Information providing method and system

Abstract

The present invention discloses an information providing method and system, the method comprising: an edge computing device acquires product data and / or historical operation data; the edge computing device determines at least one characteristic description tag of an industrial product based on the product data, and uses at least one characteristic description tag of the industrial product as a characteristic of the industrial product; and / or, determines at least one characteristic description tag of a user based on historical operation data, and uses at least one characteristic description tag of the user as a characteristic of the user; the edge computing device sends the characteristics of the industrial product and / or the characteristics of the user to a human-computer interaction device for display on a human-computer interaction interface. The present invention provides reference suggestions for users to operate and control industrial products.

Description

Technical Field

[0001] The present invention relates to the field of computer control technology, and in particular to an information providing method and system. Background Art

[0002] Industrial automation products (e.g., CNC machine tools, frequency converters, etc.) have many functions, parameters, and operations, and users who operate industrial automation products have various characteristics, such as maintenance engineers, operators, etc. Different users have different work goals, operating habits, etc. Therefore, it is necessary to provide some adaptive personalized information for a certain user's operation of a certain industrial product to achieve effectiveness and efficiency of the operation. Summary of the invention

[0003] In view of this, an object of the present invention is to provide an information providing method and system, which can provide some adaptive personalized information and provide a reference for users to operate and control industrial products.

[0004] On the one hand, an embodiment of the present invention provides an information providing method, the method comprising: an edge computing device acquires product data of an industrial product and / or historical operation data of a user who operates the industrial product; the edge computing device determines at least one feature description tag of the industrial product according to the product data, and uses at least one feature description tag of the industrial product as a feature of the industrial product; and / or, determines at least one feature description tag of the user according to the historical operation data, and uses at least one feature description tag of the user as a feature of the user; and the edge computing device sends the feature of the industrial product and / or the feature of the user to a human-computer interaction device for display on a human-computer interaction interface of the human-computer interaction device. In an embodiment of the present invention, the edge computing device analyzes user features and industrial product features according to the acquired product data and historical operation data, and then displays them on the human-computer interaction interface, and both the user features and the industrial product features are described by at least one feature description tag, and the specific conditions of the user's work content, work objectives, common operations, etc. can be understood through at least one feature description tag of the user, and the specific conditions of the work characteristics, common operations, functional characteristics, etc. of the industrial product can be understood through at least one feature description tag of the industrial product. The specific circumstances of the above-mentioned users and industrial products can provide a reasonable reference for users to control the operation of industrial products, thereby achieving high efficiency and effectiveness of the operation control.

[0005] In some embodiments, the edge computing device determines at least one characteristic description tag of the industrial product based on the product data, including: the edge computing device extracts key fields describing the industrial product from the product data, calculates the similarity between the extracted key fields and a plurality of preset product characteristic description tags, and determines the product characteristic description tags with a similarity higher than a first predetermined value as the characteristic description tag of the industrial product; and / or, the edge computing device determines at least one characteristic description tag of the user based on the historical operation data, including: the edge computing device extracts key fields describing the user from the historical operation data; calculates the similarity between the extracted key fields and a plurality of preset user characteristic description tags; and determines the user characteristic description tag with a similarity higher than a second predetermined value as the user's characteristic description tag. In the embodiment of the present invention, by calculating the similarity between the key fields in the product data and a plurality of preset product characteristic description tags, at least one product characteristic description tag with a higher similarity is selected as the characteristic of the industrial product. The method for determining the user characteristic is similar to the method for determining the industrial product characteristic. This calculation method is simple and easy to implement.

[0006] In some embodiments, the method further includes: the edge computing device sends the characteristics of the industrial product and the characteristics of the user to the cloud platform; the cloud platform determines the recommended cloud function of the industrial product based on the characteristics of the industrial product and the characteristics of the user, and sends the recommended cloud function to the human-computer interaction device through the edge computing device to be displayed on the human-computer interaction interface. Since the embodiment of the present invention also uses the cloud platform to determine the recommended cloud function, the personalized information of the recommended cloud function is displayed on the human-computer interaction device, so as to provide reference suggestions for users to use the industrial product functions.

[0007] In some embodiments, the cloud platform determines the recommended cloud function of the industrial product according to the characteristics of the industrial product and the characteristics of the user, including: the cloud platform calculates the user's interest in a plurality of preset cloud functions according to the characteristics of the industrial product and the characteristics of the user; and determines the cloud function with a higher interest than a third predetermined value as the recommended cloud function. The embodiment of the present invention calculates the user's interest in a plurality of cloud functions, and then selects the cloud function with a high interest as the recommended function. This method is simple and easy to implement.

[0008] In some embodiments, the cloud platform uses a first formula to calculate the user's interest level in each cloud function, and the first formula includes:

[0009]

[0010] Where interest1 represents the user's interest in the cloud function; μ User represents the weight value of the relationship between the user and the cloud function; N represents the number of characteristic description tags of the cloud function; p User，k represents the relevance of the user to the kth feature description tag of the cloud function; q k，Func Represents the weight value of the kth feature description label of the cloud function; μ product The weight value representing the relationship between the industrial product and the cloud function; p product，k Indicates the relevance of the industrial product to the kth feature description label of the cloud function.

[0011] In some embodiments, the cloud platform determines the recommended cloud function of the industrial product according to the characteristics of the industrial product and the characteristics of the user, including: the cloud platform performs collaborative filtering on multiple preset cloud functions according to the characteristics of the industrial product to obtain at least one first cloud function; performs collaborative filtering on multiple preset cloud functions according to the characteristics of the user to obtain at least one second cloud function; and determines the common cloud function of the at least one first cloud function and the at least one second cloud function as the recommended cloud function. The embodiments of the present invention use collaborative filtering to determine the recommended cloud function, which can improve the speed and robustness of the algorithm.

[0012] In some embodiments, the method further includes: the edge computing device sends the characteristics of the industrial product, the characteristics of the user, and the current operation information of the user on the industrial product to the cloud platform; the cloud platform determines the recommended operation of the user on the industrial product based on the characteristics of the industrial product, the characteristics of the user, and the current operation information, and sends the recommended operation to the human-computer interaction device through the edge computing device to be displayed on the human-computer interaction interface. The embodiment of the present invention also determines the recommended operation through the cloud platform and displays it on the human-computer interaction device, providing reference, guidance, suggestions, etc. for the user's operation of the industrial product.

[0013] In some embodiments, the cloud platform determines the user's recommended operation for the industrial product based on the characteristics of the industrial product, the characteristics of the user, and the current operation information, including: the cloud platform calculates the user's interest in multiple preset historical operations based on the characteristics of the industrial product, the characteristics of the user, and the current operation information, and determines the historical operation with a higher interest level than a fourth predetermined value as the recommended operation. The embodiment of the present invention calculates the user's interest level in multiple historical operations respectively, and then selects the historical operation with a high interest level as the recommended operation. This method is simple and easy to implement.

[0014] In some embodiments, the cloud platform uses a second formula to calculate the user's interest level in each historical operation, and the second formula includes:

[0015]

[0016] Among them, interest2 represents the user's interest in the historical operation, μ′ User Represents the weight value of the relationship between the user and the historical operation, p′ User，k represents the relevance of the user to the kth feature description label of the historical operation, q k，Operation Represents the weight value of the kth feature description label of the historical operation, μ′ product The weight value representing the relationship between the industrial product and the historical operation, p′ product，k represents the relevance of the industrial product to the kth feature description tag of the historical operation, and M is the number of feature description tags of the historical operation.

[0017] On the other hand, the present invention provides an information providing system, which includes: a human-computer interaction device; an industrial product; and an edge computing device, wherein the edge computing device connects the human-computer interaction device and the industrial product, and the edge computing device is used to obtain product data of the industrial product and / or historical operation data of a user who operates the industrial product; determine at least one feature description tag of the industrial product based on the product data, and use at least one feature description tag of the industrial product as a feature of the industrial product; and / or, determine at least one feature description tag of the user based on the historical operation data, and use at least one feature description tag of the user as a feature of the user; and send the features of the industrial product and / or the features of the user to the human-computer interaction device for display on the human-computer interaction interface of the human-computer interaction device.

[0018] In some embodiments, the system further comprises: a cloud platform;

[0019] Among them, the edge computing device is also used to send the characteristics of the industrial product and the characteristics of the user to the cloud platform; the cloud platform is used to determine the recommended cloud function of the industrial product based on the characteristics of the industrial product and the characteristics of the user, and send the recommended cloud function to the human-computer interaction device through the edge computing device for display on the human-computer interaction interface.

[0020] In some embodiments, the system further comprises: a cloud platform;

[0021] Among them, the edge computing device is also used to send the characteristics of the industrial product, the characteristics of the user and the current operation information of the user on the industrial product to the cloud platform; the cloud platform is used to determine the recommended operation of the user on the industrial product based on the characteristics of the industrial product, the characteristics of the user and the current operation information, and send the recommended operation to the human-computer interaction device through the edge computing device for display on the human-computer interaction interface. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings so that the above and other features and advantages of the present invention will be more apparent to those skilled in the art. In the accompanying drawings:

[0023] Figure 1 is a flow chart of an information providing method in one embodiment of the present invention;

[0024] Figure 2 is a schematic diagram of the structure of an information providing system in one embodiment of the present invention;

[0025] Figure 3 is a schematic diagram of a human-computer interaction interface for displaying industrial product features, user features, and recommended functions in one embodiment of the present invention;

[0026] Figure 4 is a schematic diagram of a human-computer interaction interface showing feature description labels in industrial product features and user features in one embodiment of the present invention;

[0027] Figure 5 is a schematic diagram of a human-computer interaction interface showing recommended parameter values ​​in one embodiment of the present invention;

[0028] Figure 6 is a schematic diagram of a human-computer interaction interface for displaying recommended maintenance suggestions in one embodiment of the present invention;

[0029] The reference numerals are as follows:

[0030] 101～103 step 200 Information provision system 201a~201e Various industrial products 202 Human-computer interaction equipment 203 Edge computing devices 204 Gateway and\or Firewall 205 Cloud Platform 301 Icon for user feature 302 Icons of industrial product characteristics 303a, 303b Recommended basic cloud capabilities 304a, 304b Recommended advanced cloud features 401a~401h Multiple feature description labels for user features 402a~402h Multiple feature description tags for industrial product features 501 Parameter value input box on the operation recommendation interface 502 A display box for parameter recommended values ​​on the operation recommendation interface 503 The minimum value of the parameter on the operation recommendation interface 504 The maximum value of the parameter on the operation recommendation interface 505 - Current values ​​of parameters on the operation recommendation interface 601a~601c Multiple fault warnings on an operation recommendation interface 602a~602c Multiple fault causes and corresponding maintenance suggestions on the operation recommendation interface DETAILED DESCRIPTION

[0031] In order to have a clearer understanding of the technical features, purposes and effects of the invention, the specific embodiments of the present invention are now described with reference to the accompanying drawings. The same reference numerals in the drawings represent components with the same structure or similar structures but the same functions.

[0032] In this document, “exemplary” means “serving as an example, instance or illustration”, and any diagram or implementation described in this document as “exemplary” should not be interpreted as a more preferred or more advantageous technical solution.

[0033] In order to simplify the drawings, only the parts related to the present invention are schematically shown in each figure, and they do not represent the actual structure of the product. In addition, in order to simplify the drawings and facilitate understanding, in some figures, only one of the parts with the same structure or function is schematically drawn or marked.

[0034] In one aspect, the present invention provides a method for providing information, such as Figure 1 As shown, in box S101, the edge computing device obtains product data of an industrial product and / or historical operation data of a user who operates the industrial product.

[0035] In one example, the edge computing device can obtain the above-mentioned product data and / or historical operation data in response to the trigger information from the human-computer interaction device. Specifically, when an operation on an industrial product is received on the human-computer interaction interface of the human-computer interaction device, the trigger information can be sent to the edge computing device. For example, when a user operates an industrial product on the human-computer interaction interface of the human-computer interaction device, the edge computing device can be triggered to perform the operations in boxes S101 to 103.

[0036] It is understandable that the human-machine interaction device has a human-machine interaction interface, and the operation of industrial products can be realized through the human-machine interaction device. The specific form of the human-machine interaction device is not limited, and it can be a common user terminal, such as a mobile phone, a tablet computer, a personal computer, etc., and it can also be a special device for operating and controlling industrial products.

[0037] It is understandable that the industrial product may be a numerically controlled machine tool (CNC for short), a programmable logic controller (PLC), a drive, a frequency converter, and the like.

[0038] It is understandable that the above-mentioned users are users who use human-computer interaction devices to operate and control industrial products.

[0039] Among them, the connection method between edge computing devices and industrial products and human-computer interaction devices can be network connection.

[0040] For example, at a work site, user A logs in to the operation control system on the human-computer interaction device on site. When logging in to the system, user A needs to enter information such as user name and password to determine whether user A is a registered user of the operation control system and whether the login information of the registered user is filled in correctly. After user A logs in to the system, he will see multiple industrial products, which are industrial equipment on site, and these industrial products are all connected to the edge computing device. User A can operate and control these industrial products on the human-computer interaction device. When user A selects one of the industrial products B on the human-computer interaction interface and operates it, an operation control instruction for the industrial product B is generated. Industrial product B receives the operation control instruction and can perform corresponding operations. Among them, the human-computer interaction device and each industrial product can be connected through a network, and the two can directly communicate and control. Of course, the human-computer interaction device and the industrial product can also communicate and transmit data through the edge computing device to achieve operation control. When user A operates and controls industrial product B on the human-computer interaction interface, the human-computer interaction device will send trigger information to the edge computing device to trigger the edge computing device to perform the operations in box S101 to box 103.

[0041] In actual application, historical operation data can be stored on the human-computer interaction device, so the edge computing device can obtain the user's historical operation data on the industrial product from the human-computer interaction device. Product data can be stored in the edge computing device, industrial product or cloud platform, so the edge computing device can obtain the product data of the industrial product from the edge computing device itself, industrial product or cloud platform.

[0042] In actual application, the product data may include configuration files, work log files, key parameters, etc. of industrial products. The historical operation data may include information such as user operation logs.

[0043] In the previous example, the edge computing device obtains product data from industrial product B and obtains historical operation data of user A on industrial product B from the human-computer interaction device.

[0044] In box S102, the edge computing device determines at least one feature description tag of the industrial product based on the product data, and uses the at least one feature description tag of the industrial product as a feature of the industrial product; and / or determines at least one feature description tag of the user based on the historical operation data, and uses the at least one feature description tag of the user as a feature of the user.

[0045] In a specific implementation, the process of determining the characteristics of the industrial product by the edge computing device, that is, the process of determining at least one characteristic description tag of the industrial product according to the product data, may include:

[0046] Extract key fields describing the industrial product from the product data; calculate the similarity between a plurality of preset product feature description tags and the key fields respectively; and determine the product feature description tag with a similarity higher than a first predetermined value as the feature description tag of the industrial product.

[0047] Among them, the key field is the key information in the product data, specifically the field in the product data that is most closely related to the industrial product.

[0048] Among them, the preset multiple product feature description tags may include feature description tags of multiple industrial products in multiple aspects, so that a suitable feature description tag can be matched to any industrial product in the human-computer interaction device.

[0049] For example, through the above steps, multiple feature description labels of a machine tool can be obtained: CNC machine tool, long working time, high workload, high failure rate, and common failures.

[0050] It is understandable that product features can be used to understand some specific situations of industrial products, such as product types, application scenarios, working characteristics, common operations, functional characteristics, etc.

[0051] In a specific implementation, the process of the edge computing device determining the characteristics of the user, that is, the process of determining at least one characteristic description tag of the user according to the historical operation data, may include:

[0052] Extract key fields describing the user from the historical operation data; determine the similarities between a plurality of preset user feature description tags and the key fields; and determine a user feature description tag with a similarity higher than a second predetermined value as a feature description tag of the user.

[0053] The key field is key information in the historical operation data, specifically, a field in the historical operation data that is most highly associated with the user.

[0054] Among them, the preset multiple user feature description tags can include feature description tags of multiple users (for example, maintenance personnel, operators, quality inspectors, etc.) in multiple aspects, so that any user who logs in on the human-computer interaction device can be matched with a suitable feature description tag.

[0055] For example, through the above steps, multiple feature description tags of a certain user can be obtained: maintenance engineer, CNC machine tool diagnosis, working hours, work efficiency (for example, troubleshooting success rate), common operations, etc.

[0056] It is understandable that some specific information about the user can be learned through the user characteristics, such as the user's identity, work objectives (eg, CNC machine tool diagnosis), work characteristics, common operations, etc.

[0057] In box S103, the edge computing device sends the characteristics of the industrial product and / or the characteristics of the user to the human-computer interaction device for display on the human-computer interaction interface of the human-computer interaction device.

[0058] When the edge computing device sends the characteristics of industrial products and users to the human-computer interaction device, the human-computer interaction device can display them on its human-computer interaction interface. In this way, the user can learn some personalized information about the industrial products and users on the human-computer interaction interface, so as to provide effective reference for the user's subsequent operations.

[0059] In the method provided by the present invention, the edge computing device analyzes the user characteristics and the characteristics of the industrial product based on the acquired product data and / or historical operation data, and then displays them on the human-computer interaction interface, and the user characteristics and the characteristics of the industrial product are described by at least one characteristic description label. Through at least one characteristic description label of the user, the specific conditions of the user's work content, work goals, common operations, etc. can be understood, and through at least one characteristic description label of the industrial product, the specific conditions of the work characteristics, common operations, functional characteristics, etc. of the industrial product can be understood. The specific conditions of the above-mentioned users and industrial products can provide a reasonable reference for the user's operation control of the industrial product, thereby achieving high efficiency and effectiveness of the operation control.

[0060] It is understandable that the personalized information providing method provided by the present invention can be based on Figure 2The information providing system 200 shown in the figure is implemented, and the information providing system 200 includes multiple industrial products 201a~201e, a human-computer interaction device 202, an edge computing device 203, a gateway and / or a firewall 204, and a cloud platform 205, wherein the edge computing device 203 and the multiple industrial products 201a~201e are connected, and the edge computing system is connected to the human-computer interaction device 202, and the edge computing system 203 communicates data with the cloud platform 205 through the gateway and / or the firewall 204. Among them, the edge computing device 203 can determine the user characteristics and industrial product characteristics based on the relevant data obtained from the human-computer interaction device 202 and any industrial product (for example, 201a), and then display the personalized information such as the user characteristics and industrial product characteristics on the human-computer interaction device 203. Of course, the human-computer interaction device 203 can also send user characteristics and industrial product characteristics to the cloud platform 205. The cloud platform 205 determines personalized information such as recommended cloud functions and recommended operations based on these data, and sends these personalized information to the human-computer interaction device 202 through the edge computing device 203 for display. The provision of personalized information such as recommended cloud functions and recommended operations can refer to the relevant content below.

[0061] In some embodiments, in addition to providing personalized information such as product features and user features to users, personalized information such as recommendation functions can also be provided to users. To this end, the personalized information providing method can also include:

[0062] The edge computing device sends the characteristics of the industrial product and the characteristics of the user to a cloud platform;

[0063] The cloud platform determines the recommended cloud function of the industrial product based on the characteristics of the industrial product and the characteristics of the user, and sends the recommended cloud function to the human-computer interaction device through the edge computing device for display on the human-computer interaction interface.

[0064] It is understandable that the above-mentioned recommended cloud functions refer to cloud functions recommended for the user, and the recommended cloud functions may be different for different users.

[0065] In actual applications, gateways, firewalls, etc. can be set up between edge computing devices and cloud platforms to ensure network security.

[0066] There are many ways for the cloud platform to determine recommended cloud functions. The following are two of them:

[0067] (1) Calculating the user's interest levels in a plurality of preset cloud functions based on the characteristics of the industrial product and the characteristics of the user; and taking a cloud function whose interest level is higher than a third predetermined value as the recommended cloud function.

[0068] The size of the third preset value can be set as needed.

[0069] The first formula may be used to calculate the user's interest in each cloud function. The first formula includes:

[0070]

[0071] Where interest1 represents the user's interest in the cloud function; μ User represents the weight value of the relationship between the user and the cloud function; N represents the number of characteristic description tags of the cloud function; p User，k represents the relevance of the user to the kth feature description tag of the cloud function; q k，Func Represents the weight value of the kth feature description label of the cloud function; μ product The weight value representing the relationship between the industrial product and the cloud function; p product，k Indicates the relevance of the industrial product to the kth feature description label of the cloud function.

[0072] The above q k，Func The weight value may be provided in advance by professionals or calculated by an algorithm, for example, by subtracting word frequency from inverse document frequency.

[0073] The above parameter p User，k , i.e., the relevance of the user to the kth feature description tag of the cloud function, can be understood as the similarity between the kth feature description tag of the cloud function and the user, where the user is represented by at least one of the above feature description tags. In other words, p User，k It is the sum of the similarities between the kth feature description tag of the cloud function and each feature description tag of the user.

[0074] The above parameter p product，k , i.e., the relevance of the industrial product to the kth feature description tag of the cloud function, can be understood as the similarity between the kth feature description tag of the cloud function and the industrial product, where the industrial product is represented by at least one of the above feature description tags. In other words, it is the sum of the similarities between the kth feature description tag of the cloud function and each feature description tag of the industrial product.

[0075] The above parameters μ User , that is, the weight value of the relationship between the user and the cloud function, for example, the user's click rate on the cloud function.

[0076] The above parameters μ product , that is, the weight value of the relationship between the industrial product and the cloud function, for example, the click rate of the industrial product to the cloud function (that is, the usage rate of the cloud function in the industrial product).

[0077] According to the first formula above, it can be understood that each cloud function can be represented by multiple feature description tags. The above formula can be used to obtain the user's interest level in each cloud function, and then at least one cloud function with a higher level of interest is selected as a recommended cloud function and sent to the edge computing device. The edge computing device then sends the recommended cloud function to the human-computer interaction device and displays it on its human-computer interaction interface, so that users can choose according to their needs.

[0078] (2) Based on the characteristics of the industrial product, collaborative filtering is performed on the preset multiple cloud functions to obtain at least one first cloud function; based on the characteristics of the user, collaborative filtering is performed on the preset multiple cloud functions to obtain at least one second cloud function; and the common cloud function of the at least one first cloud function and the at least one second cloud function is used as the recommended cloud function.

[0079] It is understandable that collaborative filtering is simply to use the preferences of groups with similar interests and common experiences to recommend information that users are interested in. Individuals respond to the information to a certain extent (such as scoring) through a cooperative mechanism and record it to achieve the purpose of filtering and then help others filter information. Based on this principle, according to the characteristics of industrial products, collaborative filtering of multiple cloud functions can obtain at least one cloud function that industrial products are more interested in, that is, the first cloud function; according to the characteristics of users, collaborative filtering of multiple cloud functions can obtain at least one cloud function that users are more interested in, that is, the second cloud function; further, the intersection of the first cloud function and the second cloud function is obtained to obtain the recommended cloud function.

[0080] Since collaborative filtering algorithms have excellent filtering speed and robustness and are very popular in the global Internet field, using collaborative filtering to determine recommendation cloud functions can improve algorithm speed and robustness.

[0081] It is understandable that no matter which method is used to determine the recommended cloud functions, the recommended cloud functions can be divided into basic cloud functions and advanced cloud functions.

[0082] In actual applications, the cloud platform can use big data tools to implement the calculation process of the above two recommended cloud functions. There are many big data tools, such as Hadoop, Spark, Scala, MapReduce, etc.

[0083] For example, if Figure 3 As shown, the human-computer interaction interface displays an icon 301 of user characteristics and an icon 302 of industrial product characteristics. When the user clicks on icon 301 or 302, the human-computer interaction device displays Figure 4The human-computer interaction interface shown in FIG. 4 shows a plurality of feature description tags 401a to 401h of user features and a plurality of feature description tags 402a to 402h of industrial product features. Figure 4 The human-computer interaction interface shown in the figure can provide some personalized information about users and industrial products. Figure 3 Recommended functions are also displayed: 2 recommended basic cloud functions 303a and 303b, and 2 recommended advanced cloud functions 304a and 304b, providing a reference for users to use industrial products.

[0084] In some embodiments, in addition to any of the above personalized information, personalized information such as recommended operations can also be provided to the user. To this end, the personalized information providing method can also include:

[0085] The edge computing device sends the characteristics of the industrial product, the characteristics of the user, and the user's current operation information on the industrial product to the cloud platform;

[0086] The cloud platform determines the user's recommended operation for the industrial product based on the characteristics of the industrial product, the characteristics of the user and the current operation information, and sends the recommended operation to the human-computer interaction device through the edge computing device for display on the human-computer interaction interface.

[0087] It is understandable that the above-mentioned recommended operations can be obtained by the cloud platform through comprehensive analysis based on the characteristics of industrial products, the characteristics of users and current operation information.

[0088] The recommended operation may be an operation suggestion or a parameter value suggestion during an operation, etc. The operation suggestion may be, for example, a maintenance suggestion during a diagnosis or monitoring process.

[0089] For example, Figure 5 The human-computer interaction interface shown is an operation recommendation interface, the purpose of which is to provide users with appropriate parameter value suggestions. The interface displays a parameter value input box 501, in which a parameter value can be entered; the interface also displays a parameter recommended value display box 502, in which the recommended value of the parameter is displayed. The interface also displays a parameter value display bar, the leftmost point 503 on the display bar is the minimum value of the parameter, the rightmost point 504 on the display bar is the maximum value of the parameter, and the position of the triangular indicator block 505 on the display bar is the current value of the parameter.

[0090] For example, Figure 6The human-computer interaction interface shown is an operation recommendation interface, the purpose of which is to provide users with appropriate diagnostic information and maintenance suggestions. In this interface, multiple fault warnings 601a-601c and multiple fault causes and corresponding maintenance suggestions 602a-602c are displayed. The cloud platform can analyze the possible faults of industrial products based on the data sent by the edge computing device, and then provide fault warning information, as well as the root causes of these faults and maintenance suggestions for these faults, thereby providing appropriate personalized information for the diagnosis and maintenance of industrial products.

[0091] Among them, the method for displaying fault warnings on the human-computer interaction interface can specifically be: the cloud platform generates warning information based on the faults that may be caused by the current operation of the industrial product, and sends it to the human-computer interaction device through the edge computing device, so that the user can see the fault warning on the human-computer interaction interface; of course, the cloud platform can also obtain fault warnings from industrial products through the edge computing device, and then send them to the human-computer interaction device through the edge computing device.

[0092] Among them, the method for displaying the cause of the fault and maintenance suggestions on the human-computer interaction interface can be: the cloud platform finds the historical operation with the highest similarity to the current operation, and then sends the cause of the fault and maintenance suggestions corresponding to the historical operation with the highest similarity to the human-computer interaction device, and displays them on the human-computer interaction interface.

[0093] In specific implementation, the process of the cloud platform determining the user's recommended operation for an industrial product may include: calculating the user's interest level in a plurality of preset historical operations based on the characteristics of the industrial product, the characteristics of the user, and the current operation information, and taking the historical operations with a level of interest higher than a fourth predetermined value as the recommended operations.

[0094] The preset multiple historical operations may be optimized historical operations, and each of the historical operations may be marked with multiple description tags. For example, according to the classification of historical operations, a class of historical operations similar to the current operation is found, and then the similarity between each historical operation in the class of historical operations and the current operation is calculated, and then several historical operations with the highest similarity are selected from the class of historical operations as the preset multiple historical operations.

[0095] The size of the fourth preset value can be set as needed.

[0096] The cloud platform may use a second formula to calculate the user's interest in each historical operation, and the second formula includes:

[0097]

[0098] Where interest2 represents the user's interest in the historical operation, μ′ User Represents the weight value of the relationship between the user and the historical operation, p′ User，k represents the relevance of the user to the kth feature description label of the historical operation, q k，Operation Represents the weight value of the kth feature description label of the historical operation, μ′ product The weight value representing the relationship between the industrial product and the historical operation, p′ product，k represents the relevance of the industrial product to the kth feature description tag of the historical operation, and M is the number of feature description tags of the historical operation.

[0099] The above q k，Operation The weight value may be provided by a professional, or obtained by calculating word frequency minus inverse document frequency.

[0100] The above parameter p′ User，k , that is, the relevance of the user to the kth feature description tag of the historical operation, which can be understood as the similarity between the kth feature description tag of the historical operation and the user, where the user feature is represented by at least one feature description tag. In other words, it is the sum of the similarities between the kth feature description tag of the historical operation and each feature description tag of the user.

[0101] The above parameter p′ product，k , i.e., the relevance of the industrial product to the kth feature description tag of the historical operation, can be understood as the similarity between the kth feature description tag of the historical operation and the industrial product, where the industrial product is represented by at least one feature description tag. In other words, it is the sum of the similarities between the kth feature description tag of the historical operation and each feature description tag of the industrial product.

[0102] The above parameter μ′ User , that is, the weight value of the relationship between the user and the historical operation, for example, the click rate of the user on the historical operation.

[0103] The above parameter μ′ product , that is, the weight value of the relationship between the industrial product and the historical operation, for example, the click rate of the industrial product on the historical operation (that is, the usage rate of the historical operation in the industrial product).

[0104] The above formula can be used to obtain the user's interest level in each operation, and then at least one operation with a higher interest level is selected as a recommended operation and sent to the edge computing device. The edge computing device then sends the recommended operation to the human-computer interaction device and displays it on its human-computer interaction interface, so that the user can choose according to his or her needs.

[0105] On the other hand, the present invention further provides an information providing system 200 .

[0106] refer to Figure 2 , the system 200 includes: a human-computer interaction device 202; industrial products 201a-201e; and an edge computing device 203. The edge computing device 203 is connected to the human-computer interaction device 202 and the industrial products 201a-201e. The edge computing device 203 is used to obtain product data of the industrial products 201a-201e and / or historical operation data of users who operate the industrial products 201a-201e; determine at least one feature description tag of the industrial products 201a-201e according to the product data, and use at least one feature description tag of the industrial products 201a-201e as the feature of the industrial products 201a-201e; and / or, determine at least one feature description tag of the user according to the historical operation data, and use at least one feature description tag of the user as the feature of the user; and send the features of the industrial products 201a-201e and / or the features of the user to the human-computer interaction device 202 to be displayed on the human-computer interaction interface of the human-computer interaction device 202.

[0107] In some embodiments, the system 200 may further include: a cloud platform 205 .

[0108] In this case, the edge computing device 203 is also used to send the characteristics of the industrial products 201a~201e and the characteristics of the user to the cloud platform 205; the cloud platform 205 is used to determine the recommended cloud functions of the industrial products 201a~201e based on the characteristics of the industrial products 201a~201e and the characteristics of the user, and send the recommended cloud functions to the human-computer interaction device 202 through the edge computing device 203 for display on the human-computer interaction interface.

[0109] In some embodiments, the system 200 may further include: a cloud platform 205 .

[0110] In this case, the edge computing device 203 is also used to send the characteristics of the industrial products 201a~201e, the characteristics of the user and the current operation information of the user on the industrial products 201a~201e to the cloud platform 205; the cloud platform 205 is used to determine the recommended operations of the user on the industrial products 201a~201e based on the characteristics of the industrial products 201a~201e, the characteristics of the user and the current operation information, and send the recommended operations to the human-computer interaction device 202 through the edge computing device 203 for display on the human-computer interaction interface.

[0111] It is understandable that the personalized information providing system provided by the present invention corresponds to the above-mentioned personalized information providing method. The specific implementation methods, explanations, examples, beneficial effects, etc. of the relevant contents can refer to the corresponding parts of the above-mentioned personalized information providing method, and will not be repeated here.

[0112] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for providing information, characterized in that: include: The edge computing device obtains product data of the industrial product and historical operation data of the user who operates the industrial product; The edge computing device determines at least one feature description tag of the industrial product based on the product data, and uses the at least one feature description tag of the industrial product as a feature of the industrial product; and, determines at least one feature description tag of the user based on the historical operation data, and uses the at least one feature description tag of the user as a feature of the user; and The edge computing device sends the characteristics of the industrial product and the characteristics of the user to a human-computer interaction device for display on a human-computer interaction interface of the human-computer interaction device; Wherein, the method further comprises: The edge computing device sends the characteristics of the industrial product and the characteristics of the user to a cloud platform; The cloud platform determines the recommended cloud function of the industrial product according to the characteristics of the industrial product and the characteristics of the user, and sends the recommended cloud function to the human-computer interaction device through the edge computing device to be displayed on the human-computer interaction interface; The cloud platform determines the recommended cloud function of the industrial product according to the characteristics of the industrial product and the characteristics of the user, including: The cloud platform calculates the user's interest in a plurality of preset cloud functions respectively according to the characteristics of the industrial product and the characteristics of the user; and determines the cloud function whose interest level is higher than a third predetermined value as the recommended cloud function; The cloud platform uses a first formula to calculate the user's interest level in each cloud function, and the first formula includes: Wherein, interest1 represents the user's interest in the cloud function; μ User represents the weight value of the relationship between the user and the cloud function; N represents the number of characteristic description tags of the cloud function; p User，k represents the relevance of the user to the kth feature description tag of the cloud function; q k，F unc represents the weight value of the kth feature description label of the cloud function; μ pro duct represents the weight value of the relationship between the industrial product and the cloud function; p pro duc,tk represents the relevance of the industrial product to the kth feature description label of the cloud function.

2. The method according to claim 1, characterized in that The edge computing device determines at least one feature description tag of the industrial product based on the product data, including: the edge computing device extracts key fields describing the industrial product from the product data; calculates the similarity between the extracted key fields and a plurality of preset product feature description tags, and determines a product feature description tag having a similarity higher than a first predetermined value as a feature description tag of the industrial product; and / or The edge computing device determines at least one feature description tag of the user based on the historical operation data, including: the edge computing device extracts key fields describing the user from the historical operation data; calculates the similarity between the extracted key fields and a plurality of preset user feature description tags; and determines a user feature description tag having a similarity higher than a second predetermined value as the user's feature description tag.

3. The method according to claim 1, characterized in that The cloud platform determines the recommended cloud function of the industrial product according to the characteristics of the industrial product and the characteristics of the user, including: The cloud platform collaboratively filters multiple preset cloud functions according to the characteristics of the industrial product to obtain at least one first cloud function; collaboratively filters multiple preset cloud functions according to the characteristics of the user to obtain at least one second cloud function; and determines the common cloud function of the at least one first cloud function and the at least one second cloud function as the recommended cloud function.

4. The method according to claim 1, characterized in that: Also includes: The edge computing device sends the characteristics of the industrial product, the characteristics of the user, and the user's current operation information on the industrial product to the cloud platform; The cloud platform determines the user's recommended operation for the industrial product based on the characteristics of the industrial product, the characteristics of the user and the current operation information, and sends the recommended operation to the human-computer interaction device through the edge computing device for display on the human-computer interaction interface.

5. The method according to claim 4, characterized in that The cloud platform determines the recommended operation of the user on the industrial product according to the characteristics of the industrial product, the characteristics of the user and the current operation information, including: The cloud platform calculates the user's interest level in a plurality of preset historical operations based on the characteristics of the industrial product, the characteristics of the user, and the current operation information, and determines the historical operations whose interest level is higher than a fourth predetermined value as the recommended operations.

6. The method according to claim 5, characterized in that The cloud platform uses a second formula to calculate the user's interest level in each historical operation, and the second formula includes: Among them, interest2 represents the user's interest in the historical operation, μ′ User Represents the weight value of the relationship between the user and the historical operation, p′ User，k represents the relevance of the user to the kth feature description label of the historical operation, q k，Operation Represents the weight value of the kth feature description label of the historical operation, μ′ product The weight value representing the relationship between the industrial product and the historical operation, p′ product，k represents the relevance of the industrial product to the kth feature description tag of the historical operation, and M is the number of feature description tags of the historical operation.

7. An information providing system (200), characterized in that: include: Human-computer interaction equipment (202); Industrial products (201a-201e); as well as An edge computing device (203), wherein the edge computing device (203) is connected to the human-computer interaction device (202) and the industrial product (201a-201e), and the edge computing device (203) is used to obtain product data of the industrial product (201a-201e) and historical operation data of a user who operates the industrial product (201a-201e); determine at least one feature description tag of the industrial product (201a-201e) based on the product data, and use at least one feature description tag of the industrial product (201a-201e) as a feature of the industrial product (201a-201e); and, determine at least one feature description tag of the user based on the historical operation data, and use at least one feature description tag of the user as a feature of the user; and send the features of the industrial product (201a-201e) and the features of the user to the human-computer interaction device (202) to be displayed on the human-computer interaction interface of the human-computer interaction device (202); The system further comprises: a cloud platform (205), The edge computing device (203) is further used to send the characteristics of the industrial products (201a-201e) and the characteristics of the user to the cloud platform (205); the cloud platform (205) is used to determine the recommended cloud functions of the industrial products (201a-201e) according to the characteristics of the industrial products (201a-201e) and the characteristics of the user, and send the recommended cloud functions to the human-computer interaction device (202) through the edge computing device (203) to be displayed on the human-computer interaction interface; The cloud platform determines the recommended cloud function of the industrial product according to the characteristics of the industrial product and the characteristics of the user, including: The cloud platform calculates the user's interest in a plurality of preset cloud functions respectively according to the characteristics of the industrial product and the characteristics of the user; and determines the cloud function whose interest level is higher than a third predetermined value as the recommended cloud function; The cloud platform uses a first formula to calculate the user's interest level in each cloud function, and the first formula includes: Wherein, interest1 represents the user's interest in the cloud function; μ User represents the weight value of the relationship between the user and the cloud function; N represents the number of characteristic description tags of the cloud function; p User， k represents the relevance of the user to the kth feature description tag of the cloud function; q k，Func Represents the weight value of the kth feature description label of the cloud function; μ pro duct represents the weight value of the relationship between the industrial product and the cloud function; p pro d uc，t k represents the relevance of the industrial product to the kth feature description label of the cloud function.

8. The information providing system (200) according to claim 7, characterized in that: Also includes: Cloud Platform(205), The edge computing device (203) is also used to send the characteristics of the industrial products (201a-201e), the characteristics of the user and the current operation information of the user on the industrial products (201a-201e) to the cloud platform (205); the cloud platform (205) is used to determine the recommended operation of the user on the industrial products (201a-201e) based on the characteristics of the industrial products (201a-201e), the characteristics of the user and the current operation information, and send the recommended operation to the human-computer interaction device (202) through the edge computing device (203) for display on the human-computer interaction interface.

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