickness of the material to be punched and the distance between a punching mechanism of a puncher and the material to be punched;
based on a pressure analysis model, a speed analysis model and a vibration analysis model, extracting target data to be detected, carrying out matching analysis on the target data and the data of the perforating machine, and constructing a perforating comprehensive analysis model to obtain perforating comprehensive analysis results;
and judging whether the perforation of the perforating machine is stable and whether the perforation is abnormal according to the perforation comprehensive analysis result, and finishing perforation detection.
Inputting pressure data in the current perforation process into a pressure analysis model to obtain a pressure analysis result; inputting speed data in the current perforation process into a speed analysis model to obtain a speed analysis result; inputting vibration data in the current perforation process into a vibration analysis model to obtain a vibration analysis result; the method comprises the steps of combining puncher data and material data to be punched to obtain influence weights of pressure, speed and vibration on punching respectively;
taking pressure, speed and vibration as influencing factors, constructing an association matrix by combining weights of the influencing factors, and obtaining factor association prediction information based on the association matrix;
and outputting information such as punching depth and the like according to the associated prediction information to obtain a punching comprehensive analysis model.
Acquiring a plurality of pressure characteristic values through a sensor to form a pressure characteristic set;
determining a perforation detection pressure constraint parameter based on the pressure feature set;
and adding the perforation detection pressure constraint parameter and the perforation influence weight of the pressure to the incidence matrix.
Acquiring a plurality of speed characteristic values through a sensor to form a speed characteristic set;
determining a perforation detection speed constraint parameter based on the speed feature set;
and adding the perforation detection speed constraint parameter and the influence weight of the speed on perforation into the incidence matrix.
A plurality of vibration characteristic values are obtained through a sensor to form a vibration characteristic set;
determining perforation detection vibration constraint parameters based on the vibration feature set;
and adding the perforation detection vibration constraint parameter and the impact weight of vibration on perforation into the incidence matrix.
The method further comprises the steps of:
based on the incidence matrix, constructing probability models of all influence factors, and setting adjustment thresholds of all influence factors;
when the probability model value reaches a set threshold value, a reminder is sent out;
and dynamically adjusting the corresponding influence factors according to the constraint parameters and the influence weights of the vibration on punching.
The method further comprises the steps of:
real-time tracking is performed through a control system based on perforation detection constraint parameters, and parameter tracking data are established;
and according to the parameter tracking data, utilizing an optimization algorithm to adjust the optimization parameters in real time.
The method further comprises the steps of:
acquiring a panoramic image of a punching mechanism of a puncher and a material to be punched through a camera;
identifying the panoramic image by an image identification technology;
judging whether the puncher successfully completes punching according to the identification result.
During the perforation process, the present invention collects and analyzes basic data such as pressure, velocity, vibration, etc., to form a set of corresponding feature sets. This set of feature sets will serve as the basis for constructing the combined feature set. The combined feature set and perforation monitoring constraint parameters are then sent to a detection model, thereby creating a pressure analysis model, a velocity analysis model, and a vibration analysis model. The invention fully utilizes big data and machine learning technology, and deep analysis is carried out on the perforation process, so that the condition of the perforating machine in the running process can be monitored and detected in real time, and actions can be immediately taken when problems are found, thus greatly reducing the occurrence of perforation defects, enabling an automatic perforating machine to reach a more accurate state, and further reducing the quality problem of products caused by insufficient precision.
Example 2:
as shown in fig. 2, a system for detecting perforation of a perforation machine according to this embodiment is configured to implement the perforation detection method of a perforation machine according to embodiment 1, and the detection system includes:
the sensor module is used for collecting data in the perforation process, including information such as pressure, speed, vibration and the like;
the signal processing module is used for analyzing and processing the data acquired by the sensor module and extracting useful characteristic information;
the detection model module is used for constructing, training and evaluating a perforation detection model according to the characteristic information extracted by the signal processing module;
and the control system is used for controlling and optimizing the running state of the perforating machine according to the output result of the detection model.
The sensor module includes:
a pressure sensor for detecting the pressure applied during perforation;
the speed sensor is used for detecting the speed of the head movement during perforation;
the vibration sensor is used for detecting the amplitude of vibration generated during perforation;
the above-described sensor arrangement ensures the stability and reliability of the sensor module.
The signal processing module processes the signal based on a wavelet transform analysis method, and converts the original signal into a feature vector by analyzing wavelet coefficients of the signal.
The detection model module can adopt a deep learning algorithm to build a convolutional neural network for training and evaluating the perforation detection model. By continuously adjusting the network structure and parameters, a model can be obtained which can accurately distinguish between good perforations and bad perforations.
The control system adopts a PID controller, controls the running state of the perforating machine according to the output result of the detection model, and controls the perforating machine to stop running when the output result of the model shows that the perforation is bad, thereby avoiding the occurrence of defective products.
The detection system further comprises:
the image acquisition module comprises image acquisition equipment such as a camera and the like and is used for acquiring a perforation panoramic image;
and the visualization module comprises visualization equipment such as an electronic screen and the like and is used for displaying data and images.
The above embodiments are merely examples of the present invention, and the scope of the present invention is not limited to the above embodiments, and any suitable changes or modifications made by those skilled in the art, which are consistent with the claims of the present invention, shall fall within the scope of the present invention.
Claims (10)
1. A method of detecting perforation by a perforation machine, the method comprising:
basic data information in the perforation process is collected, wherein the basic data information comprises pressure, speed and vibration information, and pressure characteristic analysis, speed characteristic analysis and vibration characteristic analysis are carried out on the data information to obtain a pressure characteristic set, a speed characteristic set and a vibration characteristic set;
constructing a combined feature set based on the pressure feature set, the speed feature set and the vibration feature set, and setting perforation detection constraint parameters;
transmitting the combined feature set and perforation monitoring constraint parameters to a detection model, recording puncher data and material data to be punched, and constructing a pressure analysis model, a speed analysis model and a vibration analysis model; the puncher data comprise puncher use time length and punching depth information; the material to be punched data comprise the thickness of the material to be punched and the distance between a punching mechanism of a puncher and the material to be punched;
based on a pressure analysis model, a speed analysis model and a vibration analysis model, extracting target data to be detected, carrying out matching analysis on the target data and the data of the perforating machine, and constructing a perforating comprehensive analysis model to obtain perforating comprehensive analysis results;
and judging whether the perforation of the perforating machine is stable and whether the perforation is abnormal according to the perforation comprehensive analysis result, and finishing perforation detection.
2. The perforation detection method of the perforation machine according to claim 1, wherein the pressure data in the current perforation process is input into a pressure analysis model to obtain a pressure analysis result; inputting speed data in the current perforation process into a speed analysis model to obtain a speed analysis result; inputting vibration data in the current perforation process into a vibration analysis model to obtain a vibration analysis result; the method comprises the steps of combining puncher data and material data to be punched to obtain influence weights of pressure, speed and vibration on punching respectively;
taking pressure, speed and vibration as influencing factors, constructing an association matrix by combining weights of the influencing factors, and obtaining factor association prediction information based on the association matrix;
and obtaining a punching comprehensive analysis model according to the associated prediction information.
3. The method for detecting perforation by a perforation machine according to claim 2, wherein,
acquiring a plurality of pressure characteristic values through a sensor to form a pressure characteristic set;
determining a perforation detection pressure constraint parameter based on the pressure feature set;
and adding the perforation detection pressure constraint parameter and the perforation influence weight of the pressure to the incidence matrix.
4. The method for detecting perforation by a perforation machine according to claim 2, wherein,
acquiring a plurality of speed characteristic values through a sensor to form a speed characteristic set;
determining a perforation detection speed constraint parameter based on the speed feature set;
and adding the perforation detection speed constraint parameter and the influence weight of the speed on perforation into the incidence matrix.
5. The method for detecting perforation by a perforation machine according to claim 2, wherein,
a plurality of vibration characteristic values are obtained through a sensor to form a vibration characteristic set;
determining perforation detection vibration constraint parameters based on the vibration feature set;
and adding the perforation detection vibration constraint parameter and the impact weight of vibration on perforation into the incidence matrix.
6. The method of punch perforation detection according to claim 2, wherein the method further comprises:
based on the incidence matrix, constructing probability models of all influence factors, and setting adjustment thresholds of all influence factors;
when the probability model value reaches a set threshold value, a reminder is sent out;
and dynamically adjusting the corresponding influence factors according to the constraint parameters and the influence weights of the vibration on punching.
7. The method of punch perforation detection according to claim 1, wherein the method further comprises:
real-time tracking is performed through a control system based on perforation detection constraint parameters, and parameter tracking data are established;
and according to the parameter tracking data, utilizing an optimization algorithm to adjust the optimization parameters in real time.
8. The method of punch perforation detection according to claim 1, wherein the method further comprises:
acquiring a panoramic image of a punching mechanism of a puncher and a material to be punched through a camera;
identifying the panoramic image by an image identification technology;
judging whether the puncher successfully completes punching according to the identification result.
9. A method of detecting perforation by a perforation machine according to any one of claims 1 to 8, wherein the detection system is implemented based on a perforation machine perforation detection system comprising:
the sensor module is used for collecting data in the perforation process, including pressure, speed and vibration information;
the signal processing module is used for analyzing and processing the data acquired by the sensor module and extracting useful characteristic information;
the detection model module is used for training and evaluating a perforation detection model according to the characteristic information extracted by the signal processing module;
and the control system is used for controlling and optimizing the running state of the perforating machine according to the output result of the detection model.
10. The method of claim 9, wherein the sensor module comprises:
a pressure sensor for detecting the pressure applied during perforation;
the speed sensor is used for detecting the speed of the head movement during perforation;
and the vibration sensor is used for detecting the amplitude of vibration generated during perforation.
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