Excavator offline detection data analysis system, processing platform and processing method

Abstract

The invention relates to an excavator offline detection data analysis system, a processing platform and a processing method. The analysis system comprises an original data acquisition and analysis module, a detection signal display module, a user interface operation module, an analyzed data display module, a feature parameter preparation module, a feature calculation and analysis tool module, a feature extraction and coding module and a storage access and feature value uploading module. The processing platform is based on the analysis system and comprises a server, data display processing software and report form viewing software. The processing method is realized based on the processing platform. According to the method, excavator offline detection original data can be comprehensively, accurately and efficiently analyzed, operation is visual and easy to understand, data customization analysis and personalized detection reports and reports can be provided, the accuracy and efficiency of excavator offline detection are improved, the method can be applied to processing of detection data of other engineering machines, and good universality is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of engineering machinery detection and data analysis, and in particular to an off-line detection data analysis system, a processing platform and a processing method for an excavator. Background Art

[0002] With the rapid development of the construction machinery industry, excavators, as important construction equipment, have a decisive impact on construction efficiency and quality due to their performance and reliability. In order to ensure that the excavators meet the predetermined performance standards and safety requirements when leaving the factory, offline inspection has become an important part of the production process. However, traditional off-line inspection methods for excavators usually rely on manual operation and experience judgment, which is not only inefficient, but also easily affected by human factors, resulting in inaccurate inspection results.

[0003] In recent years, with the continuous development of sensor technology, data acquisition technology and data analysis technology, it has become possible to automate and intelligentize the off-line detection of excavators. By installing various sensors on the excavator, the operation data of the excavator can be collected in real time, such as machine and engine failures, electrical performance indicators, hydraulic system pressure fluctuations, etc., and these data can be transmitted to the backend server through the data acquisition system for parsing and analysis. However, due to the large sample size of excavator off-line detection data, as well as its complexity and diversity, how to accurately and efficiently parse and effectively analyze these data has become an urgent problem to be solved.

[0004] Existing raw data analysis methods mostly rely on traditional data processing software or platforms, which usually have functions such as data import, data cleaning, and data analysis. For the raw data of the excavator offline detection, the current existing technology usually stores it on the local hard disk, and further analyzes it after loading the raw data on the local hard disk through the data processing software or platform. At the same time, these platforms usually give a preset algorithm or model to analyze the data and extract key information; the data visualization module can display the analyzed data in the form of charts, curves, etc., to help users understand the data more intuitively. At present, although there are some excavator offline detection data processing systems on the market, most systems still have some problems. For example, some systems can only process a single type of data and cannot fully reflect the performance status of the excavator; some systems have complex data processing algorithms and low computing efficiency, and cannot process data with high sampling frequency and large sample size; and some systems have complex display interfaces, inconvenient operations, and poor user experience. Therefore, the existing excavator offline detection data processing software or platform mainly has the following problems: (1) Low parsing efficiency: Traditional data processing platforms often take a long time to process large amounts of data, which affects detection efficiency; (2) Insufficient customization: Since the detection data and indicators of different excavators may vary, the existing data processing platforms often find it difficult to provide customized analysis solutions and cannot meet specific needs; (3) Data security and data management are complicated and confusing: Since the original data and test reports of the data processing software or platform are usually stored on the local hard disk, there is a risk of data loss or data corruption. At the same time, when the number of tests is large, data management is complicated and confusing; (4) Inflexible report generation: Due to the single report template, users cannot generate personalized excavator offline inspection reports and statements based on the parsed data and their own needs, which is not conducive to subsequent analysis and application.

[0005] Therefore, developing a method that can comprehensively, accurately and efficiently parse and analyze the raw data of excavator offline detection, and building an intuitive and easy-to-understand data display and processing platform to provide customized data analysis and personalized detection reports and statements, has important practical significance and broad application prospects for improving the accuracy and efficiency of excavator offline detection. Summary of the invention

[0006] The purpose of the present invention is to overcome the above-mentioned shortcomings and provide a data analysis system that can comprehensively, accurately and efficiently parse and analyze the raw data of excavator offline detection, and construct an intuitive and easy-to-understand data processing platform and corresponding processing methods, provide customized data analysis and personalized detection reports and statements, and improve the accuracy and efficiency of excavator offline detection.

[0007] The object of the present invention is achieved in that: The excavator offline detection data analysis system includes a raw data acquisition and analysis module, a detection signal display module, a user interface operation module, a analyzed data display module, a feature parameter configuration module, a feature calculation and analysis tool module, a feature extraction and encoding module, and a storage access and feature value upload module; The raw data acquisition and analysis module obtains historical detection models, historical detection order numbers and historical detection raw data from the database of off-line detection data of excavators, and parses the raw data by deserialization decoding to obtain detection signals and sampling sample values ​​corresponding to the detection signals; The detection signal display module displays the detection signal of the original data parsed by the original data acquisition and parsing module through a list box or a tree control; The user interface operation module sets a data filtering or smoothing algorithm, and the user selects an algorithm to process the detection signal sample data through a drop-down box or an enable key; the system executes the corresponding data processing algorithm in the background and updates the processed data in real time; The analyzed data display module graphically displays the updated detection signal sample data; The feature parameter configuration module configures the feature parameter types to be extracted for the feature calculation and analysis tool module; The feature calculation and analysis tool module provides users with feature calculation functions, including basic statistics, mathematical formula operations and filter processing; users select the feature calculation function to calculate feature parameters; The post-analysis data display module and the feature calculation and analysis tool module automatically match signals and features; The feature extraction and encoding module provides users with manual or automatic feature extraction by calling the feature calculation and analysis tool module; The storage access and feature value upload module is used to access the database data storage interface and write the extracted feature values ​​into the database.

[0008] Furthermore, the raw data acquisition and analysis module acquires the excavator detection raw data from a database stored in a server or a local hard disk through an API interface.

[0009] Furthermore, the storage access and feature value uploading module uploads the extracted feature values ​​to the server or stores them in a database on a local hard disk after receiving a storage permission response signal.

[0010] Furthermore, the analyzed data display module displays the detection signal sample data through a QChartview or QCustomplot control.

[0011] Furthermore, the characteristic parameter type includes quantitative indicators or qualitative indicators.

[0012] Furthermore, after the user selects to manually or automatically extract features, the feature extraction and encoding module performs Base64 encoding processing on the extracted feature values.

[0013] An off-line detection data processing platform for excavators, comprising a server, data display and processing software, and report viewing software; The server includes data storage and data interaction functions, is responsible for storing and managing the off-line detection data of the excavator, and interacts with the data display processing software and the report viewing software; The data display and processing software includes data acquisition, data analysis, feature extraction, and feature upload. It uses any of the above-mentioned excavator offline detection data analysis systems to obtain the excavator offline detection data from the server for analysis and processing, extract feature parameters, and upload the extracted feature parameters to the server after data encoding or encryption; The report viewing software includes data acquisition, report configuration, report generation, preview and download, and is responsible for acquiring data from the server and generating test reports or reports.

[0014] Furthermore, the server deploys a database and provides an API interface for data interaction; the data interaction between the server and the data display processing software and report form viewing software adopts the same encoding or encryption method.

[0015] Furthermore, the login report viewing software also provides a test report preview and download function, which is convenient for users to directly preview the effect after generating the report, and is convenient for users to save and use.

[0016] A method for processing off-line detection data of an excavator is implemented based on the above-mentioned off-line detection data processing platform of an excavator, and comprises the following steps: Step S100, user login: the user logs in to the data display processing software, and the system first determines whether the user has the authority to use the system according to the user's authority; the verification of the user's authority is achieved by matching the user name and password or assigning role authority; according to the verification result, the system grants the user corresponding operation authority, including accessing the server to obtain data, obtaining data types, extracting feature parameters and viewing feature parameters; Step S200, obtaining and parsing raw data: the system obtains a historical list of all tested models from the server according to the user's authority; the historical list includes all design models of the tested models; the user selects the model to be viewed, and the system obtains the historical test order number corresponding to the model from the server according to the selected model list; the historical test order number records the unique identification of each test, which is convenient for users to track and query; the user selects the test order number to be viewed, and the system obtains the historical raw data corresponding to the test order number from the server according to the selected test order number; the historical raw data includes test items, test signals, and test results; the system loads the obtained raw data into the data display and processing software to facilitate the user to perform subsequent operations; Step S300, user interface loading: the data display processing software automatically loads the user interface to provide support for subsequent data calculation and analysis; Step S400, interface operation and feature parameter configuration: the user performs data analysis and display by calling the feature calculation and analysis tool module and the analyzed data display module in the data processing software, and configures the feature parameter list to be extracted through the feature parameter configuration module; Step S500, feature value extraction and encoding: The user selects the detected signal to be processed, and the feature extraction and encoding module performs manual or automatic data analysis on the signal data to obtain the feature value; manual data analysis allows the user to freely configure the implementation form of feature calculation through the feature parameter configuration module; automatic data analysis uses the built-in algorithm of the feature calculation and analysis tool module to quickly process and analyze the signal. After obtaining the feature value, the feature value is combined into a feature value list for encoding, and then uploaded to the server; Step S600, storage access and feature value upload: access the server data storage interface, and after obtaining a storage permission response signal, upload the extracted feature values ​​to the server for subsequent report and form generation.

[0017] Step S700, obtaining the test report: the user logs in to the report viewing software, the report viewing software obtains the analyzed and processed characteristic parameters from the server, and the user selects the type, style and content of the test report or report; the report viewing software generates the corresponding test report or test report according to the report configuration selected by the user.

[0018] Compared with the prior art, the present invention has the following beneficial effects: The excavator offline detection data analysis system of the present invention adopts a feature parameter configuration module and a feature calculation and analysis tool module that are set to optimize data processing algorithms and efficient operation mechanisms, and can quickly and efficiently process a large amount of raw data; through the graphical interface of the data display module after analysis and a rich data display method, users can understand the data more intuitively and quickly obtain the required information, which reduces the user's learning cost and operation difficulty; The excavator offline detection data processing platform of the present invention integrates a server to manage various data information, ensures data security and comprehensiveness of detection data, and ensures that various data are effectively managed; builds an intuitive, easy-to-understand, and efficient data processing data display and processing software, so that users can understand data more intuitively and quickly obtain required information, reducing the user's learning cost and operation difficulty; through the report viewing software, a flexible report generation function is provided, and the template and content of the report can be customized as needed to generate a detection report that meets one's own requirements, thereby improving the flexibility and customizability of the report and making the report more in line with the user's actual needs and usage habits; The method for processing offline detection data of an excavator of the present invention adopts a method of interactively cooperating with a server, data display processing software and report viewing software, which can meet the actual needs of a large sample size of the original offline detection data and a variety of sampling sample types, and improve the efficiency and functional completeness of data analysis; systematically manages detection data, analysis data, characteristic parameters, and detection report reports, effectively and quickly and conveniently manages test data and test reports, and ensures data security; through a graphical interface and rich data display methods (such as charts, curves, etc.) and data processing algorithms (basic statistics, filtering, etc.), the human-computer interactivity of the offline detection data processing platform and the practicality of data analysis are improved, and the configurability is higher when performing feature extraction; The excavator offline detection data analysis system, processing platform and processing method of the present invention can not only be applied to the offline detection data processing of excavators, but also be applicable to the offline detection data processing application of engineering machinery such as pile drivers and lumberjacks, and have good versatility. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a structural schematic diagram of the excavator offline detection data analysis system of the present invention.

[0020] Figure 2 It is a structural schematic diagram of the excavator offline detection data processing platform of the present invention.

[0021] Figure 3 The present invention is a flow chart of the method for processing off-line detection data of an excavator.

[0022] in: Original data acquisition and analysis module 1, detection signal display module 2, user interface operation module 3, analyzed data display module 4, characteristic parameter configuration module 5, characteristic calculation and analysis tool module 6, characteristic extraction and encoding module 7, storage access and characteristic value upload module 8; Server 11, data display and processing software 12, report viewing software 13. DETAILED DESCRIPTION Example

[0023] See also Figure 1 The present invention relates to an off-line detection data analysis system for an excavator, comprising a raw data acquisition and analysis module 1, a detection signal display module 2, a user interface operation module 3, a post-analysis data display module 4, a feature parameter configuration module 5, a feature calculation and analysis tool module 6, a feature extraction and encoding module 7, and a storage access and feature value upload module 8; The raw data acquisition and analysis module 1 obtains the historical detection model, historical detection order number and historical detection raw data from the database of the excavator offline detection data stored in the server or local hard disk through the API interface, and parses the raw data by deserialization decoding to obtain the detection signal and the sampling sample value corresponding to the detection signal; The detection signal display module 2 displays the detection signal of the original data parsed by the original data acquisition and parsing module 1 through a list box or a tree control; The user interface operation module 3 sets a data filtering or smoothing processing algorithm, and the user selects an algorithm to process the detection signal sample data through a drop-down box or an enable key; the system executes the corresponding data processing algorithm in the background and updates the processed data in real time; The analyzed data display module 4 displays the updated detection signal sample data graphically through controls such as QChartview or QCustomplot; The characteristic parameter configuration module 5 configures the characteristic parameter type to be extracted for the characteristic calculation and analysis tool module 6; the characteristic parameter type includes quantitative indicators or qualitative indicators, wherein the quantitative indicators are exemplified as: a maximum value, average value or minimum value of a detection signal; the qualitative indicators are exemplified as: an objective evaluation of a detection signal or a curve graph that can represent its characterization; The feature calculation and analysis tool module 6 provides users with feature calculation functions, including basic statistics, mathematical formula operations and filter processing; wherein basic statistics include mean, peak, maximum and minimum values, variance, etc., mathematical formula operations include addition, subtraction, multiplication and division, etc., and filter processing includes low pass, high pass, band pass, band stop, etc.; users can select these feature calculation functions according to their needs to calculate feature parameters; The analyzed data display module 4 and the feature calculation and analysis tool module 6 automatically match signals and features; the signal samples displayed in the analyzed data display module 4 and the feature parameters calculated by the feature calculation and analysis tool module 6 match and correspond to each other; The feature extraction and encoding module 7 provides the user with a manual or automatic way to extract features by calling the feature calculation and analysis tool module 6. The extracted feature values ​​will be directly encoded in Base64 format to ensure data security; The storage access and feature value upload module 8 is used to access the database data storage interface and write the extracted feature values ​​into the database; specifically, the storage access and feature value upload module 8 uploads the extracted feature values ​​to the server or stores them in the database on the local hard disk after receiving the storage permission response signal.

[0024] The excavator offline detection data analysis system of the present invention adopts a feature parameter configuration module 5 and a feature calculation and analysis tool module 6 that are set to optimize data processing algorithms and efficient operation mechanisms, and can quickly and efficiently process a large amount of raw data; through the graphical interface of the analyzed data display module 4 and a variety of data display methods (such as charts, curves, etc.), an intuitive and easy-to-understand data display and processing architecture is built, so that users can understand the data more intuitively and quickly obtain the required information, reducing the user's learning cost and operation difficulty. Example

[0025] See also Figure 2 , the present invention relates to an excavator offline detection data processing platform, comprising a server 11, data display and processing software 12 and report viewing software 13; The server 11 deploys a database and provides an API interface for data interaction, including data storage function and data interaction function, and is responsible for storing and managing the off-line detection data of the excavator, and interacting with the data display processing software 12 and the report viewing software 13. The data interaction uses the same encoding or encryption method to ensure data security. The specific functions are as follows: a). Data storage: The server 11 is deployed with a high-performance database for storing historical detection models, historical detection order numbers, historical detection raw data, and analyzed and processed feature parameters; b). Data interaction: The server 11 interacts with the data display processing software 11 and the report viewing software 12 through the API interface. The API interface supports data upload, download and query functions to ensure the real-time and accuracy of the data.

[0026] The data display and processing software 12 adopts the excavator offline detection data analysis system of Example 1, including data acquisition, data analysis, feature extraction, and feature upload. It is responsible for acquiring the excavator offline detection data from the server 11 for analysis and processing, extracting feature parameters, and uploading the extracted feature parameters to the server 11 after data encoding or encryption. The specific functions are as follows: a). Data acquisition: The software obtains historical detection models, historical detection order numbers and historical detection raw data from the server 11 through the API interface; b). Data analysis and feature extraction: The software has built-in data analysis algorithms and feature extraction algorithms. Users can freely configure them to process and analyze the acquired raw data and extract key feature parameters according to their needs; c). Data encryption and result upload: The software will first encode the analyzed feature parameters, and then upload them to the server through the API interface for use by other software. From the perspective of data security and data analysis, the data encoding usually uses the Base64 encoding format, but is not limited to using other data encoding formats and data encryption methods. Regardless of the method used, as long as the two software interacting with the server use the same encoding or encryption method.

[0027] The report viewing software 13 includes data acquisition, report configuration, report generation, preview and download, and is responsible for acquiring data from the server 11 and generating a test report or report; the specific functions are as follows: a). Data acquisition: The software obtains the analyzed and processed characteristic parameters from the server 11 through the API interface.

[0028] b). Report configuration: The software provides flexible report configuration function, and users can choose the report type, style and content according to their needs.

[0029] c). Report generation: The software automatically generates test reports or test statements based on user configuration and supports multiple formats such as PDF, Excel, etc.

[0030] d). Preview and download: The software provides a preview function, and users can directly preview the results after generating the report; at the same time, the software also supports the report download function, which is convenient for users to save and use.

[0031] Compared with traditional data processing platforms, the excavator offline detection data processing platform of the present invention adopts optimized data processing algorithms and efficient computing mechanisms, and can quickly and efficiently process a large amount of raw data. At the same time, the present invention integrates the server to manage various types of data information, ensuring data security and ensuring its effective management. An intuitive and easy-to-understand data display and processing software architecture is built. Through a graphical interface and rich data display methods (such as charts, curves, etc.), users can understand the data more intuitively and quickly obtain the required information, reducing the user's learning cost and operating difficulty. A flexible report generation function is provided, and users can customize the report template and content according to their needs to generate a test report that meets their requirements, which improves the flexibility and customizability of the report and makes the report more in line with the user's actual needs and usage habits. Example

[0032] See also Figure 3 The present invention relates to an excavator offline detection data processing method, which is implemented based on the excavator offline detection data processing platform of Example 2, and comprises the following steps: Step S100, user login: the user logs in to the data display processing software 12, and the system first determines whether the user has the authority to use the system according to the user's authority; the verification of the user's authority is realized by matching the user name and password, assigning role authority, and other verification methods; according to the verification result, the system grants the user corresponding operation authority, including accessing the server 11 to obtain data, obtaining data types, extracting feature parameters, and viewing feature parameters, etc.; Step S200, obtaining and parsing raw data: the system obtains a historical list of all tested models from the server 11 according to the user's authority; the historical list includes all design models of the tested models; the user selects the model to be viewed, and the system obtains the historical test order number corresponding to the model from the server 11 according to the selected model list; the historical test order number records the unique identification of each test, which is convenient for users to track and query; the user selects the test order number to be viewed, and the system obtains the historical raw data corresponding to the test order number from the server 11 according to the selected test order number; the historical raw data includes detailed information such as test items, test signals, and test results; the system loads the obtained raw data into the data display and processing software 12, which is convenient for users to perform subsequent operations; Step S300, user interface loading: the data display processing software 12 automatically loads the user interface to provide support for subsequent data calculation and analysis; Step S400, interface operation and feature parameter configuration: the user performs data analysis and display by calling the feature calculation and analysis tool module 6 in the data processing software 12 and the curve loading and display function of the analyzed data display module 4, and configures the feature parameter list to be extracted through the feature parameter configuration module 5; Step S500, feature value extraction and encoding: the user selects the detected signal to be processed, and the feature extraction and encoding module 7 performs manual or automatic data analysis on the signal data to obtain the feature value; wherein, the manual data analysis allows the user to freely configure the implementation form of the feature calculation through the feature parameter configuration module 5; the automatic data analysis uses the built-in algorithm of the feature calculation and analysis tool module 6 to quickly process and analyze the signal. After obtaining the feature value, the feature value is composed into a feature value list for encoding, and then uploaded to the server; Step S600, storage access and feature value upload: access the data storage API interface of the server 11, and after obtaining a storage permission response signal, upload the extracted feature values ​​to the server 11 for subsequent report and form generation.

[0033] Step S700, obtain the test report: the user logs in to the report viewing software 13, the report viewing software 13 obtains the analyzed and processed characteristic parameters from the server 11, and the user selects the type, style and content of the test report or report; the report viewing software 13 generates a corresponding test report or test report according to the report configuration selected by the user.

[0034] The method for processing off-line detection data of an excavator of the present invention adopts the interactive cooperation of a server, data display processing software and report viewing software, which can meet the actual needs of a large sample size and a variety of sampling sample types of off-line detection raw data, and improve the efficiency and functional completeness of data analysis; systematically manage detection data, analysis data, characteristic parameters, and detection report reports, effectively and quickly manage test data and test reports, and ensure data security; build an intuitive and easy-to-understand data display and processing software architecture, through a graphical interface and rich data display methods (such as charts, curves, etc.) and data processing algorithms (basic statistics, filtering, etc.), to improve the human-computer interactivity of the off-line detection data processing platform and the practicality of data analysis, and higher configurability when performing feature extraction.

[0035] The excavator offline detection data analysis system, processing platform and processing method of the present invention can not only be applied to the offline detection data processing of excavators, but also be applicable to the offline detection data processing application of engineering machinery such as pile drivers and felling machines.

[0036] In addition: It should be noted that the above specific implementation is only an optimization scheme of this patent. Any changes or improvements made by technicians in this field based on the above concept are within the scope of protection of this patent.

Claims

1. An off-line detection data analysis system for an excavator, characterized in that: It comprises a raw data acquisition and analysis module (1), a detection signal display module (2), a user interface operation module (3), a post-analysis data display module (4), a feature parameter configuration module (5), a feature calculation and analysis tool module (6), a feature extraction and encoding module (7), and a storage access and feature value upload module (8); The raw data acquisition and analysis module (1) acquires historical detection machine models, historical detection order numbers and historical detection raw data from a database of off-line detection data of excavators, and parses the raw data by deserialization decoding to obtain detection signals and sampling sample values ​​corresponding to the detection signals; The detection signal display module (2) displays the detection signal of the original data parsed by the original data acquisition and parsing module (1) through a list box or a tree control; The user interface operation module (3) sets a data filtering or smoothing processing algorithm, and the user selects an algorithm through a drop-down box or an enable key to process the detection signal sample data; the system executes the corresponding data processing algorithm in the background and updates and displays the processed data in real time; The analyzed data display module (4) graphically displays the updated detection signal sample data; The characteristic parameter configuration module (5) configures the characteristic parameter type to be extracted for the characteristic calculation and analysis tool module (6); The feature calculation and analysis tool module (6) provides the user with a feature calculation function, including basic statistics, mathematical formula operations and filter processing; the user selects the feature calculation function to calculate feature parameters; The post-analysis data display module (4) and the feature calculation and analysis tool module (6) automatically match signals and features; The feature extraction and encoding module (7) provides the user with a manual or automatic method for extracting features by calling the feature calculation and analysis tool module (6); The storage access and feature value upload module (8) is used to access the database data storage interface and write the extracted feature values ​​into the database.

2. The excavator offline detection data analysis system according to claim 1 is characterized in that: The raw data acquisition and analysis module (1) acquires the excavator detection raw data from a database stored in a server or a local hard disk through an API interface.

3. The excavator offline detection data analysis system according to claim 2 is characterized in that: The storage access and feature value uploading module (8) uploads the extracted feature value to a server or stores it in a database on a local hard disk after receiving a storage permission response signal.

4. The excavator offline detection data analysis system according to claim 1 is characterized in that: The analyzed data display module (4) displays the detection signal sample data through a QChartview or QCustomplot control.

5. The excavator offline detection data analysis system according to claim 1 is characterized in that: The characteristic parameter type includes a quantitative indicator or a qualitative indicator.

6. The excavator offline detection data analysis system according to claim 1 is characterized in that: The feature extraction and encoding module (7) performs Base64 encoding processing on the extracted feature values ​​after the user selects manual or automatic feature extraction.

7. An excavator offline detection data processing platform, characterized by: It includes a server (11), data display and processing software (12) and report viewing software (13); The server (11) includes a data storage function and a data interaction function, is responsible for storing and managing the off-line detection data of the excavator, and interacts with the data display and processing software (12) and the report viewing software (13); The data display processing software (12) includes data acquisition, data analysis, feature extraction, and feature upload, and adopts any one of the excavator offline detection data analysis systems in claims 1 to 6, and is responsible for acquiring the excavator offline detection data from the server (11) for analysis and processing, extracting feature parameters, and uploading the extracted feature parameters to the server (11) after data encoding or encryption; The report viewing software (13) includes data acquisition, report configuration, report generation, preview and download, and is responsible for acquiring data from the server (11) and generating a test report or report.

8. The excavator offline detection data processing platform according to claim 7 is characterized by: The server (11) deploys a database and provides an API interface for data interaction; the data interaction between the server (11) and the data display processing software (12) and the report viewing software (13) adopts the same encoding or encryption method.

9. The excavator offline detection data processing platform according to claim 7, characterized in that: The login report viewing software (13) also provides a test report preview and download function, which is convenient for users to directly preview the results after generating the report, and convenient for users to save and use.

10. A method for processing off-line detection data of an excavator, characterized in that: The method is implemented based on the excavator offline detection data processing platform of claim 7 or claim 8, and comprises the following steps: Step S100, user login: the user logs in to the data display processing software (12), and the system first determines whether the user has the authority to use the system according to the user's authority; the verification of the user's authority is achieved by matching the user name and password or assigning role authority; according to the verification result, the system grants the user corresponding operation authority, including accessing the server (11) to obtain data, obtain data type, extract feature parameters and view feature parameters; Step S200, obtaining and parsing raw data: the system obtains a historical list of all detected models from the server (11) according to the user's authority; the historical list includes all design models of the detected models; The user selects the model to be viewed, and the system obtains the historical test order number corresponding to the model from the server (11) according to the selected model list; the historical test order number records the unique identification of each test, which is convenient for the user to track and query; the user selects the test order number to be viewed, and the system obtains the historical original data corresponding to the test order number from the server (11) according to the selected test order number; the historical original data includes test items, test signals, and test results; the system loads the obtained original data into the data display processing software (12), which is convenient for the user to perform subsequent operations; Step S300, user interface loading: the data display processing software (12) automatically loads the user interface to provide support for subsequent data calculation and analysis; Step S400, interface operation and feature parameter configuration: the user performs data analysis and display by calling the feature calculation and analysis tool module (6) and the analyzed data display module (4) in the data display processing software (12), and configures a list of feature parameters to be extracted through the feature parameter configuration module (5); Step S500, feature value extraction and encoding: the user selects the detected signal to be processed, and performs manual or automatic data analysis on the signal data through the feature extraction and encoding module (7) to obtain the feature value; manual data analysis allows the user to freely configure the implementation form of feature calculation through the feature parameter configuration module (5); automatic data analysis uses the built-in algorithm of the feature calculation and analysis tool module (6) to quickly process and analyze the signal. After obtaining the feature value, the feature value is combined into a feature value list for encoding, so as to be uploaded to the server; Step S600, storage access and feature value upload: access the data storage interface of the server (11), and after receiving a storage permission response signal, upload the extracted feature values ​​to the server (11) for subsequent report and form generation; Step S700, obtaining a test report: the user logs in to the report viewing software (13), the report viewing software (13) obtains the analyzed and processed characteristic parameters from the server (11), and the user selects the type, style and content of the test report or report; the report viewing software (13) generates a corresponding test report or test report according to the report configuration selected by the user.

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