Equipment fault inspection system based on automatic assembly line

Abstract

The invention discloses an equipment fault inspection system based on an automatic assembly line, relates to the technical field of equipment inspection, and solves the problem of large precision deviation of an original judgment mode. The method comprises the following steps: identifying related associated items with relatively large features in corresponding equipment, determining a main feature item from a plurality of associated items, locking a feature interval associated with the corresponding main feature item based on related feature data of the main feature item, and subsequently, confirming the associated intervals of other associated items one by one based on the confirmed feature interval. Based on the corresponding feature interval confirmed in the recent period, the accuracy of the monitoring data can be further guaranteed, a more accurate feature determination effect is achieved, and the determination accuracy of the abnormal equipment can be fully guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of equipment inspection, and in particular to an equipment fault inspection system based on an automated assembly line. Background Art

[0002] An automated assembly line is a process that connects a series of automated equipment and devices in a predetermined process sequence to form a continuous production line.

[0003] The application with publication number CN114721849A discloses a machine equipment fault inspection system, including an inspection device and a server. The inspection device includes a sensing module, a processing module and a transmission module. The sensing module senses the movement of the parts of the machine equipment to generate a sensing signal. The processing module is electrically connected to the sensing module, and determines whether a fault signal is generated according to the sensing signal. The transmission module is electrically connected to the processing module and transmits the fault signal. The server includes a communication unit, a processing unit and a storage unit. The communication unit receives the fault signal. The processing unit is electrically connected to the communication unit, and generates a part fault code signal according to the fault signal. The storage unit is electrically connected to the processing unit and the communication unit, and stores multiple fault analysis reports of the machine equipment; the multiple fault analysis reports correspond to the part fault code signal, and when the processing unit generates the part fault code signal, the fault analysis report is transmitted via the communication unit.

[0004] For the associated equipment in the automated assembly line, the monitoring parameters associated with the associated equipment are identified, and then whether the associated equipment is abnormal is determined based on the monitoring parameters, so as to make relevant judgments on the abnormal equipment. However, the original judgment method does not make a comprehensive judgment based on the relevant life reduction process of each equipment. The reference standards are all the original standards, which are not the most suitable standards for the corresponding equipment. This will cause a large deviation in the accuracy of the judgment of abnormal equipment and fail to achieve a more accurate abnormal equipment judgment effect. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides an equipment fault inspection system based on an automated assembly line, which solves the problem that the original determination method has a large accuracy deviation.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: an equipment fault detection system based on an automated assembly line, comprising:

[0007] The equipment feature confirmation end performs relevant confirmation of the feature intervals of the related equipment associated in the automated assembly line. Based on the historical cycle data of the related equipment, the main feature interval of the main feature data of the related equipment is confirmed first, and then based on the time characteristics of the feature interval of the main feature data, the associated feature intervals of other associated items are confirmed in turn. The specific method is as follows:

[0008] Based on the related equipment associated with this automated assembly line, the main feature items belonging to this related equipment are confirmed, a group of cycle data closest to the current moment is determined from the historical cycle data, and the main feature data associated with the main feature items are confirmed from the cycle data. The historical cycle data is the historically collected operating data of all associated items of this related equipment, and each historical cycle is a preset cycle;

[0009] Based on the confirmed main feature data and the timeline associated with the main feature data, a main feature data change curve is generated, feature confirmation is performed on the main feature data change curve, the maximum value and the minimum value of the main feature data change curve are locked, and a highest standard line and a lowest standard line passing through the maximum value and the minimum value and perpendicular to the vertical coordinate axis are constructed, so that the highest standard line and the lowest standard line move toward each other, and the speed of their movement toward each other is inconsistent, and variance processing is performed on a plurality of main feature data contained in the highest standard line and the lowest standard line in each movement process, and the variance value F is determined;

[0010] The moving process with F≤Y1 is calibrated as the standard process, where Y1 is the preset value, and the standard process with the maximum variance value F is calibrated as the selection process. Based on the maximum and minimum values ​​of several main feature data associated with this selection process, the main feature interval of the main feature item of the relevant equipment is confirmed, and the time line associated with this selection process is calibrated as the selection time line;

[0011] No calibration is performed on the movement process of F>Y1;

[0012] If there is no standard process with F≤Y1, then an error signal can be directly generated for display;

[0013] Based on the selected timeline, the data of other associated items of the related device are confirmed in the same interval determination method, and the associated feature interval of the corresponding associated item is locked;

[0014] The real-time monitoring end monitors the values ​​of the related equipment in the automated assembly line, and transmits the values ​​of different related items monitored in real time to the abnormality assessment end;

[0015] The abnormality assessment end confirms whether the values ​​monitored by the relevant equipment in real time are abnormal based on the main characteristic interval and the associated characteristic interval determined by the relevant equipment, and performs abnormality calibration on the relevant equipment based on the specific results of the real-time confirmation. The specific method is as follows:

[0016] The main feature interval and the associated feature interval associated with the relevant equipment are both proposed as standard intervals, and the relevant values ​​S monitored by the corresponding associated items of the relevant equipment at the corresponding time are i Check with the standard interval, where i represents different related terms. If Si ∈ standard interval, then the eigenvalue T determined by this association item at the current moment i Calibrated to 0, if Standard interval, then determine the relevant value S i Difference from the standard interval: If S i < standard interval, then the difference = minimum value of the standard interval - S i , if S i > standard interval, then the difference = S i -The maximum value of the standard interval, the determined difference is used as the characteristic value T determined by this association item at the current moment i ;

[0017] Different eigenvalues ​​T determined based on different associated items at the current moment i , i=1, 2, ..., n, where n represents the total number of items associated with the corresponding equipment, using Determine its rating value PD i , where C i The fixed factor set for the corresponding correlation item;

[0018] The assessment value PD i Compare with the preset value Y2: If PD i >Y2, mark the corresponding related equipment as abnormal equipment, and evaluate whether the equipment subsequently associated with this abnormal equipment is synchronously abnormal within 5 minutes based on this automated assembly line. If the synchronization is abnormal, the equipment with synchronization abnormality and this abnormal equipment are marked as linkage abnormal equipment. If the synchronization is not abnormal, the determined abnormal equipment number is directly displayed through the display terminal. This linkage abnormal equipment only includes two groups of abnormal equipment. However, when there are three groups of abnormal equipment with synchronization abnormality, two groups of linkage abnormal equipment will be generated.

[0019] If PD i ≤Y2, no calibration is performed;

[0020] The linkage device confirmation end determines the initial abnormal device of the linkage abnormal device for the confirmed linkage abnormal device, confirms the abnormal item of the initial abnormal device, identifies whether the abnormal item generated by the subsequent abnormal device is consistent with the abnormal item generated by the initial abnormal device, and evaluates whether such linkage abnormal device is linkage abnormal or single abnormal based on the identification result. The specific method is as follows:

[0021] Based on this automated pipeline, the initial abnormal device of this linkage abnormal device is determined, and based on the abnormal confirmation process of the initial abnormal device, the abnormal item belonging to this initial abnormal device is identified. The abnormal item is The associated terms of the standard interval;

[0022] Identify other abnormal devices following the initial abnormal device from the linked abnormal devices, and identify whether the abnormal items generated by other abnormal devices are consistent with the abnormal items of the initial abnormal device:

[0023] If they are consistent, the linkage abnormal device is marked as linkage abnormal, and a linkage abnormal signal is generated and displayed through the display terminal;

[0024] If the abnormal items generated by other abnormal devices are inconsistent with the abnormal items of the initial abnormal device, it means that the abnormal devices associated with this linkage abnormal device are all single abnormal situations, and they are directly displayed through the display terminal.

[0025] The present invention provides an equipment fault detection system based on an automated assembly line. Compared with the prior art, it has the following beneficial effects:

[0026] The present invention identifies the relevant associated items with greater characteristics of the corresponding equipment in the historical cycle data of each different equipment in the pipeline, and then determines the main characteristic item from a number of associated items, and then locks the characteristic interval associated with the corresponding main characteristic item based on the relevant characteristic data of the main characteristic item. Subsequently, based on the confirmed characteristic interval, the associated intervals of other associated items are confirmed one by one. Based on the corresponding characteristic interval confirmed in the most recent cycle, the accuracy of the monitoring data can be further guaranteed to achieve a more accurate feature determination effect, so that the accuracy of determining abnormal equipment can be fully guaranteed;

[0027] Based on the monitoring data generated during the actual monitoring process of each device, identify whether the corresponding device is in an abnormal state. Based on the specific identification and monitoring results of multiple related items, lock the abnormal device. Then, based on the related linkage abnormal process of multiple abnormal devices, lock the linkage abnormal device, and based on the specific identification and processing results, make relevant displays to facilitate relevant operators to perform timely maintenance, so as to achieve better equipment maintenance and repair effects. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 It is a schematic diagram of the principle framework of the present invention;

[0029] Figure 2 It is a schematic diagram for determining abnormal equipment of the present invention. DETAILED DESCRIPTION

[0030] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0031] First embodiment

[0032] See also Figure 1 , the present application provides an equipment fault inspection system based on an automated assembly line, comprising an equipment feature confirmation terminal, an abnormality assessment terminal, a real-time monitoring terminal, a linkage equipment confirmation terminal and a display terminal, and the real-time monitoring terminal is electrically connected to an input node of the abnormality assessment terminal, wherein the abnormality assessment terminal is electrically connected to an input node of the linkage equipment confirmation terminal or a display terminal respectively, and the linkage equipment confirmation terminal is electrically connected to an input node of the display terminal;

[0033] Among them, the equipment feature confirmation end performs relevant confirmation of the feature interval of the related equipment associated in the automated assembly line. Based on the historical cycle data of the related equipment, the main feature interval of the main feature data of the related equipment is confirmed first, and then based on the time characteristics of the feature interval of the main feature data, the associated feature intervals of other related items are confirmed in turn. Specifically, in an automated assembly line, there are several related equipment in operation. When the related equipment is in operation, there are corresponding data features. Based on the corresponding data features, the feature interval can be confirmed and analyzed, and the data features of each related equipment can be confirmed. Subsequently, the operating status of such equipment is monitored based on the numerical features of such data features to identify whether such equipment is in normal operation. The specific method for confirming the feature interval of the related equipment is as follows:

[0034] Based on the related equipment associated with this automated assembly line, confirm the main feature items belonging to this related equipment. The main feature items have been marked in advance by relevant personnel and can be understood as relevant energy features with characteristic significance such as voltage input value or energy input value of the corresponding equipment. Determine a set of cycle data closest to the current moment from the historical cycle data, and confirm the main feature data associated with the main feature items from this cycle data. The historical cycle data is the operating data of all related items of this related equipment collected in the past, and each historical cycle is a preset cycle, generally taking a value of 24h;

[0035] Based on the confirmed main feature data and the timeline associated with the main feature data, a main feature data change curve is generated (the horizontal coordinate axis of this curve is the timeline, but the vertical coordinate axis is the corresponding data parameter), the main feature data change curve is feature confirmed, the maximum value and the minimum value of this main feature data change curve are locked, and the highest standard line and the lowest standard line that pass through the maximum value and the minimum value and are perpendicular to the vertical coordinate axis are constructed, the value corresponding to the highest standard line is consistent with the maximum value, and the value corresponding to the lowest standard line is consistent with the minimum value, so that the highest standard line and the lowest standard line move towards each other (that is, approach each other), and the speed of their movement towards each other is inconsistent, and the variance processing is performed on a number of main feature data contained in the highest standard line and the lowest standard line in each movement process, and the variance value F is determined;

[0036] The moving process of F≤Y1 is calibrated as the standard process, where Y1 is a preset value, and its specific value is determined by the operator based on experience. The standard process with the maximum variance value F is calibrated as the selection process. Based on the maximum and minimum values ​​of several main feature data associated with this selection process, the main feature interval of the main feature item of the relevant equipment is confirmed, and the timeline associated with this selection process is calibrated as the selection timeline. Here, the moving process of F>Y1 is not calibrated. If there is no standard process of F≤Y1, an error signal is directly generated for display, and the relevant operator intervenes;

[0037] Based on this selected timeline, the same interval determination method is used to confirm the interval of the data of other related items of this related equipment, and the associated feature interval of the corresponding associated item is locked. Specifically, the same interval determination method here is the corresponding determination method when the main feature interval is determined, and a change curve of the associated data of the corresponding associated item is generated. Based on the maximum and minimum values ​​of the corresponding change curve, the relevant standard line is confirmed, and then by moving the relevant standard line and variance confirmation, the feature interval with the most obvious numerical characteristics is locked, and the corresponding associated feature interval is confirmed in this way.

[0038] Because the service life of each different device will change during use, in order to achieve a more accurate fault judgment process, it is necessary to confirm the relevant feature intervals of each device one by one. Then, based on the corresponding feature intervals confirmed in the most recent period, the accuracy of the monitoring data can be further guaranteed to achieve a more accurate feature determination effect, so that the accuracy of determining abnormal equipment can be fully guaranteed.

[0039] Second embodiment

[0040] In the specific implementation process of this embodiment, compared with the above embodiment, this embodiment is mainly aimed at the relevant determination of abnormal devices, and its specific execution ends include a real-time monitoring end and an abnormality assessment end;

[0041] Its real-time monitoring end monitors the values ​​of the related equipment in the automated assembly line, and transmits the values ​​of different related items monitored in real time to the abnormality assessment end;

[0042] The abnormality assessment end confirms whether the real-time monitoring value of the relevant equipment is abnormal based on the main characteristic interval and the associated characteristic interval determined by the relevant equipment, and performs abnormal calibration on the relevant equipment based on the specific results of real-time confirmation. Each relevant equipment has completed abnormal calibration from the historical cycle data, so there is a corresponding abnormal equipment. After the abnormal equipment is confirmed, it needs to be displayed. The specific method of abnormal calibration is:

[0043] Combination Figure 2 , the main feature interval and the associated feature interval associated with the relevant equipment are proposed as standard intervals, and the relevant values ​​S monitored by the corresponding associated items of the relevant equipment at the corresponding time i Check with the standard interval, where i represents different related terms. If S i ∈ standard interval, then the eigenvalue T determined by this association item at the current moment i Calibrated to 0, if Standard interval, then determine the relevant value S i Difference from the standard interval: If S i < standard interval, then the difference = minimum value of the standard interval - S i , if S i > standard interval, then the difference = S i -The maximum value of the standard interval, the determined difference is used as the characteristic value T determined by this association item at the current moment i ;

[0044] Different eigenvalues ​​T determined based on different associated items at the current moment i , i=1, 2, ..., n, where n represents the total number of items associated with the corresponding equipment, using Determine its rating value PD i , where C i The fixed factor set for the corresponding associated item, its specific value is determined in advance by the operator based on experience;

[0045] The assessment value PD i Compare with the preset value Y2: If PD i ≤Y2, no calibration is performed. If PD i >Y2, mark the corresponding related equipment as abnormal equipment. Based on this automated assembly line, evaluate whether the equipment subsequently associated with this abnormal equipment has synchronous abnormalities within 5 minutes. If there is a synchronization abnormality, the equipment with synchronous abnormality and this abnormal equipment are marked as linked abnormal equipment. If there is no synchronization abnormality, the determined abnormal equipment number is directly displayed through the display terminal for external personnel to view and conduct relevant inspection or maintenance on this abnormal equipment in time. This linked abnormal equipment only includes two groups of abnormal equipment, but when there are three groups of abnormal equipment with synchronous abnormalities, two groups of linked abnormal equipment will be generated.

[0046] Third embodiment

[0047] The linkage device confirmation end determines the initial abnormal device of the linkage abnormal device for the confirmed linkage abnormal device, confirms the abnormal item of the initial abnormal device, identifies whether the abnormal item generated by the subsequent abnormal device is consistent with the abnormal item generated by the initial abnormal device, and evaluates whether such linkage abnormal device is linkage abnormal or single abnormal based on the identification result, wherein the specific method of evaluating is:

[0048] Based on this automated pipeline, the initial abnormal device of this linkage abnormal device is determined, and based on the abnormal confirmation process of the initial abnormal device, the abnormal item belonging to this initial abnormal device is identified. The abnormal item is The associated terms of the standard interval;

[0049] Identify other abnormal devices following the initial abnormal device from the linked abnormal devices, and identify whether the abnormal items generated by other abnormal devices are consistent with the abnormal items of the initial abnormal device:

[0050] If they are consistent, the linkage abnormal device is marked as linkage abnormal, and a linkage abnormal signal is generated and displayed through the display terminal to facilitate the relevant operators to perform inspection and maintenance;

[0051] If they are not consistent, it means that the abnormal devices associated with this linkage abnormal device are all single abnormal situations, and they will be directly displayed through the display terminal for external personnel to view and perform timely inspection and maintenance.

[0052] Specifically, when an abnormal device has a linkage abnormality, it is very likely that the abnormal device is caused by the linkage abnormality of the previous group of abnormal devices. That is, when the previous group of abnormal devices is abnormal, the abnormal device will simultaneously become abnormal, resulting in a linkage abnormality. Therefore, confirming the linkage abnormal device can effectively facilitate the inspection and maintenance of relevant operators and achieve better abnormality handling effects.

[0053] Fourth embodiment

[0054] The specific implementation process of this embodiment includes all the implementation processes of the above three groups of embodiments.

[0055] Some of the data in the above formulas are dimensionless and numerically calculated. Meanwhile, the contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0056] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. Equipment fault inspection system based on automated assembly line, characterized by: include: The equipment feature confirmation end performs relevant confirmation of the feature intervals of the related equipment associated in the automated assembly line. Based on the historical cycle data of the related equipment, the main feature interval of the main feature data of the related equipment is confirmed first, and then based on the time characteristics of the feature interval of the main feature data, the associated feature intervals of other related items are confirmed in sequence; The real-time monitoring end monitors the values ​​of the related equipment in the automated assembly line, and transmits the values ​​of different related items monitored in real time to the abnormality assessment end; The abnormality assessment end confirms whether the values ​​monitored in real time by the relevant equipment are abnormal based on the main characteristic interval and the associated characteristic interval determined by the relevant equipment, and performs abnormality calibration on the relevant equipment based on the specific results confirmed in real time; The linkage device confirmation end determines the initial abnormal device of the linkage abnormal device for the confirmed linkage abnormal device, confirms the abnormal items of the initial abnormal device, identifies whether the abnormal items generated by the subsequent abnormal devices are consistent with the abnormal items generated by the initial abnormal device, and assesses whether such linkage abnormal devices are linkage abnormal or single abnormal based on the identification results.

2. The equipment fault detection system based on the automated assembly line according to claim 1 is characterized in that: The specific method of the device feature confirmation end confirming the main feature interval of the main feature data of the relevant device is: Based on the related equipment associated with this automated assembly line, the main feature items belonging to this related equipment are confirmed, a group of cycle data closest to the current moment is determined from the historical cycle data, and the main feature data associated with the main feature items are confirmed from the cycle data. The historical cycle data is the historically collected operating data of all associated items of this related equipment, and each historical cycle is a preset cycle; Based on the confirmed main feature data and the timeline associated with the main feature data, a main feature data change curve is generated, feature confirmation is performed on the main feature data change curve, the maximum value and the minimum value of the main feature data change curve are locked, and a highest standard line and a lowest standard line passing through the maximum value and the minimum value and perpendicular to the vertical coordinate axis are constructed, so that the highest standard line and the lowest standard line move toward each other, and the speed of their movement toward each other is inconsistent, and variance processing is performed on a plurality of main feature data contained in the highest standard line and the lowest standard line in each movement process, and the variance value F is determined; The moving process with F≤Y1 is calibrated as the standard process, where Y1 is the preset value. The standard process with the maximum variance value F is calibrated as the selection process. Based on the maximum and minimum values ​​of several main feature data associated with this selection process, the main feature interval of the main feature item of the relevant equipment is confirmed, and the timeline associated with this selection process is calibrated as the selection timeline.

3. The equipment fault detection system based on the automated assembly line according to claim 2 is characterized in that: No calibration is performed on the movement process of F>Y1; If there is no standard process of F≤Y1, an error signal can be directly generated for display.

4. The equipment fault detection system based on the automated assembly line according to claim 2 is characterized in that: Based on the selected timeline, the data of other associated items of the related equipment are interval confirmed using the same interval determination method, and the associated feature interval of the corresponding associated item is locked.

5. The equipment fault detection system based on the automated assembly line according to claim 1 is characterized in that: The specific method of the abnormal assessment end for abnormal calibration of related equipment is: The main feature interval and the associated feature interval associated with the relevant equipment are both proposed as standard intervals, and the relevant values ​​S monitored by the corresponding associated items of the relevant equipment at the corresponding time are i Check with the standard interval, where i represents different related terms. If S i ∈ standard interval, then the eigenvalue T determined by this association item at the current moment i Calibrated to 0, if Standard interval, then determine the relevant value S i Difference from the standard interval: If S i < standard interval, then the difference = minimum value of the standard interval - S i , if S i > standard interval, then the difference = S i -The maximum value of the standard interval, the determined difference is used as the characteristic value T determined by this association item at the current moment i ; Different eigenvalues ​​T determined based on different associated items at the current moment i , i=1, 2, ..., n, where n represents the total number of items associated with the corresponding equipment, using Determine its rating value PD i , where C i The fixed factor set for the corresponding correlation item; The assessment value PD i Compare with the preset value Y2: If PD i >Y2, mark the corresponding related equipment as abnormal equipment. Based on this automated assembly line, evaluate whether the equipment subsequently associated with this abnormal equipment has synchronization abnormalities within 5 minutes. If the synchronization is abnormal, the equipment with synchronization abnormalities and this abnormal equipment are marked as linkage abnormal equipment. If there is no synchronization abnormality, the determined abnormal equipment number is directly displayed through the display terminal. This linkage abnormal equipment only includes two groups of abnormal equipment. However, when there are three groups of abnormal equipment with synchronization abnormalities, two groups of linkage abnormal equipment will be generated.

6. The equipment fault detection system based on the automated assembly line according to claim 5 is characterized in that: If PD i ≤Y2, no calibration is performed.

7. The equipment fault detection system based on the automated assembly line according to claim 5 is characterized in that: The linkage device confirmation end evaluates such linkage abnormal devices as linkage abnormal in the following specific ways: Based on this automated pipeline, the initial abnormal device of this linkage abnormal device is determined, and based on the abnormal confirmation process of the initial abnormal device, the abnormal item belonging to this initial abnormal device is identified. The abnormal item is The associated terms of the standard interval; Identify other abnormal devices following the initial abnormal device from the linked abnormal devices, and identify whether the abnormal items generated by other abnormal devices are consistent with the abnormal items of the initial abnormal device: If they are consistent, the linkage abnormal device is marked as linkage abnormal, and a linkage abnormal signal is generated and displayed through the display terminal.

8. The equipment fault detection system based on the automated assembly line according to claim 7 is characterized in that: If the abnormal items generated by other abnormal devices are inconsistent with the abnormal items of the initial abnormal device, it means that the abnormal devices associated with this linkage abnormal device are all single abnormal situations, and they are directly displayed through the display terminal.

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