Digital electronic detonator data acquisition method and device and tagging instrument

Abstract

The invention relates to the technical field of industrial detection instruments and meters, in particular to a digital electronic detonator data acquisition method and device and a tagging instrument. The digital electronic detonator data acquisition method comprises the following steps: preprocessing data to be processed to obtain initial data; extracting feature information in the initial data through a pre-training machine learning model, wherein the feature information comprises a digital electronic detonator ID, a detection result, current analog quantity data, detection time, a tagging result, appearance data and a control chip type; and performing data analysis on the feature information through a pre-trained machine learning model to obtain a data result, the data result including key features, abnormal values and yield. Through data acquisition and analysis, the quality of the digital electronic detonator is monitored and traced in real time, and it is ensured that the digital electronic detonator meets related standards and requirements.

Description

Technical Field

[0001] The invention relates to the technical field of industrial detection instruments and meters, and in particular to a digital electronic detonator data acquisition method and a coding instrument. Background Art

[0002] With the rapid development of information technology, big data and artificial intelligence have been widely used in all walks of life. Through data collection and analysis of production data, it can be used to monitor equipment status, analyze production efficiency, identify potential problems of digital electronic detonators, and perform predictive maintenance. Through digital technology, production managers can better understand the operation of the production line and take corresponding measures to improve efficiency and quality.

[0003] At present, the data collection method for the automated production line of digital electronic detonators is that each chip manufacturer independently collects its own production data, which is only used for display and archiving. There is no deeper data mining and risk prediction, and it cannot meet diverse needs. At the same time, the data analysis system also has problems such as single function and low efficiency.

[0004] Therefore, developing a system that can intelligently collect and analyze data is of great significance and is also an important task to solve the pain points of the pipe factory's automated production line. Summary of the invention

[0005] The object of the present invention is to provide a digital electronic detonator data collection method and a coding instrument, which can solve the above-mentioned technical problems.

[0006] The first aspect of the present invention provides a digital electronic detonator data acquisition method, comprising: Get the data to be processed; Preprocessing the data to be processed to obtain initial data; Extracting feature information from the initial data through a pre-trained machine learning model, the feature information including: digital electronic detonator ID, test results, current analog data, test time, coding results, appearance data and control chip type; The feature information is analyzed by a pre-trained machine learning model to obtain data results, wherein the data results include: key features, outliers, and yield rate.

[0007] In one embodiment, a digital electronic detonator data acquisition method further includes: The display unit displays the chart and / or data to the user through a display screen.

[0008] In one embodiment, a method for collecting data of a digital electronic detonator, wherein the preprocessing of the data to be processed to obtain initial data comprises: One or more operations of cleaning, deduplication and formatting are performed on the data to be processed.

[0009] A second aspect of the present invention provides a digital electronic detonator data acquisition device, comprising: An integrated universal coding instrument, which integrates multiple coding boards into one device, realizes automatic switching of the coding boards through the host computer main control software, and can automatically call the corresponding integrated universal coding instrument control software according to the selected coding board; A data acquisition unit, which automatically extracts and detects data in coded communication messages or databases through a machine learning algorithm, can identify electrical characteristic parameters, anomalies or specific information in the data by training the machine learning model, and extracts relevant data according to preset rules or user needs; Data analysis unit: The data analysis unit automatically analyzes and mines the detection data and coding data in the database through machine learning algorithms; A core control unit is connected to a host computer via an IO interface, and the core control unit controls the connection between the integrated universal coding instrument, the data acquisition unit and the data analysis unit.

[0010] In one embodiment, a digital electronic detonator data acquisition device, the data acquisition unit includes: A data preprocessing module, wherein the data preprocessing module is used to preprocess the collected data; Feature extraction module, which is used to extract feature information useful for machine learning algorithms from preprocessed data A pre-trained machine learning model is used to automatically identify patterns, anomalies, or specific information in data.

[0011] In one embodiment, a digital electronic detonator data acquisition device, the data acquisition unit further includes: Data extraction module: extracts qualified data from the database based on the recognition results of the pre-trained machine learning model.

[0012] In one embodiment, a digital electronic detonator data acquisition device is provided, wherein the digital electronic detonator data acquisition device further comprises: Display module: The display module uses charts and report visualization tools to intuitively display the analysis results to users.

[0013] The third aspect of the present invention provides a coding instrument, comprising: a digital electronic detonator data acquisition method in the above embodiment, a digital electronic detonator data acquisition device in the above embodiment, a host computer, a tooling and a digital electronic detonator, the digital electronic detonator is connected to the digital electronic detonator data acquisition device through the tooling, and the host computer controls the connection of the digital electronic detonator data acquisition and coding.

[0014] A fourth aspect of the present invention provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the method of the above embodiment when executing the computer program.

[0015] A fifth aspect of the present invention provides a computer storage medium having a computer program stored thereon, wherein the computer program implements the steps of the method of the above embodiment when executed by a processor.

[0016] The digital electronic detonator data acquisition method, device and coding instrument of the present invention have the following beneficial effects: obtaining data to be processed; preprocessing the data to be processed to obtain initial data; extracting feature information in the initial data through a pre-trained machine learning model, the feature information including: digital electronic detonator ID, test results, current analog data, test time, coding results, appearance data and control chip type; performing data analysis on the feature information through a pre-trained machine learning model to obtain data results, wherein the data results include: key features, outliers, and yield rate. The present application realizes real-time monitoring and tracing of the quality of digital electronic detonators through data collection and analysis, ensuring that digital electronic detonators meet relevant standards and requirements. When there is a problem with the quality of digital electronic detonators, the cause of the problem can be quickly located through data analysis, and corresponding improvement measures can be taken to improve the production quality of digital electronic detonators. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1 A schematic diagram of a digital electronic detonator data acquisition method of the present invention; Figure 2 It is a schematic diagram of a digital electronic detonator data acquisition device of the present invention; Figure 3 FIG. 4 is a diagram showing the internal structure of a microcontroller unit in one embodiment. DETAILED DESCRIPTION

[0019] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0020] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the referred device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as limiting the present invention.

[0021] In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined. In addition, the terms "installed", "connected" and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal connection of two components. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0022] See also Figure 1 The present invention provides a digital electronic detonator data acquisition method, comprising: Get the data to be processed; Preprocessing the data to be processed to obtain initial data; Extracting feature information from the initial data through a pre-trained machine learning model, the feature information including: digital electronic detonator ID, test results, current analog data, test time, coding results, appearance data and control chip type; The feature information is analyzed by a pre-trained machine learning model to obtain data results, wherein the data results include: key features, outliers, and yield rate.

[0023] In one embodiment, a digital electronic detonator data acquisition method further includes: The display unit displays the chart and / or data to the user through a display screen.

[0024] In one embodiment, a method for collecting data of a digital electronic detonator, wherein the preprocessing of the data to be processed to obtain initial data comprises: One or more operations of cleaning, deduplication and formatting are performed on the data to be processed.

[0025] In this embodiment, a data source of a digital electronic detonator data acquisition device can be a detection and coding message of an open communication protocol, or a message containing relevant content such as electrical characteristic parameters, or a database to be collected and extracted, all of which contain the original data of the digital electronic detonator detection and coding results.

[0026] A digital electronic detonator data acquisition device uses a data preprocessing module to perform preprocessing operations such as cleaning, deduplication, and formatting on the original data to improve data quality and meet the requirements of the pre-trained machine learning model. A feature extraction module of a digital electronic detonator data acquisition device extracts feature information useful for the pre-trained machine learning model from the pre-processed data. These features can be detonator ID, test results, current analog data, test time, coding results, appearance data, chip module type, etc. The pre-trained machine learning model uses the extracted features to train the machine learning model. After the model training is completed, it will be able to automatically identify patterns, anomalies or specific information in the data.

[0027] A data extraction module for a digital electronic detonator data acquisition device extracts data that meets the conditions from a database based on the recognition results of a pre-trained machine learning model. A data analysis system for a digital electronic detonator data acquisition device uses a machine learning algorithm to automatically analyze and mine the detection and coding data in the database. The pre-trained machine learning model can automatically identify key features in the data, discover outliers, predict future yields, etc., establish a prediction model based on historical data, and predict and evaluate key indicators such as production efficiency and failure rate. Then, through visualization technology, using visualization tools such as charts and reports, the analysis results are intuitively displayed to users to help users better understand the data and make decisions.

[0028] It should be understood that although Figure 1 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 1At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequentially, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0029] See also Figure 2 In one embodiment, a digital electronic detonator data acquisition device is provided, comprising: An integrated universal coding instrument, which integrates multiple coding boards into one device, realizes automatic switching of the coding boards through the host computer main control software, and can automatically call the corresponding integrated universal coding instrument control software according to the selected coding board; A data acquisition unit, which automatically extracts and detects data in coded communication messages or databases through a machine learning algorithm, can identify electrical characteristic parameters, anomalies or specific information in the data by training the machine learning model, and extracts relevant data according to preset rules or user needs; Data analysis unit: The data analysis unit automatically analyzes and mines the detection data and coding data in the database through machine learning algorithms; A core control unit is connected to a host computer via an IO interface, and the core control unit controls the connection between the integrated universal coding instrument, the data acquisition unit and the data analysis unit.

[0030] In one embodiment, a digital electronic detonator data acquisition device, the data acquisition unit includes: A data preprocessing module, wherein the data preprocessing module is used to preprocess the collected data; Feature extraction module, which is used to extract feature information useful for machine learning algorithms from preprocessed data A pre-trained machine learning model is used to automatically identify patterns, anomalies, or specific information in data.

[0031] In one embodiment, a digital electronic detonator data acquisition device, the data acquisition unit further includes: Data extraction module: extracts qualified data from the database based on the recognition results of the pre-trained machine learning model.

[0032] In one embodiment, a digital electronic detonator data acquisition device is provided, wherein the digital electronic detonator data acquisition device further comprises: Display module: The display module uses charts and report visualization tools to intuitively display the analysis results to users.

[0033] In one embodiment, a coding instrument is provided, comprising: a digital electronic detonator data acquisition method in the above embodiment, a digital electronic detonator data acquisition device in the above embodiment, a host computer, a tooling and a digital electronic detonator, the digital electronic detonator is connected to the digital electronic detonator data acquisition device via the tooling, and the host computer controls the connection of the digital electronic detonator data acquisition and coding.

[0034] The coder provided in this application can optimize production plans: based on the collected data, users can more accurately predict production progress, reasonably arrange production tasks, avoid resource waste and waiting time in the production process, and thus improve overall production efficiency. Through the data acquisition system, the operating status and production parameters of each device on the production line can be monitored in real time, so as to promptly discover production bottlenecks or abnormal situations and make corresponding adjustments to improve production efficiency.

[0035] The coding instrument provided in this application can improve the production process: through the analysis of detection data, it is possible to find out the problem links and bottleneck links in the production process, such as equipment-specific channel failures, unreasonable process flow, etc., so as to make targeted improvements. Based on the collected data, users can adjust production parameters to optimize the production process and improve the consistency and stability of digital electronic detonators.

[0036] The coding instrument provided in this application can improve the quality of digital electronic detonators: through data collection and analysis, users can achieve real-time monitoring and traceability of the quality of digital electronic detonators to ensure that digital electronic detonators meet relevant standards and requirements. When there is a problem with the quality of digital electronic detonators, users can quickly locate the cause of the problem through data analysis and take corresponding improvement measures to improve the quality of digital electronic detonators.

[0037] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 3As shown. The computer device includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store periodic task allocation data, such as configuration files, theoretical operating parameters and theoretical deviation value ranges, task attribute information, etc. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for determining a target path in a building is implemented.

[0038] Those skilled in the art can understand that Figure 3 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0039] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of the method of the above embodiment are implemented: Get the data to be processed; Preprocessing the data to be processed to obtain initial data; Extracting feature information from the initial data through a pre-trained machine learning model, the feature information including: digital electronic detonator ID, test results, current analog data, test time, coding results, appearance data and control chip type; The feature information is analyzed by a pre-trained machine learning model to obtain data results, wherein the data results include: key features, outliers, and yield rate.

[0040] In one embodiment, when the processor executes the computer program, the implementation further includes: The display unit displays the chart and / or data to the user through a display screen.

[0041] In one embodiment, when the processor executes the computer program, the preprocessing of the data to be processed to obtain the initial data includes: One or more operations of cleaning, deduplication and formatting are performed on the data to be processed.

[0042] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented: Get the data to be processed; Preprocessing the data to be processed to obtain initial data; Extracting feature information from the initial data through a pre-trained machine learning model, the feature information including: digital electronic detonator ID, test results, current analog data, test time, coding results, appearance data and control chip type; The feature information is analyzed by a pre-trained machine learning model to obtain data results, wherein the data results include: key features, outliers, and yield rate.

[0043] In one embodiment, when the computer program is executed by a processor, the implementation further includes: The display unit displays the chart and / or data to the user through a display screen.

[0044] In one embodiment, when the computer program is executed by the processor, the preprocessing of the data to be processed to obtain the initial data includes: One or more operations of cleaning, deduplication and formatting are performed on the data to be processed.

[0045] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A digital electronic detonator data acquisition method, characterized in that: include: Get the data to be processed; Preprocessing the data to be processed to obtain initial data; Extracting feature information from the initial data through a pre-trained machine learning model, the feature information including: digital electronic detonator ID, test results, current analog data, test time, coding results, appearance data and control chip type; The feature information is analyzed by a pre-trained machine learning model to obtain data results, wherein the data results include: key features, outliers, and yield rate.

2. A digital electronic detonator data acquisition method according to claim 1, characterized in that: Also includes: The display unit displays the chart and / or data to the user through a display screen.

3. A digital electronic detonator data acquisition method according to claim 1, characterized in that: The preprocessing of the data to be processed to obtain initial data includes: One or more operations of cleaning, deduplication and formatting are performed on the data to be processed.

4. A digital electronic detonator data acquisition device, characterized in that: include: An integrated universal coding instrument, which integrates multiple coding boards into one device, realizes automatic switching of the coding boards through the host computer main control software, and can automatically call the corresponding integrated universal coding instrument control software according to the selected coding board; A data acquisition unit, which automatically extracts and detects data in coded communication messages or databases through a machine learning algorithm, can identify electrical characteristic parameters, anomalies or specific information in the data by training the machine learning model, and extracts relevant data according to preset rules or user needs; Data analysis unit: The data analysis unit automatically analyzes and mines the detection data and coding data in the database through machine learning algorithms; A core control unit is connected to a host computer via an IO interface, and the core control unit controls the connection between the integrated universal coding instrument, the data acquisition unit and the data analysis unit.

5. A digital electronic detonator data acquisition device according to claim 4, characterized in that: The data acquisition unit comprises: A data preprocessing module, wherein the data preprocessing module is used to preprocess the collected data; Feature extraction module, which is used to extract feature information useful for machine learning algorithms from preprocessed data A pre-trained machine learning model is used to automatically identify patterns, anomalies, or specific information in data.

6. A digital electronic detonator data acquisition device according to claim 4, characterized in that: The data acquisition unit further includes: Data extraction module: extracts qualified data from the database based on the recognition results of the pre-trained machine learning model.

7. A digital electronic detonator data acquisition device according to claim 4, characterized in that: The digital electronic detonator data acquisition device also includes: Display module: The display module uses charts and report visualization tools to intuitively display the analysis results to users.

8. A coding instrument, characterized in that: include: A digital electronic detonator data acquisition method as described in any one of claims 1-3, a digital electronic detonator data acquisition device, a host computer, a tooling and a digital electronic detonator as described in any one of claims 4-7, the digital electronic detonator is connected to the digital electronic detonator data acquisition device through the tooling, and the host computer controls the connection of the digital electronic detonator data acquisition and coding.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 3 are implemented.

10. A computer storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 3 are implemented.

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