Method and system for monitoring running condition of open-pit mine wide-body vehicle

Abstract

The invention discloses a method and a system for monitoring the running condition of a strip mine wide-body vehicle, and relates to the technical field of mine vehicle operation and maintenance management, and the method comprises the steps: collecting wide-body vehicle data, carrying out the preprocessing, and constructing a server-side database; automatic classification and statistics are carried out according to vehicle states, data of wide-body vehicles are generated, and future states are predicted based on historical data; a report containing vehicle state information is generated, and access permissions of different roles to data are controlled based on multi-level permissions; and an efficient query function of historical data is provided, and operation and maintenance data of the wide-body vehicle are traced according to conditions selected by a user. Through the automatic data preprocessing and storage module, wide-body vehicle operation and maintenance data are collected and updated in real time, and delay and errors caused by traditional manual recording are avoided. According to the system, a multi-level real-time sharing mechanism is adopted, and based on a distributed database architecture, edge cache and role permission control, different departments can quickly access latest data within a permission range, so that the collaboration efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of mine vehicle operation and maintenance management, and in particular to a method and system for monitoring the operation of a wide-body vehicle in an open-pit mine. Background Art

[0002] In the production operation of open-pit mines, wide-body vehicles are the core equipment for transporting ore and earth. Such vehicles are operated under high load in harsh environments for a long time, are prone to various failures, and require frequent maintenance and servicing. Therefore, the status monitoring and operation and maintenance management of wide-body vehicles is one of the key tasks in mine management. At present, the operation and maintenance management of wide-body vehicles in mining areas mainly relies on manual records and regular inspections. Managers fill in operation and maintenance records and fault logs manually, and then various departments summarize and transmit the data step by step. This traditional management model has the following major defects:

[0003] Since operation and maintenance data mostly rely on manual recording and aggregation, information delays and data errors are prone to occur. Especially in multi-level management and complex environments, data cannot be updated in real time, making it difficult for managers to grasp the actual operating status of the vehicle in a timely manner.

[0004] The operation and maintenance data of wide-body vehicles needs to be shared among multiple departments in the mine, such as the dispatch center, maintenance department, and workshop. However, the traditional data transmission method relies on manual sorting and reporting step by step, which is inefficient in information sharing and prone to data omissions or delays, which is not conducive to cross-departmental coordination and affects the accuracy of operation and maintenance scheduling.

[0005] Under the traditional management model, operation and maintenance records are mostly kept in paper files or scattered spreadsheets. Data is difficult to store in a systematic manner, and there is a lack of a unified historical data management method, which makes data retrieval and traceability analysis difficult, and it is impossible to effectively use historical data to predict equipment status and optimize maintenance plans.

[0006] In the mining environment, wide-body truck failures have certain regularity and periodicity. The scattered data and manual statistical methods under the traditional management model make it difficult to analyze failure modes and predict status through historical data, making it difficult to discover potential problems in a timely manner, resulting in frequent sudden failures and affecting the continuity of mining production.

[0007] In summary, the existing wide-body vehicle operation and maintenance management technology cannot meet the needs of efficient, real-time and intelligent management of mining areas. Summary of the invention

[0008] In view of the above-mentioned problems, the present invention is proposed.

[0009] Therefore, the technical problem solved by the present invention is: how to realize real-time data collection, automatic classification statistics, multi-level data sharing, historical data query and fault prediction in the operation and maintenance management of open-pit mine wide-body vehicles.

[0010] In order to solve the above technical problems, the present invention provides the following technical solutions: a method for monitoring the operation of a wide-body vehicle in an open-pit mine, comprising the following steps:

[0011] Collect wide-body vehicle data for preprocessing and build a server-side database;

[0012] Automatically classify and count the pre-processed data according to vehicle status, generate the registration rate, intact rate and failure rate of wide-body vehicles, and predict future status based on historical data;

[0013] Generate reports containing vehicle status information and control the access rights of different roles to data based on multi-level permissions;

[0014] It provides efficient query function for historical data and traces the operation and maintenance data of wide-body vehicles according to the conditions selected by the user.

[0015] As a preferred solution of the method for monitoring the operation of a wide-body vehicle in an open-pit mine according to the present invention, the wide-body vehicle data is operation and maintenance data of the wide-body vehicle, including temporary maintenance, shutdown maintenance, daily maintenance, and vehicle operation status data;

[0016] The preprocessing is to remove null values, non-compliant formats or abnormal values ​​in the data, standardize the data from different data sources into a unified format, classify and archive the data according to preset fields or tags, and mark or annotate abnormal information in the original data.

[0017] As a preferred solution of the method for monitoring the operation of a wide-body vehicle in an open-pit mine described in the present invention, the pre-processed data is automatically classified and counted according to the vehicle status to generate the registration rate, intact rate and failure rate of the wide-body vehicle, and the future status is predicted based on historical data, including:

[0018] The pre-processed wide-body vehicle operation and maintenance data is divided into three categories according to the vehicle status: registered status, intact status and faulty status. Based on the vehicle's operation and maintenance records, the current status of the vehicle is automatically identified and classified through a machine learning algorithm.

[0019] As a preferred solution of the method for monitoring the operation of a wide-body vehicle in an open-pit mine described in the present invention, the pre-processed data is automatically classified and counted according to the vehicle status to generate the registration rate, intact rate and failure rate of the wide-body vehicle, and the future status is predicted based on historical data, which also includes:

[0020] According to the vehicle status classification results, the wide-body vehicle registration rate, intact rate and failure rate statistics are automatically generated, and the generated statistics, vehicle status classification and prediction results are synchronized to relevant departments in real time through a multi-level real-time sharing mechanism;

[0021] Divide statistical data and forecast results into different logical partitions in the main database according to departmental authority and usage requirements. Users in each department will first obtain the required data from their logical partitions. Establish a local cache on the application interface or edge node of each department, and give priority to storing real-time classification and statistical data. When department users access data, they can directly obtain it from the cache.

[0022] A configuration data synchronization mechanism is established to automatically synchronize the classification results and prediction status to each logical partition and cache when they are updated.

[0023] As a preferred solution of the method for monitoring the operation of a wide-body vehicle in an open-pit mine described in the present invention, wherein: the generation of a report containing vehicle status information and the control of access rights of different roles to data based on multi-level authority include:

[0024] Generate several real-time reports on vehicle operation and maintenance status based on the real-time status data of wide-body vehicles;

[0025] Real-time reports are generated on a daily, weekly or monthly basis according to the needs of different departments.

[0026] As a preferred solution of the method for monitoring the operation of a wide-body vehicle in an open-pit mine described in the present invention, wherein: the generating of a report containing vehicle status information, and the control of the access rights of different roles to data based on multi-level authority also include:

[0027] A multi-level permission control mechanism based on roles is adopted. Different roles are assigned different access rights. Users in the dispatch center have the highest permissions and can access the status, history and forecast information of all vehicles. Workshop managers can only access the vehicle information of this workshop; ordinary operators can only view the basic information of task-related vehicles.

[0028] The real-time report includes the current status of each vehicle, statistical data of each status and forecast information.

[0029] As a preferred solution of the method for monitoring the operation of a wide-body vehicle in an open-pit mine described in the present invention, wherein: the efficient query function of providing historical data, tracing the operation and maintenance data of the wide-body vehicle according to the conditions selected by the user, includes:

[0030] Establish multiple indexes for key fields in the database, build an efficient retrieval structure for historical data, set multiple query conditions, and users can combine and filter according to actual needs;

[0031] Generate a traceability view based on the query results and display it in the form of a chart or list, so that the historical operation and maintenance information of the vehicle can be presented in a structured manner.

[0032] Another object of the present invention is to provide a monitoring system for the operation of wide-body vehicles in open-pit mines, which can realize real-time status monitoring of wide-body vehicles and multi-department data collaboration through automatic data processing and a multi-level sharing mechanism, thereby solving the problems of data delay, low sharing efficiency and lack of predictive maintenance in the prior art.

[0033] In order to solve the above technical problems, the present invention provides the following technical solutions: A monitoring system for the operation of wide-body vehicles in open-pit mines, comprising: a data preprocessing and storage module, an automatic classification and status statistics module, a multi-level real-time sharing module, and a historical data query and prediction module;

[0034] The data preprocessing and storage module performs preprocessing and storage management on wide-body vehicle operation and maintenance data, collects original operation and maintenance data of wide-body vehicles, cleans, formats and structures the data, generates standardized data fields, and stores the cleaned data in the database;

[0035] The automatic classification and status statistics module automatically classifies the vehicle status according to the vehicle operation and maintenance data, and generates status statistics information of the wide-body vehicle;

[0036] The multi-level real-time sharing module is configured with multi-level authority control, assigns access rights to different roles, uses distributed database logical partitioning and local cache mechanism, and reduces the access pressure of the main database;

[0037] The historical data query and prediction module establishes multiple indexes for key fields, optimizes the retrieval efficiency of historical data, configures condition screening and query optimization mechanisms, supports users to perform combined queries based on vehicle ID, time interval, and fault type, predicts vehicle faults and maintenance needs, and generates prediction results for future status.

[0038] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of the above-mentioned method for monitoring the operation of a wide-body vehicle in an open-pit mine are implemented.

[0039] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the method for monitoring the operation of a wide-body vehicle in an open-pit mine as described above.

[0040] Beneficial effects of the present invention: The present invention adopts an automated data preprocessing and storage module to ensure that the operation and maintenance data of wide-body vehicles can be collected and updated in real time, avoiding data delays and errors caused by traditional manual records. The system uses a multi-level real-time sharing mechanism, a distributed database architecture, edge caching, and a role-based permission control mechanism to enable different departments to quickly access the latest operation and maintenance data within their respective authority, significantly improving the efficiency of cross-departmental collaboration. With the help of multiple indexes and conditional screening functions of historical data, the system supports querying historical records by combination of conditions such as vehicle ID, time interval, and fault type, solving the problems of difficult data query and lack of system management in the traditional mode. In addition, through time series analysis, regression analysis, and machine learning algorithms, the system can predict the time and type of vehicle failures based on historical data, realize predictive maintenance of equipment, reduce the impact of sudden failures on production, and improve the efficiency and safety of mine operation and maintenance management. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. Among them:

[0042] Figure 1 The present invention provides an overall flow chart of a method for monitoring the operation of a wide-body vehicle in an open-pit mine according to a first embodiment of the present invention. DETAILED DESCRIPTION

[0043] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0044] Example 1, reference Figure 1 According to an embodiment of the present invention, a method for monitoring the operation of a wide-body vehicle in an open-pit mine is provided, comprising:

[0045] Collect wide-body vehicle data for preprocessing and build a server-side database;

[0046] Automatically classify and count the pre-processed data according to vehicle status, generate the registration rate, intact rate and failure rate of wide-body vehicles, and predict future status based on historical data;

[0047] Generate reports containing vehicle status information and control the access rights of different roles to data based on multi-level permissions;

[0048] It provides efficient query function for historical data and traces the operation and maintenance data of wide-body vehicles according to the conditions selected by the user.

[0049] Wide-body vehicle data refers to the operation and maintenance data of wide-body vehicles, including temporary maintenance, shutdown maintenance, daily maintenance, and vehicle operation status data.

[0050] Eliminate empty values, non-compliant formats or outliers in the data, standardize data from different data sources into a unified format, classify and archive data according to preset fields or labels, and mark or annotate abnormal information in the original data.

[0051] It is further explained that:

[0052] Eliminate empty values, irregular formats, or outliers in the data to ensure data validity. For example, when recording vehicle status, remove duplicate records or correct incorrectly entered data fields.

[0053] Standardize data from different data sources (such as operation and maintenance logs, vehicle status records, etc.) into a unified format. This may involve unifying the format of timestamps, mapping different fault codes, etc., to ensure that the data is in a consistent format when entering the database.

[0054] Classify and archive the data according to preset fields or tags for subsequent intelligent classification and statistics. This step can organize the data of wide-body vehicles into structured data fields such as "fault records", "repair time", and "maintenance frequency" to facilitate database management and query.

[0055] Mark or annotate abnormal information in the original data (such as sudden failures, abnormal downtime, etc.) so that abnormal situations can be identified and processed in subsequent classification and prediction algorithms.

[0056] The pre-processed wide-body vehicle operation and maintenance data is divided into three categories according to the vehicle status: registered status, intact status and faulty status. Based on the vehicle's operation and maintenance records, the current status of the vehicle is automatically identified and classified through a machine learning algorithm.

[0057] It is further explained that:

[0058] After completing the classification, statistics and prediction of vehicle status, the system synchronizes various results to different departments in real time through a multi-level real-time sharing mechanism, including:

[0059] Distributed database logical partitioning: The system distributes statistical data and forecast results to logical partitions according to departmental authority. Users in each department get data from logical partitions first, reducing frequent access to the main database.

[0060] Configure edge node cache on the interface of each department to prioritize the storage of the latest classification, statistical and forecast data. Users from each department can access the data directly from the cache, which improves data reading speed.

[0061] An automatic data synchronization mechanism is established between the main database, logical partitions and edge node caches to ensure that when classification, statistical and forecasting data are updated, they can be immediately synchronized to the partitions and caches of each department, ensuring real-time and data consistency.

[0062] According to the vehicle status classification results, the wide-body vehicle registration rate, intact rate and failure rate statistics are automatically generated, and the generated statistics, vehicle status classification and prediction results are synchronized to relevant departments in real time through a multi-level real-time sharing mechanism;

[0063] Divide statistical data and forecast results into different logical partitions in the main database according to departmental authority and usage requirements. Users in each department will first obtain the required data from their logical partitions. Establish a local cache on the application interface or edge node of each department, and give priority to storing real-time classification and statistical data. When department users access data, they can directly obtain it from the cache.

[0064] A configuration data synchronization mechanism is established to automatically synchronize the classification results and prediction status to each logical partition and cache when they are updated.

[0065] It is further explained that:

[0066] Extract the historical operation and maintenance data of wide-body vehicles from the database (including failure frequency, maintenance intervals and maintenance cycles), and apply time series analysis, regression analysis or machine learning models to predict the future status of the vehicle, including:

[0067] Based on the vehicle's historical fault records, usage time and maintenance frequency, predict the possible time and type of future faults. Based on the vehicle's operation and maintenance frequency and health status, predict the time of the next maintenance or repair to provide reference for maintenance planning.

[0068] Generate several real-time reports on vehicle operation and maintenance status based on the real-time status data of wide-body vehicles;

[0069] Real-time reports are generated on a daily, weekly or monthly basis according to the needs of different departments.

[0070] A multi-level permission control mechanism based on roles is adopted. Different roles are assigned different access rights. Users in the dispatch center have the highest permissions and can access the status, history and forecast information of all vehicles. Workshop managers can only access the vehicle information of this workshop; ordinary operators can only view the basic information of task-related vehicles.

[0071] The real-time report includes the current status of each vehicle, statistical data of each status and forecast information.

[0072] It is further explained that:

[0073] Generate a real-time report on the vehicle operation and maintenance status based on the real-time status data of wide-body vehicles (such as registration rate, intact rate, and failure rate). The report content includes the current status of each vehicle, statistical data of each status, and forecast information (such as the next maintenance time and possible failure type). The system provides a variety of report templates to meet the needs of different departments, and supports periodic generation by day, week, and month to ensure that the data in the report is updated in real time.

[0074] In terms of data access control, the system adopts a role-based multi-level permission control mechanism. Different roles are assigned different access rights: users in the dispatch center have the highest permissions and can access the status, history, and forecast information of all vehicles; workshop managers can only access the vehicle information of this workshop; ordinary operators can only view the basic information of vehicles related to their tasks. The system controls the visible data range of different users through role identification to ensure that each user can only access data content that matches their permissions. To ensure data security, the system records the log of each data access, allowing administrators to regularly review the use of permissions to further ensure the compliance and security of data access.

[0075] Establish multiple indexes for key fields in the database, build an efficient retrieval structure for historical data, set multiple query conditions, and users can combine and filter according to actual needs;

[0076] Generate a traceability view based on the query results and display it in the form of a chart or list, so that the historical operation and maintenance information of the vehicle can be presented in a structured manner.

[0077] It is further explained that:

[0078] Multiple indexes are established in the database for key fields (such as vehicle ID, fault type, repair time, and operation and maintenance record time) to build an efficient retrieval structure for historical data, which facilitates rapid positioning and access to target data.

[0079] The system sets a variety of query conditions, including vehicle ID, time interval, fault type and maintenance record, allowing users to combine and filter according to actual needs. The query engine has a built-in optimization algorithm, which decomposes complex query conditions through the SQL query optimizer to optimize data screening and retrieval efficiency.

[0080] Temporarily store query results in cache to support continuous access by users and avoid system load caused by repeated queries. The system provides paging display function to load and display query results page by page to reduce the impact of one-time data loading on the system.

[0081] The query function is embedded with a multi-level permission control mechanism, and the system limits user query permissions through role identification. Users in the dispatch center can view all vehicle data, while workshop managers can only view records of their workshops. Each query generates an access log, recording the user ID, query conditions, and time, forming a complete access record for security management and permission review.

[0082] A traceability view is generated based on the query results, which includes historical operation and maintenance data such as vehicle status changes and maintenance records, and is displayed in the form of charts or lists, so that the vehicle's historical operation and maintenance information is presented in a structured manner, supporting further data interpretation and analysis.

[0083] Create indexes for key fields in the database (such as vehicle ID, fault type, maintenance time, operation and maintenance record time, etc.). Each index is centered on a specific field to form an independent index table, which helps the system quickly lock specific data when querying. For common multi-condition queries (such as querying fault records by vehicle ID and time interval), the system creates a combined index so that the database can skip line-by-line retrieval when processing multi-condition queries and quickly locate data through indexes. If historical data includes text descriptions (such as fault causes or repair instructions), the system can use full-text indexing or inverted indexing to facilitate quick search of relevant text content through keyword retrieval.

[0084] For data queried by time interval, the system partitions the data by month or year, so that each query only accesses the data partitions of the relevant time period, thereby speeding up the query. For data queried by time interval, the system partitions the data by month or year, so that each query only accesses the data partitions of the relevant time period, thereby speeding up the query.

[0085] The system has a built-in query optimizer. When a user initiates a multi-condition query, the optimizer analyzes the selectivity of each index, determines the optimal index combination, and generates a query execution plan.

[0086] For commonly used queries (such as querying historical fault data by vehicle ID), the system will cache the optimized query execution plan. When the same query conditions are used again, the cached execution plan will be directly called to improve query efficiency.

[0087] The system defines stored procedures for commonly used queries (such as querying the maintenance records of a specific vehicle in a specified time period), which reduces the parsing time of query statements and improves the query response speed. For specific query conditions, the system pre-compiles query statements so that there is no need to recompile the statements each time a query is made, and they can be executed directly, further shortening the query time.

[0088] Embodiment 2 is an embodiment of the present invention, which provides a system for monitoring the operation of a wide-body vehicle in an open-pit mine, including: a data preprocessing and storage module, an automatic classification and status statistics module, a multi-level real-time sharing module, and a historical data query and prediction module;

[0089] The data preprocessing and storage module performs preprocessing and storage management on wide-body vehicle operation and maintenance data, collects original operation and maintenance data of wide-body vehicles, cleans, formats and structures the data, generates standardized data fields, and stores the cleaned data in the database;

[0090] The automatic classification and status statistics module automatically classifies the vehicle status according to the vehicle operation and maintenance data, and generates status statistics information of the wide-body vehicle;

[0091] The multi-level real-time sharing module is configured with multi-level authority control, assigns access rights to different roles, uses distributed database logical partitioning and local cache mechanism, and reduces the access pressure of the main database;

[0092] The historical data query and prediction module establishes multiple indexes for key fields, optimizes the retrieval efficiency of historical data, configures condition screening and query optimization mechanisms, supports users to perform combined queries based on vehicle ID, time interval, and fault type, predicts vehicle faults and maintenance needs, and generates prediction results for future status.

[0093] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program code.

[0094] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0095] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0096] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0097] Embodiment 3: In this embodiment, in order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments. This embodiment experiments the existing traditional method and the method of this embodiment respectively.

[0098] This experiment aims to objectively verify the superiority of the present invention in terms of data real-time performance, sharing efficiency, query speed, and fault prediction accuracy through simulated scenarios and real data sets. The significant improvement of the system of the present invention in various performance indicators is demonstrated through data comparison, table records, and chart analysis. The improvements of the present invention in terms of data real-time performance, sharing efficiency, query speed, and fault prediction accuracy are verified, and the performance advantages over traditional methods are objectively demonstrated.

[0099] The historical operation and maintenance data set (more than 6 months) of wide-body vehicles in mining areas is extracted, including vehicle status, fault records, repair time and maintenance logs, and organized into a standardized format to ensure compatibility between the traditional method and the system of the present invention.

[0100] Traditional method: simulate the traditional manual recording and step-by-step summary method to record the time from the change of vehicle status to the completion of data update.

[0101] The system of the present invention simulates the automatic data collection, preprocessing and updating process through a simulation system, and records the delay time of the system completing data updating.

[0102] The update delay time of multiple experiments was recorded, the average, maximum and minimum values ​​were calculated, and a bar graph was used to compare the data update delay of the two methods.

[0103] Table 1 Data display table

[0104]

[0105] Traditional method: simulate the sharing process of data transmission step by step, and record the delay time from collection to final sharing.

[0106] The system of the present invention records the access time and synchronization delay of different roles under multi-level permissions through a data sharing mechanism within the system.

[0107] Data display: By comparing the sharing time, a bar chart is used to display the difference in delay between the traditional method and the system of the present invention in multi-department data synchronization.

[0108] Table 2 Data sharing efficiency test table

[0109]

[0110] Historical data query speed test

[0111] Traditional method: query according to the traditional record method (paper files or electronic spreadsheets), and record the time spent on query under specific conditions.

[0112] The system of the present invention sets the same query conditions in the historical data query module of the system and records the query time.

[0113] Data display: Use query speed comparison tables and bar charts under multiple condition combinations to show the query efficiency of the two methods under different query conditions.

[0114] Table 3 Historical data table

[0115]

[0116] Fault prediction accuracy test

[0117] Using the fault records in the real historical data set, tests were conducted under the prediction models of the traditional management system and the system of the present invention, and the actual fault time and system prediction results were recorded.

[0118] Data display: The deviation between the actual fault time and the predicted result is recorded in a table, the predicted fault type matching rate, time deviation, etc. are calculated, and the prediction effect is displayed with an accuracy bar chart.

[0119] Table 4 Fault prediction accuracy test table

[0120]

[0121] The average data update delays of the traditional method and the system of the present invention are compared to analyze the improvement of the present invention in data real-time performance.

[0122] The difference in data sharing time between the two methods is compared to demonstrate the advantages of the present invention in multi-level data synchronization. The difference in query time under different conditions is used to demonstrate the high efficiency of the present invention in query speed.

[0123] Prediction accuracy analysis: The fault type matching rate and time deviation of the prediction results are compared to prove the effectiveness of the present invention in fault prediction and preventive maintenance.

[0124] The data update delay of the system of the present invention should be significantly lower than that of the traditional method, showing higher real-time performance.

[0125] The effect of multi-level real-time sharing should be better than the traditional level-by-level sharing method in terms of data synchronization time. Under complex condition queries, the query time of the system of the present invention is much shorter than that of the traditional method, showing the query efficiency advantage.

[0126] In fault prediction, the system of the present invention should show higher accuracy, smaller time deviation and higher prediction validity.

[0127] 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 preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for monitoring the operation of a wide-body vehicle in an open-pit mine, characterized in that: include: Collect wide-body vehicle data for preprocessing and build a server-side database; Automatically classify and count the pre-processed data according to vehicle status, generate the registration rate, intact rate and failure rate of wide-body vehicles, and predict future status based on historical data; Generate reports containing vehicle status information and control the access rights of different roles to data based on multi-level permissions; It provides efficient query function for historical data and traces the operation and maintenance data of wide-body vehicles according to the conditions selected by the user.

2. A method for monitoring the operation of a wide-body vehicle in an open-pit mine according to claim 1, characterized in that: The wide-body vehicle data refers to the operation and maintenance data of the wide-body vehicle, including temporary maintenance, shutdown maintenance, daily maintenance, and vehicle operation status data; The preprocessing is to remove null values, non-compliant formats or abnormal values ​​in the data, standardize the data from different data sources into a unified format, classify and archive the data according to preset fields or tags, and mark or annotate abnormal information in the original data.

3. A method for monitoring the operation of a wide-body vehicle in an open-pit mine as claimed in claim 2, characterized in that: The pre-processed data is automatically classified and counted according to vehicle status to generate the registration rate, intact rate and failure rate of wide-body vehicles, and the future status is predicted based on historical data, including: The pre-processed wide-body vehicle operation and maintenance data is divided into three categories according to the vehicle status: registered status, intact status and faulty status. Based on the vehicle's operation and maintenance records, the machine learning algorithm is used to automatically identify the vehicle's current status and classify the status.

4. A method for monitoring the operation of a wide-body vehicle in an open-pit mine as claimed in claim 3, characterized in that: The pre-processed data is automatically classified and counted according to vehicle status to generate the registration rate, intact rate and failure rate of wide-body vehicles, and the future status is predicted based on historical data, and also includes: According to the vehicle status classification results, the wide-body vehicle registration rate, intact rate and failure rate statistics are automatically generated, and the generated statistics, vehicle status classification and prediction results are synchronized to relevant departments in real time through a multi-level real-time sharing mechanism; Divide statistical data and forecast results into different logical partitions in the main database according to departmental authority and usage requirements. Users in each department will first obtain the required data from their logical partitions. Establish a local cache on the application interface or edge node of each department, and give priority to storing real-time classification and statistical data. When department users access data, they can directly obtain it from the cache. A configuration data synchronization mechanism is established to automatically synchronize the classification results and prediction status to each logical partition and cache when they are updated.

5. A method for monitoring the operation of a wide-body vehicle in an open-pit mine as claimed in claim 4, characterized in that: The generation of a report containing vehicle status information and the control of data access rights of different roles based on multi-level permissions include: Generate several real-time reports on vehicle operation and maintenance status based on the real-time status data of wide-body vehicles; Real-time reports are generated on a daily, weekly or monthly basis according to the needs of different departments.

6. A method for monitoring the operation of a wide-body vehicle in an open-pit mine as claimed in claim 5, characterized in that: The generating of a report containing vehicle status information and controlling the access rights of different roles to data based on multi-level permissions also include: A multi-level permission control mechanism based on roles is adopted. Different roles are assigned different access rights. Users in the dispatch center have the highest permissions and can access the status, history and forecast information of all vehicles. Workshop managers can only access the vehicle information of this workshop; ordinary operators can only view the basic information of task-related vehicles. The real-time report includes the current status of each vehicle, statistical data of each status and forecast information.

7. A method for monitoring the operation of a wide-body vehicle in an open-pit mine as claimed in claim 6, characterized in that: The efficient query function of providing historical data and tracing the operation and maintenance data of wide-body vehicles according to the conditions selected by the user include: Establish multiple indexes for key fields in the database, build an efficient retrieval structure for historical data, set multiple query conditions, and users can combine and filter according to actual needs; Generate a traceability view based on the query results and display it in the form of a chart or list, so that the historical operation and maintenance information of the vehicle can be presented in a structured manner.

8. A system using the method for monitoring the operation of an open-pit mine wide-body vehicle according to any one of claims 1 to 7, characterized in that: It includes data preprocessing and storage module, automatic classification and status statistics module, multi-level real-time sharing module, historical data query and prediction module; The data preprocessing and storage module performs preprocessing and storage management on wide-body vehicle operation and maintenance data, collects original operation and maintenance data of wide-body vehicles, cleans, formats and structures the data, generates standardized data fields, and stores the cleaned data in the database; The automatic classification and status statistics module automatically classifies the vehicle status according to the vehicle operation and maintenance data, and generates status statistics information of the wide-body vehicle; The multi-level real-time sharing module is configured with multi-level authority control, assigns access rights to different roles, uses distributed database logical partitioning and local cache mechanism, and reduces the access pressure of the main database; The historical data query and prediction module establishes multiple indexes for key fields, optimizes the retrieval efficiency of historical data, configures condition screening and query optimization mechanisms, supports users to perform combined queries based on vehicle ID, time interval, and fault type, predicts vehicle faults and maintenance needs, and generates prediction results for future status.

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 a method for monitoring the operation status of an open-pit mine wide-body vehicle according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of a method for monitoring the operation of an open-pit mine wide-body vehicle as described in any one of claims 1 to 7 are implemented.

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