Automatic configuration method, device and system for electro-hydraulic control action platform

Abstract

The invention relates to the technical field of electro-hydraulic control hydraulic systems, in particular to an automatic configuration method, device and system for an electro-hydraulic control action platform. The order text at least comprises one or more of equipment information, action names and working conditions of production line equipment in the electro-hydraulic control action platform; extracting keywords in the order text; the keywords at least comprise one or more of an equipment keyword, an action keyword and a working condition keyword; searching the configuration information of the production line equipment in an equipment configuration table through the keyword; configuration information of different production line devices is pre-stored in the device configuration table; and performing parameter configuration on the production line equipment based on the configuration information. By identifying the order text, the configuration information of the production line equipment in the electro-hydraulic control action platform is automatically obtained, and the production line equipment is automatically configured, so that a non-professional user can conveniently use the method and the system, and errors are not easy to occur.

Description

Technical Field

[0001] The present application relates to the technical field of electro-hydraulic controlled hydraulic systems, and in particular to an automatic configuration method, device and system for an electro-hydraulic controlled action platform. Background Art

[0002] In the field of industrial automation, the electro-hydraulic control platform is a widely used electro-hydraulic control system used to precisely control the movement of mechanical equipment, such as lifting columns, lowering columns, automatic following machines, etc. With the development of Industry 4.0 and smart manufacturing, higher requirements are placed on the intelligence, automation, and user-friendliness of the electro-hydraulic control platform, including the ability to quickly respond to changes in production needs, provide flexible configuration options, and achieve efficient data processing and intelligent decision-making.

[0003] Existing electro-hydraulic motion control platforms usually have basic motion control functions. However, configuration file management usually relies on traditional control panels. The configuration process is complicated and error-prone, making it difficult for non-professional users to perform effective configuration. Summary of the invention

[0004] The present application aims to solve at least one of the technical problems in the prior art or related art that configuration file management usually relies on a traditional control panel, the configuration process is complicated and error-prone, and it is difficult for non-professional users to perform effective configuration.

[0005] To this end, the present application provides an automatic configuration method for an electro-hydraulic control action platform, which automatically obtains the configuration information of the production line equipment in the electro-hydraulic control action platform by identifying the order text, and automatically configures the production line equipment, so that non-professional users can use it conveniently and are not prone to errors.

[0006] The present application also provides an automatic configuration device and system for an electro-hydraulic control action platform including this method.

[0007] According to an embodiment of the first aspect of the present application, an automatic configuration method for an electro-hydraulic control action platform is provided, including: obtaining an order text; the order text includes at least one or more of the equipment information, action name and working conditions of the production line equipment in the electro-hydraulic control action platform; extracting keywords in the order text; the keywords include at least one or more of the equipment keywords, action keywords and working condition keywords; searching for the configuration information of the production line equipment in the equipment configuration table through the keywords; the configuration information of different production line equipment is pre-stored in the equipment configuration table; and parameter configuration of the production line equipment is performed based on the configuration information.

[0008] Optionally, extracting keywords from the order text includes: building an entity recognition model; inputting the order text into the entity recognition model to obtain the keywords from the order text.

[0009] Optionally, constructing an entity recognition model includes: collecting a number of order texts as first training data; annotating the first training data with keywords; dividing the annotated first training data into a first training set and a first verification set; inputting the first training set and the first verification set into a NER model for training, and using the trained NER model as an entity recognition model; wherein the first training set is used to train the NER model, and the first verification set is used to iteratively update model parameters in the NER model until a first loss function of the NER model is less than a preset threshold, and the NER model training is judged to be completed.

[0010] Optionally, parameter configuration is performed on the production line equipment based on the configuration information, including: mapping the configuration information according to the configuration template to generate a first parameter configuration file, the configuration template is in JSON format; and sending a first configuration instruction to the production line equipment, the first configuration instruction is used to instruct the production line equipment to perform parameter configuration based on the first parameter configuration file.

[0011] Optionally, sending a first configuration instruction to the production line equipment includes: sending an inquiry signal to the production line equipment; receiving a response signal sent by the production line equipment, the response signal carrying the equipment serial number, the response signal being generated by the production line equipment in response to the inquiry signal; retrieving equipment information of the production line equipment in an equipment list based on the equipment serial number; pre-storing equipment information of all production line equipment in the electro-hydraulic control action platform in the equipment list; determining whether the equipment information of the production line equipment matches the equipment information in the first parameter configuration file; and if so, sending the first configuration instruction to the production line equipment.

[0012] Optionally, after configuring the parameters of the production line equipment based on the configuration information, the method also includes: constructing an adaptive adjustment configuration model; collecting operating data of the production line equipment; the operating data includes at least one or more of configuration data, operating action data, operating working conditions and equipment health status; inputting the operating data into the adaptive adjustment configuration model to generate optimized configuration information; determining whether to use the optimized configuration information; and if so, configuring the parameters of the production line equipment based on the optimized configuration information.

[0013] Optionally, constructing an adaptive adjustment configuration model includes: collecting historical operation data; cleaning and standardizing the historical operation data to obtain second training data; annotating the second training data with equipment characteristics; the equipment characteristics include at least one or more of configuration data, operation action data, operation working conditions and equipment health status; dividing the annotated second training data into a second training set and a second verification set; using the second training set and the second verification set to train the adaptive algorithm model to obtain an adaptive adjustment configuration model; wherein the second training set is used to train the adaptive adjustment configuration model, and the second verification set is used to iteratively update the model parameters in the adaptive adjustment configuration model until the second loss function of the adaptive adjustment configuration model is less than a preset threshold, and it is judged that the training of the adaptive adjustment configuration model is completed.

[0014] The second aspect of the present application provides an automatic configuration device for an electro-hydraulic control motion platform, comprising:

[0015] An acquisition module, used to acquire an order text; the order text includes at least one or more of equipment information, action name and working conditions of production line equipment in the electro-hydraulic control action platform;

[0016] An extraction module, used to extract keywords from the order text; the keywords include at least one or more of device keywords, action keywords and working condition keywords;

[0017] A query module is used to query the configuration information of the production line equipment in the equipment configuration table by using keywords; the equipment configuration table pre-stores the configuration information of different production line equipment;

[0018] The configuration module is used to configure parameters of production line equipment based on configuration information.

[0019] The third aspect of the present application provides an automatic configuration system for an electro-hydraulic control motion platform, including:

[0020] Production line equipment is configured to execute control actions of the electro-hydraulic control action platform;

[0021] The controller is configured to execute an automatic configuration method for an electro-hydraulic control action platform as described in the first aspect or in its various implementations.

[0022] A fourth aspect of the present application provides an electronic device, characterized in that it includes:

[0023] A processor and a memory, the memory is used to store a computer program, and the processor is used to call and run the computer program stored in the memory to execute an automatic configuration method for an electro-hydraulic control action platform as in the first aspect or its various implementations.

[0024] One of the above technical solutions has at least the following advantages or beneficial effects:

[0025] For an automatic configuration method of an electro-hydraulic control action platform in an embodiment of the present application, the method includes: obtaining an order text; the order text includes at least one or more of the equipment information, action name, and working conditions of the production line equipment in the electro-hydraulic control action platform; extracting keywords in the order text; the keywords include at least one or more of the equipment keywords, action keywords, and working condition keywords; querying the configuration information of the production line equipment in the equipment configuration table through the keywords; the equipment configuration table pre-stores the configuration information of different production line equipment; and configuring the parameters of the production line equipment based on the configuration information. By identifying the order text, the configuration information of the production line equipment in the electro-hydraulic control action platform is automatically obtained, and the production line equipment is automatically configured, so that non-professional users can use it conveniently and are not prone to errors.

[0026] An automatic configuration device and system for an electro-hydraulic controlled motion platform provided in an embodiment of the present application is provided with the above method. Since the method has the above technical effect, an automatic configuration device and system for an electro-hydraulic controlled motion platform provided with the method should also have corresponding technical effects. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 A schematic diagram of the structure of an automatic configuration system for an electro-hydraulic control motion platform provided in an embodiment of the present application is shown;

[0028] Figure 2 One of the flow charts of an automatic configuration method of an electro-hydraulic control action platform provided in an embodiment of the present application is shown;

[0029] Figure 3 A second flow chart of an automatic configuration method of an electro-hydraulic control action platform provided in an embodiment of the present application is shown;

[0030] Figure 4 A schematic diagram of the structure of an automatic configuration device for an electro-hydraulic control motion platform provided in an embodiment of the present application is shown;

[0031] Figure 5 A schematic structural diagram of an electronic device provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0032] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0033] As mentioned above, some common production line equipment in comprehensive mining working faces include: hydraulic supports, which are used to support and protect the working face to ensure the stability and safety of the working face; coal mining machines, which are used to mine coal and are key equipment in mining production; scraper conveyors, which are used to transport the coal mined by the coal mining machine to the ground; crushers, which are used to crush large pieces of coal or other ores into small pieces, etc. These production line equipment need to rely on electro-hydraulic control motion platforms for control to improve coal mining efficiency and safety.

[0034] When these production line devices are connected to the electro-hydraulic control motion platform, they need to be configured first. For example, the hydraulic support needs to be configured with its model, working pressure, action type, etc. The existing electro-hydraulic control motion platform configuration file management usually relies on the traditional control panel. For example, when configuring the hydraulic support, the operator needs to first find the configuration page on the traditional control panel, and then manually enter its model, working pressure, action type and other configuration information. The configuration process is complicated and prone to errors, making it difficult for non-professional users to perform effective configuration.

[0035] In order to solve at least one of the technical problems existing in the prior art or related technology, the present application provides an automatic configuration method, device and system for an electro-hydraulic control action platform, the method comprising: obtaining an order text; the order text at least includes one or more of the equipment information, action name and working conditions of the production line equipment in the electro-hydraulic control action platform; extracting keywords in the order text; the keywords at least include one or more of the equipment keywords, action keywords and working condition keywords; querying the configuration information of the production line equipment in the equipment configuration table through the keywords; the equipment configuration table pre-stores the configuration information of different production line equipment; and configuring the parameters of the production line equipment based on the configuration information. By identifying the order text, the configuration information of the production line equipment in the electro-hydraulic control action platform is automatically obtained, and the production line equipment is automatically configured, so that non-professional users can use it conveniently and are not prone to errors.

[0036] The following describes the automatic configuration method, device and system of the electro-hydraulic control action platform according to some embodiments provided by the present application with reference to the accompanying drawings.

[0037] See also Figures 1 to 5 The first aspect of the present application provides an automatic configuration method for an electro-hydraulic control action platform, comprising:

[0038] S210: Obtain order text; the order text includes at least one or more of equipment information, action name and working conditions of production line equipment in the electro-hydraulic control action platform.

[0039] The purchase information of all production line equipment in the electro-hydraulic control action platform corresponding to the order text can be generated from the order of the electro-hydraulic control action platform. The order will include one or more of the equipment information, action name and working conditions of all production line equipment. The order text can be easily exported from the ERP (Enterprise Resource Planning) system or order management system; if it is a paper order, the order text can also be generated by scanning.

[0040] S220: Extract keywords from the order text; the keywords include at least one or more of equipment keywords, action keywords and working condition keywords.

[0041] Keywords are pre-designed core information. The keywords in the order text are extracted through extraction tools. For example, the order text is "Order number 12345, product name XYZ-1000 hydraulic support, working pressure 200MPa, action sequence includes lifting and moving". The equipment keywords extracted from the order text include the equipment name is hydraulic support, the equipment model is XYZ-1000; the working condition keywords include: working pressure is 200MPa; the action keywords include actions such as lifting and moving.

[0042] In an exemplary embodiment, extracting keywords from the order text includes:

[0043] S221: Build an entity recognition model, including:

[0044] S221-1: Collect a certain number of order texts as first training data.

[0045] Export historical order texts from ERP systems or order management systems, or, if real data is not available, create simulated order texts by writing scripts to generate orders with random or predefined attributes. These data will be used to train the entity recognition model so that the model can learn and understand the key information and patterns in the order text.

[0046] Furthermore, the first training data is cleaned and preprocessed to remove information irrelevant to the training model from the order text, such as sales information, delivery information, logistics information, etc., which can reduce data redundancy and reduce overfitting and underfitting in the model training process, thereby improving the efficiency and accuracy of model training.

[0047] S221-2: Perform keyword labeling on the first training data.

[0048] Define keyword categories, such as equipment keywords, including equipment name, equipment model, equipment type, etc.; working condition keywords, including pressure, temperature, flow, time, etc.; action keywords, including lifting, moving, starting, stopping, etc. Establish clear labeling rules for each keyword category, for example, use specific tags to mark keywords, such as <id> 、 <name>Etc., and specify the placement of labels, such as before or after keywords, etc. According to the marking rules, read the order text one by one and mark the keywords.

[0049] S221-3: Divide the labeled first training data into a first training set and a first validation set.

[0050] Organize the annotated order text into a format suitable for model training, such as JSON (JavaScript Object Notation), XML (Extensible Markup Language), etc. According to the specific needs of model training, determine the division ratio between the first training set and the first validation set, such as 70% / 30%, 80% / 20%, etc. Use a randomized method to divide the annotated first training data into the first training set and the first validation set. When dividing the data, try to keep the categories in the first training set and the first validation set, such as equipment type, working conditions, actions, etc., similar in proportion, which will help obtain more accurate performance evaluation on the first validation set during model training.

[0051] S221-4: Input the first training set and the first validation set into the NER model for training, and use the trained NER model as an entity recognition model; wherein the first training set is used to train the NER model, and the first validation set is used to iteratively update the model parameters in the NER model until the first loss function of the NER model is less than a preset threshold, and the NER model training is judged to be completed.

[0052] The NER (Named Entity Recognition) model is an important and basic task in natural language processing. Its main function is to identify and classify pre-defined entity types in a text, such as names of people, places, names of organizations, dates, etc.

[0053] Input the first training set into the NER model, calculate the value of the first loss function by forward propagation, such as the cross entropy loss function or the negative log-likelihood loss function; use optimization algorithms, such as stochastic gradient descent SGD, Adam, etc., to back-propagate and update the model parameters in the NER model according to the gradient of the first loss function; repeat the above forward propagation and back-propagation process, that is, perform multiple rounds of iterations, and in each round of iteration, the data is randomly shuffled and batch processed. After each round of iteration or a fixed number of iterations, use the first validation set to evaluate the performance of the NER model, input the first validation set data into the current model for prediction, and calculate the performance indicators of the model on the first validation set, such as accuracy, recall rate, F1 score, etc. When the value of the first loss function of the NER model on the first validation set is less than the preset threshold, it can be considered that the model has been trained well enough and training can be stopped. This threshold is set according to the specific task, data set and model characteristics; or, observe the performance indicators on the validation set. If the performance indicators do not improve significantly after multiple iterations, it can also be considered that the model has converged and training can be stopped.

[0054] S222: Input the order text into the entity recognition model to obtain keywords in the order text.

[0055] The trained NER model is output as an entity recognition model and can be used in actual named entity recognition tasks. The order text to be recognized is input into the entity recognition model, and the model will output the keywords recognized in the text.

[0056] S230: Query the configuration information of the production line equipment in the equipment configuration table by using the keyword; the equipment configuration table pre-stores the configuration information of different production line equipment.

[0057] The configuration information of various production line equipment is pre-set in the equipment configuration table. The corresponding configuration information can be found in the equipment configuration table through keywords. For example, through the keywords: the equipment name is hydraulic support, the equipment model is XYZ-1000, the working pressure is 200MPa, and the action is lifting and moving, the corresponding configuration information of the XYZ-1000 model hydraulic support when the working pressure is 200MPa and the action is lifting and moving can be found. SQL (Structured Query Language) query can be used to retrieve equipment configuration information based on keywords. The query statement can match the corresponding fields in the equipment configuration table. For example, the WHERE clause is used to specify the values ​​of the fields such as the equipment name is hydraulic support, the equipment model is XYZ-1000, the working pressure is 200MPa, and the action is lifting and moving. The query results will contain the equipment configuration information that matches the keywords.

[0058] S240: Perform parameter configuration on the production line equipment based on the configuration information.

[0059] In an exemplary embodiment, parameter configuration of production line equipment is performed based on configuration information, including:

[0060] S241: Map the configuration information according to the configuration template to generate a first parameter configuration file, where the configuration template is in JSON format.

[0061] Production line equipment may include hydraulic supports, coal mining machines, scraper conveyors, crushers, etc. Each type of production line equipment corresponds to a configuration template. For example, the configuration template of the hydraulic support is as follows:

[0062] {

[0063] "id":"10000",

[0064] "device_type":"Hydraulic support",

[0065] "model":"XYZ-1000",

[0066] "pressure":"200MPa",

[0067] "actions":["lift","move"]

[0068] }

[0069] The configuration template for the coal mining machine is as follows:

[0070] {

[0071] "id":"10001",

[0072] "device_type":"coal mining machine",

[0073] "model":"CMJ-2000",

[0074] "cutting_width":"2.5m",

[0075] "cutting_height":"1.5m",

[0076] "power":"800kW",

[0077] "actions":["cut","forward","backward","rotate"]

[0078] }

[0079] The configuration template of the scraper conveyor is as follows:

[0080] {

[0081] "id":"10002",

[0082] "device_type":"Scraper conveyor",

[0083] "model":"GS-500",

[0084] "length":"500m",

[0085] "width":"1.2m",

[0086] "capacity":"1000t / h",

[0087] "actions":["Start","Stop","Adjust speed"]

[0088] }

[0089] The configuration template of the crusher is as follows:

[0090] {

[0091] "id":"10003",

[0092] "device_type":"crusher",

[0093] "model":"PJ-1000",

[0094] "input_size":"500mm",

[0095] "output_size":"50mm",

[0096] "capacity":"800t / h",

[0097] "actions":["crushing","adjusting feed speed","cleaning"]

[0098] }

[0099] JSON format is language-independent. It uses text to store and represent data, so it can be read and written by any programming language. Many programming languages ​​provide built-in JSON parsers and generators, which greatly simplifies the transmission and processing of data between the client and the server. Whether it is serializing an object into a JSON string or deserializing a JSON string into an object, it can be implemented very conveniently. At the same time, JSON format is a lightweight data exchange format. Compared with XML, it occupies less space with the same amount of data, which makes network transmission more efficient. Moreover, since the data structure of JSON format is clear, data redundancy is reduced, further improving the efficiency of data transmission.

[0100] S242: Send a first configuration instruction to the production line equipment, where the first configuration instruction is used to instruct the production line equipment to perform parameter configuration based on the first parameter configuration file.

[0101] In an illustrative embodiment, sending a first configuration instruction to a production line device includes:

[0102] S242-1: Send an inquiry signal to the production line equipment.

[0103] Before configuring the production line equipment, sending an inquiry signal can obtain the status information, performance parameters, and diagnostic data of the production line equipment. The inquiry signal can be sent by broadcasting.

[0104] S242-2: Receive a response signal sent by the production line equipment. The response signal carries the equipment serial number. The response signal is generated by the production line equipment in response to the inquiry signal.

[0105] When the production line equipment receives the inquiry signal, it will generate a response signal. The response signal carries the device serial number, also known as the device serial number, device ID, etc. The device serial number is used to uniquely identify each device on the production line for easy tracking, management and maintenance.

[0106] S242-3: Query the equipment information of the production line equipment in the equipment list based on the equipment serial number; the equipment list pre-stores the equipment information of all the production line equipment in the electro-hydraulic control action platform.

[0107] Search the device information that matches the device serial number in the device list. For example, if the device serial number is 100, the device information includes the device name as hydraulic support and the device model as XYZ-1000; if the device serial number is 101, the device information includes the device name as coal mining machine and the device model as CMJ-2000.

[0108] S242-4: Determine whether the device information of the production line device matches the device information in the first parameter configuration file; if so, send a first configuration instruction to the production line device.

[0109] When the device information of the production line device matches the device information in the first parameter configuration file, it means that the first parameter configuration file can configure the production line device. At this time, the first configuration instruction is sent to the production line device to configure the production line device.

[0110] If not, a first configuration error alarm is sent. When the device information of the production line device does not match the device information in the first parameter configuration file, it means that the first parameter configuration file cannot configure the production line device. At this time, a first configuration error alarm needs to be sent to prompt the operator to handle it.

[0111] In an illustrative embodiment, Figure 3 As shown, after configuring the parameters of the production line equipment based on the configuration information, the method further includes:

[0112] S310: Building an adaptive adjustment configuration model, including:

[0113] S310-1: Collect historical operation data.

[0114] Collect historical operation data of production line equipment, including configuration data, operation action data, operating working conditions and equipment health status. Configuration data includes configuration information of production line equipment; operation action data includes specific operations and status changes of production line equipment in the process of executing production tasks, such as starting, stopping, speed adjustment, load change, lifting, moving, etc.; operating working conditions include condition parameters of production line equipment when working, such as temperature, humidity, pressure, voltage, current, etc.; equipment health status includes health performance status of production line equipment, such as degree of wear, fault alarm, maintenance history, etc.

[0115] S310-2: Clean and standardize the historical operation data to obtain second training data.

[0116] Cleaning and standardizing historical operation data is an important step in data preprocessing, which can improve data quality, reduce the impact of noise and outliers, and ensure the consistency and comparability of data, thereby providing a reliable foundation for subsequent model training.

[0117] S310-3: Annotate the second training data with equipment characteristics; equipment characteristics include at least one or more of configuration data, operation action data, operation working conditions and equipment health status.

[0118] Equipment feature labeling of the second training data is an important step in machine learning, which involves identifying and labeling key features in the data related to configuration data, operation action data, operating working conditions, and equipment health status. These features will be used as input to the model to train the model to predict the matching relationship between equipment health status and configuration data, operation action data, and operating working conditions.

[0119] S310-4: Divide the labeled second training data into a second training set and a second validation set.

[0120] The process of step S310-4 is the same as step S221-3 and will not be repeated here.

[0121] S310-5: Use the second training set and the second validation set to train the adaptive algorithm model to obtain an adaptive adjustment configuration model; wherein the second training set is used to train the adaptive adjustment configuration model, and the second validation set is used to iteratively update the model parameters in the adaptive adjustment configuration model until the second loss function of the adaptive adjustment configuration model is less than a preset threshold, and it is determined that the training of the adaptive adjustment configuration model is completed.

[0122] Use TensorFlow or PyTorch to build an adaptive algorithm model, such as using a convolutional neural network (CNN) or a recurrent neural network (RNN), so that the model can output optimized configuration information based on the input configuration data, operation action data, operating working conditions and equipment health status. The second loss function can be set to a mean square error (MSE) loss function, a cross entropy loss function, etc. The training process of the adaptive algorithm model is the same as the training process of the NER model in step S221-4, which will not be repeated here.

[0123] S320: Collecting operation data of production line equipment; the operation data includes at least one or more of configuration data, operation action data, operation working conditions and equipment health status.

[0124] Collect the operation data of the production line equipment within a period of time. For example, within one month, for the XYZ-1000 model hydraulic support, the collected configuration information includes the working pressure of 200MPa, the collected operation action data includes the actions of lifting and moving, the collected operation working conditions include the working pressure of 100MPa-150MPa, and the collected equipment health status includes the fault alarm of 2 times.

[0125] S330: Inputting the operating data into the adaptive adjustment configuration model to generate optimized configuration information.

[0126] For example, for the XYZ-1000 model hydraulic support, the configuration information includes a working pressure of 200MPa, the actual operating conditions include a working pressure of 100MPa-150MPa, and the equipment health status includes 2 fault alarms. In order to obtain a better equipment health status, the configuration model is adaptively adjusted to output the optimized configuration information and set the working pressure to 130MPa.

[0127] S340: Determine whether to use optimized configuration information.

[0128] After the optimized configuration information is generated, a prompt message is sent, and the operator can choose whether to use the optimized configuration information according to the actual situation.

[0129] S350: If yes, configure parameters of the production line equipment based on the optimized configuration information.

[0130] The process of step S350 is the same as step S240 and will not be repeated here.

[0131] The second aspect of the present application provides an automatic configuration device for an electro-hydraulic control action platform, such as Figure 4 As shown, including:

[0132] The acquisition module 41 is used to acquire the order text; the order text includes at least one or more of the equipment information, action name and working conditions of the production line equipment in the electro-hydraulic control action platform;

[0133] An extraction module 42 is used to extract keywords from the order text; the keywords include at least one or more of a device keyword, an action keyword, and a working condition keyword;

[0134] The query module 43 is used to query the configuration information of the production line equipment in the equipment configuration table by using keywords; the equipment configuration table pre-stores the configuration information of different production line equipment;

[0135] The configuration module 44 is used to configure parameters of the production line equipment based on the configuration information.

[0136] In some embodiments of the present application, the extraction module 42 can be used to build an entity recognition model; the order text is input into the entity recognition model to obtain keywords in the order text.

[0137] In some embodiments of the present application, the extraction module 42 can be used to collect a number of order texts as first training data; perform keyword labeling on the first training data; divide the labeled first training data into a first training set and a first verification set; input the first training set and the first verification set into the NER model for training, and use the trained NER model as an entity recognition model; wherein the first training set is used to train the NER model, and the first verification set is used to iteratively update the model parameters in the NER model until the first loss function of the NER model is less than a preset threshold, and the NER model training is judged to be completed.

[0138] In some embodiments of the present application, the configuration module 44 can be used to map the configuration information according to the configuration template to generate a first parameter configuration file, and the configuration template is in JSON format; send a first configuration instruction to the production line equipment, and the first configuration instruction is used to instruct the production line equipment to perform parameter configuration based on the first parameter configuration file.

[0139] In some embodiments of the present application, the configuration module 44 can be used to send an inquiry signal to the production line equipment; receive a response signal sent by the production line equipment, the response signal carries a device serial number, and the response signal is generated by the production line equipment in response to the inquiry signal; retrieve the device information of the production line equipment in the device list based on the device serial number; the device list pre-stores the device information of all production line equipment in the electro-hydraulic control action platform; determine whether the device information of the production line equipment matches the device information in the first parameter configuration file; if so, send a first configuration instruction to the production line equipment.

[0140] In some embodiments of the present application, the automatic configuration device of the electro-hydraulic control motion platform further includes:

[0141] A construction module 45 is used to construct an adaptive adjustment configuration model;

[0142] The collection module 46 is used to collect the operation data of the production line equipment; the operation data includes at least one or more of configuration data, operation action data, operation working conditions and equipment health status;

[0143] A generating module 47, for inputting the operating data into the adaptive adjustment configuration model to generate optimized configuration information;

[0144] The judgment module 48 is used to judge whether to use the optimized configuration information; if so, configure the parameters of the production line equipment based on the optimized configuration information.

[0145] In some embodiments of the present application, the construction module 45 can be used to collect historical operation data; clean and standardize the historical operation data to obtain second training data; annotate the second training data with equipment characteristics; the equipment characteristics include at least one or more of configuration data, operation action data, operation working conditions and equipment health status; divide the annotated second training data into a second training set and a second verification set; use the second training set and the second verification set to train the adaptive algorithm model to obtain an adaptive adjustment configuration model; wherein the second training set is used to train the adaptive adjustment configuration model, and the second verification set is used to iteratively update the model parameters in the adaptive adjustment configuration model until the second loss function of the adaptive adjustment configuration model is less than a preset threshold, and it is judged that the training of the adaptive adjustment configuration model is completed.

[0146] The third aspect of the present application provides an automatic configuration system for an electro-hydraulic control action platform, such as Figure 1 As shown, including:

[0147] The production line equipment 100 is configured to execute the control action of the electro-hydraulic control action platform;

[0148] The controller 110 is configured to execute an automatic configuration method for an electro-hydraulic control motion platform in the first aspect or its various implementations.

[0149] The controller 110 can be a mobile phone, a tablet computer, a desktop computer, a laptop computer, a server, an industrial computer, a single-chip microcomputer, a PLC (Programmable Logic Controller), a DSP (digital signal processor), an FPGA (Field Programmable Gate Array), an ASIC (Application-specific integrated circuit), and other devices with storage and computing functions, which are not limited in the embodiments of the present application.

[0150] Since the automatic configuration system for the electro-hydraulic controlled motion platform provided in this embodiment has the automatic configuration method for the electro-hydraulic controlled motion platform provided in any of the above embodiments, the automatic configuration system for the electro-hydraulic controlled motion platform has all the beneficial effects of the automatic configuration method for the electro-hydraulic controlled motion platform provided in any of the above embodiments, which will not be repeated here.

[0151] A fourth aspect of the present application provides an electronic device, such as Figure 5 As shown, including:

[0152] A processor 51 and a memory 52, the memory 52 is used to store computer programs, and the processor 51 is used to call and run the computer program stored in the memory to execute an automatic configuration method for an electro-hydraulic control action platform in the first aspect or its various implementation methods.

[0153] For example, the processor 51 may be used to execute the above method embodiments according to the instructions in the computer program.

[0154] In some embodiments of the present invention, the processor 51 may include but is not limited to:

[0155] General-purpose processor, digital signal processor (DSP), application-specific integrated circuit (ASIC), field programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, etc.

[0156] In some embodiments of the present invention, the memory 52 includes but is not limited to:

[0157] Volatile memory and / or non-volatile memory. Among them, the non-volatile memory can be read-only memory (ROM), programmable ROM (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM) or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link DRAM (SLDRAM) and direct memory bus random access memory (Direct Rambus RAM, DR RAM).

[0158] In some embodiments of the present invention, the computer program may be divided into one or more modules, which are stored in the memory 52 and executed by the processor 51 to complete the method provided by the present invention. The one or more modules may be a series of computer program instruction segments capable of completing specific functions, and the instruction segments are used to describe the execution process of the computer program in the controller.

[0159] like Figure 5 As shown, the electronic device may also include:

[0160] The transceiver 53 may be connected to the processor 51 or the memory 52 .

[0161] The processor 51 may control the transceiver 53 to communicate with other devices, specifically, to send data or data to other devices, or to receive data or data sent by other devices. The transceiver 53 may include a transmitter and a receiver. The transceiver 53 may further include an antenna, and the number of antennas may be one or more.

[0162] It should be understood that the various components in the electronic device are connected via a bus system, wherein the bus system includes not only a data bus but also a power bus, a control bus and a status signal bus.

[0163] It should be noted that the terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein, for example. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0164] In the description of this specification, the description of the terms "one embodiment", "some embodiments", "embodiment", "exemplary embodiment", "example", "specific example" or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, unless they are contradictory.

[0165] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in the field can change, modify, replace and modify the above embodiments within the scope of the present application.< / name> < / id>

Claims

1. A method for automatic configuration of an electro-hydraulic control motion platform, characterized in that: include: Get order text; The order text includes at least one or more of equipment information, action name and working conditions of production line equipment in the electro-hydraulic control action platform; Extracting keywords from the order text; the keywords include at least one or more of device keywords, action keywords and working condition keywords; The configuration information of the production line equipment is retrieved in the equipment configuration table by using the keyword; the configuration information of different production line equipment is pre-stored in the equipment configuration table; Parameters of the production line equipment are configured based on the configuration information.

2. The method for automatic configuration of an electro-hydraulic control motion platform according to claim 1, characterized in that: The extracting keywords from the order text includes: Build an entity recognition model; The order text is input into the entity recognition model to obtain keywords in the order text.

3. The method for automatic configuration of an electro-hydraulic control motion platform according to claim 2, characterized in that: The constructing of the entity recognition model comprises: Collect a certain number of order texts as first training data; Performing keyword labeling on the first training data; Dividing the first labeled training data into a first training set and a first validation set; Inputting the first training set and the first validation set into a NER model for training, and using the trained NER model as the entity recognition model; Among them, the first training set is used to train the NER model, and the first validation set is used to iteratively update the model parameters in the NER model until the first loss function of the NER model is less than a preset threshold, and it is judged that the NER model training is completed.

4. The method for automatic configuration of an electro-hydraulic control motion platform according to claim 1, characterized in that: The performing parameter configuration on the production line equipment based on the configuration information includes: Mapping the configuration information according to the configuration template to generate a first parameter configuration file, wherein the configuration template is in JSON format; A first configuration instruction is sent to the production line equipment, where the first configuration instruction is used to instruct the production line equipment to perform parameter configuration based on the first parameter configuration file.

5. The method for automatic configuration of an electro-hydraulic control motion platform according to claim 4, characterized in that: The sending a first configuration instruction to the production line equipment includes: Send inquiry signals to production line equipment; Receiving a response signal sent by the production line device, wherein the response signal carries a device serial number, and the response signal is generated by the production line device in response to the inquiry signal; Based on the device serial number, retrieve the device information of the production line device in the device list; the device list pre-stores the device information of all production line devices in the electro-hydraulic control action platform; Determine whether the device information of the production line device matches the device information in the first parameter configuration file; If so, a first configuration instruction is sent to the production line equipment.

6. The method for automatic configuration of an electro-hydraulic control motion platform according to claim 1, characterized in that: After configuring parameters of the production line equipment based on the configuration information, the method further includes: Build an adaptive adjustment configuration model; Collecting operation data of the production line equipment; the operation data includes at least one or more of configuration data, operation action data, operation working conditions and equipment health status; Inputting the operating data into the adaptive adjustment configuration model to generate optimized configuration information; Determine whether to use optimized configuration information; If so, parameter configuration is performed on the production line equipment based on the optimized configuration information.

7. The method for automatically configuring an electro-hydraulic control motion platform according to claim 6, characterized in that: The step of constructing the adaptive adjustment configuration model includes: Collect historical operation data; Cleaning and standardizing the historical operation data to obtain second training data; Annotating the second training data with equipment characteristics; the equipment characteristics at least include one or more of configuration data, operation action data, operation working conditions and equipment health status; Dividing the labeled second training data into a second training set and a second validation set; Using the second training set and the second validation set to train an adaptive algorithm model to obtain an adaptive adjustment configuration model; Among them, the second training set is used to train the adaptive adjustment configuration model, and the second validation set is used to iteratively update the model parameters in the adaptive adjustment configuration model until the second loss function of the adaptive adjustment configuration model is less than a preset threshold, and it is judged that the training of the adaptive adjustment configuration model is completed.

8. An automatic configuration device for an electro-hydraulic control action platform, characterized in that: include: Acquisition module, used to obtain order text; The order text includes at least one or more of equipment information, action name and working conditions of production line equipment in the electro-hydraulic control action platform; An extraction module, used to extract keywords from the order text; the keywords include at least one or more of device keywords, action keywords and working condition keywords; A query module, used to query the configuration information of the production line equipment in the equipment configuration table through the keyword; the equipment configuration table pre-stores the configuration information of different production line equipment; A configuration module is used to perform parameter configuration on the production line equipment based on the configuration information.

9. An automatic configuration system for an electro-hydraulic control motion platform, characterized in that: include: Production line equipment is configured to execute control actions of the electro-hydraulic control action platform; A controller is configured to execute an automatic configuration method for an electro-hydraulic control motion platform according to any one of claims 1-7.

10. An electronic device, characterized in that: include: A processor and a memory, wherein the memory is used to store a computer program, and the processor is used to call and run the computer program stored in the memory to execute an automatic configuration method for an electro-hydraulic control action platform as described in any one of claims 1-7.

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