CN115712268B - Fault early warning system for automatic electronic product auxiliary material laminating device - Google Patents
Fault early warning system for automatic electronic product auxiliary material laminating device Download PDFInfo
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Abstract
The invention belongs to the technical field of monitoring of electronic product production equipment, and particularly relates to a fault early warning system for an automatic electronic product auxiliary material laminating device. The laminating device can send out corresponding alarm signal when the laminating device breaks down, can also calculate out its deviation value, whether combine the failure prediction model to judge laminating equipment to exceed standard deviation trend threshold value, thereby can send out early warning signal according to its running state's deviation trend before the trouble takes place, under this state, the laminating device still is in normal operating, and then can avoid the electronic product in the course of working to take place to damage, then stop the laminating device that is running, and carry out the troubleshooting processing can, reduce the unnecessary loss of enterprise or mill.
Description
Technical Field
The invention belongs to the technical field of monitoring of electronic product production equipment, and particularly relates to a fault early warning system for an automatic electronic product auxiliary material laminating device.
Background
In the process of producing electronic products, a plurality of electrical devices are needed to assist, for example, a conveying device for conveying materials, a clamping device for clamping materials, a pressing device for adhering materials and the like, a large number of motors, hydraulic cylinders and the like are needed to assist in the process, and because the devices operate according to a set program, if faults occur, the damage of the processed products is likely to occur, and the damage of the electronic products in batches can also occur under serious conditions, so that a real-time fault monitoring and early warning system should be added in the operation process of the devices, and the damage condition in the adhering process of the electronic products and auxiliary materials is avoided.
Traditional automatic laminating of electronic product auxiliary material is failure early warning system for device always reports to the police after the trouble takes place to send the instruction of out of service to electrical equipment, then carry out corresponding maintenance by the staff, but this in-process, the electronic product that is processing probably takes place to destroy, this can lead to the corresponding increase of manufacturing cost undoubtedly, cause unnecessary loss for mill or enterprise, on the basis of this, this scheme provides one kind can carry out the monitored control system of early warning before the laminating device breaks down.
Disclosure of Invention
The invention aims to provide a fault early warning system for an automatic electronic product auxiliary material laminating device, which can send out an early warning signal before the laminating device breaks down, so that the damage of an electronic product in the processing process is avoided, and unnecessary loss of enterprises or factories is reduced.
The technical scheme adopted by the invention is as follows:
a fault early warning system for an automatic electronic product accessory laminating device comprises a data acquisition module, a data extraction module, a screening module, a pre-estimation module, an alarm module and an early warning module;
the data acquisition module is used for acquiring operation parameters of the laminating device, wherein the operation parameters at least comprise hydraulic cylinder pressure parameters and motor rotating speed parameters;
the data extraction module is used for acquiring all the operation parameters, constructing the operation parameters into a training sample set, and calibrating the operation data in the training sample set into training samples;
the screening module is used for acquiring standard operation parameters, comparing the standard operation parameters with all training samples one by one, calibrating the training samples exceeding the standard operation parameters as abnormal samples, recording time nodes corresponding to the abnormal samples, calibrating the abnormal samples as abnormal nodes, calculating the time length between two adjacent abnormal nodes to obtain an evaluation time length, comparing a standard evaluation period with the evaluation time length, screening out the evaluation time length longer than the standard evaluation period time length, and calibrating the evaluation time length as a training period;
the estimation module is used for acquiring all training samples in the training period, inputting the training samples into a trend estimation model to obtain the change trend rate of the laminating device, and calculating the estimated value of the laminating device under the current node by combining the change trend rate;
the alarm module is used for acquiring the current operation parameters of the laminating device, comparing the current operation parameters with the estimated value to obtain a deviation value, and judging whether the laminating device normally operates or not and whether an alarm signal is sent out or not according to the deviation value;
the early warning module is used for obtaining all deviation values of the laminating device in a normal operation state, substituting the deviation values into the fault prediction model to obtain deviation trend values of the laminating device, and judging whether the automatic laminating device has fault risks or not and sending out early warning signals according to the deviation trend values.
In a preferred scheme, after screening out the evaluation duration longer than the standard evaluation period duration, counting all the evaluation durations shorter than the standard evaluation period duration, and calibrating the evaluation durations as abnormal periods;
acquiring all abnormal periods, and arranging according to the sequence of time nodes;
comparing the durations of adjacent abnormal periods to obtain an evaluation difference time;
obtaining a standard evaluation threshold, comparing the standard evaluation threshold with the evaluation difference, screening out the evaluation difference larger than the standard evaluation threshold, and calibrating the evaluation difference as an abnormal difference;
judging whether the head nodes and the tail nodes of the adjacent abnormal periods corresponding to the abnormal difference are connected;
if yes, judging that the laminating device has a risk of abnormal operation, and sending an early warning signal by the early warning module;
if not, judging that the laminating device normally operates, and not acting the early warning module.
In a preferred embodiment, the specific process of inputting the training sample into a trend estimation model to obtain the variation trend rate of the fitting device is as follows:
acquiring a plurality of training samples in the training period, and calculating the average fluctuation amount of all the training samples in each training period;
acquiring a trend function from a trend estimation model;
and inputting all the average fluctuation amounts into a trend function to obtain the change trend rate of the laminating device.
In a preferred embodiment, the trend rate of change is determined;
acquiring previous operation parameters of a current node;
acquiring a prediction function from the trend prediction model;
and inputting the previous operation parameters and the change trend rate of the current node into an estimation function together to obtain an estimated value of the current node of the laminating device.
In a preferred embodiment, the deviation value is a difference between the current operation parameter and a predicted value, and when determining whether the bonding apparatus is operating normally and whether an alarm signal is sent according to the deviation value, the determining process is as follows:
acquiring a standard deviation threshold value, and comparing the standard deviation threshold value with the deviation value;
if the deviation value is smaller than a standard deviation threshold value, judging that the laminating device normally operates;
if the deviation value is larger than or equal to the standard deviation threshold value, judging that the laminating device is abnormal in operation, stopping the operation of the laminating device at the moment, and sending an alarm signal.
In a preferred embodiment, when calculating the deviation trend value, an objective function is obtained from the fault prediction model, and the deviation value is input into the objective function, wherein the deviation values input into the fault prediction model are all smaller than a standard deviation threshold value.
In a preferred embodiment, the process of determining whether the automatic bonding device has a failure risk and sends out an early warning signal according to the deviation trend value is as follows:
acquiring a standard deviation trend threshold value, and comparing the standard deviation trend threshold value with the deviation trend value;
if the standard deviation trend threshold is smaller than the deviation trend value, judging that the laminating device has a fault risk, stopping the operation of the laminating device, and sending out an early warning signal;
and if the standard deviation trend threshold value is larger than or equal to the deviation trend value, judging that the laminating device normally operates.
In a preferable scheme, before the early warning signal is sent out, the early warning level of the early warning signal is judged according to the deviation of the deviation trend value;
wherein the evaluation interval of the early warning grade is [ a, b ], [ b, c) and [ c, d ];
when the deviation amount of the deviation trend value belongs to the evaluation interval [ a, b ], the laminating device sends a primary early warning signal;
when the deviation amount of the deviation trend value belongs to the evaluation interval [ b, c), the laminating device sends out a secondary early warning signal;
and when the deviation of the deviation trend value belongs to the evaluation interval [ c, d ], the laminating device sends out a three-level early warning signal.
In a preferred embodiment, the alarm signal has a higher priority than the warning signal.
The invention also provides a fault early warning terminal for the automatic electronic product auxiliary material laminating device, which comprises:
at least one processor;
and a memory communicatively coupled to the at least one processor;
the storage stores a computer program which can be executed by the at least one processor, and the computer program is executed by the at least one processor, so that the at least one processor can execute the fault early warning system for the automatic electronic product auxiliary material laminating device.
The invention has the technical effects that:
the invention can not only send out corresponding alarm signals when the laminating device fails, but also measure and calculate the deviation value of the laminating device, and then judge whether the laminating device exceeds the standard deviation trend threshold value by combining with the fault prediction model, so that the invention can send out early warning signals according to the deviation trend of the running state of the laminating device before the failure occurs, and under the state, the laminating device still runs normally, thereby avoiding the damage of the electronic product in the processing process, then stopping the running laminating device, and carrying out fault removal treatment, thus reducing unnecessary loss of enterprises or factories.
Drawings
FIG. 1 is a flow chart of a system provided by an embodiment of the present invention;
fig. 2 is a block diagram of a system provided by an embodiment of the present invention.
Detailed description of the preferred embodiments
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in detail below.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, but the present invention may be practiced in other ways than those specifically described and will be readily apparent to those of ordinary skill in the art without departing from the spirit of the present invention, and therefore the present invention is not limited to the specific embodiments disclosed below.
Furthermore, reference herein to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one implementation of the invention. The appearances of the phrase "in one preferred embodiment" in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments.
Furthermore, the present invention is described in detail with reference to the drawings, and in the detailed description of the embodiments of the present invention, the cross-sectional view illustrating the structure of the device is not enlarged partially according to the general scale for convenience of illustration, and the drawings are only exemplary and should not be construed as limiting the scope of the present invention. In addition, the three-dimensional dimensions of length, width and depth should be included in the actual fabrication.
Referring to fig. 1 and 2, the invention provides a fault early warning system for an automatic electronic product accessory laminating device, which comprises a data acquisition module, a data extraction module, a screening module, an estimation module, an alarm module and an early warning module;
the data acquisition module is used for acquiring the operation parameters of the laminating device, wherein the operation parameters at least comprise hydraulic cylinder pressure parameters and motor rotating speed parameters;
the data extraction module is used for acquiring all the operation parameters, constructing the operation parameters into a training sample set, and calibrating the operation data in the training sample set into training samples;
the screening module is used for acquiring standard operation parameters, comparing the standard operation parameters with all training samples one by one, calibrating the training samples exceeding the standard operation parameters as abnormal samples, recording time nodes corresponding to the abnormal samples, calibrating the abnormal samples as the abnormal nodes, calculating the time length between two adjacent abnormal nodes to obtain an evaluation time length, comparing a standard evaluation period with the evaluation time length, screening out the evaluation time length longer than the standard evaluation period time length, and calibrating the evaluation time length as a training period;
the estimation module is used for acquiring all training samples in a training period, inputting the training samples into the trend estimation model to obtain the change trend rate of the laminating device, and calculating the estimated value of the laminating device under the current node by combining the change trend rate;
the alarm module is used for acquiring the current operation parameters of the laminating device, comparing the current operation parameters with the estimated value to obtain a deviation value, and judging whether the laminating device normally operates or not and whether an alarm signal is sent out or not according to the deviation value;
the early warning module is used for acquiring all deviation values of the laminating device in a normal operation state, substituting the deviation values into the fault prediction model to obtain deviation trend values of the laminating device, and judging whether the automatic laminating device has fault risks or not and whether an early warning signal is sent out or not according to the deviation trend values.
Specifically, when the electronic product auxiliary material is attached, the steps of feeding, correcting, pressing and the like are needed, a plurality of electrical equipment are needed for assistance in the period, and due to the fact that the electrical equipment is automatic equipment, when the electrical equipment is used, the attachment of the electronic product auxiliary material cannot be stably carried out under the condition that any electrical equipment runs, the normal working progress is influenced, and meanwhile batch damage of the electronic product auxiliary material can be caused The method comprises the steps of calculating depreciation and the like, wherein the depreciation and the depreciation rate are different for different devices, specifically, when a standard deviation trend threshold value is set, the setting is carried out according to the type and the type of the attaching device, the description is omitted, and if the deviation value exceeds the standard deviation trend threshold value, the early warning grade can be determined according to the deviation amount, so that different early warning signals are sent out, and workers can make different maintenance schemes.
In a preferred embodiment, after screening out the evaluation duration longer than the standard evaluation period duration, counting all the evaluation durations shorter than the standard evaluation period duration, and calibrating as an abnormal period;
acquiring all abnormal periods, and arranging according to the sequence of time nodes;
comparing the durations of adjacent abnormal periods to obtain an evaluation difference time;
acquiring a standard evaluation threshold, comparing the standard evaluation threshold with the evaluation difference, screening out the evaluation difference larger than the standard evaluation threshold, and calibrating the evaluation difference as an abnormal difference;
judging whether the head nodes and the tail nodes of the adjacent abnormal periods are connected when the abnormal difference corresponds to the abnormal difference;
if yes, judging that the laminating device has a risk of abnormal operation, and sending an early warning signal by an early warning module;
if not, the laminating device is judged to normally operate, and the early warning module does not act.
In this embodiment, it should be further understood that, after the abnormal period is determined, by setting the evaluation difference, it can be intuitively determined whether the time length of the abnormal period after the adjacent bit is greater than the time length of the abnormal period before the adjacent bit, and the calculation formula is as follows:
in, is greater than or equal to>
Represents a poor evaluation, is>
Represents an abnormal period next in time, and>
representing abnormal periods next to each other, judging based on a standard evaluation threshold in the process, setting the standard evaluation threshold to be 0, if the value is greater than 0 when the evaluation is poor, namely, indicating that faults of the laminating device occur more and more frequently, and calibrating the faults as abnormal differences, then screening out adjacent abnormal periods corresponding to the abnormal differences, judging whether the head and tail nodes of the adjacent abnormal periods are connected, if so, indicating that continuity exists between the connected abnormal periods, maintaining of the laminating device after the faults is not perfect, sending an early warning signal at the moment, and arranging a worker to perform comprehensive investigation, if not, indicating that the head and tail nodes of the adjacent abnormal periods are connected, indicating that the repairing of the laminating device after the faults is perfect, the laminating device can normally operate, and the abnormal periods next to each other are abnormalIn the case that the cycle is selected to be the last abnormal cycle, and the end node of the abnormal cycle is the current fault node, considering that the abnormal cycle is shortened, whether the fault is related to the last-time fault electrical equipment or not should be checked, so that the laminating equipment can stably operate for a long time.
In a preferred embodiment, the specific process of inputting the training samples into the trend estimation model to obtain the trend rate of the laminating device is as follows:
s1, obtaining training samples in a plurality of training periods, and calculating the average fluctuation quantity of all the training samples in each training period;
s2, acquiring a trend function from the trend estimation model;
and S3, inputting all the average fluctuation amounts into a trend function to obtain the change trend rate of the laminating device.
As mentioned in the above steps S1 to S3, when the average fluctuation amount of all training samples in each training period is obtained, the calculation formula is:
in, is greater than or equal to>
Indicates the fifth->
Average undulation amount of all training samples in a training period->
=1，2，3……，/>
Represents 1 to>
The value of the operating parameter of the middle training sample, ->
Representing the total number of all training samples, and inputting all average fluctuation quantities into the trend function：/>
In, is greater than or equal to>
Indicates the change trend rate of the bonding device>
Represents the total number of training cycles>
Represents 1 to>
The average amount of fluctuation of the training samples over the training period, wherein,
，/>
represents 1 to 5>
The duration of the training period.
In a preferred embodiment, after the trend rate of change is determined;
s4, acquiring previous operation parameters of the current node;
s5, obtaining a prediction function from the trend prediction model;
and S6, inputting the previous operation parameters and the change trend rate of the current node into the estimation function together to obtain the estimated value of the current node of the laminating device.
As described in the above steps S4-S6, after the previous operation parameter of the current node is obtained, the interval period of the data acquisition module is obtained and is input to the pre-estimation function together, where the pre-estimation function is:
in, is greater than or equal to>
Represents a pre-evaluated value for an operating parameter of the laminating device under the current node, and represents a value which is evaluated in advance for the operating parameter of the laminating device under the current node>
The acquisition interval time of the data acquisition module is represented, and for different electrical equipment, the acquisition interval time is different, and the acquisition interval time is specifically set according to actual requirements, and is not specifically limited.
In a preferred embodiment, the deviation value is a difference value between the current operation parameter and the estimated value, and when determining whether the laminating device is operating normally and whether an alarm signal is sent out according to the deviation value, the determining process is as follows:
acquiring a standard deviation threshold value and comparing the standard deviation threshold value with a deviation value;
if the deviation value is smaller than the standard deviation threshold value, judging that the laminating device normally operates;
if the deviation value is larger than or equal to the standard deviation threshold value, judging that the laminating device operates abnormally, stopping the operation of the laminating device at the moment, and sending an alarm signal.
In this embodiment, the standard deviation threshold is an initial preset value, which is set according to depreciation and daily loss of the laminating device and is only a judgment basis, which is not a key point in the present embodiment, and when the standard deviation threshold is compared with the deviation value, and the deviation value is greater than the standard deviation threshold, it indicates that the operation of the laminating device deviates from the expected loss, the operation of the laminating device has a certain risk, at this time, the operation of the laminating device should be stopped, and a worker is arranged to perform troubleshooting, so that the laminating device is paralyzed in the subsequent operation.
In a preferred embodiment, when calculating the deviation trend values, an objective function is obtained from the fault prediction model, and the deviation values are input into the objective function, wherein the deviation values input into the fault prediction model are all smaller than the standard deviation threshold.
In the above, the purpose of calculating the deviation tendency value is to judge whether there is a risk of failure in the operation of the bonding apparatus, so as to maintain the bonding apparatus before the failure occurs, and prevent excessive wear of the bonding apparatus, wherein,the objective function used to calculate the deviation trend values is:
in the formula (II)>
Represents a deviation trend value>
Indicates the total number of deviation values for the reference calculation, and>
represents 1 to 5>
A deviating trend value of->
And the average value of all deviation values is represented, wherein all deviation values participating in operation are smaller than a standard deviation threshold value, so that the accuracy of deviation trend value measurement is ensured, and the value is preferably a deviation trend value with continuity.
In a preferred embodiment, the process of determining whether the automatic bonding device has a failure risk and sends out the warning signal according to the deviation trend value is as follows:
acquiring a standard deviation trend threshold value, and comparing the standard deviation trend threshold value with a deviation trend value;
if the standard deviation trend threshold is smaller than the deviation trend value, judging that the laminating device has a fault risk, stopping the operation of the laminating device, and sending out an early warning signal;
and if the standard deviation trend threshold value is larger than or equal to the deviation trend value, judging that the laminating device normally operates.
As described in the above determination process, the operation of the laminating apparatus is not continuously and stably performed, and due to various factors in the production, such as the increase and decrease of the output power of the electrical apparatus, the deviation of the operation parameter has a certain fluctuation, in the present embodiment, a standard deviation trend threshold is set for defining, for example, if the standard deviation trend threshold is 10%, it indicates that the fluctuation of the deviation value within 0% to 10% is acceptable by the laminating apparatus, but if the deviation value exceeds 10%, it indicates that there is a significant trend of deviation to the fault, and then a corresponding warning signal is sent, and meanwhile, the shutdown maintenance is performed.
In a preferred embodiment, before the early warning signal is sent out, the early warning level of the early warning signal is judged according to the deviation amount of the deviation trend value;
wherein the evaluation interval of the early warning grade is [ a, b ], [ b, c) and [ c, d ];
when the deviation of the deviation trend value belongs to the evaluation interval [ a, b ], the laminating device sends out a primary early warning signal;
when the deviation amount of the deviation trend value belongs to the evaluation interval [ b, c), the laminating device sends out a secondary early warning signal;
and when the deviation amount of the deviation trend value belongs to the evaluation interval [ c, d ], the laminating device sends out a three-level early warning signal.
In this embodiment, when it is determined that the deviation trend value is higher than the standard deviation trend threshold, the embodiment further analyzes the deviation amount, the manual standard deviation trend threshold is defined by 10%, and the deviation amount does not rise by 30%, the level of the early warning signal is raised by one level, and the level of the three-level early warning signal is the highest, so that a worker can make different obstacle removal and maintenance schemes according to early warning signals of different levels.
Further, the priority of the alarm signal is higher than that of the early-warning signal, the alarm signal corresponds to the condition that the fault has occurred, and the early-warning signal corresponds to the condition that the fault has not occurred, so that the priority of the alarm signal is higher than that of the early-warning signal during setting, that is, the early-warning signal does not need to be sent out under the condition that the alarm signal is sent out.
The invention also provides a fault early warning terminal for an automatic electronic product accessory laminating device, which comprises:
at least one processor;
and a memory communicatively coupled to the at least one processor;
the storage stores a computer program which can be executed by at least one processor, and the computer program is executed by the at least one processor, so that the at least one processor can execute the fault early warning system for the automatic electronic product auxiliary material laminating device.
It will be appreciated by those skilled in the art that the malfunction alerting terminal of the present invention can be specially designed and manufactured for the required purposes, or can comprise a known device in a general-purpose computer. These devices have stored therein computer programs or applications that are selectively activated or reconfigured. Such a computer program may be stored in a device (e.g., computer) readable medium, including, but not limited to, any type of disk including floppy disks, hard disks, optical disks, CD-ROMs, and magnetic-optical disks, ROMs (Read-Only memories), RAMs (Random access memories), EPROMs (Erasable Programmable Read-Only memories), EEPROMs (Electrically Erasable Programmable Read-Only memories), flash memories, magnetic cards, or optical cards, or any type of media suitable for storing electronic instructions, and each coupled to a bus. That is, a readable medium includes any medium that stores or transmits information in a form readable by a device (e.g., a computer).
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, apparatus, article, or method. Without further limitation, an element defined by the phrases "comprising a," "8230," "8230," or "comprising" does not exclude the presence of another identical element in a process, apparatus, article, or method comprising the element.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that those skilled in the art can make various improvements and modifications without departing from the principle of the present invention, and these improvements and modifications should also be construed as the protection scope of the present invention. Structures, devices, and methods of operation not specifically described or illustrated herein are not specifically illustrated or described, but are instead contemplated to be practiced in the art by those skilled in the art.
Claims (10)
1. The utility model provides an automatic laminating of electronic product auxiliary material trouble early warning system for device, includes data acquisition module, data extraction module, screening module, predicts module, alarm module and early warning module, its characterized in that:
the data acquisition module is used for acquiring operation parameters of the laminating device, wherein the operation parameters at least comprise hydraulic cylinder pressure parameters and motor rotating speed parameters;
the data extraction module is used for acquiring all the operation parameters, constructing the operation parameters into a training sample set, and calibrating the operation data in the training sample set into training samples;
the screening module is used for acquiring standard operation parameters, comparing the standard operation parameters with all training samples one by one, calibrating the training samples exceeding the standard operation parameters as abnormal samples, recording time nodes corresponding to the abnormal samples, calibrating the abnormal samples as abnormal nodes, calculating the time length between two adjacent abnormal nodes to obtain an evaluation time length, comparing a standard evaluation period with the evaluation time length, screening out the evaluation time length longer than the standard evaluation period time length, and calibrating the evaluation time length as a training period;
the estimation module is used for acquiring all training samples in the training period, inputting the training samples into a trend estimation model to obtain the change trend rate of the laminating device, and calculating the estimated value of the laminating device under the current node by combining the change trend rate;
the alarm module is used for acquiring the current operation parameters of the laminating device, comparing the current operation parameters with the estimated value to obtain a deviation value, and judging whether the laminating device normally operates or not and whether an alarm signal is sent out or not according to the deviation value;
the early warning module is used for obtaining all deviation values of the laminating device in a normal operation state, substituting the deviation values into the fault prediction model to obtain deviation trend values of the laminating device, and judging whether the automatic laminating device has fault risks or not and whether an early warning signal is sent out or not according to the deviation trend values.
2. The fault early warning system for the automatic laminating device of electronic product auxiliary materials according to claim 1, characterized in that: after screening out the evaluation duration longer than the standard evaluation period duration, counting all the evaluation durations shorter than the standard evaluation period duration, and calibrating as an abnormal period;
acquiring all abnormal periods, and arranging according to the sequence of time nodes;
comparing the durations of adjacent abnormal periods to obtain an evaluation difference time;
obtaining a standard evaluation threshold, comparing the standard evaluation threshold with the evaluation difference, screening out the evaluation difference larger than the standard evaluation threshold, and calibrating the evaluation difference as an abnormal difference;
judging whether the head nodes and the tail nodes of the adjacent abnormal periods are connected when the abnormal difference corresponds to the abnormal difference;
if yes, judging that the laminating device has a risk of abnormal operation, and sending an early warning signal by the early warning module;
if not, judging that the laminating device normally operates, and not acting the early warning module.
3. The fault early warning system for the automatic laminating device of electronic product auxiliary materials according to claim 1, characterized in that: the specific process of inputting the training sample into a trend estimation model to obtain the change trend rate of the laminating device is as follows:
acquiring a plurality of training samples in the training period, and calculating the average fluctuation quantity of all the training samples in each training period;
acquiring a trend function from a trend estimation model;
and inputting all the average fluctuation amounts into a trend function to obtain the change trend rate of the laminating device.
4. The fault early warning system for the automatic attaching device of the auxiliary materials of the electronic products as claimed in claim 3, wherein: after the determination of the rate of change trend;
acquiring previous operation parameters of a current node;
acquiring a prediction function from the trend prediction model;
and inputting the previous operation parameters and the change trend rate of the current node into an estimation function together to obtain an estimated value of the current node of the laminating device.
5. The fault early warning system for the automatic attaching device of the auxiliary materials of the electronic products as claimed in claim 4, wherein: the deviation value is a difference value between the current operation parameter and the estimated value, and when judging whether the laminating device normally operates and whether an alarm signal is sent out according to the deviation value, the judging process is as follows:
acquiring a standard deviation threshold value and comparing the standard deviation threshold value with the deviation value;
if the deviation value is smaller than a standard deviation threshold value, judging that the laminating device normally operates;
if the deviation value is larger than or equal to the standard deviation threshold value, judging that the laminating device is abnormal in operation, stopping the operation of the laminating device at the moment, and sending an alarm signal.
6. The fault early warning system for the automatic laminating device of electronic product auxiliary materials according to claim 1, characterized in that: and when the deviation trend value is calculated, acquiring an objective function from the fault prediction model, and inputting the deviation value into the objective function, wherein the deviation values input into the fault prediction model are all smaller than a standard deviation threshold value.
7. The fault early warning system for the automatic attaching device of the auxiliary materials of the electronic products as claimed in claim 6, wherein: the process of judging whether the automatic laminating device has fault risk or not and whether an early warning signal is sent out or not according to the deviation trend value is as follows:
acquiring a standard deviation trend threshold value, and comparing the standard deviation trend threshold value with the deviation trend value;
if the standard deviation trend threshold is smaller than the deviation trend value, judging that the laminating device has a fault risk, stopping the operation of the laminating device and sending out an early warning signal;
and if the standard deviation trend threshold value is larger than or equal to the deviation trend value, judging that the laminating device normally operates.
8. The fault early warning system for the automatic bonding device of electronic product auxiliary materials according to claim 7, characterized in that: before the early warning signal is sent out, judging the early warning level of the early warning signal according to the deviation of the deviation trend value;
wherein the evaluation interval of the early warning grade is [ a, b ], [ b, c) and [ c, d ];
when the deviation amount of the deviation trend value belongs to the evaluation interval [ a, b ], the laminating device sends a primary early warning signal;
when the deviation amount of the deviation trend value belongs to the evaluation interval [ b, c), the laminating device sends out a secondary early warning signal;
and when the deviation amount of the deviation trend value belongs to the evaluation interval [ c, d ], the laminating device sends out a three-level early warning signal.
9. The fault early warning system for the automatic attaching device of the auxiliary materials of the electronic products as claimed in claim 1, which is characterized in that: the priority of the alarm signal is higher than that of the early warning signal.
10. The utility model provides an automatic laminating of electronic product auxiliary material trouble early warning terminal for device which characterized in that: the method comprises the following steps:
at least one processor;
and a memory communicatively coupled to the at least one processor;
wherein the memory stores a computer program executable by the at least one processor, the computer program being executable by the at least one processor to enable the at least one processor to execute the malfunction early warning system for an electronic product accessory automatic bonding apparatus according to any one of claims 1 to 8.
Priority Applications (1)
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| CN116302848B (en) * | 2023-05-19 | 2023-09-01 | 杭州安脉盛智能技术有限公司 | Detection method and device for bias of evaluation value, electronic equipment and medium |
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| CN117113108A (en) * | 2023-07-19 | 2023-11-24 | 大唐保定热电厂 | Power plant boiler operation fault adjustment method and system based on data fusion |
| CN117113260B (en) * | 2023-10-19 | 2024-01-30 | 深圳市磐锋精密技术有限公司 | Intelligent laminating equipment fault early warning system based on data analysis |
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