Generation and management system and method for remote intelligent metering test outline

Abstract

The invention relates to the technical field of detection and calibration and Internet of Things, and discloses a generation and management system and method for a remote intelligent metering test outline, and the system consists of a remote database, a field collection and display terminal, a test outline generation and management terminal and a remote guidance terminal. An intelligent Internet of Things remote intelligent control system which is composed of a remote database, a remote computing platform, a mobile terminal and a remote guidance terminal and is based on information interaction is constructed through an Internet of Things network control technology. The system takes data management and supervised machine learning as the core to realize automatic acquisition of standard information, intelligent matching of a test method and a standard, remote editing of a test outline and generation of a high-quality outline text through an automatic typesetting program; the test scheme making and generating efficiency of the long-distance non-standard sample is improved, and the cost of detection personnel for carrying out detection in different places is effectively saved.

Description

Technical Field

[0001] The present invention relates to the fields of detection and calibration technology and the Internet of Things technology, and more specifically, to a system and method for generating and managing a remote intelligent metering test outline. Background Art

[0002] In the current metrology and testing industry, there are still many challenges in the production of intelligent test outlines. Existing practices often rely on manual operations, which are not only time-consuming and labor-intensive, but also prone to errors. First, testers need to conduct on-site confirmation of the samples to be tested, formulate corresponding test methods based on experience and reference to existing technical information, and select relevant standard devices. This is not only lacking in systematization and intelligence, but also has to bear the time and travel cost problems caused by the samples failing to meet the measurement requirements; secondly, the recording of environmental data (such as temperature, humidity, and pressure, etc.) is done manually, which not only cannot understand the fluctuations of environmental factors, but also creates the risk of erroneous records; finally, testers need to write test outlines in graphical text editing software. This process involves a lot of text editing and chart typesetting work, which is not only inefficient, but also the typesetting effect is affected by the text content and typesetting method, and it is difficult to ensure consistency and accuracy.

[0003] Due to the lack of effective management of the test report content, the reusability and expansion flexibility of the test report as a template are limited, which not only increases the time cost of making the test report, but also causes a huge waste of resources.

[0004] Therefore, the present invention proposes a generation and management system and method solution for intelligent metrology test outlines, aiming to improve the efficiency and quality of the testing industry through intelligent and automated means. The system can automatically collect customer inspection information and environmental data, intelligently match test methods and standard devices, quickly generate test outlines and reports, and achieve effective typesetting through a professional text editing and processing system. At the same time, the system also has a periodic reminder function, which can automatically remind test personnel to promptly handle test outlines that are about to expire, ensuring that traceability work is timely and effective.

[0005] Through the implementation of the present invention, not only can the efficiency of making and generating test outlines be significantly improved, the error rate introduced by manual intervention can be reduced, but also the standardization and consistency of outlines made by different testers can be ensured. A machine learning intelligent algorithm is adopted in the test outline formulation system. With the continuous use and accumulation of users, the generation quality of the measurement method can be effectively improved, and the formulation efficiency of the test outline can be improved. The remote test outline generation and management module is operated by a small mobile terminal, and can be logged in through remote verification, and cooperate with the remote guidance terminal to realize remote confirmation of the samples to be tested and remote production and generation of the test outline. It can effectively reduce travel costs and provide a technical basis for the overall planning of outbound testing. Summary of the invention

[0006] In order to overcome the above-mentioned defects existing in the prior art, the present invention provides a remote intelligent metering test outline generation and management system, which is composed of a remote database, an outline generation and management terminal, a mobile field acquisition and display terminal and a remote guidance terminal. There is two-way communication between the remote database, the outline generation and management terminal, the mobile field acquisition and display terminal and the remote guidance terminal. The mobile field acquisition and display terminal includes a temperature and humidity sensor, a video acquisition module, a handwriting display screen and a movable micro-processing terminal. The communication is carried out using the OpenVPN encryption technology based on SSL / TLS, and the ECC encryption method is used to protect the data during data transmission. The outline generation and management terminal is composed of a TEX typesetting system, a supervised machine learning algorithm and an efficient parallel computing terminal. The remote guidance terminal is composed of an image acquisition device and a micro-computing terminal. The mobile field acquisition and display terminal includes a security verification module, an environmental information acquisition module, and a sample information acquisition module to be tested.

[0007] The above technical purpose of the present invention is achieved through the following technical solutions: a remote intelligent metering test outline generation and management system, including a remote database, a mobile field collection and display terminal, a test outline generation and management terminal and a remote guidance terminal, the field collection and display terminal includes a detection personnel information collection module, an environmental information collection module and a sample information collection module; the outline management and generation terminal includes a test outline management module and a test outline generation module.

[0008] A method for generating and managing a remote intelligent metering test outline, characterized in that it comprises the following steps:

[0009] S1. User key login, including:

[0010] (1) Start the mobile terminal:

[0011] The user turns on the pre-configured mobile terminal device on site;

[0012] (2) Key login:

[0013] The user enters the unique key obtained from the inspector to log in;

[0014] (3) Login verification:

[0015] The system verifies the input key to confirm its validity and corresponding user authority;

[0016] (4) Complete verification:

[0017] The customer enters the system information input interface, and the inspector enters the inspector-exclusive interface. The inspector can view the on-site situation in real time through the image acquisition interface;

[0018] S2. Information entry and transmission, including:

[0019] (1) Environmental information collection:

[0020] After the user successfully authenticates and enters the system, the system immediately activates the built-in sensors of the mobile terminal to capture and record the on-site environmental parameters and related environmental indicators in real time; after the test cycle is over, the average values ​​of these environmental parameters are automatically calculated, and the raw data and calculation results are transmitted to the database for subsequent analysis and evaluation;

[0021] (2) Input the information of the sample to be tested. The steps are as follows:

[0022] a. Process start;

[0023] b. Check whether the sample has a quotation number;

[0024] c. Check whether the sample has a certificate number or scan the QR code for inspection;

[0025] d. Information processing of samples without quotation number, certificate number or inspection QR code;

[0026] (3) Information verification and integrity check:

[0027] After the test outline is completed, the test personnel will check the information and completeness. If the check is correct, the system will directly generate a test outline based on this information; if the check is incorrect, the information will be updated and corrected, and a new test outline will be generated. The information will be saved in the database and the matching algorithm will be updated and iterated;

[0028] S3. Presentation of test outline results: The tester organizes the generated test outline into a PDF report format and transmits it to the user terminal.

[0029] Furthermore, in step S2, it is checked whether the sample has a quotation number. If the sample has a quotation number, then: the user enters the quotation number through the input interface, and the system searches based on the existing information, accurately reads various data related to the sample to be tested, and loads this information into the test outline; if the sample does not have a quotation number, then: for samples that have been sent for inspection before, the user can enter the previous certificate number, or scan the QR code on the sample to retrieve and call historical information.

[0030] Furthermore, in step S2, check whether the sample has a certificate number or a scanned QR code for inspection. If the sample has a certificate number or a scanned QR code for inspection, then: the system will search for historical information through data based on the read information and load it; this information includes scope, references, test items, test conditions, test components, data collection and processing, and test result processing; if the sample does not have a certificate number or a scanned QR code for inspection, then: the system guides the user to enter the sample information.

[0031] Furthermore, in step S2, the sample information processing without quotation number and certificate number or inspection QR code includes the following steps:

[0032] (1) User inputs sample information:

[0033] For samples that do not meet the above two conditions, information needs to be collected according to the specific situation. For such special samples, the system provides detailed input interface guidance, requiring users to enter relevant information of the samples to be tested, including: instrument name, model specifications, factory number, quantity, appearance description, grade, expected extraction date and information of the sending unit;

[0034] (2) Image acquisition and remote communication:

[0035] The inspectors can communicate with the site in real time through the image acquisition device, allowing the user to introduce and display the samples in detail; according to the specific requirements of the remote inspectors, the users are guided to conduct detailed inspection and verification of the samples to be inspected, and collect necessary pictures and upload them to the database;

[0036] (3) Intelligent matching:

[0037] After completing the information collection and confirmation, the system will start the intelligent matching program based on machine learning;

[0038] If the match is successful, the information collection module will load the corresponding outline information into the remote guidance terminal, and the test personnel can directly view the corresponding information; the test personnel will confirm the corresponding information based on the on-site inspection of the tested samples; for information that does not meet the requirements, the test personnel will update and correct it in the corresponding text, picture, formula or list module, update it according to actual needs, and save the updated information into the database; the updated data will be used as new training data to train the matching system;

[0039] If the match fails, the tester needs to manually perform more accurate and detailed matching operations based on the existing outline and fill in the information required by the test outline;

[0040] (4) Information verification and integrity check;

[0041] Information verification: During the entire information collection process, each step requires careful verification by the inspector to ensure the accuracy and completeness of the information;

[0042] Completeness Check: The system also automatically performs a completeness check on the information to ensure that all required fields are filled and the information is valid.

[0043] In summary, the present invention has the following beneficial effects:

[0044] (1) High terminal controllability: The present invention realizes efficient controllability of the terminal through the generation and management system of remote intelligent metering test outlines. The system integrates temperature and humidity sensors, video acquisition modules and other equipment through mobile on-site acquisition and display terminals, and can collect on-site environmental data and sample information in real time. Combined with the remote database and outline generation and management terminal, the system can intelligently analyze and process the collected data, thereby realizing remote editing and automatic typesetting of the test outline. In addition, the system uses OpenVPN encryption technology based on SSL / TLS and ECC encryption method for data transmission protection, ensuring the security of terminal operations and the integrity of data.

[0045] (2) High security: In terms of security, the present invention adopts multi-level security measures to protect the security of the entire system. First, the system adopts SSL / TLS encryption technology during data transmission, which is a widely recognized secure communication protocol that can ensure the confidentiality and integrity of data during transmission. Secondly, the system adopts ECC encryption for data storage and processing, which is an efficient public key encryption technology that can provide high security with a smaller key length. In addition, the system also includes a security verification module, which requires the user to enter the remotely received key to complete the preliminary security verification step, further enhancing the security of the system.

[0046] (3) High reliability: The system of the present invention performs well in terms of reliability. The system collects environmental data and sample information in real time, and combined with supervised machine learning algorithms, it can intelligently match test methods and standard devices to quickly generate test outlines and reports. This intelligent processing method reduces the possibility of human error and improves the accuracy and reliability of test outline generation. At the same time, the system has a periodic reminder function that can automatically remind testers to promptly handle test outlines that are about to expire, ensuring that traceability work is timely and effective.

[0047] (4) Versatility: In terms of versatility, the system design of the present invention takes into account the application requirements in different scenarios. The system is not only suitable for laboratory environments, but also can adapt to the testing requirements of field environments. The system can flexibly collect and process data in different environments through mobile field acquisition and display terminals. In addition, the system supports the storage of multiple data formats and chart information, so that the system can be widely used in different test items and test methods. This flexibility and adaptability of the system make it widely versatile and worth promoting.

[0048] (5) Scalability and flexibility: The system is designed with future scalability in mind, allowing for easy addition of new test items, methods, and standard devices. At the same time, the modular design of the system also allows for customization and expansion according to different needs, improving the system's flexibility and ability to adapt to different testing needs.

[0049] (6) High degree of integration: The system of the present invention integrates multiple functional modules such as remote database module, on-site collection and display module, test outline generation and management module and remote guidance module through a highly integrated design to form a complete solution. This integration not only improves the work efficiency of the system, but also simplifies the operation process, allowing test personnel to generate and manage test outlines more conveniently.

[0050] (7) Real-time and dynamic response: The system can respond to changes in the on-site environment and sample information in real time, and realize instant data collection and processing through the Internet of Things technology. This real-time feature enables the system to quickly adapt to changes in on-site conditions, adjust the test plan in a timely manner, and ensure the accuracy and timeliness of the test results.

[0051] (8) Improved efficiency: The Internet of Things technology enables the interconnection of databases, computing platforms, remote guidance modules, and mobile information collection and display modules, which together constitute the generation and management system of remote intelligent metering test outlines, improving the efficiency of information transmission and interconnection. This system can be used to remotely check test requirements, collect data, and quickly generate and produce customized test outlines.

[0052] (9) Intelligent iteration: The supervised machine learning algorithm K nearest neighbor algorithm is used as the core algorithm for automatic generation of detection outlines, realizing the automatic generation mechanism of new sample detection outlines, and through continuous supervision and iteration, its accuracy and intelligence are improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 It is a structural diagram of a remote intelligent metering test outline generation and management system in an embodiment of the present invention;

[0054] Figure 2 It is a module overview diagram of a remote intelligent metering test outline generation and management system in an embodiment of the present invention;

[0055] Figure 3 is a flow chart of sample information collection in an embodiment of the present invention;

[0056] Figure 4 Schematic diagram of a machine learning classification algorithm in an embodiment of the present invention. DETAILED DESCRIPTION

[0057] The following is combined with Figure 1-4 The present invention is described in further detail.

[0058] Embodiment: A remote intelligent metering test outline generation and management system, such as Figure 1-4 As shown, the following is a detailed description of a specific implementation of the system:

[0059] The following steps are involved:

[0060] S1. User key login, including:

[0061] (1) Start the mobile terminal:

[0062] The user turns on the pre-configured mobile terminal device on site;

[0063] (2) Key login:

[0064] The user enters the unique key obtained from the inspector to log in;

[0065] (3) Login verification:

[0066] The system verifies the input key to confirm its validity and corresponding user authority;

[0067] (4) Complete verification:

[0068] The customer enters the system information input interface, and the inspector enters the inspector-exclusive interface. The inspector can view the on-site situation in real time through the image acquisition interface;

[0069] S2. Information entry and transmission, including:

[0070] (1) Environmental information collection:

[0071] After the user successfully authenticates and enters the system, the system immediately activates the built-in sensors of the mobile terminal to capture and record the on-site environmental parameters and related environmental indicators in real time; after the test cycle is over, the average values ​​of these environmental parameters are automatically calculated, and the raw data and calculation results are transmitted to the database for subsequent analysis and evaluation;

[0072] (2) Input the information of the sample to be tested. The steps are as follows:

[0073] a. Process start;

[0074] b. Check whether the sample has a quotation number;

[0075] c. Check whether the sample has a certificate number or scan the QR code for inspection;

[0076] d. Information processing of samples without quotation number, certificate number or inspection QR code;

[0077] (3) Information verification and integrity check:

[0078] After the test outline is completed, the test personnel will check the information and completeness. If the check is correct, the system will directly generate a test outline based on this information; if the check is incorrect, the information will be updated and corrected, and a new test outline will be generated. The information will be saved in the database and the matching algorithm will be updated and iterated;

[0079] S3. Presentation of test outline results: The tester organizes the generated test outline into a PDF report format and transmits it to the user terminal.

[0080] As a preferred solution of this embodiment, in step S2, check whether the sample has a quotation number. If the sample has a quotation number, then: the user enters the quotation number through the input interface, and the system searches based on the existing information, accurately reads various data related to the sample to be tested, and loads this information into the test outline; if the sample does not have a quotation number, then: for samples that have been sent for inspection before, the user can enter the previous certificate number, or scan the QR code on the sample to retrieve and call historical information.

[0081] As a preferred solution of this embodiment, in step S2, check whether the sample has a certificate number or a scanned QR code for inspection. If the sample has a certificate number or a scanned QR code for inspection, then: the system will search for historical information through data based on the read information and load it; this information includes scope, references, test items, test conditions, test components, data collection and processing, and test result processing; if the sample does not have a certificate number or a scanned QR code for inspection, then: the system guides the user to enter the sample information.

[0082] As a preferred solution of this embodiment, in step S2, the sample information processing without quotation number and certificate number or inspection QR code includes the following steps:

[0083] (1) User inputs sample information:

[0084] For samples that do not meet the above two conditions, information needs to be collected according to the specific situation. For such special samples, the system provides detailed input interface guidance, requiring users to enter relevant information of the samples to be tested, including: instrument name, model specifications, factory number, quantity, appearance description, grade, expected extraction date and information of the sending unit;

[0085] (2) Image acquisition and remote communication:

[0086] The inspectors can communicate with the site in real time through the image acquisition device, allowing the user to introduce and display the samples in detail; according to the specific requirements of the remote inspectors, the users are guided to conduct detailed inspection and verification of the samples to be inspected, and collect necessary pictures and upload them to the database;

[0087] (3) Intelligent matching:

[0088] After completing the information collection and confirmation, the system will start the intelligent matching program based on machine learning;

[0089] If the match is successful, the information collection module will load the corresponding outline information into the remote guidance terminal, and the test personnel can directly view the corresponding information; the test personnel will confirm the corresponding information based on the on-site inspection of the tested samples; for information that does not meet the requirements, the test personnel will update and correct it in the corresponding text, picture, formula or list module, update it according to actual needs, and save the updated information into the database; the updated data will be used as new training data to train the matching system;

[0090] If the match fails, the tester will need to manually perform more accurate and detailed matching operations based on the existing outline and fill in the information required by the test outline.

[0091] (4) Information verification and integrity check;

[0092] Information verification: During the entire information collection process, each step requires careful verification by the inspector to ensure the accuracy and completeness of the information;

[0093] Completeness Check: The system also automatically performs a completeness check on the information to ensure that all required fields are filled and the information is valid.

[0094] The generation and management system of the remote intelligent metering test outline provided in this embodiment has security and traceability, which is reflected in the following three aspects:

[0095] (1) Key verification:

[0096] Through key verification, the system can accurately identify and record the user's information to ensure the security and traceability of the calibration work.

[0097] (2) Data encryption and storage:

[0098] The system encrypts the collected and stored sensitive data such as the inspection personnel information to ensure the security of the data.

[0099] (3) Log Records:

[0100] The system records relevant information of each calibration work, such as operation time, operator, calibration results, etc., to facilitate subsequent query and audit.

[0101] This embodiment further improves the security and traceability of calibration work by introducing the key verification function. The system can accurately identify and record the user's information, effectively preventing unauthorized personnel from performing calibration operations. At the same time, the system automatically collects and records relevant information, greatly reducing manual operations and improving work efficiency and accuracy.

[0102] This specific embodiment is merely an explanation of the present invention and is not a limitation of the present invention. After reading this specification, those skilled in the art may make non-creative modifications to the present embodiment as needed. However, as long as they are within the scope of the claims of the present invention, they are protected by the patent law.

Claims

1. A remote intelligent metering test outline generation and management system, characterized in that: It includes a remote database, a mobile on-site collection and display terminal, a test outline generation and management terminal and a remote guidance terminal. The on-site collection and display terminal includes a detection personnel information collection module, an environmental information collection module and a sample information collection module; The outline management and generation terminal includes a test outline management module and a test outline generation module.

2. A method for generating and managing a remote intelligent metering test outline, characterized in that: The following steps are involved: S1. User key login, including: (1) Start the mobile terminal: The user turns on the pre-configured mobile terminal device on site; (2) Key login: The user enters the unique key obtained from the inspector to log in; (3) Login verification: The system verifies the input key to confirm its validity and corresponding user authority; (4) Complete verification: The customer enters the system information input interface, and the inspector enters the inspector-exclusive interface. The inspector can view the on-site situation in real time through the image acquisition interface; S2. Information entry and transmission, including: (1) Environmental information collection: After the user successfully authenticates and enters the system, the system immediately activates the built-in sensors of the mobile terminal to capture and record the on-site environmental parameters and related environmental indicators in real time; after the test cycle is over, the average values ​​of these environmental parameters are automatically calculated, and the raw data and calculation results are transmitted to the database for subsequent analysis and evaluation; (2) Input the information of the sample to be tested. The steps are as follows: a. Process start; b. Check whether the sample has a quotation number; c. Check whether the sample has a certificate number or scan the QR code for inspection; d. Information processing of samples without quotation number, certificate number or inspection QR code; (3) Information verification and integrity check: After the test outline is completed, the test personnel will check the information and completeness. If the check is correct, the system will directly generate a test outline based on this information; if the check is incorrect, the information will be updated and corrected, and a new test outline will be generated. The information will be saved in the database and the matching algorithm will be updated and iterated; S3. Presentation of test outline results: The tester organizes the generated test outline into a PDF report format and transmits it to the user terminal.

3. The method for generating and managing a remote intelligent metering test outline according to claim 2, characterized in that: In step S2, check whether the sample has a quotation number. If the sample has a quotation number, then: the user enters the quotation number through the input interface, and the system searches based on the existing information, accurately reads various data related to the sample to be tested, and loads this information into the test outline; if the sample does not have a quotation number, then: for samples that have been tested before, the user can enter the previous certificate number, or scan the QR code on the sample to retrieve and call historical information.

4. The method for generating and managing a remote intelligent metering test outline according to claim 2, characterized in that: In step S2, check whether the sample has a certificate number or a scanned QR code for inspection. If the sample has a certificate number or a scanned QR code for inspection, then: the system will search for historical information through data based on the read information and load it; this information includes scope, references, test items, test conditions, test components, data collection and processing, and test result processing; if the sample does not have a certificate number or a scanned QR code for inspection, then: the system guides the user to enter the sample information.

5. The method for generating and managing a remote intelligent metering test outline according to claim 2, characterized in that: In step S2, the sample information processing without quotation number, certificate number or inspection QR code includes the following steps: (1) User inputs sample information: For samples that do not meet the above two conditions, information needs to be collected according to the specific situation. For such special samples, the system provides detailed input interface guidance, requiring users to enter relevant information of the samples to be tested, including: instrument name, model specifications, factory number, quantity, appearance description, grade, expected extraction date and information of the sending unit; (2) Image acquisition and remote communication: The inspectors can communicate with the site in real time through the image acquisition device, allowing the user to introduce and display the samples in detail; according to the specific requirements of the remote inspectors, the users are guided to conduct detailed inspection and verification of the samples to be inspected, and collect necessary pictures and upload them to the database; (3) Intelligent matching: After completing the information collection and confirmation, the system will start the intelligent matching program based on machine learning; If the match is successful, the information collection module will load the corresponding outline information into the remote guidance terminal, and the test personnel can directly view the corresponding information; the test personnel will confirm the corresponding information based on the on-site inspection of the tested samples; for information that does not meet the requirements, the test personnel will update and correct it in the corresponding text, picture, formula or list module, update it according to actual needs, and save the updated information into the database; the updated data will be used as new training data to train the matching system; If the match fails, the tester needs to manually perform more accurate and detailed matching operations based on the existing outline and fill in the information required by the test outline; (4) Information verification and integrity check; Information verification: During the entire information collection process, each step requires careful verification by the inspector to ensure the accuracy and completeness of the information; Completeness Check: The system also automatically performs a completeness check on the information to ensure that all required fields are filled and the information is valid.

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