CN116009463B - Bearing retainer production monitoring method, equipment and medium based on industrial Internet - Google Patents
Bearing retainer production monitoring method, equipment and medium based on industrial Internet Download PDFInfo
- Publication number
- CN116009463B CN116009463B CN202310307636.XA CN202310307636A CN116009463B CN 116009463 B CN116009463 B CN 116009463B CN 202310307636 A CN202310307636 A CN 202310307636A CN 116009463 B CN116009463 B CN 116009463B
- Authority
- CN
- China
- Prior art keywords
- production
- production equipment
- state
- operation data
- equipment
- 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.)
- Active
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
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Abstract
The application discloses a bearing retainer production monitoring method, equipment and medium based on industrial Internet, which relate to the field of data processing systems or methods for supervision or prediction purposes and comprise the following steps: confirming an established industrial Internet platform; collecting operation data of each production device in the corresponding production device group; determining that the operation data of the designated production equipment is abnormal; and overhauling the appointed production equipment and sending out early warning to other production equipment in the production equipment group where the appointed production equipment is located. Through the industrial internet platform, traceability of the monitoring and overhauling process is guaranteed. Not only overhaul the production facility that takes place unusual to carry out the early warning to other production facilities in its group, can effectively prevent that other facilities from appearing unusual, prevent in advance.
Description
Technical Field
The application relates to the field of data processing systems or methods for supervision or prediction purposes, in particular to a method, equipment and medium for monitoring production of a bearing retainer based on an industrial Internet.
Background
Bearings are an important component in contemporary mechanical devices. Its main function is to support the mechanical rotator, reduce the friction coefficient in the course of its movement and ensure its rotation accuracy. Bearing holders (also called bearing holders) are an important component in bearings, which are disposed inside the bearings and mainly used for supporting and holding other components such as balls.
In the production process of the bearing retainer, raw materials are required to be produced and processed through production equipment such as a coiling machine, a leveling machine and the like, so that a final product is obtained. In the production and processing process, the abnormal state of the production equipment needs to be monitored.
In the traditional scheme, operation data of production equipment is monitored, maintenance can be carried out only when the production equipment is abnormal, and effective early warning is difficult to carry out. In addition, the monitoring, analyzing and overhauling processes often have no unified data storage and analysis platform, and the overhauling reasons and overhauling processes are difficult to trace.
Disclosure of Invention
In order to solve the above problems, the present application proposes a method for monitoring production of a bearing cage based on the industrial internet, comprising:
confirming an established industrial Internet platform, wherein the industrial Internet platform at least comprises enterprise nodes, a bearing retainer production line and production monitoring equipment are arranged in the enterprise nodes, a plurality of production equipment groups are arranged in the bearing retainer production line, and one or more types of production equipment are arranged in each production equipment group;
Collecting operation data of each production device in a corresponding production device group through the production monitoring device, and uploading the operation data to the industrial Internet platform;
determining that the operation data of the specified production equipment are abnormal, issuing a control instruction to production monitoring equipment corresponding to the specified production equipment through the enterprise node, and uploading the control instruction to the industrial Internet platform;
and overhauling the designated production equipment through the control instruction, and sending out early warning to other production equipment in the production equipment group where the designated production equipment is located.
On the other hand, the application still provides a bearing retainer production supervisory equipment based on industry internet, includes:
at least one processor; the method comprises the steps of,
a memory communicatively coupled to the at least one processor; wherein, the liquid crystal display device comprises a liquid crystal display device,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform operations such as:
confirming an established industrial Internet platform, wherein the industrial Internet platform at least comprises enterprise nodes, a bearing retainer production line and production monitoring equipment are arranged in the enterprise nodes, a plurality of production equipment groups are arranged in the bearing retainer production line, and one or more types of production equipment are arranged in each production equipment group;
Collecting operation data of each production device in a corresponding production device group through the production monitoring device, and uploading the operation data to the industrial Internet platform;
determining that the operation data of the specified production equipment are abnormal, issuing a control instruction to production monitoring equipment corresponding to the specified production equipment through the enterprise node, and uploading the control instruction to the industrial Internet platform;
the specified production equipment is overhauled through the control instruction, and early warning is sent out to other production equipment in the production equipment group where the specified production equipment is located
In another aspect, the present application also proposes a non-volatile computer storage medium storing computer executable instructions, characterized in that the computer executable instructions are configured to:
confirming an established industrial Internet platform, wherein the industrial Internet platform at least comprises enterprise nodes, a bearing retainer production line and production monitoring equipment are arranged in the enterprise nodes, a plurality of production equipment groups are arranged in the bearing retainer production line, and one or more types of production equipment are arranged in each production equipment group;
Collecting operation data of each production device in a corresponding production device group through the production monitoring device, and uploading the operation data to the industrial Internet platform;
determining that the operation data of the specified production equipment are abnormal, issuing a control instruction to production monitoring equipment corresponding to the specified production equipment through the enterprise node, and uploading the control instruction to the industrial Internet platform;
and overhauling the designated production equipment through the control instruction, and sending out early warning to other production equipment in the production equipment group where the designated production equipment is located.
The scheme provided by the application can bring the following beneficial effects:
through the industrial internet platform that establishes, can carry out complete control to production process, the maintenance process of production facility, ensured production facility's normal operating to and in time handle after the appearance is unusual, the overall process is uploaded to industrial internet platform, has ensured the traceability to control and maintenance process.
When overhauling, not only overhaul the production facility that takes place unusual to carry out the early warning to other production facilities in its group, can effectively prevent that other facilities from appearing unusual, prevent in advance.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute an undue limitation to the application. In the drawings:
FIG. 1 is a schematic flow chart of a method for monitoring production of a bearing cage based on the industrial Internet in an embodiment of the application;
fig. 2 is a schematic diagram of an industrial internet-based bearing cage production monitoring device in an embodiment of the present application.
Detailed Description
For the purposes, technical solutions and advantages of the present application, the technical solutions of the present application will be clearly and completely described below with reference to specific embodiments of the present application and corresponding drawings. It will be apparent that the described embodiments are only some, but not all, of the embodiments of the present application. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.
The following describes in detail the technical solutions provided by the embodiments of the present application with reference to the accompanying drawings.
As shown in fig. 1, an embodiment of the present application provides a method for monitoring production of a bearing cage based on industrial internet, including:
S101: and confirming an established industrial Internet platform, wherein the industrial Internet platform at least comprises enterprise nodes, a bearing retainer production line and production monitoring equipment are arranged in the enterprise nodes, a plurality of production equipment groups are arranged in the bearing retainer production line, and one or more types of production equipment are arranged in each production equipment group.
The industrial Internet comprises four large systems of network, platform, data and safety, which is not only an infrastructure for industrial digitization, networking and intelligent transformation, but also an application mode for deep integration of Internet, big data, artificial intelligence and entity economy, and is a new industry state and new industry, and the enterprise morphology, supply chain and industry chain are remodeled.
The secondary nodes are mainly oriented to industry nodes (such as industries of bearing retainers, bearing accessories and the like), and the enterprise nodes are oriented to enterprises.
A plurality of production equipment is included in the bearing retainer production line, each production equipment includes one or more production equipment, and the production equipment can include: travelling crane, coil stock machine, evener, punching machine, subtracting material machine, bottom cutting machine, piercing press, conveyer etc..
The travelling crane is used for hanging the metal plate to a corresponding processing position, and the coiling machine and the leveling machine are respectively used for coiling and leveling the metal plate. The punching machine is used for carrying out punching separation on the metal plate to obtain bowl-shaped parts, the bottom cutting machine is used for cutting the bottom of the bowl-shaped parts, the punching machine is used for punching, the material reducing machine is used for shearing the residual materials after the punching separation, and the conveying device is used for conveying the metal plate, the residual materials, the bowl-shaped parts, finished products and the like.
Each production equipment group includes a plurality of types of production equipment, and if the production equipment groups include a plurality of types of production equipment, the production equipment groups can be considered to have corresponding relations, for example, the production process, the occurrence of abnormality and the like are similar, and the division of the production equipment groups is explained in detail below.
Each production monitoring device is provided with a corresponding production device group for monitoring operational data (e.g., operational parameters, production data, etc.) of the respective production devices within the corresponding production device group. Of course, if the number of production devices is large in one production device group, a plurality of production monitoring devices may be set, or a framework of one main monitoring device and a plurality of sub-monitoring devices may be used for monitoring.
S102: and collecting operation data of each production device in the corresponding production device group through the production monitoring device, and uploading the operation data to the industrial Internet platform.
The production monitoring equipment uploads the operation data obtained by monitoring to the industrial Internet platform, so that the data can be stored, and the abnormal analysis of the operation data can be performed by utilizing the computing capacity of the industrial Internet platform.
S103: determining that the operation data of the specified production equipment are abnormal, issuing a control instruction to production monitoring equipment corresponding to the specified production equipment through the enterprise node, and uploading the control instruction to the industrial Internet platform.
The operation data generally corresponds to corresponding standard data or standard interval, in which a critical value is set, and once the critical value is reached, the production equipment can be considered to enter a critical state, and once the critical value exceeds the standard data or standard interval, the production equipment can be considered to enter an abnormal state.
The control instruction is issued to the production monitoring equipment, and the production monitoring equipment has other functions besides a data acquisition function, such as suspending work, stopping work, calling maintenance personnel, giving an alarm and the like to the production equipment according to the received control instruction.
S104: and overhauling the designated production equipment through the control instruction, and sending out early warning to other production equipment in the production equipment group where the designated production equipment is located.
The operation data of the appointed production equipment is abnormal, and the maintenance is needed. The maintenance can be a manual maintenance by calling a maintenance personnel or an automatic maintenance by a preset script, for example, restarting an automatic operation system of the production equipment.
Since there is a certain association between the production devices in each production device group, when an abnormality occurs in a given production device, other production devices in the group may also be abnormal. At this time, the other production equipment is warned, for example, a warning alarm is sent out, so that the equipment physical examination of the other production equipment is performed in advance.
Through the industrial internet platform that establishes, can carry out complete control to production process, the maintenance process of production facility, ensured production facility's normal operating to and in time handle after the appearance is unusual, the overall process is uploaded to industrial internet platform, has ensured the traceability to control and maintenance process.
When overhauling, not only overhaul the production facility that takes place unusual to carry out the early warning to other production facilities in its group, can effectively prevent that other facilities from appearing unusual, prevent in advance.
In one embodiment, when the production equipment group is set, operation data of various production equipment contained in the bearing retainer production line at a plurality of moments is collected, and a corresponding state label at each moment is generated based on the operation data of the various production equipment. By determining whether the operation data reaches the critical data or the standard data, the operation state of the operation data can be determined, so that a corresponding state label is generated, for example, the state label can comprise a normal state, a critical state and an abnormal state.
For each type of production equipment (when one type of production equipment comprises a plurality of production equipment, one of the production equipment can be selected, or a plurality of corresponding values can be averaged), an operation data curve is obtained according to the operation data fitting of the type of production equipment at each moment (for example, curve fitting is performed through a least square method).
And intercepting and dividing the operation data curve through the state label to obtain a plurality of sub-curves. In the intercepting and dividing process, firstly, determining a state label of the operation data corresponding to the first moment in the operation data curve, wherein the operation data curve is generated by fitting the operation data at a plurality of moments, each operation data corresponds to a corresponding moment when being generated by fitting, all the corresponding moments of the operation data are recorded, the state label of the operation data at each moment is recorded, and a mapping relation is established between the moment and the state label. And then sequentially searching each moment from the first moment to the back according to the recorded moments, if the state label corresponding to the moment is consistent with the state label corresponding to the previous moment, continuing searching the next moment in the same sub-curve with the state label of the previous moment, and if the state label of the moment is inconsistent with the state label of the previous moment, intercepting and dividing a curve formed by the moment before the moment (excluding the moment) with different state labels to serve as a sub-curve, and then taking the moment with different state labels as the first moment in a new sub-curve, and repeating the searching process. At this time, only one type of state label exists in each of the sub-curves, and the state labels existing in the adjacent sub-curves are different, so that one type of state label exists in the divided plurality of sub-curves, and the one type of state label is not distributed in the plurality of sub-curves.
And determining the association degree between various production equipment according to the similarity between the corresponding sub-curves of the various production equipment under the state label aiming at each state label, wherein the association degree is positively correlated with the similarity, and the higher the similarity between the sub-curves of the various production equipment is, the higher the association degree is. When the association degree is high and exceeds a first threshold value, the plurality of production devices are used as a production device group.
Specifically, the operation state of the production equipment can be basically determined only by the operation data, but in some cases, the operation data of the production equipment is normal, but the operation state thereof is still abnormal to some extent, for example, the operation frequency, the operation voltage and the like of the punching machine are normal, but the operation state thereof is abnormal due to the damage of the punching die, which is difficult to judge by the operation data.
Based on this, the pending label is generated by the operation data at each time for each type of production equipment, and the pending label can be understood as a state label obtained after the determination by the operation data only, which includes a normal state, a critical state and an abnormal state, the determination rule of the pending label is the same as the description of the state label above, and the pending label is obtained by comparing the operation data with the standard data and the standard interval. This is referred to herein as a "pending tag" because it may be subject to adjustment in some scenarios and is not the final state tag at this time, and is referred to as a pending tag, and the adjustment process will be described in detail below. If the undetermined label is an abnormal label, the operation state of the undetermined label can be determined to be abnormal without continuous judgment, and if the undetermined label is in a normal state or a critical state, further judgment is needed.
At this time, the image acquisition device corresponding to the production equipment acquires the corresponding product image of the production equipment after production and processing. The image acquisition device is arranged near (e.g. on both sides or on top of) the production equipment and can acquire images of products processed by the production equipment, for example, the image acquisition device can be a monitoring probe.
And extracting the characteristics of the product image, and obtaining auxiliary variables according to the extracted image characteristics. The extracted image features can represent features of the product in the product image, for example, it may be features representing product thickness, height, punching size, etc.
If the auxiliary variable meets the preset requirement, the operation data is likely to be normal, but the operation state is not normal, and at the moment, the label to be measured is adjusted to obtain the corresponding state label of the production equipment at the moment
Further, different kinds of production equipment correspond to different processing technologies, for example, a conical bearing retainer is taken as an example, and a leveling machine corresponds to processing technology for extruding and leveling a metal plate. At this time, the physical characteristic of the product which can most embody the processing technology is the thickness of the product.
When the image features are extracted, because of different image shooting parameters (such as view projection direction, shooting distance, shooting focal length, etc.), image representation features for extracting the physical features of the product are different in the product image, for example, when the shooting angle is a side surface, the height (image representation features) of the raw material plate directly corresponds to the thickness (physical features of the product) in the image, and if the shooting angle is obliquely above the side surface, the side surface height (image representation features) of the raw material plate can correspond to the thickness (physical features of the product) of the product after correction through the shooting angle is needed. Therefore, it is necessary to obtain the image expression characteristics by the image capturing parameters.
And carrying out image analysis on the product image according to the image expression characteristics to extract the image characteristics (namely, specific values corresponding to the image expression characteristics in the product image) from the product image, namely, taking the image characteristics as actual product parameters, and then obtaining auxiliary variables according to the actual product parameters.
Specifically, a standard parameter corresponding to the product parameter (the standard parameter is a parameter corresponding to a standard product) is obtained, and a difference value between the standard parameter and the product parameter is determined.
And obtaining an auxiliary variable according to the difference value, wherein the difference value and the auxiliary variable are positively correlated, and the higher the difference value is, the higher the auxiliary variable is, and the two can be in a corresponding relation of 1 to 1.
For example, in the machining process of the conical bearing retainer and the punching machine, the corresponding bowl-shaped piece is punched on the metal plate, and at this time, the product physical characteristics capable of embodying the machining process include: the inner diameter of the bowl, the outer diameter of the bowl, the inclination of the bowl, the height of the bowl, etc. In the bearing retainer production line, a deflection feeder is arranged in subsequent production equipment of the punching machine, bowl parts can be conveyed onto corresponding conveyor belts, the bowl parts on the conveyor belts can be in a back-off state on the conveyor belts in a manual auxiliary mode, in the state, one side of the bowl parts with smaller inner diameter is located above, and one side with larger inner diameter is located below.
At this time, the camera is arranged right above the conveyor belt, and the view projection direction of the camera is not required to be adjusted, and the camera is only required to be adjusted according to the shooting distance and the shooting focal length. For example, for the outer diameter (physical characteristic of a product) of a bowl-shaped article, the outer diameter of the bowl-shaped article occupies 200 pixel points in total, and the 200 pixel points can be directly used as image expression characteristics because the view projection direction is not needed to be considered this time, if the view projection direction of a camera is one side of a conveyor belt, the 200 pixel points need to be adjusted by adjusting proportions to obtain the image expression characteristics, wherein the adjusting process can be used for shooting an object with a known length by taking the same view projection direction, shooting distance and shooting focal length in advance, and then shooting the same object right above on the basis of only changing the view projection direction, and generating corresponding proportions according to the difference of the pixel points of the object in the two shooting processes, wherein the proportions are the adjusting proportions.
After 200 pixel points of the image representation characteristic are obtained, the image representation characteristic can be obtained through conversion according to the shooting distance and the shooting focal length, the image representation characteristic corresponds to the actual size of 20mm (image characteristic), and the image characteristic is the corresponding product parameter, wherein the conversion process is similar to the adjustment process, an object with a known length is shot through the same shooting distance and the shooting focal length in advance, and then the proportion is calculated according to the pixel point length and the actual length in the image, so that the proportion in conversion is obtained.
Of course, if the view projection direction is obliquely above, the adjustment ratio is assumed to be 1.5, and 200 pixels are in the image, and at this time, the adjustment ratio is adjusted to 200×1.5=300 pixels, and the 300 pixels are image representation features, and at this time, the corresponding image features are 30mm, and the product parameters are also 30mm.
Still taking a product parameter of 20mm as an example, if the standard parameter of the outer diameter of the bowl is 21mm, and the difference is 1mm, the auxiliary variable can be set to be 1 according to the corresponding relation of 1 to 1.
At this time, when the to-be-marked tag is adjusted, if the auxiliary variable is higher and exceeds the second threshold, it is indicated that the difference is larger, and the to-be-marked tag needs to be adjusted by one stage in the direction of serious abnormality to modify the normal state into the critical state and modify the critical state into the abnormal state. If the auxiliary variable is very high and exceeds a preset third threshold (the third threshold is larger than the second threshold), the undetermined label is required to be adjusted to be in a larger extent so as to change the normal state into the abnormal state, and if the undetermined label is in the critical state, the undetermined label is also changed into the abnormal state. The second threshold and the third threshold often have different standards for different standards and different models, and in general, the allowable error range is 10%, and the allowable error range is 2.1mm for the standard parameter of 21mm, where the second threshold may be set to 1.6 and the third threshold may be set to 2.1.
In addition, when the association degree is determined, the similarity between the sub-curves corresponding to various production equipment under the state label is determined for each state label, and the similarity confirmation between the curves can be obtained by integrating the covariance, the curve difference and the like. When the similarity is compared, the sub-curves under each state label are respectively compared, and if the state label is provided with a plurality of sub-curves, the sub-curve with the highest similarity can be selected as the similarity of the state label. Therefore, misjudgment caused by curve uplink versus curve downlink can be screened out.
According to the weights corresponding to the state labels, the similarity is overlapped to obtain the association degree between various production devices, wherein the critical state and the abnormal state are higher in weight because whether the production devices are abnormal or not needs to be judged, and the critical state is short in time and has reference significance, so that the weights of the state labels are as follows in sequence from large to small: critical state, abnormal state, normal state. For example, the weights are 0.5, 0.4, and 0.1 in order.
For example, a first type of production facility has the following sub-curves: A. b (corresponding to normal state), C (corresponding to critical state), D (corresponding to abnormal state), whereas the second type of production device has the following sub-curves: e (corresponding to a normal state), F (corresponding to a critical state), G (corresponding to an abnormal state).
When the similarity is calculated, for the state label in the normal state, the similarity between A and E is calculated to be 0.8, and the similarity between B and E is calculated to be 0.2, and at the moment, 0.8 is selected as the similarity in the normal state. Similarly, the similarity of the critical state and the abnormal state is 0.7 and 0.5, respectively. When the weights are 0.5, 0.4 and 0.1 in sequence, the degree of association between the first type of production equipment and the second type of production equipment can be calculated as follows: 0.8 x 0.1+0.7 x 0.5+0.5 x 0.4=0.63.
In one embodiment, after determining that there is an abnormality in the operation data of a specified production apparatus (specified production apparatus refers to production apparatus in which there is an abnormality, which is referred to for distinction from other production apparatuses), if a control instruction is to be generated, the data type of the operation data in which there is an abnormality is determined first. For example, the data types of the operation data may include operation parameters, production data, etc., and when the data types are divided more specifically, the operation parameters may include operation voltage, operation power, and the production data may include: operating frequency, daily throughput, etc.
And generating a corresponding control instruction according to the data type, wherein the control instruction is used for calling a maintenance strategy locally stored in the production monitoring equipment, the maintenance strategy comprises automatic maintenance and/or manual maintenance calling, and the maintenance strategy is specifically explained below.
When different data types are abnormal, the maintenance strategies called in the control instructions are also different, the degree of influence on production equipment is different, for example, if the operation voltage of the production equipment is abnormal, equipment damage is easy to occur, the degree of influence is large, at the moment, more urgent and important maintenance strategies needing to be manually participated are needed to be selected, if the standby time is too long to cause the abnormality, the system fault at the software level is likely, serious consequences are not caused, and at the moment, the rapid and automatic maintenance strategies with higher efficiency can be selected. Therefore, the required maintenance strategy can be judged through the data type, and then the identification ID corresponding to the selected maintenance strategy is added to the control instruction.
Further, after receiving the control instruction, selecting a specified overhaul strategy from locally stored overhaul strategies through the control instruction. As already mentioned above, the control instruction carries related information (for example, an identifier ID corresponding to the overhaul policy), and the selection of the specified overhaul policy is performed according to the information.
And sequentially calling the specified overhaul strategies according to the order corresponding to the overhaul strategies until no abnormality occurs in the operation data within the preset time period (different time periods corresponding to the strategies can be different or can be set to be universal time periods, for example, 10 minutes) after overhaul, and uploading the overhaul result to the industrial Internet platform.
The sequence is preset, in the sequence, automatic overhaul is relatively more convenient and automatic, but the abnormality which can be processed by the automatic overhaul is usually less and is relatively fixed, so the automatic overhaul sequence precedes manual overhaul, and in the automatic overhaul, various schemes are generally included, such as general overhaul (restarting a control system of production equipment, clearing a cache and the like), equipment special overhaul (on-site measurement analysis is performed through special software of the production equipment), and the general overhaul is more rapid and universal, so the general overhaul sequence precedes the equipment special overhaul.
When the early warning is carried out on other production equipment, the other production equipment does not generate abnormality at the moment, and the scheme which is relatively forward and universal in the sequence is difficult to check, so that the maintenance strategy which is the rearmost in the sequence can be used as an early warning strategy, and the early warning is sent out to the other production equipment in the production equipment group where the specified production equipment is located according to the early warning strategy.
For example, if according to the control instruction, the selected specified maintenance strategy includes: restarting the control system of the production equipment (belonging to general overhaul) and calling manual overhaul, when the specified production equipment is overhauled, restarting the control system of the production equipment, calling the manual overhaul if the control system is still abnormal after restarting, and when other production equipment is pre-warned, directly adopting a mode of calling the manual overhaul to pre-warn, and dispatching manual forward to carry out overhaul pre-warning.
As shown in fig. 2, the embodiment of the present application further provides an industrial internet-based bearing cage production monitoring device, including:
at least one processor; the method comprises the steps of,
a memory communicatively coupled to the at least one processor; wherein, the liquid crystal display device comprises a liquid crystal display device,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform operations such as:
confirming an established industrial Internet platform, wherein the industrial Internet platform at least comprises enterprise nodes, a bearing retainer production line and production monitoring equipment are arranged in the enterprise nodes, a plurality of production equipment groups are arranged in the bearing retainer production line, and one or more types of production equipment are arranged in each production equipment group;
collecting operation data of each production device in a corresponding production device group through the production monitoring device, and uploading the operation data to the industrial Internet platform;
determining that the operation data of the specified production equipment are abnormal, issuing a control instruction to production monitoring equipment corresponding to the specified production equipment through the enterprise node, and uploading the control instruction to the industrial Internet platform;
And overhauling the designated production equipment through the control instruction, and sending out early warning to other production equipment in the production equipment group where the designated production equipment is located.
The embodiments also provide a non-volatile computer storage medium storing computer executable instructions configured to:
confirming an established industrial Internet platform, wherein the industrial Internet platform at least comprises enterprise nodes, a bearing retainer production line and production monitoring equipment are arranged in the enterprise nodes, a plurality of production equipment groups are arranged in the bearing retainer production line, and one or more types of production equipment are arranged in each production equipment group;
collecting operation data of each production device in a corresponding production device group through the production monitoring device, and uploading the operation data to the industrial Internet platform;
determining that the operation data of the specified production equipment are abnormal, issuing a control instruction to production monitoring equipment corresponding to the specified production equipment through the enterprise node, and uploading the control instruction to the industrial Internet platform;
and overhauling the designated production equipment through the control instruction, and sending out early warning to other production equipment in the production equipment group where the designated production equipment is located.
All embodiments in the application are described in a progressive manner, and identical and similar parts of all embodiments are mutually referred, so that each embodiment mainly describes differences from other embodiments. In particular, for the apparatus and medium embodiments, the description is relatively simple, as it is substantially similar to the method embodiments, with reference to the section of the method embodiments being relevant.
The devices and media provided in the embodiments of the present application are in one-to-one correspondence with the methods, so that the devices and media also have similar beneficial technical effects as the corresponding methods, and since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the devices and media are not described in detail herein.
The foregoing is merely exemplary of the present application and is not intended to limit the present application. Various modifications and changes may be made to the present application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc. which are within the spirit and principles of the present application are intended to be included within the scope of the claims of the present application.
Claims (6)
1. The method for monitoring the production of the bearing retainer based on the industrial Internet is characterized by comprising the following steps of:
Confirming an established industrial Internet platform, wherein the industrial Internet platform at least comprises enterprise nodes, a bearing retainer production line and production monitoring equipment are arranged in the enterprise nodes, a plurality of production equipment groups are arranged in the bearing retainer production line, and one or more types of production equipment are arranged in each production equipment group;
collecting operation data of each production device in a corresponding production device group through the production monitoring device, and uploading the operation data to the industrial Internet platform;
determining that the operation data of the specified production equipment are abnormal, issuing a control instruction to production monitoring equipment corresponding to the specified production equipment through the enterprise node, and uploading the control instruction to the industrial Internet platform;
overhauling the designated production equipment through the control instruction, and sending out early warning to other production equipment in the production equipment group where the designated production equipment is located;
before the production monitoring equipment collects the operation data of each production equipment in the corresponding production equipment group, the method further comprises:
collecting operation data of various production equipment contained in a bearing retainer production line at a plurality of moments, and generating corresponding state labels at each moment based on the operation data of the various production equipment, wherein the state labels comprise a normal state, a critical state and an abnormal state;
Fitting operation data of each type of production equipment at each time to obtain an operation data curve;
intercepting and dividing the operation data curve through the state labels to obtain a plurality of sub-curves, so that only one state label exists in each sub-curve, and the state labels existing in adjacent sub-curves are different;
for each state label, determining the association degree between various production devices according to the similarity between the sub-curves corresponding to the various production devices under the state label, wherein the association degree is positively correlated with the similarity;
taking a plurality of types of production equipment with the association degree exceeding a first threshold value as a production equipment group;
based on the operation data of various production devices, generating a corresponding state label at each moment specifically comprises the following steps:
determining operation data of the production equipment at each moment aiming at each type of production equipment, and generating a pending label of the production equipment at the moment according to the operation data, wherein the pending label comprises a normal state, a critical state and an abnormal state;
if the undetermined label is in the normal state or the critical state, acquiring corresponding product images of the production equipment after production and processing at the moment through a corresponding image acquisition device;
Extracting features of the product image, obtaining an auxiliary variable according to the extracted image features, and adjusting the undetermined label under the condition that the auxiliary variable meets the preset requirement to obtain a corresponding state label of the production equipment at the moment;
extracting the characteristics of the product image, and obtaining auxiliary variables according to the extracted image characteristics, wherein the method specifically comprises the following steps:
determining corresponding processing technologies of the production equipment, and determining the physical characteristics of products capable of reflecting the processing technologies;
determining image shooting parameters corresponding to the product image, and determining image expression characteristics of the product physical characteristics in the product image according to the image shooting parameters;
carrying out image analysis on the product image according to the image expression characteristics to obtain image characteristics, and obtaining product parameters according to the image characteristics;
obtaining auxiliary variables according to the product parameters;
obtaining auxiliary variables according to the product parameters, wherein the auxiliary variables specifically comprise:
obtaining standard parameters corresponding to the product parameters, and determining the difference between the standard parameters and the product parameters;
obtaining an auxiliary variable according to the difference value, wherein the difference value and the auxiliary variable are positively correlated;
Under the condition that the auxiliary variable meets the preset requirement, the undetermined label is adjusted, which specifically comprises the following steps:
if the auxiliary variable exceeds a second threshold, the undetermined label is adjusted to modify the normal state into a critical state and modify the critical state into an abnormal state;
and if the auxiliary variable exceeds a third threshold, the undetermined tag is adjusted to modify the normal state into the abnormal state, and the third threshold is larger than the second threshold.
2. The industrial internet-based bearing retainer production monitoring method according to claim 1, wherein for each status tag, determining the degree of association between various types of production equipment by the degree of similarity between the sub-curves corresponding to the various types of production equipment under the status tag specifically comprises:
for each state label, determining the similarity between the sub-curves corresponding to various production equipment under the state label, wherein if a plurality of sub-curves are arranged under the state label, the similarity between two sub-curves with the highest similarity is selected and used as the corresponding similarity under the state label;
and superposing the similarity according to the weight corresponding to each state label to obtain the association degree among various production devices, wherein the weights of the state labels are as follows in sequence from large to small: critical state, abnormal state, normal state.
3. The industrial internet-based bearing retainer production monitoring method according to claim 1, wherein determining that the operation data of the specified production equipment is abnormal, and issuing a control instruction to the production monitoring equipment corresponding to the specified production equipment through the enterprise node specifically comprises:
determining that the operation data of the designated production equipment is abnormal, and determining the data type of the abnormal operation data;
generating a corresponding control instruction according to the data type, wherein the control instruction is used for calling an overhaul strategy locally stored in production monitoring equipment, and the overhaul strategy comprises automatic overhaul and/or manual overhaul calling;
and issuing the control instruction to the production monitoring equipment corresponding to the designated production equipment through the enterprise node.
4. The method for monitoring production of bearing retainers based on industrial internet according to claim 3, wherein the method for overhauling the designated production equipment and sending out early warning to other production equipment in the production equipment group where the designated production equipment is located by the control command specifically comprises:
selecting a specified overhaul strategy from locally stored overhaul strategies through the control instruction;
Invoking the specified overhaul strategies in sequence according to the sequence corresponding to the overhaul strategies until the operation data are not abnormal within the preset duration after overhaul, and uploading overhaul results to the industrial Internet platform, wherein in the sequence, the automatic overhaul precedes the manual overhaul by calling, and the general overhaul in the automatic overhaul precedes the special overhaul of equipment;
and selecting the overhaul strategy with the rearmost order from the appointed overhaul strategies as an early warning strategy, and sending early warning to other production equipment in the production equipment group where the appointed production equipment is located according to the early warning strategy.
5. Bearing retainer production supervisory equipment based on industry internet, characterized by, include:
at least one processor; the method comprises the steps of,
a memory communicatively coupled to the at least one processor; wherein, the liquid crystal display device comprises a liquid crystal display device,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform operations such as:
confirming an established industrial Internet platform, wherein the industrial Internet platform at least comprises enterprise nodes, a bearing retainer production line and production monitoring equipment are arranged in the enterprise nodes, a plurality of production equipment groups are arranged in the bearing retainer production line, and one or more types of production equipment are arranged in each production equipment group;
Collecting operation data of each production device in a corresponding production device group through the production monitoring device, and uploading the operation data to the industrial Internet platform;
determining that the operation data of the specified production equipment are abnormal, issuing a control instruction to production monitoring equipment corresponding to the specified production equipment through the enterprise node, and uploading the control instruction to the industrial Internet platform;
overhauling the designated production equipment through the control instruction, and sending out early warning to other production equipment in the production equipment group where the designated production equipment is located;
before the production monitoring equipment collects the operation data of each production equipment in the corresponding production equipment group, the production monitoring equipment further comprises:
collecting operation data of various production equipment contained in a bearing retainer production line at a plurality of moments, and generating corresponding state labels at each moment based on the operation data of the various production equipment, wherein the state labels comprise a normal state, a critical state and an abnormal state;
fitting operation data of each type of production equipment at each time to obtain an operation data curve;
Intercepting and dividing the operation data curve through the state labels to obtain a plurality of sub-curves, so that only one state label exists in each sub-curve, and the state labels existing in adjacent sub-curves are different;
for each state label, determining the association degree between various production devices according to the similarity between the sub-curves corresponding to the various production devices under the state label, wherein the association degree is positively correlated with the similarity;
taking a plurality of types of production equipment with the association degree exceeding a first threshold value as a production equipment group;
based on the operation data of various production devices, generating a corresponding state label at each moment specifically comprises the following steps:
determining operation data of the production equipment at each moment aiming at each type of production equipment, and generating a pending label of the production equipment at the moment according to the operation data, wherein the pending label comprises a normal state, a critical state and an abnormal state;
if the undetermined label is in the normal state or the critical state, acquiring corresponding product images of the production equipment after production and processing at the moment through a corresponding image acquisition device;
Extracting features of the product image, obtaining an auxiliary variable according to the extracted image features, and adjusting the undetermined label under the condition that the auxiliary variable meets the preset requirement to obtain a corresponding state label of the production equipment at the moment;
extracting the characteristics of the product image, and obtaining auxiliary variables according to the extracted image characteristics, wherein the method specifically comprises the following steps:
determining corresponding processing technologies of the production equipment, and determining the physical characteristics of products capable of reflecting the processing technologies;
determining image shooting parameters corresponding to the product image, and determining image expression characteristics of the product physical characteristics in the product image according to the image shooting parameters;
carrying out image analysis on the product image according to the image expression characteristics to obtain image characteristics, and obtaining product parameters according to the image characteristics;
obtaining auxiliary variables according to the product parameters;
obtaining auxiliary variables according to the product parameters, wherein the auxiliary variables specifically comprise:
obtaining standard parameters corresponding to the product parameters, and determining the difference between the standard parameters and the product parameters;
obtaining an auxiliary variable according to the difference value, wherein the difference value and the auxiliary variable are positively correlated;
Under the condition that the auxiliary variable meets the preset requirement, the undetermined label is adjusted, which specifically comprises the following steps:
if the auxiliary variable exceeds a second threshold, the undetermined label is adjusted to modify the normal state into a critical state and modify the critical state into an abnormal state;
and if the auxiliary variable exceeds a third threshold, the undetermined tag is adjusted to modify the normal state into the abnormal state, and the third threshold is larger than the second threshold.
6. A non-transitory computer storage medium storing computer-executable instructions, the computer-executable instructions configured to:
confirming an established industrial Internet platform, wherein the industrial Internet platform at least comprises enterprise nodes, a bearing retainer production line and production monitoring equipment are arranged in the enterprise nodes, a plurality of production equipment groups are arranged in the bearing retainer production line, and one or more types of production equipment are arranged in each production equipment group;
collecting operation data of each production device in a corresponding production device group through the production monitoring device, and uploading the operation data to the industrial Internet platform;
Determining that the operation data of the specified production equipment are abnormal, issuing a control instruction to production monitoring equipment corresponding to the specified production equipment through the enterprise node, and uploading the control instruction to the industrial Internet platform;
overhauling the designated production equipment through the control instruction, and sending out early warning to other production equipment in the production equipment group where the designated production equipment is located;
before the production monitoring equipment collects the operation data of each production equipment in the corresponding production equipment group, the production monitoring equipment further comprises:
collecting operation data of various production equipment contained in a bearing retainer production line at a plurality of moments, and generating corresponding state labels at each moment based on the operation data of the various production equipment, wherein the state labels comprise a normal state, a critical state and an abnormal state;
fitting operation data of each type of production equipment at each time to obtain an operation data curve;
intercepting and dividing the operation data curve through the state labels to obtain a plurality of sub-curves, so that only one state label exists in each sub-curve, and the state labels existing in adjacent sub-curves are different;
For each state label, determining the association degree between various production devices according to the similarity between the sub-curves corresponding to the various production devices under the state label, wherein the association degree is positively correlated with the similarity;
taking a plurality of types of production equipment with the association degree exceeding a first threshold value as a production equipment group;
based on the operation data of various production devices, generating a corresponding state label at each moment specifically comprises the following steps:
determining operation data of the production equipment at each moment aiming at each type of production equipment, and generating a pending label of the production equipment at the moment according to the operation data, wherein the pending label comprises a normal state, a critical state and an abnormal state;
if the undetermined label is in the normal state or the critical state, acquiring corresponding product images of the production equipment after production and processing at the moment through a corresponding image acquisition device;
extracting features of the product image, obtaining an auxiliary variable according to the extracted image features, and adjusting the undetermined label under the condition that the auxiliary variable meets the preset requirement to obtain a corresponding state label of the production equipment at the moment;
Extracting the characteristics of the product image, and obtaining auxiliary variables according to the extracted image characteristics, wherein the method specifically comprises the following steps:
determining corresponding processing technologies of the production equipment, and determining the physical characteristics of products capable of reflecting the processing technologies;
determining image shooting parameters corresponding to the product image, and determining image expression characteristics of the product physical characteristics in the product image according to the image shooting parameters;
carrying out image analysis on the product image according to the image expression characteristics to obtain image characteristics, and obtaining product parameters according to the image characteristics;
obtaining auxiliary variables according to the product parameters;
obtaining auxiliary variables according to the product parameters, wherein the auxiliary variables specifically comprise:
obtaining standard parameters corresponding to the product parameters, and determining the difference between the standard parameters and the product parameters;
obtaining an auxiliary variable according to the difference value, wherein the difference value and the auxiliary variable are positively correlated;
under the condition that the auxiliary variable meets the preset requirement, the undetermined label is adjusted, which specifically comprises the following steps:
if the auxiliary variable exceeds a second threshold, the undetermined label is adjusted to modify the normal state into a critical state and modify the critical state into an abnormal state;
And if the auxiliary variable exceeds a third threshold, the undetermined tag is adjusted to modify the normal state into the abnormal state, and the third threshold is larger than the second threshold.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310307636.XA CN116009463B (en) | 2023-03-28 | 2023-03-28 | Bearing retainer production monitoring method, equipment and medium based on industrial Internet |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310307636.XA CN116009463B (en) | 2023-03-28 | 2023-03-28 | Bearing retainer production monitoring method, equipment and medium based on industrial Internet |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116009463A CN116009463A (en) | 2023-04-25 |
| CN116009463B true CN116009463B (en) | 2023-07-07 |
Family
ID=86030258
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310307636.XA Active CN116009463B (en) | 2023-03-28 | 2023-03-28 | Bearing retainer production monitoring method, equipment and medium based on industrial Internet |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116009463B (en) |
Families Citing this family (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116221038B (en) * | 2023-05-10 | 2023-07-14 | 山东金帝精密机械科技股份有限公司 | Bearing operation monitoring method and device based on wind power bearing retainer |
| CN116578049B (en) * | 2023-05-16 | 2023-10-31 | 安徽企服工业技术有限公司 | Digital transformation method based on industrial Internet |
| CN117234160B (en) * | 2023-09-13 | 2024-03-08 | 广东汇博机器人技术有限公司 | Automatic production remote control system and method |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106843149A (en) * | 2017-03-28 | 2017-06-13 | 吴小江 | A kind of mechanical zero fastener product system of processing |
Family Cites Families (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN210072402U (en) * | 2019-07-31 | 2020-02-14 | 李自拓 | Production line automation monitoring control system |
| CN110990386A (en) * | 2019-11-27 | 2020-04-10 | 工业互联网创新中心（上海）有限公司 | Industrial internet platform monitoring data transmission and exchange method and system |
| AU2020104272A4 (en) * | 2020-12-23 | 2021-03-11 | Hunan Tian He Guo Yun Technology Co., Ltd. | Blockchain-based industrial internet data security monitoring method and system |
| CN113932849A (en) * | 2021-09-30 | 2022-01-14 | 深圳市中金岭南有色金属股份有限公司凡口铅锌矿 | Fault detection method of mining equipment and terminal equipment |
| CN114360703A (en) * | 2021-12-30 | 2022-04-15 | 成都中科信息技术有限公司 | Medical equipment fault early warning method |
| CN114884942A (en) * | 2022-04-18 | 2022-08-09 | 江苏欧软信息科技有限公司 | Industrial equipment internet cloud management method and system |
| CN115393363B (en) * | 2022-10-31 | 2023-03-17 | 山东金帝精密机械科技股份有限公司 | Production early warning method, equipment and medium for bearing retainer |
-
2023
- 2023-03-28 CN CN202310307636.XA patent/CN116009463B/en active Active
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106843149A (en) * | 2017-03-28 | 2017-06-13 | 吴小江 | A kind of mechanical zero fastener product system of processing |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116009463A (en) | 2023-04-25 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN116009463B (en) | Bearing retainer production monitoring method, equipment and medium based on industrial Internet | |
| CN109242276B (en) | Logistics equipment fault monitoring operation and maintenance management system | |
| CN109772724B (en) | Flexible detection and analysis system for major surface and internal defects of castings | |
| CN106996367B (en) | The perception alarm system and perception alarm method of pumping station operation | |
| KR102334965B1 (en) | Predictive maintenance system for efficient management of factory automation equipment and productivity improvement | |
| JP2020027470A (en) | Production management device, production management system, and production management method | |
| CN116468427B (en) | Equipment operation and maintenance intelligent supervision system and method based on big data | |
| CN116188440A (en) | Production analysis optimization method, equipment and medium for bearing retainer | |
| CN114707970B (en) | Electrolytic production parameter determining method | |
| CN108748936A (en) | A kind of injection workshop Intelligent Production Management System and its method | |
| Wang et al. | Intelligent predictive maintenance (IPdM) for elevator service-through CPS, IOT&S and data mining | |
| EP3167975A1 (en) | Installation used in the metallurgy, rolling, smithing or piping industry and method for the operation thereof | |
| CN114168576A (en) | Internet of things data processing method, equipment and storage medium | |
| CN212375416U (en) | Electroplating system | |
| JP2013228297A (en) | Automatic defect inspection system | |
| CN106776911A (en) | Lot abnormality processings optimization method and system that the alarm of WAT boards causes | |
| CN111079954A (en) | Communication equipment overhaul management system based on big data | |
| CN104164555A (en) | Visualization and interactive sequence control system and method of medium and thick plate heat treatment production line | |
| CN116090724B (en) | Intelligent management platform based on steel bar production | |
| CN116362561A (en) | Centralized control station operation auxiliary decision-making method based on big data | |
| CN111624961A (en) | Control method and control system for hanging system | |
| CN114815760A (en) | Safe production tracking and processing system and method | |
| CN115456963A (en) | Stock yard belt deviation detection method and system based on visual identification | |
| CN111768150A (en) | Logistics equipment health management platform based on 5G network | |
| CN109254009B (en) | Real-time detection processing system for embossing of nailing section |
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 |