CN115712268A - 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
- Publication number
- CN115712268A CN115712268A CN202211660232.0A CN202211660232A CN115712268A CN 115712268 A CN115712268 A CN 115712268A CN 202211660232 A CN202211660232 A CN 202211660232A CN 115712268 A CN115712268 A CN 115712268A
- Authority
- CN
- China
- Prior art keywords
- deviation
- early warning
- laminating device
- trend
- value
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/30—Computing systems specially adapted for manufacturing
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 production process of electronic products, a plurality of electrical equipment are needed to assist, for example, a conveying device for conveying materials, a clamping device for clamping materials, a laminating 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 the equipment runs according to a set program, if faults occur, products being processed are likely to be damaged, and under severe conditions, the electronic products can be damaged in batches, so that a real-time fault monitoring and early warning system is needed in the running process of the equipment, and the condition that the electronic products are damaged in the adhering process of auxiliary materials is avoided.
Traditional automatic laminating of electronic product auxiliary material is trouble early warning system for device often all 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, based on this, this scheme provides one kind and 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 accessory laminating device, which can send out an early warning signal before the laminating device breaks down, avoid the damage of an electronic product in the processing process and reduce unnecessary loss of enterprises or factories.
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 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 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 at 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 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.
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 into an estimation function together to obtain an estimated value of the current node of the laminating device.
In a preferred scheme, the deviation value is a difference value between the current operation parameter and a predicted value, and when judging whether the bonding 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;
and if the deviation value is greater than or equal to a standard deviation threshold value, judging that the operation of the laminating device is abnormal, 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.
In a preferred scheme, the process of judging whether the automatic laminating device has a fault 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 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 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.
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 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 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 a corresponding alarm signal when the laminating device fails, but also measure and calculate the deviation value of the laminating device, and judge whether the laminating device exceeds a standard deviation trend threshold value by combining a fault prediction model, so that an early warning signal can be sent out according to the deviation trend of the running state before the failure occurs, and the laminating device still runs normally under the state, thereby avoiding the damage of the electronic product in the processing process, then stopping the running laminating device, and carrying out fault removal treatment, thereby reducing the 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
In order to make the aforementioned objects, features and advantages of the present invention more comprehensible, embodiments accompanying figures of the present invention 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, however, the present invention may be practiced otherwise than as specifically described herein, and it will be appreciated by those skilled in the art that the present invention may be practiced without departing from the spirit and scope of the present invention and that the present invention is not limited by the specific embodiments disclosed below.
Furthermore, the references herein to "one embodiment" or "an embodiment" refer to a particular feature, structure, or characteristic that may be included in at least one implementation of the present 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 for convenience of illustration, the cross-sectional views illustrating the device structures are not enlarged partially according to the general scale when describing the embodiments of the present invention, and the drawings are only exemplary, which should not limit 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 that the standard deviation trend threshold value is set, the standard deviation trend threshold value is set according to the loss and the depreciation rate of different devices, the standard deviation trend threshold value is set according to the loss and the depreciation rate of the different devices, the standard deviation trend threshold value is not repeated in the text, 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 time lengths of adjacent abnormal periods to obtain evaluation time difference;
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 the 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 time 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:T difference (D) = T Front side - T Rear end In the formula (I), wherein,T difference between When it is indicated that the evaluation is poor,T difference (D) Indicating the cycle of the exception that is next to the previous bit,T rear end Representing the abnormal period next to the level, judging based on the standard evaluation threshold, setting the standard evaluation threshold to be 0, if the evaluation is poor, the value is greater than 0, namely, the faults of the laminating device are more and more frequent, and when the faults are marked as abnormal differences, then screening out the adjacent abnormal period corresponding to the abnormal differences, and judging the first abnormal periodWhether tail nodes are connected or not, if yes, continuity exists between the connected abnormal periods, maintenance of the laminating equipment after the laminating equipment fails is not perfect, an early warning signal is sent out, and workers are arranged to carry out comprehensive examination, if yes, the head nodes and the tail nodes of the adjacent abnormal periods are not connected, maintenance of the laminating equipment after the laminating equipment fails is perfect, the laminating equipment can normally operate, the abnormal period next to the last abnormal period is selected, the ending node of the abnormal period is the current fault node, under the condition, the abnormal period is considered to be shortened, whether the fault is related to the electrical equipment which fails last time or not is examined, and 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 amount 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 the formula (I), the reaction is carried out,
is shown asaThe average fluctuation amount of all training samples in a training period,a =1，2，3……，
is 1 &nThe values of the operating parameters of the middle training sample,nrepresenting the total number of all training samples, and then inputting all average fluctuation quantities to the trend function:
in the formula (I), wherein,Qindicates the rate of change trend of the attaching device,mwhich represents the total number of training cycles,
is 1 &mThe average amount of fluctuation of the training samples over the training period, wherein,m=a， S m is 1 &mThe 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 into an estimation function together to obtain an estimated value of the current node of the laminating device.
As described in the foregoing steps S4 to 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 into the prediction function together, where the prediction function is:
in the formula (I), wherein,Y b representing the estimated value of the operation parameter of the laminating device under the current node,tthe 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 bonding apparatus 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 is abnormal in operation, 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 value, 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 value.
In the foregoing, the purpose of calculating the deviation trend value is to determine whether there is a risk of failure in the operation of the laminating apparatus, so as to maintain the laminating apparatus before the failure occurs, and prevent the laminating apparatus from being excessively worn, wherein an objective function for calculating the deviation trend value is:
in the formula (I), the reaction is carried out,Ra value indicating the tendency of the deviation is indicated,Nindicates the total number of deviation values for the parameter operation,P k is 1 &NThe deviation-tendency value in (1) is,
and the average value of all deviation values is represented, wherein all deviation values participating in the operation are smaller than the standard deviation threshold value, so that the accuracy of calculating the deviation trend value is ensured, and the deviation trend value is preferably continuous.
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, judging the early warning level of the early warning signal 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 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 value, the embodiment further analyzes the deviation amount, the human standard deviation trend threshold value is defined by 10%, and the deviation amount does not rise by 30%, the level of the early warning signal is increased by one level, and the level of the three-level early warning signal is the highest, so that a worker can make different obstacle removing and maintaining 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 when the alarm signal is sent out.
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 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, readable media 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, for those skilled in the art, various modifications and amendments can be made without departing from the principle of the present invention, and these modifications and amendments should also be considered as the protection scope of the present invention. Structures, devices, and methods of operation not specifically described or illustrated herein are generally practiced in the art without specific recitation or limitation.
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 attaching device of the auxiliary materials of the electronic products as claimed in claim 1, which is characterized in that: after screening out the evaluation time length longer than the standard evaluation period time length, counting all the evaluation time lengths shorter than the standard evaluation period time length, and calibrating the evaluation time lengths 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.
3. 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: inputting the training samples into a trend estimation model, wherein the specific process of obtaining the change 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.
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 change trend rate 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 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 laminating device of electronic product auxiliary materials according to claim 4, characterized in that: the deviation value is the 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;
and if the deviation value is greater than or equal to a standard deviation threshold value, judging that the operation of the laminating device is abnormal, 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 risks and whether an early warning signal is sent out 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 laminating 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 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 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 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 system of any one of claims 1 to 8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211660232.0A CN115712268B (en) | 2022-12-23 | 2022-12-23 | Fault early warning system for automatic electronic product auxiliary material laminating device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211660232.0A CN115712268B (en) | 2022-12-23 | 2022-12-23 | Fault early warning system for automatic electronic product auxiliary material laminating device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115712268A true CN115712268A (en) | 2023-02-24 |
| CN115712268B CN115712268B (en) | 2023-04-14 |
Family
ID=85236077
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211660232.0A Active CN115712268B (en) | 2022-12-23 | 2022-12-23 | Fault early warning system for automatic electronic product auxiliary material laminating device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115712268B (en) |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116020076A (en) * | 2023-03-30 | 2023-04-28 | 飞龙消防技术有限公司 | Fire extinguishing device remote monitoring system and method based on fire safety |
| CN116302848A (en) * | 2023-05-19 | 2023-06-23 | 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 |
| CN116340112A (en) * | 2023-05-29 | 2023-06-27 | 南京优倍利科技有限公司 | Equipment state monitoring system based on big data analysis and edge calculation |
| 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 |
| CN117113260A (en) * | 2023-10-19 | 2023-11-24 | 深圳市磐锋精密技术有限公司 | Intelligent laminating equipment fault early warning system based on data analysis |
| CN117420811A (en) * | 2023-12-19 | 2024-01-19 | 武汉佰思杰科技有限公司 | Production line quality monitoring method and system for automatic production |
| CN117719385B (en) * | 2024-02-18 | 2024-05-03 | 弘安天启(南京)科技有限公司 | Intelligent charging pile control system and method |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105046370A (en) * | 2015-08-18 | 2015-11-11 | 国电南瑞科技股份有限公司 | Four-line one-storehouse spare part inventory prediction system and establishing method thereof |
| CN108958180A (en) * | 2018-06-21 | 2018-12-07 | 苏州微感网络科技有限公司 | Production managing and control system applied to surface mounting technology |
| JP2019021305A (en) * | 2017-07-14 | 2019-02-07 | 株式会社明電舎 | Monitoring system |
| CN110298455A (en) * | 2019-06-28 | 2019-10-01 | 西安因联信息科技有限公司 | A kind of mechanical equipment fault intelligent early-warning method based on multivariable estimation prediction |
| CN111882833A (en) * | 2020-07-21 | 2020-11-03 | 华润电力唐山丰润有限公司 | Equipment fault early warning method, device, equipment and medium based on outlier parameters |
| CN114704538A (en) * | 2022-03-24 | 2022-07-05 | 深圳市创立宏科技有限公司 | Automatic laminating device of electronic product auxiliary material |
-
2022
- 2022-12-23 CN CN202211660232.0A patent/CN115712268B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105046370A (en) * | 2015-08-18 | 2015-11-11 | 国电南瑞科技股份有限公司 | Four-line one-storehouse spare part inventory prediction system and establishing method thereof |
| JP2019021305A (en) * | 2017-07-14 | 2019-02-07 | 株式会社明電舎 | Monitoring system |
| CN108958180A (en) * | 2018-06-21 | 2018-12-07 | 苏州微感网络科技有限公司 | Production managing and control system applied to surface mounting technology |
| CN110298455A (en) * | 2019-06-28 | 2019-10-01 | 西安因联信息科技有限公司 | A kind of mechanical equipment fault intelligent early-warning method based on multivariable estimation prediction |
| CN111882833A (en) * | 2020-07-21 | 2020-11-03 | 华润电力唐山丰润有限公司 | Equipment fault early warning method, device, equipment and medium based on outlier parameters |
| CN114704538A (en) * | 2022-03-24 | 2022-07-05 | 深圳市创立宏科技有限公司 | Automatic laminating device of electronic product auxiliary material |
Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116020076A (en) * | 2023-03-30 | 2023-04-28 | 飞龙消防技术有限公司 | Fire extinguishing device remote monitoring system and method based on fire safety |
| CN116302848A (en) * | 2023-05-19 | 2023-06-23 | 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 |
| 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 |
| CN116340112A (en) * | 2023-05-29 | 2023-06-27 | 南京优倍利科技有限公司 | Equipment state monitoring system based on big data analysis and edge calculation |
| CN116340112B (en) * | 2023-05-29 | 2023-07-21 | 南京优倍利科技有限公司 | Equipment state monitoring system based on big data analysis and edge calculation |
| 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 |
| CN117113260A (en) * | 2023-10-19 | 2023-11-24 | 深圳市磐锋精密技术有限公司 | Intelligent laminating equipment fault early warning system based on data analysis |
| 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 |
| CN117420811A (en) * | 2023-12-19 | 2024-01-19 | 武汉佰思杰科技有限公司 | Production line quality monitoring method and system for automatic production |
| CN117420811B (en) * | 2023-12-19 | 2024-03-08 | 武汉佰思杰科技有限公司 | Production line quality monitoring method and system for automatic production |
| CN117719385B (en) * | 2024-02-18 | 2024-05-03 | 弘安天启(南京)科技有限公司 | Intelligent charging pile control system and method |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115712268B (en) | 2023-04-14 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN115712268B (en) | Fault early warning system for automatic electronic product auxiliary material laminating device | |
| CN110596486B (en) | Intelligent early warning operation and maintenance method and system for charging pile | |
| CN108638128B (en) | Real-time abnormity monitoring method and system of industrial robot | |
| CN116316613B (en) | Power equipment operation monitoring method, system, electronic equipment and storage medium | |
| CN110920009B (en) | State determination device and state determination method | |
| CN110057406B (en) | Multi-scale self-adaptive mechanical equipment trend early warning method | |
| CN113658414B (en) | Mine equipment fault early warning method and device, terminal equipment and storage medium | |
| CN116645010B (en) | Chemical industry safety in production inspection system | |
| CN111324083A (en) | Real-time monitoring and early warning method and system for key components of mechanical equipment | |
| US9669479B2 (en) | Data collection system for electric discharge machines | |
| CN112304446A (en) | Electric power equipment alarm processing method and device | |
| CN111865680A (en) | Factory production and processing equipment fault early warning system | |
| CN111531830A (en) | State determination device and state determination method | |
| CN110726936A (en) | Method for judging and processing voltage sampling fault and voltage extreme value fault | |
| CN113955149B (en) | Health diagnosis method and device for motor system | |
| CN106483457A (en) | A kind of catalyst fault early warning method and prior-warning device | |
| CN115422504A (en) | Power distribution equipment fault risk identification method and device | |
| CN114706347A (en) | Fault diagnosis system and method for electrolytic machining tool | |
| CN116412087A (en) | Abnormality detection method and related device for wind generating set | |
| CN210323201U (en) | Ground resistance monitoring system | |
| CN113341332A (en) | Battery thermal runaway early warning method and device, operation machine and electronic equipment | |
| CN112558539A (en) | Energy management system based on panoramic perception, monitoring method and air conditioner | |
| JP7184997B2 (en) | State determination device and state determination method | |
| CN116323038A (en) | State determination device and state determination method | |
| CN115509177B (en) | Method, device, equipment and medium for monitoring abnormality in part machining process |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |