Internet control-based mine vehicle operation management method and system

Abstract

The present invention relates to the technical field of intelligent mine vehicle management. Disclosed are an Internet control-based mine vehicle operation management method and system. The method comprises: transmitting collected state data to a database via the Internet; and making statistics on preprocessed data results, and managing operation of mine vehicles on the basis of a statistical result. The present invention effectively solves the problems of incomplete data collection and low management efficiency in mine vehicle operation management, and dynamically adjusts the acquisition frequencies and positions of sensors on the basis of real-time data, so as to ensure the accuracy and integrity of data, thus improving the precision and timeliness of state monitoring in mine vehicle operation, and providing reliable support for the safety and efficiency of mine vehicle operation.

Description

A method and system for managing mining truck operation based on Internet control Technical Field

[0001] This invention relates to the field of intelligent mining truck management technology, and in particular to a mining truck operation management method and system based on Internet control. Background Technology

[0002] The current society faces challenges in mine operation and management. Traditional mine truck operation and management methods have a series of problems, such as incomplete data collection, low management efficiency, and untimely monitoring. Traditional methods mainly rely on manual operation and limited sensor data, resulting in insufficient accuracy in monitoring and managing the status of mine trucks, which makes it difficult to meet the needs of mine operation.

[0003] Currently, existing mining truck operation management technologies suffer from numerous problems. Uneven data collection leads to incomplete monitoring of the mining truck's status; inaccuracy and timeliness of sensor data result in low management efficiency; furthermore, traditional data processing methods often require significant manpower and time, and are inefficient in handling abnormal or missing data. This invention addresses these issues by proposing an internet-based data collection and dynamic adjustment strategy. This strategy enables precise monitoring and management of the mining truck's operating status. By employing intelligent data processing and management methods, it overcomes the shortcomings of traditional methods in data acquisition, processing, and management, thereby improving the efficiency and safety of mine operations. Summary of the Invention

[0004] In view of the problems existing in the current Internet-based mining truck operation management methods and systems, this invention is proposed.

[0005] Therefore, the purpose of this invention is to provide a mining truck operation management method and system based on Internet control. In view of the problems of incomplete data collection and low management efficiency of mining trucks, this invention adopts an Internet-based data collection and dynamic adjustment strategy to solve the problem.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0007] In a first aspect, embodiments of the present invention provide a mining truck operation management method based on Internet control, which includes collecting operation status data through sensors installed on the mining truck and transmitting the collected status data to a database via the Internet;

[0008] The data cleaning process based on rules preprocesses the state data in the database, statistically analyzes the preprocessed data results, and manages the operation of mining trucks based on the statistical results.

[0009] As a preferred embodiment of the Internet-based mine truck operation management method of the present invention, the installation includes installing sensors according to the mine truck's operating status indicators, spatial location, and operating conditions at different time periods, and introducing a dynamic adjustment strategy within the mine truck system, wherein the dynamic adjustment strategy includes speed changes, temperature changes, and pressure changes.

[0010] If the speed within the operating status index of the mine car changes, the mine car is in a high-speed or low-speed operating state. At this time, temperature and pressure sensors are installed at the front, middle and rear of the mine car respectively.

[0011] The operating status refers to the standard value of the speed v of the mine car. If the speed of the mine car is greater than v, it is considered high speed. If the speed of the mine car is lower than v, it is considered low speed. If the speed of the mine car is equal to v, it is considered normal speed.

[0012] If the mine car is running at high speed, the sampling frequency of the temperature and pressure sensors needs to be increased; conversely, if the mine car is running at low speed, the sampling frequency of the temperature and pressure sensors needs to be decreased.

[0013] As a preferred embodiment of the internet-based mine truck operation management method of the present invention, the method for collecting operation status data includes calculating the collection frequency of operation status data based on the temperature values ​​output from different spatial locations, and the specific calculation formula is as follows:

[0014] Where t represents the sensor temperature, f(t) represents the data acquisition frequency at different spatial locations, A represents the amplitude parameter, B represents the angular frequency parameter, C represents the amplitude parameter, D represents the angular frequency parameter, E represents the offset parameter, and F represents the amplitude parameter.

[0015] As a preferred embodiment of the Internet-based mining truck operation management method of the present invention, the preprocessing includes formulating cleaning rules to preprocess the status data in the database, and the preprocessing includes removing, filling and processing the acquisition frequency;

[0016] The removal process includes using data processing tools to scan and compare the state data in the database, identifying and locating duplicate data points, and making a judgment based on preset identifiers for duplicate data points.

[0017] If a data point appears only once, then a second scan of the database is performed.

[0018] If the data contains missing values, an interpolation algorithm is used to fill in the missing values ​​based on the numerical characteristics of surrounding data points.

[0019] If a data point appears more than once, the duplicate data point is deleted from the database. The deletion includes merging the duplicate data points, calculating the average value of the data points, and using a merging function to summarize the average value.

[0020] As a preferred embodiment of the internet-based mine truck operation management method of the present invention, the specific calculation formula of the interpolation algorithm is as follows:

[0021] Where k represents the degree of the interpolation polynomial, j represents the index of the data point used when constructing the interpolation polynomial, and P k (x i ) represents the Lagrange interpolation polynomial, and f(t) represents the sampling frequency of the running status data;

[0022] Where, f(x) i () represents the estimated value of the missing value, which is used to fill in the missing value's position.

[0023] As a preferred embodiment of the internet-based mine truck operation management method of the present invention, the specific calculation formula of the merging function is as follows:

[0024] Where m represents the number of data points, y1, y2, ..., y m This represents the values ​​of the data points to be merged;

[0025] The aggregation includes calculating the weighted average of each data point based on a merging function. The weighted average of each data point is proportional to the sampling frequency. When the sampling frequency is uneven, a proportional function is used to perform a secondary processing on the merging function. The specific calculation formula is as follows:

[0026] Where, f(t) i This represents the sampling frequency of the i-th data point in the spatial location.

[0027] As a preferred embodiment of the Internet-based mine truck operation management method of the present invention, the statistics include statistical analysis of the data collection frequency of each data point in the spatial location based on the processing of the merging function and the direct proportional function.

[0028] If the sampling frequency is uneven, the sampling frequency of data points at different spatial locations will be different. In this case, a direct proportional function is used to perform secondary processing on the merging function. The direct proportional function is adjusted according to the sampling frequency of each spatial location to realize the management of mine truck operation.

[0029] Secondly, embodiments of the present invention provide a mining truck operation management system based on Internet control, which includes: a data acquisition module, which acquires operation status data through sensors installed on the mining truck and transmits the acquired status data to a database via the Internet;

[0030] The processing module preprocesses the status data in the database based on rule-based data cleaning conditions, performs statistical analysis on the preprocessed data results, and manages the operation of mining trucks based on the statistical results.

[0031] Thirdly, embodiments of the present invention provide a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement any step of the above-described Internet-based mine truck operation management method.

[0032] Fourthly, embodiments of the present invention provide a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, it implements any step of the above-described Internet-based mine truck operation management method.

[0033] The beneficial effects of this invention are as follows: This invention adopts an Internet-based data acquisition and dynamic adjustment strategy, which effectively solves the problems of incomplete data acquisition and low management efficiency in mine truck operation management. The data collected by the sensors is transmitted to the database in real time, and the acquisition frequency and location of the sensors are dynamically adjusted according to the real-time data to ensure the accuracy and integrity of the data. This improves the accuracy and timeliness of mine truck operation status monitoring and provides reliable support for the safety and efficiency of mine truck operation. Attached Figure Description

[0034] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein:

[0035] Figure 1 is a flowchart of a mining truck operation management method and system based on Internet control according to an embodiment of the present invention.

[0036] Figure 2 is an internal structure diagram of a computer device for a mining truck operation management method and system based on Internet control, provided in an embodiment of the present invention. Detailed Implementation

[0037] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0038] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0039] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0040] This invention is described in detail with reference to the schematic diagrams. When detailing the embodiments of this invention, for ease of explanation, the cross-sectional views illustrating the device structure may be partially enlarged, not adhering to the usual scale. Furthermore, the schematic diagrams are merely examples and should not be construed as limiting the scope of protection of this invention. In actual fabrication, the three-dimensional spatial dimensions of length, width, and depth should be included.

[0041] Furthermore, in the description of this invention, it should be noted that the terms "upper," "lower," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. These terms are used solely for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. In addition, the terms "first," "second," or "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0042] Unless otherwise explicitly specified and limited, the terms "installation," "connection," and "joining" in this invention should be interpreted broadly. For example, they can refer to fixed connections, detachable connections, or integral connections; similarly, they can refer to mechanical connections, electrical connections, or direct connections, or indirect connections through an intermediate medium, or internal connections between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0043] Example 1

[0044] Referring to Figures 1 and 2, the first embodiment of the present invention provides a mining truck operation management method based on Internet control, including:

[0045] S1: Collect operational status data through sensors installed on the mining truck, and transmit the collected status data to the database via the Internet.

[0046] The installation includes installing sensors based on the operating status indicators, spatial location, and operating conditions of the mining truck at different times, and introducing dynamic adjustment strategies within the mining truck system. These dynamic adjustment strategies include speed changes, temperature changes, and pressure changes.

[0047] If the speed within the operating status index of the mine car changes, the mine car is in a high-speed or low-speed operating state. At this time, temperature and pressure sensors are installed at the front, middle and rear of the mine car respectively.

[0048] Operating status refers to the working state of the mine car. The speed v is the standard value. If the mine car speed is greater than v, it is high speed. If the mine car speed is lower than v, it is low speed. If the mine car speed is equal to v, it is normal speed.

[0049] If the mine car is running at high speed, the sampling frequency of the temperature and pressure sensors needs to be increased; conversely, if the mine car is running at low speed, the sampling frequency of the temperature and pressure sensors needs to be decreased.

[0050] The speed 'v' mentioned above refers to the operating speed of the mining truck, serving as one of the indicators of its operating status. The specific value depends on the speed level achieved by the truck during operation. For example, when the truck's speed exceeds the preset standard value of 50 km / h, it indicates high-speed operation; when the speed is less than the preset standard value of 20 km / h, it indicates low-speed operation; and when the speed is at the standard value of 30 km / h, it indicates that the truck's speed is within the normal range. The specific speed values ​​are set and adjusted according to actual conditions and operational needs. The relationship between the truck speed range and the sensor acquisition frequency adjustment is shown in Table 1 below.

[0051] Table 1. Relationship between mine car speed range and sensor acquisition frequency adjustment data.

[0052] The table shows the adjustment of the sampling frequency of the temperature and pressure sensors for the mine car at different speed ranges. As the speed increases, the sensor sampling frequency increases accordingly to monitor the mine car status more promptly.

[0053] S1.1: The acquisition of operational status data includes calculating the acquisition frequency of operational status data based on the temperature values ​​output from different spatial locations. The specific calculation formula is as follows:

[0054] Where t represents the sensor temperature, f(t) represents the data acquisition frequency at different spatial locations, A represents the amplitude parameter, B represents the angular frequency parameter, C represents the amplitude parameter, D represents the angular frequency parameter, E represents the offset parameter, and F represents the amplitude parameter.

[0055] S2: Based on rule-based data cleaning conditions, preprocess the state data in the database, statistically analyze the preprocessed data results, and manage the operation of mining trucks based on the statistical results.

[0056] Preprocessing includes formulating cleaning rules to preprocess the state data in the database, and preprocessing includes removing, filling and processing the acquisition frequency.

[0057] The removal process involves using data processing tools to scan and compare the status data in the database, identifying and locating duplicate data points, and then making a judgment based on preset identifiers for the duplicate data points.

[0058] If a data point appears only once, then a second scan of the database is performed.

[0059] If the data contains missing values, an interpolation algorithm is used to fill in the missing values ​​based on the numerical characteristics of surrounding data points.

[0060] If a data point appears more than once, the duplicate data point is deleted from the database. The deletion process includes merging the duplicate data points, calculating the average value of the data points, and using a merge function to summarize the average value.

[0061] Furthermore, this step is designed to ensure the accuracy and completeness of the mine truck status data collected from the sensors. Through preprocessing and data cleaning, duplicate data can be removed and missing values ​​can be filled. The data can also be merged and summarized to obtain more reliable data results, which helps to improve data quality and provide a reliable data foundation for subsequent statistical analysis and mine truck operation management.

[0062] S2.1: The specific calculation formula for the interpolation algorithm is as follows:

[0063] Where k represents the degree of the interpolation polynomial, j represents the index of the data point used when constructing the interpolation polynomial, and P k (x i ) represents the Lagrange interpolation polynomial, and f(t) represents the sampling frequency of the running status data;

[0064] Where, f(x) i () represents the estimated value of the missing value, which is used to fill in the missing value's position.

[0065] S2.2: The specific calculation formula for the merge function is as follows:

[0066] Where m represents the number of data points, y1, y2, ..., y m This represents the values ​​of the data points to be merged;

[0067] The summary includes calculating the weighted average of each data point based on the merging function. This weighted average is directly proportional to the sampling frequency. When the sampling frequency is uneven, a proportional function is used to perform a secondary processing on the merging function. The specific calculation formula is as follows:

[0068] Where, f(t) i This represents the sampling frequency of the i-th data point in the spatial location.

[0069] Furthermore, the statistics include statistical analysis of the data collection frequency of each data point within a spatial location based on the processing of the merging function and the direct proportion function;

[0070] If the sampling frequency is uneven, the sampling frequency of data points at different spatial locations will be different. In this case, a direct proportional function is used to perform secondary processing on the merging function. The direct proportional function is adjusted according to the sampling frequency of each spatial location to realize the management of mine truck operation.

[0071] In a preferred embodiment, a mining truck operation management system based on Internet control includes a data acquisition module that collects operating status data through sensors installed on the mining truck and transmits the collected status data to a database via the Internet.

[0072] The processing module preprocesses the status data in the database based on rule-based data cleaning conditions, performs statistical analysis on the preprocessed data results, and manages the operation of mining trucks based on the statistical results.

[0073] The above-mentioned unit modules can be embedded in the processor of the computer device in hardware form or independent of it, or they can be stored in the memory of the computer device in software form, so that the processor can call and execute the corresponding operations of the above modules.

[0074] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram is shown in Figure 2. The computer device includes a processor, memory, communication interface, display screen, and input device connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage medium. The communication interface is used for wired or wireless communication with external terminals. Wireless communication can be achieved through Wi-Fi, carrier networks, NFC (Near Field Communication), or other technologies. The display screen may be an LCD screen or an e-ink screen. The input device may be a touch layer covering the display screen, buttons, a trackball, or a touchpad mounted on the computer device casing, or an external keyboard, touchpad, or mouse.

[0075] In summary, this invention employs an internet-based data acquisition and dynamic adjustment strategy, effectively solving the problems of incomplete data acquisition and low management efficiency in mine truck operation management. Data collected by sensors is transmitted to the database in real time, and the acquisition frequency and location of the sensors are dynamically adjusted based on the real-time data to ensure the accuracy and integrity of the data. This improves the precision and timeliness of mine truck operation status monitoring, providing reliable support for the safety and efficiency of mine truck operation.

[0076] Example 2

[0077] Referring to Figures 1 and 2, the second embodiment of the present invention is provided, which provides a mining truck operation management method based on Internet control. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0078] First, the operating status data of the mining truck is collected, including information such as speed, temperature and pressure. The temperature sensor installed at the front records a temperature of 20℃, the middle a temperature of 25℃, and the rear a temperature of 22℃. The speed sensor records speeds of 30km / h, 35km / h and 28km / h respectively.

[0079] The collected data is transmitted to the database via the Internet. In the database, rule-based data cleaning and preprocessing are performed. Data processing tools are used to scan and compare the state data in the database to identify and locate duplicate data points. For duplicate data points, a judgment is made based on preset identifiers, and the data in the database is scanned a second time to ensure that each data point appears only once.

[0080] Missing values ​​in the detection data are filled in using an interpolation algorithm based on the numerical characteristics of surrounding data points. If temperature data is missing at a certain moment, the missing value is filled in by interpolating the temperature data before and after that moment, thus ensuring the integrity and continuity of the data.

[0081] If a data point appears more than once, it will be deleted from the database. This process includes merging duplicate data points and calculating their average. For example, if the temperature data at a certain moment is recorded twice, at 20℃ and 22℃ respectively, the average of these two values ​​will be calculated as 21℃. A merging function is introduced to summarize the average value for better statistical analysis of the mine truck's operating status data. The temperature data recorded by the temperature sensors at different locations on the mine truck are shown in Table 2 below.

[0082] Table 2 Temperature data recorded by the temperature sensor

[0083] This table displays temperature data recorded by temperature sensors at different locations on the mining truck, including the front, middle, and rear positions. By comparing these data, the temperature changes at different locations can be understood, providing a reference for mining truck operation management. A comparison with existing technologies is shown in Table 3 below:

[0084] Table 3 Comparison with Existing Technologies

[0085] The table above compares the main features and advantages of the technical solution of the present invention with those of the prior art. The technical solution of the present invention significantly improves the efficiency and accuracy of mine truck operation management by real-time data acquisition, dynamic adjustment and effective data processing.

[0086] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A mining truck operation management method based on Internet control, characterized in that: include, The system collects operational status data using sensors installed on the mining trucks, and then transmits the collected data to a database via the internet. The data cleaning process based on rules preprocesses the state data in the database, statistically analyzes the preprocessed data results, and manages the operation of mining trucks based on the statistical results.

2. The mining truck operation management method based on Internet control as described in claim 1, characterized in that: The installation includes installing sensors based on the operating status indicators, spatial location, and operating conditions of the mining truck at different times, and introducing dynamic adjustment strategies within the mining truck system, including speed changes, temperature changes, and pressure changes. If the speed within the operating status index of the mine car changes, the mine car is in a high-speed or low-speed operating state. At this time, temperature and pressure sensors are installed at the front, middle and rear of the mine car respectively. The operating status refers to the standard value of the speed v of the mine car. If the speed of the mine car is greater than v, it is considered high speed. If the speed of the mine car is lower than v, it is considered low speed. If the speed of the mine car is equal to v, it is considered normal speed. If the mine car is running at high speed, the sampling frequency of the temperature and pressure sensors needs to be increased; conversely, if the mine car is running at low speed, the sampling frequency of the temperature and pressure sensors needs to be decreased.

3. The mining truck operation management method based on Internet control as described in claim 2, characterized in that: The collected operational status data includes calculating the data collection frequency based on the temperature values ​​output from different spatial locations. The specific calculation formula is as follows: Where t represents the sensor temperature, f(t) represents the data acquisition frequency at different spatial locations, A represents the amplitude parameter, B represents the angular frequency parameter, C represents the amplitude parameter, D represents the angular frequency parameter, E represents the offset parameter, and F represents the amplitude parameter.

4. The mining truck operation management method based on Internet control as described in claim 3, characterized in that: The preprocessing includes formulating cleaning rules to preprocess the state data in the database, and the preprocessing includes removing, filling and processing the acquisition frequency; The removal process includes using data processing tools to scan and compare the state data in the database, identifying and locating duplicate data points, and making a judgment based on preset identifiers for duplicate data points. If a data point appears only once, then a second scan of the database is performed. If the data contains missing values, an interpolation algorithm is used to fill in the missing values ​​based on the numerical characteristics of surrounding data points. If a data point appears more than once, the duplicate data point is deleted from the database. The deletion includes merging the duplicate data points, calculating the average value of the data points, and using a merging function to summarize the average value.

5. The mining truck operation management method based on Internet control as described in claim 4, characterized in that: The specific calculation formula for the interpolation algorithm is as follows: Where k represents the degree of the interpolation polynomial, j represents the index of the data point used when constructing the interpolation polynomial, and P k (x i ) represents the Lagrange interpolation polynomial, and f(t) represents the sampling frequency of the running status data; Where, f(x) i () represents the estimated value of the missing value, which is used to fill in the missing value's position.

6. The mining truck operation management method based on Internet control as described in claim 5, characterized in that: The specific calculation formula for the merging function is as follows: Where m represents the number of data points, y1, y2, ..., y m This represents the values ​​of the data points to be merged; The aggregation includes calculating the weighted average of each data point based on a merging function. The weighted average of each data point is proportional to the sampling frequency. When the sampling frequency is uneven, a proportional function is used to perform a secondary processing on the merging function. The specific calculation formula is as follows: Where, f(t) i This represents the sampling frequency of the i-th data point in the spatial location.

7. The mining truck operation management method based on Internet control as described in claim 6, characterized in that: The statistics include statistical analysis of the data collection frequency of each data point within a spatial location based on the processing of the merging function and the direct proportional function; If the sampling frequency is uneven, the sampling frequency of data points at different spatial locations will be different. In this case, a direct proportional function is used to perform secondary processing on the merging function. The direct proportional function is adjusted according to the sampling frequency of each spatial location to realize the management of mine truck operation.

8. A mine truck operation management system based on Internet control, based on the mine truck operation management method based on Internet control according to any one of claims 1 to 7, characterized in that: include, The data acquisition module collects operational status data through sensors installed on the mining truck and transmits the collected status data to the database via the Internet. The processing module preprocesses the status data in the database based on rule-based data cleaning conditions, performs statistical analysis on the preprocessed data results, and manages the operation of mining trucks based on the statistical results.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, it implements the steps of the Internet-based mine truck operation management method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the steps of the Internet-based mine truck operation management method as described in any one of claims 1 to 7.

Images