Data acquisition method based on unmanned weighing system interface

Abstract

The invention discloses a data acquisition method based on an unmanned weighing system interface, which comprises the following steps of: constructing an MES system data dictionary interface, setting a data interface field, transmitting basic data to an unmanned system business library, and simultaneously establishing a weighing house unmanned customer and merchant cloud management, transportation and sales management system and a field terminal all-in-one machine. Basic data are stored in an unattended system service library to form complete weighing basic data, the complete weighing basic data are uniformly integrated by a weighing house unattended field management system to form production service data, a production service data interface is established and transmitted to an MES system, and in the process, the MES system establishes a data correction mechanism and a test data matching mechanism to complete weighing of the weighing house. And processing the transmitted data to finally form the data required by the sales business. The problems of data security, data leakage and data accuracy are solved, the efficiency, accuracy and timeliness of data statistics are effectively improved, and the effects of real-time data transmission, clear background details, data full-flow penetration and function point open and instant use are achieved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of information management, and relates to a management algorithm technology of an unmanned weighing system, in particular to a method for interface data collection based on an unmanned weighing system. BACKGROUND

[0002] In the field of enterprise information management, system interface data plays an extremely important role, and it undertakes the role of quickly transmitting information between various business systems, effectively supports the unified standard of enterprise data and the embodiment of data value, and prevents the enterprise informatization from entering the situation of data duplication and information island. With the requirement of business management on production details, more and more production and operation data will be accessed to the main information system through the interface. How to orderly obtain, store, sort out and display these data, and provide data basis for business analysis and meet the requirements of production management has become the top priority of the development of enterprise informationization.

[0003] At present, the MES system is basically based on manual data input by operation personnel, and then the system generates the required information by statistics, which does not meet the needs of enterprises for efficient, safe and stable data acquisition process, and a new method is needed to solve the data acquisition and automatic generation of operation data. For interface transmission errors, cross-cycle timing reading can be used to ensure that the data can still be stably acquired after correction.

[0004] Specifically, the following defects and deficiencies exist: The internal weighing management system (such as the weighing room site system), the sales management system, the MES system and the like are often independently operated, and there is a "data island". The basic information of customers, suppliers and materials is repeatedly stored in each system, and the definition standards are different, which leads to the fact that the data cannot be interchanged. The identification rules of each system for the same business entity are different, and the data integration needs to be manually processed again.

[0005] The data transmission between traditional systems depends on a simple interface, and data loss or error is easily caused by network fluctuations and equipment failures. In addition, there is no effective correction mechanism. If the weighing data is transmitted when the network is interrupted, the data may be lost, and the system has no automatic retransmission or supplement mechanism, and manual reentry is required. The same weighing single may be transmitted multiple times due to system retries, resulting in duplicate records in the MES. If the data needs to be modified, such as filling the test number, the traditional system cannot identify the "modified data", and the old version is easily retained.

[0006] In the traditional process, the weighing data needs to be manually entered, audited and summarized before entering the MES system, resulting in long data processing period (such as the weighing data of the same day can only be generated the next day) and inability to support sales management in real time; the sales department cannot grasp the daily delivery volume and customer pickup progress in real time; the production department is difficult to adjust the production plan in time according to the weighing data (such as when the material out-of-stock volume exceeds the expectation, it is difficult to quickly supplement the production); The matching of weighing data (such as wet weight and train number) and test data (such as grade and moisture) is a core link of concentrate sales, but the traditional technology has two difficulties: Low matching efficiency: manual searching for corresponding test results according to the weighing number, when the train number is large and the test sample is complex, such as combined test of the same batch in multiple trains, it is easy to mismatch, such as associating the test results of train A to train B; Non-uniform rules: the test rules of different concentrates are quite different, such as "one train like" for tin concentrate and "two trains like" for zinc concentrate, which is difficult for manual operation, resulting in calculation errors of core indicators such as dry weight and metal ton.

[0007] The traditional system lacks data full life cycle record, when the data is disputed (such as customer questioning the weighing weight) or needs to be audited, it is difficult to trace the source of the data, modification history; if the weight of a weighing sheet is modified, it is difficult to query the modifier, modification time and modification reason; when the data is transmitted from the weighing system to the MES, if it is lost or wrong, it is difficult to locate the problem in the transmission link or the system processing link. SUMMARY

[0008] To solve the above problems, the purpose of the present application is to provide a method for collecting interface data based on an unmanned weighing system, to realize the acquisition of data of different sources and different categories and the automatic algorithm matching generation function of weighing operation data, so that the weighing data in the weighing room can be automatically acquired by the equipment, and transmitted to the MES system through the interface for further method logic processing to form the data and report required by sales management.

[0009] To achieve the above purpose, the present application provides the following technical scheme: a method for collecting interface data based on an unmanned weighing system, comprising the following steps: Step S1, constructing a data dictionary interface: based on the basic original data of the MES system, constructing a data dictionary interface of the MES system; Step S2, synchronizing basic data: establishing a data dictionary table in the MES system business library, and periodically reading and storing the customer, supplier, material, starting point and terminal basic data in the data dictionary table in the unmanned on-site management system to the unmanned business library; the unmanned business library is called, and a unified uniqueness is created to ensure consistency with the primary ID of the MES system; Step S3, establishing a distribution management system: maintaining procurement plan, sales plan, internal export plan, and import basic data to the system, and storing them in the unattended business library; Step S4, establishing a customer cloud management system: maintaining shipping units, freight plans, procurement contracts, sales contracts, and shipping order data in the system, and storing them in the unattended business library; Step S5, obtaining equipment data: arranging an integrated service terminal at the weighing room site, obtaining related equipment, obtaining the tare weight, gross weight, weighing time, and weighbridge number information transmitted by the equipment end, and storing them in the unattended business library; Step S6, pushing weighing data: establishing a production business data interface to push the data generated by the weighing business to the MES system business library; Step S7, establishing MES system business library data correction logic: the data correction logic includes: comparing the time stamp recorded by the MES system with the historical data to solve the time difference problem; the MES system records the time stamp of each data according to the weighing single primary key ID; when the data is transmitted to the MES system business library, the weighing single primary key ID is compared first; if there is no ID and no time stamp in the business library, it is determined as new data and saved; if the ID already exists, the time stamp is compared, and the business library time stamp is earlier than the original data, and the later one is determined as repeated uploading and not saved, so as to ensure the latest and accurate data, and to solve the time difference problem caused by time synchronization difference; Step S8, establishing an MES system business library manual input mechanism: manual input of production business data is enabled; Step S9, establishing an MES system assay data matching logic: using the data transmitted by the production business data interface to match the MES system assay data, corresponding to the assay results of the weighed sales ore; when the weighing data of the "sales-shipment" type is transmitted to the MES system, the system automatically generates corresponding assay tasks according to the "concentrate type" in the weighing single, and different concentrate types follow different rules; after the assay is completed, the MES system associates the assay results with the corresponding weighing single through the "assay number", ensuring that the "weighing single-assay result" is one-to-one corresponding; Step S10, establishing a business report: based on the production business data, sales data and business reports are formed to meet the business needs, including weighing single list and weighing single summary table functions.

[0010] Further, the step S7 further comprises: according to the transmitted production business data timestamp, if the weighing list primary key ID is consistent, and the data timestamp in the MES business library is earlier than the data timestamp of the production business data transmission, it is judged that the data is modified and re-uploaded, and the MES system business library saves and covers the original data; if the weighing list primary key ID is consistent, and the data timestamp in the MES business library is later than the data timestamp of the production business data transmission, it is judged that the data is repeatedly uploaded, and the MES system business library does not save the data; and a timestamp compatibility mechanism is established, so as to ensure that the addition, modification and deletion of data are kept up-to-date and error-free.

[0011] Further, the step S9 further comprises: according to the different test types and concentrate types, different test rules are adopted respectively, wherein tin concentrate, copper concentrate are one-car same rule, zinc concentrate main element is two-car same rule, impurities are multi-car same comprehensive sample rule, iron concentrate and sulfur-iron concentrate are multi-car same rule, and concentrate moisture is detected separately; when the test is completed and the result is published and saved, the MES system matches the concentrate test result to the weighing list according to the test result and the test number, and calculates the dry weight data and metal ton data of the concentrate in the current weighing list according to the grade and moisture.

[0012] Further, the data transmitted by the production business data interface is timestamped and compared to judge whether the transmitted data is coincident with the historical data or is newly added; and the timestamp also establishes a compatibility mechanism, according to the running time difference of the two servers, having a ±8 hour time difference compatibility mechanism, to ensure that there is no omission of data, and to keep the latest and accurate state without error.

[0013] Further, for the automatic matching mechanism of the test result, according to the divided weighing list type, the type "sales-delivery" is identified, and different test rule judgments are made according to different concentrate types, the results recorded by the test sheet are automatically matched with the weighing list according to the corresponding test number, and the remaining data is calculated to perfect the missing part of the weighing list.

[0014] Further, in step S7, the data correction logic further comprises the following algorithm steps: On the basis of timestamp and primary key check, a data rationality rule library is added, abnormal data is automatically identified and early warning is triggered to avoid error data entering the business library;Based on historical weighing data, multi-dimensional abnormal judgment logic is defined, including weight abnormality, single vehicle load exceeding vehicle rated load ± 30%;Time anomaly, the time interval between two weighings of the same vehicle is less than 10 minutes;Information conflict: license plate number and historical registration place, carrier unit do not match;When the data triggers the abnormal rule, it is marked as "to be audited" state and pushed to the administrator terminal;Introduce a simple machine learning model, continuously optimize the abnormal rule threshold through historical audit data, and reduce the misjudgment rate.

[0015] Further, in step S7, the data correction logic further includes the following algorithm steps: dynamically calculate the time deviation of different systems, adaptively adjust the fault tolerance range, and reduce the data loss caused by different time synchronization;Including: in the unattended system and the MES system, time synchronization package is sent regularly, the sending / receiving time of both parties is recorded, and the cumulative deviation value is calculated;The system automatically generates a time deviation curve to record the deviation trend to determine whether it is continuously expanding;Based on the real-time deviation value, the fault tolerance range of the timestamp comparison is automatically adjusted;If the deviation exceeds the threshold, the system time calibration reminder is triggered and pushed to the administrator terminal;If the timestamp is wrong due to equipment failure, the system determines that it is an invalid timestamp, and marks the data as to be manually checked to avoid directly discarding important data.

[0016] Further, in step S9, the assay data matching logic further includes the following algorithm steps: establish a mine type rule in the MES system, define the economic type and ore type hit by each mine type in different grade combinations, and provide a defined interface specification for the grade interface of the assay system;Integrate assay grade data and dispatching operation data to form statistical data in combination with mine type specifications;The assay system acts as a data provider to provide analysis data of ore grade and metal content, and the calling party is the MES system, which is used to obtain the ore type, ore grade and metal content of the weighing;Establish data interface rules between the MES system and the assay system to determine the format, frequency and content of data transmission, ensure smooth and accurate data interaction between the two systems, build a data dictionary for the MES system and the assay system, and realize accurate mapping of the data dictionaries of the two systems. Through the mapping relationship, eliminate the obstacles caused by the differences in data structures of different systems, and promote the effective integration and utilization of data.

[0017] The working principle of the present application: the present application is a full-process automation solution based on data interaction between the unmanned weighing system and the MES system, and the core is to realize full-link closed-loop management of weighing data from the device end to the business report through multi-system data integration, automatic acquisition and transmission, and intelligent processing and matching;By building a three-level architecture of "basic data layer-business data layer-system user layer", the weighing data is processed in a full-process unmanned manner from acquisition, transmission, correction to application: Basic data layer: integrate MES system basic data (customers, materials, etc.) and unattended system business data (plans, contracts, equipment data, etc.), realize cross-system synchronization through data dictionary interface, and ensure data uniqueness; Business data layer: collect raw data through on-site equipment, transmit to MES system through interface, combine data correction logic and test matching logic to complete data cleaning and association, and generate business data for settlement; System user layer: finally present data in the form of reports (weighing list, summary table, etc.) to support sales and business decision-making.

[0018] The overall process realizes system interaction through.net framework, API technology, ensures data consistency with "primary key ID combined with timestamp" as the core identifier, and realizes "equipment automatic sampling-system automatic processing-report automatic generation" closed loop by replacing manual operation with "standardized logic".

[0019] One of the cores, basic data synchronization and consistency guarantee: data dictionary interface construction, based on MES system raw data (customers, suppliers, materials, etc.), standard data dictionary interface is constructed, data field format, type and primary key ID (such as customer ID, material code) are defined, which is used as "language specification" for cross-system data interaction; Two-way synchronization mechanism, MES system data dictionary table is synchronized to unattended business library regularly (such as every hour), to ensure that the basic data called by unattended system (transportation and sales management, customer cloud management, etc.) is consistent with MES; Through "primary key ID unique binding" mechanism, it is guaranteed that the ID of the same entity (such as the same customer) in the two systems is exactly the same, avoiding data association confusion.

[0020] The second core, weighing data collection and transmission: equipment data collection, deploy integrated service terminal in the weighing room, connect ground scale and surrounding equipment in real time through Internet of Things protocol (such as Modbus, TCP / IP), collect raw equipment data such as tare weight, gross weight, weighing time, ground scale number, etc., and store them in unattended business library; Business data integration, unattended system (transportation and sales management, customer cloud management) associates procurement plan, sales contract, shipping order dispatching and other business data with equipment collection data to form complete weighing list information (including weighing list number, license plate number, material model, etc.); Interface transmission to MES, through production business data interface (based on API technology), the integrated weighing data is pushed to MES system business library, transmission fields include weighing date, weighing type, weight, material information, etc. 20 key items, to ensure data integrity.

[0021] Core three, data correction logic: through the double check of "primary key ID and timestamp", solve the problem of repetition, lag, modification in data transmission; New data judgment, if there is no primary key ID of the weighing slip in the MES business library, or there is ID but no timestamp record, it is judged as new data and directly saved; Modification data judgment, if the primary key ID exists and the timestamp stored in MES is earlier than the timestamp of the transmission data, it is judged as "modified and re-uploaded", covering the old data and updating the timestamp; Repeat data judgment, if the primary key ID exists and the new timestamp is later than the old timestamp, it is judged as repeated upload, refused to save and record log; Time difference compatibility, allow ± 30 seconds of time synchronization error, if the timestamp difference of two systems is within this range, modify through the "take the later timestamp" rule to avoid misjudgment.

[0022] Core four, assay data matching and ore species rule definition, system interface specification and data integration mechanism: from four dimensions of data standardization, system cooperation, business intelligentization and resource utilization optimization, it has significant technical significance; make the weighing system from "simple data acquisition terminal" to "intelligent data hub": realize data interconnection through semantic standardization, improve data value through intelligent association, guarantee data reliability through quality control, accelerate business flow through cooperation optimization, meet the compliance requirements through whole chain traceability.

[0023] Compared with the prior art, the beneficial effects of the present application are: 1、The present application uses a large amount of data of Internet of Things technology, through the deployment of terminal all-in-one machine in the field and the establishment of customer, marketing and field management system, through the transformation of automatic equipment, detailed weighing data is obtained, and the interface is transmitted to the MES system, which reduces the interference of human factors in the field, ensures the transparency, full automation and data security of the concentrate sales process, and realizes the whole process of unmanned interference from the planning initiation of the weighing business to the field transportation and the assay result; 2、Since the sales and marketing data and the assay data are the key operating data, and the data volume is large, manual statistics is used to make plans, details and reports, the workload is too large and the data accuracy cannot be guaranteed; the present application uses the method of integrating with the unmanned weighing system, and generates various details by the method of combining the local data of the MES system, so that personnel do not need to manually count and remember, and the function effect of "point opening" is realized; 3、The present application uses a data correction mechanism for the data interface of the production business data, which can automatically identify whether the current data is new or revised data, the whole process is free from human interference, the process does not need to be controlled, the data correction effect is automatically saved, and the time difference compatibility mechanism is provided; 4、The present application establishes different concentrate types of testing mechanism and testing task according to different weighing types (sales, procurement, internal transportation), combined with data matching and missing data automatic calculation mechanism, the testing personnel only need to test according to the testing task generated by the system, and the system can automatically trace the corresponding weighing sheet according to the test results, and assign values to the element grade of the weighing sheet, and calculate the corresponding dry weight information; 5、After the data acquisition algorithm of the present application is established, the weighing and sales personnel transfer from basic data entry comparison work to data analysis work, reducing the number of on-site personnel and reducing the work intensity of personnel, realizing efficient data collection and statistics, improving the sales settlement efficiency and weighing safety and work efficiency; 6、The present application realizes the whole life cycle tracing of weighing data from collection, transmission, correction to test matching through time stamp recording, primary key ID association and operation log (such as data synchronization log, modification record). The source, modification history and transmission state of each data can be traced back, not only meeting the verification needs of enterprise internal management on data authenticity, but also meeting the audit requirements of supervision departments and reducing compliance risks; 7、The real-time collected weighing data and test data can generate multi-dimensional analysis report after integration, such as different customer pickup quantity trend, each concentrate type grade fluctuation, transportation efficiency analysis, etc.), which can dynamically adjust the sales strategy and optimize the production plan based on these data, realizing the upgrade from 'experience decision' to 'data driven decision'. BRIEF DESCRIPTION OF DRAWINGS

[0024] Figure 1 The development logic flowchart of the present application; Figure 2 The three-layer anomaly detection flowchart in example 2; Figure 3 The schematic diagram of modifying test data in example 3; Figure 4 One of the business report part schematic diagrams; Figure 5 The second of the business report part schematic diagrams. DETAILED DESCRIPTION

[0025] The present application will be further described in detail through specific embodiments combined with the drawings.

[0026] Example 1 The method for automatically generating mining production operation data based on the interface of the mining truck dispatching system is as follows: Step 1: Based on the basic original data in the MES system, the MES system data dictionary interface is constructed; Step 2: Establish a data dictionary table in the MES system business library, and the unattended site management system of the weighing room. Regularly read the customer, supplier, material, starting point, and ending point basic data content in the data dictionary table of the MES system and store them in the unattended business library; The data dictionary data in the MES system is synchronized to the unattended business library regularly, and the unattended business library is called at the same time, and a unified uniqueness is created to ensure consistency with the primary key ID of the MES system; Step 3: Establish an unattended operation and marketing management system for the weighing room. The procurement plan, sales plan, internal outflow plan, and inflow basic data are maintained in the system and stored in the unattended business library; Step 4: Establish an unattended customer cloud management system for the weighing room. The data of the carrier, freight plan, procurement contract, sales contract, and shipping order distribution are maintained in the system and stored in the unattended business library; Step 5: Arrange an integrated service terminal on the site of the weighing room, connect the site weighbridge and related equipment, obtain the tare weight, gross weight, weighing time, and weighbridge number information transmitted by the equipment end, and store them in the unattended system business library; Step 6: Establish an unattended site management system production business data interface for the weighing room, and push the data generated by the weighing business to the MES system business library; The data includes: weighing date, weighing number, weighing room name, weighing type, test number, whether to make up a single, supplier, customer, license plate number, driver, material information, material model (element name), loading location (starting point), unloading location (ending point), first weighing time, weight, second weighing time, weight, and wet tonnage; Step 7: Establish a data correction logic for the MES system business library. Record the time stamp of the data transmitted by the production business data interface, compare it with the historical data in the MES system, and compatible the time difference problem caused by the time synchronization difference; Data correction logic: MES records the timestamp of each data according to the main key ID of the weigh note. When the production business data is transmitted to the MES system business library, the MES system first compares the main key ID of the weigh note. If there is no main key ID of the weigh note and no timestamp record in the business library, it is judged as new data for saving. If the main key ID of the weigh note is in the business library, the data timestamp in the business library corresponding to the main key ID of the weigh note is compared with the timestamp of the production business data transmission. If the main key ID is consistent, and the data timestamp in the MES business library is earlier than the data timestamp of the production business data transmission, it is judged that the data is modified and re-uploaded. The MES system business library saves and covers the original data. If the main key ID is consistent, and the data timestamp in the MES business library is later than the data timestamp of the production business data transmission, it is judged that the data is repeatedly uploaded, and the MES system business library does not save the data. In this way, the addition, modification and deletion of data are kept up-to-date and accurate. It can avoid repeated entry caused by network fluctuations or system retries, such as multiple uploads of the same weigh note by the weighbridge. Ensure that when the data is modified, such as correcting the weight and supplementing the vehicle information, the MES system always saves the latest version. Automatic verification replaces manual checking, improves processing efficiency, especially in scenarios where the daily weigh-in volume reaches thousands of times. Ensure that the weigh-in data used for settlement is the latest and accurate, avoiding settlement disputes caused by data lag. Based on real-time data, accurate production report, inventory analysis and other management decision-making basis are generated. Complete data change history is recorded to meet the requirements of regulatory authorities for data traceability. Step 8: Establish a manual input mechanism for the MES system business library, which can manually input production business data. Manual input mechanism: When the site does not have unmanned weigh-in conditions and does not have data interface and related hardware facilities, the MES system establishes a manual input of weigh-in information mechanism, which can manually maintain all information related to weigh-in based on the existing basic data of the MES system. Step 9: Establish the matching logic of the MES system test data, use the data transmitted by the production business data interface to match the test results of the weighed sales ore. The assay data matching logic: after the production business data is transmitted to the MES system business library for storage, the MES system selects the type of "sales-delivery" according to the type of weighing generated by the unattended sales management system of the weighing room and the assay number, and establishes a sales assay task according to the type of the sold concentrate. The tin concentrate and copper concentrate are the same rules for one car, the main element of zinc concentrate is the same rule for two cars, the impurities are the comprehensive sample rules for multiple cars, the iron concentrate and sulfur iron concentrate are the multiple car rules, and the concentrate moisture is detected separately. When the assay is completed and the results are published and stored, the MES system matches the assay results and the assay number, and corresponds the concentrate assay results to the weighing sheet, and calculates the dry weight data and metal ton data of the concentrate in the current weighing sheet according to the grade and moisture. The data automatic association is realized, the weighing data such as car number and tonnage are accurately matched with the assay results such as grade and moisture, the mistakes caused by manual matching are avoided, such as the assay results of A car are mistakenly associated with B car. Clear assay rules are formulated for different concentrate types to ensure the standardization and consistency of the assay task, and to avoid the non-uniformity of the assay standard caused by the difference in human judgment. The dry weight and metal ton are automatically calculated by algorithm to reduce the manual calculation error and ensure the accuracy of the core data in sales settlement. Through the whole link association of "weighing sheet-assay results", the quality data of each batch of concentrate can be traced, which provides data support for production process optimization and supplier evaluation. Step 10: based on the production business data, the sales data and business report (weighing sheet list and weighing sheet summary table functions) meeting the business requirements are finally formed; as shown in Figure 4 , Figure 5 .

[0027] The application utilizes the.net framework, API technology to realize the function of interface data collection based on unmanned weighing system, and the current daily weighing room sales weighing data (tonnage, assay grade, train number, etc.) is the core data in the enterprise operation and profit creation, which can directly reflect the accuracy of daily, monthly and annual sales, procurement and internal transportation, and realize the comparison of plan completion rate. The scheme can quickly realize the rapid acquisition of weighing condition, and has the advantages of strong universality, strong expansibility, stable use and the like. For the data of production business data interface transmission to the MES system business library, the MES system first compares the weighing single primary key ID. If there is no weighing single primary key ID and no timestamp record in the business library, it is judged as new data for saving. If the weighing single primary key ID is in the business library, the data timestamp of the corresponding weighing single primary key ID in the business library is compared with the timestamp of the production business data transmission. If the weighing single primary key ID is consistent, and the data timestamp in the MES business library is earlier than the data timestamp of the production business data transmission, it is judged that the data is modified and re-uploaded, and the MES system business library saves and covers the original data. If the weighing single primary key ID is consistent, and the data timestamp in the MES business library is later than the data timestamp of the production business data transmission, it is judged that the data is repeatedly uploaded, and the MES system business library does not save the data. For the data that has been transmitted to the MES system, the weighing type and the assay number generated by the unmanned weighing room management system are selected, the type of which is "sales-delivery", and the sales assay task is established according to the type of the sold concentrate. The tin concentrate and copper concentrate are the same rules for one car, the main element of zinc concentrate is the same rule for two cars, the impurities are the comprehensive sample rules for multiple cars, the iron concentrate and sulfur-iron concentrate are the multiple car rules, and the concentrate moisture is detected separately. When the assay is completed and the result is published and saved, the MES system matches the assay result and the assay number, corresponds the concentrate assay result to the weighing single, and calculates the dry weight data and metal ton data of the concentrate in the current weighing single according to the grade and moisture, respectively. Thus, a complete weighing single list and a weighing single summary table are formed. The above is only a preferred embodiment of the present application, and is not used to limit the present application. Any slight modification, equivalent replacement and improvement made to the above embodiment according to the technical essence of the present application shall be included in the protection scope of the technical scheme of the present application.

[0028] Example 2: On the basis of example 1, the data correction logic further includes the following algorithm steps: On the basis of timestamp and primary key verification, increase the data rationality rule base, automatically identify abnormal data and trigger early warning, avoid error data into the business library; Based on historical weighing data, define multi-dimensional abnormal judgment logic, including weight abnormality, single vehicle load exceeds vehicle approved load ± 30%; Time anomaly, the same vehicle twice weighing time interval < 10 minutes; Information conflict: license plate number and historical registration of the registered place, the carrier does not match; When the data triggers the abnormal rule, it is marked as "to be reviewed" state, and pushed to the administrator terminal; Introduce a simple machine learning model, constantly optimize the abnormal rule threshold through historical audit data, reduce the misjudgment rate; With "active error prevention", avoid abnormal data into the business library after the report, settlement chain effect, reduce the cost of artificial post-correction.

[0029] Specific rule base core decision logic Machine learning optimization mechanism model selection adopts lightweight algorithm, such as IsolationForest, One-ClassSVM, for high-dimensional sparse data, such as weighing records, to detect abnormalities; Feature engineering: extract time features (hours, weeks), spatial features (weighing position), business features (customer type) to build multi-dimensional vectors; Iterative optimization: based on expert experience to set threshold value (such as ± 30%) in the initial stage; Learning stage through historical audit data to train model, identify rule blind area (such as the real load of a certain vehicle model often exceeds the approved 25%); Dynamically adjust the rule base every week, convert misjudgment cases into new rules (such as "a certain vehicle model allows 25% floating").

[0030] Dynamic calculation of time deviation of different systems, adaptive adjustment of fault tolerance range, reduction of data loss caused by time asynchronization; including: in the unattended system and MES system, time synchronization package is sent and received regularly, the sending / receiving time of both parties is recorded, and the cumulative deviation value is calculated; the system automatically generates a time deviation curve to record the deviation trend to determine whether it is continuously expanding; based on the real-time deviation value, the fault tolerance range of time stamp comparison is automatically adjusted; if the deviation exceeds the threshold, the system time calibration reminder is triggered and pushed to the administrator terminal; if the timestamp is wrong due to equipment failure, the system determines it as invalid timestamp, marks the data as pending manual verification, and avoids directly discarding important data; a version management mechanism is added to each weighing data to record the modification record throughout the life cycle, supporting backtracking query. When the data correction logic determines to "modify and reupload", the system does not directly overwrite the old data, but generates a new version record while retaining the old version and marking it as "historical version"; all versions are associated through the weighing single primary key ID to form a "version chain". Provide "version traceability" function, users can view all modification records by inputting the weighing single primary key ID, including modification time, operator, and data comparison before and after modification; support filtering by "modification reason" and "time period", meet the compliance audit requirements, such as regulatory department checks data modification rationality. Realize "traceable and auditable" of data modification, solve the problem of "data tampered without trace" in traditional systems, especially suitable for scenarios with high requirements for data authenticity such as concentrate sales.

[0031] Time synchronization package mechanism: two systems send and receive "time synchronization package" at fixed intervals, such as every hour, the package contains the sending system time, accurate to milliseconds, and contains a unique identifier. The receiver records the local receiving time and calculates the single deviation through the formula: Single deviation value = receiver local time - sender system time For example: the unattended system sends time at 10:00:00.000, and the MES system receives time at 10:00:00.500, then the single deviation is 500ms (MES time is 500ms faster than the unattended system).

[0032] Cumulative deviation calculation: the system takes the average of multiple single deviations, such as 12 times / day, to get the "cumulative deviation value", eliminating accidental errors caused by transient network delay. For example: the average of 12 single deviations is 8 minutes, then it is determined that the unattended system time is 8 minutes slower than the MES system.

[0033] Time deviation trend analysis: predict risks and intervene in advance Through "time deviation curve", the deviation change rule can be visualized to avoid small deviation accumulation as a big problem.

[0034] Curve generation logic: With time as the horizontal axis and the cumulative deviation value per day as the vertical axis, the system automatically draws a curve, labels the fluctuation range of the deviation, such as ±2 minutes, and the trend direction, up / down / flat. For example: the deviation increases from 5 minutes to 10 minutes for 3 consecutive days, the curve shows an upward trend, indicating that the system clock deviation is continuously expanding.

[0035] Trend warning threshold: Set the "trend slope threshold", such as an increase in deviation of more than 3 minutes per day. When the curve slope exceeds the threshold, trigger the "potential time misalignment" warning in advance, prompting the administrator to pay attention to the system clock hardware, such as whether the battery-powered floor clock is abnormal.

[0036] 3. Adaptive fault-tolerant adjustment: dynamically match the time deviation, reduce false positives, dynamically adjust the fault-tolerant range of timestamp comparison based on real-time deviation value, solve the problem of fixed fault tolerance such as ±5 minutes that cannot adapt to the actual deviation.

[0037] Fault tolerance range calculation formula: Dynamic fault tolerance range = Real-time cumulative deviation value + Buffer value (min) For example: the real-time deviation is 8 minutes slower than the unattended system compared to the MES, and the fault tolerance range is set to ±10 minutes, 8 minutes deviation + 2 minutes buffer, to ensure that the timestamp difference between the two systems due to normal deviation will not be misjudged as "duplicate data".

[0038] Fault tolerance adjustment period: synchronized with the time deviation monitoring period, ensure that the fault tolerance range always matches the latest deviation every hour. If the deviation fluctuates sharply within a short period of time, from 2 minutes to 15 minutes within 1 hour, temporarily shorten the adjustment period to every 10 minutes to quickly adapt to abnormal situations.

[0039] 4. Extreme case handling: combine fault tolerance with manual verification to avoid data loss For extreme scenarios such as invalid timestamps or deviation exceeding limits, a hierarchical processing mechanism is designed to balance automation and reliability.

[0040] Deviation exceeding limit triggers calibration: set an "absolute deviation threshold", such as ±30 minutes. When the cumulative deviation exceeds this value, the system automatically pushes a calibration reminder to the administrator's terminal, along with a deviation curve screenshot and calibration operation guide, forcing manual intervention to correct the system time.

[0041] Invalid timestamp processing: if the timestamp is obviously abnormal, such as showing 2000-01-01 or future time, the system determines it as "invalid timestamp" and does not directly execute the "discard" operation, but marks it as "pending manual verification" and highlights it in red in the data list, while recording the abnormal reason, such as "timestamp earlier than system deployment time", to ensure that valid weighing data caused by device failure, such as clock battery depletion, is not mistakenly deleted.

[0042] Example 3: On the basis of example 1, the assay data matching logic further includes the following algorithm steps: Establishing a mine type rule in the MES system, defining the economic type and ore type hit by each mine type in different grade combinations, providing a defined interface specification for the grade interface of the assay system; integrating assay grade data and dispatching operation data to form statistical data in combination with the mine type specification; the assay system as a data provider provides analysis data of ore grade and metal content, the calling party is the MES system, which is used to obtain the ore type, ore grade and metal content of the weighing; establishing data interface rules between the MES system and the assay system to determine the format, frequency and content of data transmission, ensuring smooth and accurate data interaction between the two systems, constructing a data dictionary of the MES system and the assay system, realizing accurate mapping of the data dictionaries of the two systems, eliminating the obstacles caused by the differences in data structures of different systems, and promoting effective integration and utilization of data; wherein the economic type includes industrial ore, low-grade ore and waste rock resources, and the ore type includes zinc co-tin associated copper ore, single copper ore and low-grade ore, which provides a defined rule for the grade interface of the assay system, example: by obtaining the assay data of the assay system, the specific mine type is judged in combination with the industrial index rule management, rule example: the specific data transmitted by the assay system is "mining zinc assay grade ≥1.500%, mining tin assay grade ≥0.200%, mining copper assay grade ≥0.400%", then according to the grade and distribution, the mine type is identified as zinc co-tin associated copper ore in the system, which is used as a rule to judge the mine type rule.

[0043] The weighing system obtains the mine type determined by the MES system based on the assay data through the interface, and directly writes it into the weighing list without manual intervention. When the assay system detects that the zinc content of a batch of ore is greater than or equal to 1.5% and the tin content is greater than or equal to 0.2%, the MES system automatically pushes the mine type to the weighing system, and the "mine type" field in the weighing list is automatically filled with "zinc co-tin associated copper ore". The weighing data is synchronously associated with the economic type (such as "industrial ore" and "low-grade ore") determined by the MES system, providing a unified semantic basis for subsequent processes (such as transportation scheduling and settlement pricing).

[0044] The problem of mutual independence of traditional weighing data, weight, vehicle number and assay data grade, mine type and metal content, which cannot be directly associated, is solved, which can avoid the disconnection of "weight data" and "value data", and realize real-time calculation of the metal content value of the ore of a vehicle; The weighing system obtains the assay index corresponding to the ore of the vehicle in the MES system in real time through the interface, such as zinc grade 55% and moisture 8%, and calculates the key indicators, such as Dry weight = wet weight x (1-moisture%); Metal content = dry weight x grade For example, if the weight is 30 tons, the moisture content is 8%, and the zinc grade is 55%, the system automatically calculates the dry weight as 27.6 tons and the zinc metal amount as 15.18 tons, which can be directly written into the weighing slip. Based on the associated ore type and economic type, the subsequent business processes can be automatically triggered. It can realize the quality control of data collection, improve the reliability of data, and be used for intelligent identification of abnormal data such as vehicle tare weight abnormality, metal quantity and weight mismatch; During the weighing data collection stage, the pre-set ore rules in the MES system are verified synchronously.

[0045] For example, if the weight is abnormal: the gross weight of a vehicle is 50 tons, but the theoretical weight calculated based on the test data should be 45 tons (deviation exceeds 10%), the system automatically marks "weight abnormality, pending re-inspection"; For example, if the grade conflicts: the weighing slip is marked "zinc concentrate", but the test data shows that the zinc grade is only 0.8% (far lower than the industrial ore standard of 1.5%), the system triggers a "mine type identification error" warning.

[0046] As shown in Figure 3 , the test data correction can be optimized to ensure the full-link traceability of key value data for sales. After the test results are issued, the weighing system automatically obtains the test results corresponding to the test number in the test system and fills them in, and records the test result correction in detail. The modification date, sample type, sample original number, test number, modified test element, value before and after change, person who made the document, person who changed, change date, etc. are recorded. Ensure that when the test information changes, it can be traced back to the operator.

[0047] It can support full-link traceability of data collection. The weighing system records the source of each piece of data such as "ore type pushed by MES system", processing process such as "industrial ore determined based on test rule X", modification history such as "2025-05-25 10:00:00 predicted value changed to 2025-05-25 15:30:00 actual measured value"; synchronously record the version of the ore determination rule, such as "use a certain rule to determine the ore", to ensure that the audit can trace back to the determination basis of the ore of a certain batch. For example, based on a sales record, the ore data weighed on May 25, 2025 can be queried.

[0048] In this embodiment, data interconnection is realized through semantic standardization of test data matching logic, data value is improved through intelligent association, data reliability is guaranteed through quality control, business flow is accelerated through collaborative optimization, and compliance requirements are met through full-chain traceability.

[0049] The above application of specific examples to illustrate the present invention, is only used to help understand the present invention, and does not limit the present invention. For the skilled in the art to which the present invention belongs, according to the idea of the present invention, several simple deductions, deformation or replacement can be made.

Claims

1. A method for interface data collection based on unmanned weighing system, characterized in that The method comprises the following steps: Step S1, constructing a data dictionary interface: based on the MES system basic original data, constructing an MES system data dictionary interface; Step S2, synchronizing basic data: establishing a data dictionary table in the MES system business library, and regularly reading and storing the customer, supplier, material, starting point and terminal basic data in the data dictionary table into the unattended business library by the unattended site management system of the weighing room; the unattended business library is called, and a unified uniqueness is created to ensure that the primary key ID is consistent with the MES system; Step S3, establishing a transportation and sales management system: maintaining the procurement plan, sales plan, internal export plan and import basic data to the system and storing them in the unattended business library; Step S4, establishing a customer cloud management system: maintaining the transportation unit, freight plan, procurement contract, sales contract and waybill dispatch data to the system and storing them in the unattended business library; Step S5, obtaining equipment data: arranging an integrated service terminal on the site of the weighing room, obtaining related equipment, obtaining the tare weight, gross weight, weighing time and weighbridge number information transmitted by the equipment end and storing them into the unattended business library; Step S6, pushing the weighing data: establishing a production business data interface and pushing the data generated by the weighing business to the MES system business library; Step S7, establishing a data correction logic of the MES system business library: the data correction logic comprises: comparing the time stamp recorded by the MES system with the historical data to solve the time difference problem; the MES system records the time stamp of each data according to the weighing single primary key ID; when the data is transmitted to the MES system business library, the weighing single primary key ID is compared first; if the ID does not exist in the business library and there is no time stamp, it is determined as new data and saved; if the ID already exists, the time stamp is compared, the business library time stamp is earlier, the original data is overwritten, and the late one is determined as repeated uploading and not saved, so as to ensure that the data is the latest and correct, and to solve the time difference problem caused by the time synchronization difference; Step S8, establishing a manual input mechanism of the MES system business library: the production business data can be manually inputted; Step S9, establishing a test data matching logic of the MES system: the data transmitted by the production business data interface is matched with the test data of the MES system, the test result of the weighed sales ore is matched, when the weighing data of the "sales-delivery” type is transmitted to the MES system, the system automatically generates the corresponding test task according to the "concentrate type” in the weighing single, different concentrate types follow different rules; after the test is completed, the MES system associates the test result with the corresponding weighing single through the "test number” to ensure that the "weighing single-test result” is one-to-one; Step S10, establishing a business report: based on the production business data, the sales data and the business report meeting the business demand are formed, including the weighing single list and the weighing single summary table functions.

2. The method of claim 1, wherein, The step S7 further includes: according to the transmitted production business data timestamp, if the weighing list primary key ID is consistent, and the data timestamp in the MES business library is earlier than the data timestamp of the production business data transmission, it is judged that the data is modified and re-uploaded, and the MES system business library saves and covers the original data; if the weighing list primary key ID is consistent, and the data timestamp in the MES business library is later than the data timestamp of the production business data transmission, it is judged that the data is repeatedly uploaded, and the MES system business library does not save the data; and a timestamp compatibility mechanism is established, so as to ensure that the addition, modification and deletion of data are kept up-to-date and accurate.

3. The method of claim 1, wherein, The step S9 further includes: according to the different test types and concentrate types, different test rules are adopted respectively, wherein tin concentrate and copper concentrate are one-car same rule, zinc concentrate main element is two-car same rule, impurities are multi-car same comprehensive sample rule, iron concentrate and pyrite concentrate are multi-car same rule, and concentrate moisture is detected separately; when the test is completed and the result is published and saved, the MES system matches the concentrate test result to the weighing list according to the test result and the test number, and calculates the dry weight data and metal ton data of the concentrate in the current weighing list according to the grade and moisture.

4. The method according to claim 1 or 2, characterized in that, The timestamp of the data transmitted by the production business data interface is compared, it is judged whether the transmitted data is coincident with the historical data or is newly added; and the timestamp also establishes a compatibility mechanism, according to the running time difference of the two servers, it has a ±8 hour time difference compatibility mechanism, so as to ensure that there is no omission of data, and the latest accurate state is kept.

5. The method according to claim 1 or 3, characterized in that, For the automatic matching mechanism of the test result, according to the divided weighing list type, the type "sales-delivery" is recognized, and different test rules are judged according to different concentrate types, the results recorded by the test sheet are automatically matched with the weighing list according to the corresponding test number, and the remaining data is calculated to perfect the missing part of the weighing list.

6. The method of claim 1, wherein, In step S7, the data correction logic further includes the following algorithm steps: On the basis of timestamp and primary key verification, a data rationality rule library is added, abnormal data is automatically identified and a warning is triggered to avoid incorrect data entering the business library; based on historical weighing data, multi-dimensional abnormal judgment logic is defined, including weight abnormality, single vehicle load exceeding vehicle rated load ±30%; time abnormality, the time interval between two weighings of the same vehicle <10 minutes; information conflict: the license plate number and the registered place and the carrier unit do not match; when the data triggers the abnormal rule, it is marked as "to be audited" state and pushed to the administrator terminal; a simple machine learning model is introduced, the abnormal rule threshold is continuously optimized through historical audit data, and the misjudgment rate is reduced.

7. The method of claim 1, wherein, In step S7, the data correction logic further includes the following algorithm steps: The time deviation of different systems is dynamically calculated, the fault tolerance range is adaptively adjusted, and the data loss caused by different time is reduced. The time synchronization package is sent between the unattended system and the MES system at regular intervals, the sending / receiving time of both sides is recorded, the cumulative deviation value is calculated, the time deviation curve is automatically generated by the system, the deviation trend is recorded, and whether the deviation is continuously expanded is judged. Based on the real-time deviation value, the fault tolerance range of the time stamp comparison is automatically adjusted. If the deviation exceeds the threshold value, the system time calibration reminder is triggered and pushed to the administrator terminal. If the time stamp is wrong due to equipment failure, the system determines that it is an invalid time stamp, marks the data as to be manually checked, and avoids directly discarding important data.

8. The method of claim 1, wherein, The assay data matching logic in the step S9 further includes the following algorithm steps: In the MES system, a mineral rule is established, the economic type and the ore type hit by each mineral in different grade combinations are defined, the interface specification of the grade interface of the assay system is provided, the assay grade data and the scheduling operation data are integrated to form statistical data in combination with the mineral specification, the assay system serves as a data provider to provide analysis data of the ore grade and the metal content, the MES system serves as a calling party to obtain the ore type, the ore grade and the metal content of the weighing, the data interface rules of the MES system and the assay system are established to determine the format, the frequency and the content of data transmission, the smooth and accurate data interaction between the two systems is ensured, the data dictionary of the MES system and the assay system is constructed, the accurate mapping of the data dictionaries of the two systems is realized, the obstacles caused by the structural differences of the data of different systems are eliminated through the mapping relationship, and the effective integration and utilization of the data are promoted.

Images