CN118332641A - Mining machinery complete set application analysis system based on BIM technology - Google Patents

Abstract

The invention discloses a mining machinery complete application analysis system based on BIM technology, which comprises a model building subsystem, a mining machinery complete application analysis system and a mining machinery complete application analysis system, wherein the model building subsystem is used for building a three-dimensional model by inputting raw data of the mining machinery complete application; the information management subsystem is used for carrying out informatization processing on the model; the data acquisition subsystem comprises a sensor integration module, a data preprocessing module and a data transmission module; the data analysis subsystem is used for carrying out deep analysis on the acquired data and carrying out pipeline collision detection; BIM model and visualization subsystem and decision support subsystem. The mining machinery complete application analysis system based on the BIM technology has the beneficial effects of improving efficiency, enhancing collaborative operation, optimizing decision support, reducing cost, enhancing safety and the like. This helps ensure safe, stable and efficient operation of the mining machinery kit.

Description

A complete application analysis system for mining machinery based on BIM technology

Technical Field

The present invention belongs to the technical field of mining machinery, and in particular is a complete application analysis system for mining machinery based on BIM technology.

Background technique

BIM stands for Building Information Modeling, which means building information modeling. It refers to the concept, method, technology and process of managing the entire life cycle of construction projects from design to construction to operation by using the created digital model. BIM technology has been widely used in building, infrastructure and factory design. Through three-dimensional models, BIM technology can realize information sharing and collaborative work, and improve the efficiency of design, construction and operation.

Due to the particularity of mechanical complete system integration projects, there are high investments, long upstream and downstream industrial chains, and various parts suppliers, many uncertainties, slow capital recovery, etc. Therefore, mechanical complete system integration projects are required to fully coordinate business and integrate resources. However, the development of mechanical complete system integration projects has long been in a scattered and traditional mode, and transformation may require more time, money and energy than other industries. BIM technology can effectively reduce costs, improve quality, and accelerate the process of project transformation. It can also improve the level of project management and production efficiency, gradually strengthen project management from communication, collaboration, pre-control and other aspects, and promote the collaboration and communication of personnel from all parties involved in the construction through the BIM model, so as to achieve the purpose of rapid transformation.

Mining machinery, such as mining equipment and transportation equipment, has its own special operating environment and working conditions. Traditional mining machinery management methods often have problems such as opaque information and difficulty in collaborative work. The complete set of mining machinery applications involves the collaborative work of multiple devices, and its operation and management are highly complex. Traditional technical means are difficult to meet the needs of comprehensive and efficient management and analysis of the entire complete set of applications.

Although BIM technology has been widely used in the construction field, it also has broad application prospects in non-construction fields, such as mining. By combining BIM technology and the characteristics of mining machinery, an analysis system suitable for complete sets of mining machinery applications can be developed.

Aiming at the key issues affecting cost and efficiency in machinery complete system integration engineering projects, based on the powerful modeling and simulation functions of BIM technology and through the establishment of a machinery manufacturing parts model library, the present invention proposes a mining machinery complete application analysis system based on BIM technology to solve the above problems.

Summary of the invention

The present invention proposes a complete set of mining machinery application analysis system based on BIM technology, which can improve efficiency, enhance collaborative operations, optimize decision support, reduce costs, and enhance safety. This helps to ensure the safe, stable and efficient operation of complete sets of mining machinery applications.

In order to achieve the above-mentioned purpose, the technical solution of the present invention is as follows: a complete application analysis system for mining machinery based on BIM technology, including a model building subsystem, an information management subsystem, a data acquisition subsystem, a data analysis subsystem, a BIM model and visualization subsystem and a decision support subsystem.

The model building subsystem is used to construct a three-dimensional model by inputting the original data of the mining machinery complete set of applications.

The information management subsystem is used to process the model in an information manner.

The data acquisition subsystem includes a sensor integration module, a data preprocessing module and a data transmission module. The sensor integration module is used to monitor the operating status, position and environmental parameters of mining machinery in real time. The data preprocessing module is used to clean, filter and format the raw data. The data transmission module is used to transmit the processed data to the data analysis subsystem or cloud storage platform.

The data analysis subsystem is used to conduct in-depth analysis of the collected data and perform pipeline collision checks.

The BIM model and visualization subsystem is used to combine data analysis results with the BIM model and display them in an intuitive way.

The decision support subsystem simulates and optimizes the construction plan based on the model's information data and data analysis results, provides optimization suggestions and decision support, and generates reports.

The following beneficial effects are achieved by adopting the above scheme: the three-dimensional model is quickly constructed through the model building subsystem, which simplifies the modeling process and improves the modeling efficiency. At the same time, the information management subsystem performs information processing on the model, making the information management more efficient. The data acquisition subsystem monitors the operating status, position and environmental parameters of the mining machinery in real time to ensure the real-time and accuracy of the data. The data analysis subsystem conducts in-depth analysis of the collected data and performs pipeline collision inspection to improve the accuracy of the analysis. The BIM model and visualization subsystem combines the data analysis results with the BIM model and displays them in an intuitive way, which promotes the collaborative work between departments. The decision support subsystem simulates and optimizes the construction plan based on the information data of the model and the results of data analysis, provides optimization suggestions and decision support, generates reports, and improves the scientificity and accuracy of the decision. By improving efficiency, enhancing collaborative work and optimizing decision support, the system of the present invention helps to reduce the analysis and management costs of complete sets of mining machinery applications.

The data acquisition subsystem monitors the operating status, location and environmental parameters of mining machinery in real time, detects abnormal situations in time, and improves safety. At the same time, the BIM model and visualization subsystem display the data analysis results in an intuitive way, which facilitates the timely detection of potential safety hazards and further enhances safety.

In summary, through automated and intelligent data processing and analysis, the system can quickly generate reports and decision-making recommendations, thereby improving work efficiency. By sharing data and information in real time, departments can work together better, avoiding information islands and duplication of work. Real-time monitoring of the operating status and environmental parameters of the machinery can timely detect potential safety hazards and faults, thereby ensuring the personal safety of the staff and the normal operation of the equipment. The application of the system of the present invention is conducive to promoting the digital and intelligent development of the complete application field of mining machinery, and promoting technological innovation and industrial upgrading. Data-based analysis and decision support make decisions more scientific, reasonable and well-founded, thereby improving the quality of decision-making.

Furthermore, the input raw data includes physical information, attribute information and spatial relationships between devices.

Beneficial effects: The input raw data includes the physical information, attribute information and spatial relationship of the equipment. This information comprehensively describes the status and characteristics of the equipment and provides a complete basis for subsequent data processing and analysis. Accurate raw data is the prerequisite for ensuring the reliability of data analysis results. By recording the physical information, attribute information and spatial relationship of the equipment in detail, data errors can be reduced and the accuracy of analysis can be improved. The input raw data is structured and standardized, which is convenient for computer processing and analysis. This greatly improves the speed and efficiency of data processing and provides the possibility for real-time monitoring and early warning. The diversity of raw data enables the system to perform customized data processing and analysis according to different needs. For example, based on the physical information and attribute information of the equipment, the performance and status of the equipment can be evaluated; based on the spatial relationship between the equipment, the layout and configuration can be optimized.

Furthermore, information processing includes the entry, query and update of information on equipment procurement, transportation, installation and commissioning.

Beneficial effects: By managing the procurement, transportation, installation and commissioning of equipment through informatization, relevant information can be quickly entered, queried and updated, improving the efficiency and accuracy of information management. Informatization processing can realize real-time information sharing and promote collaborative work among departments. Relevant personnel can timely understand the status and progress of equipment through the informatization platform and jointly promote the progress of the project. In the procurement, transportation, installation and commissioning of equipment, recording key parameters and data through informatization can strengthen quality control and ensure that the performance and quality of equipment meet the requirements. Through informatization processing, managers can more accurately understand the procurement, transportation, installation and commissioning of equipment, so as to allocate resources more reasonably and optimize resource configuration. Recording the procurement, transportation, installation and commissioning information of equipment through informatization can provide detailed historical records and data support for later maintenance and management, facilitating the progress of later work.

Furthermore, the sensor integration module includes a speed sensor, a vibration sensor, an infrared sensor, a temperature sensor, a pressure sensor, an oil sensor, a GPS sensor, a mileage sensor, an angle sensor, a meteorological sensor, a soil moisture sensor, a soil quality sensor, a dust sensor, a noise sensor and a toxic gas sensor.

Beneficial effects: By integrating various types of sensors, the sensor integration module can monitor the operating status and environmental parameters of mining machinery from multiple dimensions, improving the comprehensiveness and accuracy of monitoring. The integration of multiple sensors can provide richer data information, which helps to improve the early warning subsystem's ability to judge abnormal situations, thereby issuing early warnings more promptly and accurately. Multi-sensor data can provide decision makers with more comprehensive information, helping them make more scientific and reasonable decisions, and improving the intelligence level of the entire system. By real-time monitoring of the key parts of mining machinery, the sensor integration module can promptly detect potential faults or damage, help maintenance personnel develop more reasonable and efficient maintenance strategies, and extend the service life of equipment. The integration of multiple sensors can provide more comprehensive monitoring and early warning of potential safety hazards, thereby reducing the risk of accidents and improving operational safety.

Furthermore, when the data analysis subsystem determines that the received vibration sensor data is abnormal, the analysis process of the data analysis subsystem is:

The data analysis subsystem determines whether the vibration data is abnormal due to the passage of a living organism based on the data from the infrared sensor.

The data analysis subsystem determines whether there are abnormal vibration data caused by the passing of vehicles based on the transportation data of the information management subsystem.

The data analysis subsystem determines whether the vibration data abnormality is caused by geological disasters based on the vibration frequency and fluctuation in the vibration sensor data.

At the same time, the data analysis subsystem determines whether the vibration data abnormality is caused by mechanical failure based on the historical data of the vibration sensor data.

Beneficial effects: The data analysis subsystem uses a variety of sensor data, including infrared sensors, transportation data from the information management subsystem, and historical data from vibration sensors, to conduct multi-dimensional analysis, which improves the accuracy and reliability of the analysis. The data analysis subsystem not only considers the common cause of mechanical failure, but also other potential causes such as biological passage, vehicle passage, and geological disasters, making the analysis more comprehensive and detailed. By checking and analyzing a variety of possible causes one by one, the data analysis subsystem can reduce the misjudgment of abnormal data and avoid unnecessary alarms and misoperations.

Furthermore, the system also includes an early warning subsystem, which is used to issue early warnings for abnormal situations based on the analysis results of the data analysis subsystem.

Beneficial effects: The early warning subsystem can monitor the operating status and environmental parameters of mining machinery in real time. Once an abnormal situation is found, such as mechanical failure, geological disasters, etc., it can immediately issue an early warning and notify relevant personnel to take countermeasures, which helps to deal with the problem in time and avoid the escalation of the situation. Through the real-time monitoring and early warning of the early warning subsystem, relevant personnel can understand the abnormal situation in time and take measures quickly, shortening the time for information transmission and processing and improving work efficiency. The timely early warning of the early warning subsystem can effectively reduce the losses caused by accidents. When abnormal situations occur, relevant personnel can quickly take countermeasures to reduce the risk of casualties and property losses.

Furthermore, the system also includes a safety management subsystem, which is used to monitor the operating status and environmental parameters of mining machinery in real time and provide real-time warnings and protection for dangerous areas.

Beneficial effects: By real-time monitoring of the operating status and environmental parameters of mining machinery, the safety management subsystem can promptly detect potential safety hazards or dangerous situations, such as mechanical failures, geological disasters, etc., which helps to take measures in advance to avoid accidents, thereby improving the safety of mining operations. The safety management subsystem provides real-time warnings and protections for dangerous areas, which can effectively remind relevant personnel to evacuate or take safety measures in time, thereby reducing the risk of casualties and property losses. The safety management subsystem can monitor abnormal situations in real time, and issue alarms in time through the early warning subsystem to notify relevant personnel to take countermeasures, which helps to shorten emergency response time and improve emergency response capabilities.

Furthermore, the system also includes a user management subsystem, which is used to grant different data access and usage permissions to different users based on different roles and responsibilities.

Beneficial effects: By assigning different data access and usage permissions to different users, it can ensure that only authorized users can access sensitive data, thereby improving data security. Through the user management subsystem, administrators can easily manage users, such as adding, deleting users, and modifying user permissions, which simplifies the management process and reduces management costs. The user management subsystem usually supports custom permissions and roles, so that when the system needs to process more complex data or functions, the user management subsystem can be easily expanded. Through reasonable permission allocation and management, the user management subsystem can reduce the risk of system errors or failures caused by illegal access or operations, thereby enhancing the reliability of the system.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1 is a framework diagram of an embodiment of a complete set of application analysis system for mining machinery based on BIM technology of the present invention.

Detailed ways

Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be understood as limiting the present invention.

The following is further described in detail through specific implementation methods:

Embodiment 1 is basically as shown in FIG1 : a complete application analysis system for mining machinery based on BIM technology, including a model building subsystem, an information management subsystem, a data acquisition subsystem, a data analysis subsystem, a BIM model and visualization subsystem and a decision support subsystem.

The model building subsystem is used to construct a three-dimensional model by inputting the original data of the complete set of mining machinery applications. The input original data includes the physical information, attribute information and spatial relationship between the equipment.

The information management subsystem is used to process the model in an informationized manner, including the input, query and update of information on equipment procurement, transportation, installation and commissioning.

The data acquisition subsystem includes a sensor integration module, a data preprocessing module and a data transmission module. The sensor integration module is used to monitor the operating status, position and environmental parameters of mining machinery in real time. The data preprocessing module is used to clean, filter and format the raw data. The data transmission module is used to transmit the processed data to the data analysis subsystem or cloud storage platform.

The sensor integration module includes speed sensor, vibration sensor, infrared sensor, temperature sensor, pressure sensor, oil sensor, GPS sensor, mileage sensor, angle sensor, meteorological sensor, soil moisture sensor, soil quality sensor, dust sensor, noise sensor and toxic gas sensor.

The data analysis subsystem is used to conduct in-depth analysis of the collected data and perform pipeline collision checks.

The BIM model and visualization subsystem is used to combine data analysis results with the BIM model and display them in an intuitive way.

The decision support subsystem simulates and optimizes the construction plan based on the model's information data and data analysis results, provides optimization suggestions and decision support, and generates reports.

The specific implementation process is as follows: First, the user builds a 3D model by inputting the original data of the complete set of mining machinery applications, including the physical information, attribute information and spatial relationship between the equipment. These data can be imported through special input devices or directly from existing databases.

After the model is established, the information management subsystem is responsible for informatization of the model. This includes the entry, query and update of information on the procurement, transportation, installation and commissioning of equipment. For example, when new equipment arrives, the information manager can enter the detailed information of the equipment in the system, including model, specification, production date, etc., and record the transportation and installation process of the equipment.

The data acquisition subsystem monitors the operating status, position and environmental parameters of mining machinery in real time by integrating various sensors. For example, speed sensors can monitor the operating speed of machinery, vibration sensors can monitor the vibration of machinery, infrared sensors can monitor the temperature of machinery, etc. All these raw data will be cleaned, filtered and formatted by the data preprocessing module to ensure the accuracy and reliability of the data. After that, the data transmission module transmits the processed data to the data analysis subsystem or cloud storage platform.

The data analysis subsystem is responsible for in-depth analysis of the collected data. For example, it can perform pipeline collision checks to ensure that various pipelines do not conflict in space. In addition, it can also analyze the operating efficiency of machinery, predict potential failures, etc.

The BIM model and visualization subsystem combines the results of data analysis with the BIM model and presents it to users in an intuitive way. For example, if data analysis shows that there is a pipeline collision problem somewhere, the BIM model and visualization subsystem will display the location and degree of the collision in a graphical way to help users quickly identify and solve the problem.

Based on the information data of the model and the results of data analysis, the decision support subsystem can simulate and optimize the construction plan. For example, it can simulate different construction plans, analyze their feasibility and advantages and disadvantages, and provide optimization suggestions and decision support. Finally, a report is generated for decision makers to refer to.

For example, a mine needs to install a new dumper. First, a 3D model of the dumper is built through the model building subsystem. Then, the information management subsystem enters the purchase information, transportation plan and installation location of the dumper. During the installation of the dumper, the data acquisition subsystem monitors its operating status and environmental parameters in real time, such as the vibration of the dumper, the operating speed, and the surrounding temperature and humidity. The data analysis subsystem conducts in-depth analysis of these data to determine whether the operating status of the dumper is normal and whether there are potential faults. The BIM model and visualization subsystem combines the results of data analysis with the BIM model and presents them to users in a graphical way, such as showing the running track and vibration amplitude of the dumper. Finally, the decision support subsystem simulates different dumper installation plans based on the information data and analysis results, and provides optimization suggestions and decision support. For example, it may suggest adjusting the position of the dumper or taking certain measures to reduce its vibration amplitude.

Embodiment 2 is different from the above embodiment in that when the data analysis subsystem determines that the received vibration sensor data is abnormal, the analysis process of the data analysis subsystem is as follows:

The data analysis subsystem determines whether the vibration data is abnormal due to the passage of a living organism based on the data from the infrared sensor.

The data analysis subsystem determines whether there are abnormal vibration data caused by the passing of vehicles based on the transportation data of the information management subsystem.

The data analysis subsystem determines whether the vibration data abnormality is caused by geological disasters based on the vibration frequency and fluctuation in the vibration sensor data.

At the same time, the data analysis subsystem determines whether the vibration data abnormality is caused by mechanical failure based on the historical data of the vibration sensor data.

The system also includes an early warning subsystem, which is used to issue early warnings for abnormal situations based on the analysis results of the data analysis subsystem.

The specific implementation process is as follows: First, the system collects the operation data and environmental information of mining machinery in real time through various sensors (such as vibration sensors and infrared sensors). These data include the vibration frequency, fluctuation, operation status of the machinery, as well as the temperature, humidity, biological activities, etc. in the environment. The data analysis subsystem pre-processes the collected raw data, such as filtering and denoising, to ensure the accuracy and reliability of the data. Then, according to the data from different sensors, analysis is performed:

Determine whether there is a biological process: Analyze the infrared sensor data to see if there is any sign of biological activity. If so, the vibration data may be abnormal due to the biological process.

Determine whether a vehicle is passing by: Analyze the transportation data in the information management subsystem to determine whether a vehicle is nearby or passing by. If so, the vibration data may be abnormal due to the vehicle passing by.

Determine whether a geological disaster has occurred: Based on the vibration frequency and fluctuations in the vibration sensor data, combined with geological exploration data and historical experience, determine whether a geological disaster such as an earthquake or landslide may occur.

Determine whether a mechanical failure has occurred: By analyzing the historical data of vibration sensor data, combined with the operating status and maintenance records of the machinery, determine whether a mechanical failure or potential failure signs have occurred.

Once the data analysis subsystem determines an abnormal situation, the early warning subsystem will be activated immediately. Based on the analysis results of the data analysis subsystem, the early warning subsystem determines the level of the warning (such as low, medium, high) and the method (such as sound and light warning, SMS notification, etc.).

For example:

If the data analysis subsystem determines that the passage of a living organism may cause data anomalies, the early warning subsystem may issue a low-level warning, alerting on-site personnel by flashing lights.

If it is determined that the vibration data is abnormal due to the passing of a vehicle, the early warning subsystem may issue an intermediate warning and notify relevant personnel through a sound alarm.

If it is judged that a geological disaster or mechanical failure may occur, the early warning subsystem will issue a high-level warning and quickly notify relevant personnel to take response measures through various means (such as sound, light, electricity, text messages, etc.).

In summary, when the data analysis subsystem determines that the received vibration sensor data is abnormal, its multi-dimensional analysis process can provide multiple possible explanations and causes, with beneficial effects including improving the accuracy and reliability of the analysis, comprehensively considering various potential causes, and reducing misjudgments.

Embodiment 3 is different from the above embodiments in that the system further includes a safety management subsystem, which is used to monitor the operating status and environmental parameters of mining machinery in real time and to provide real-time warning and protection for dangerous areas.

The specific implementation process is as follows: After receiving the data from the data transmission module, the safety management subsystem performs real-time analysis. The analysis includes the operating status of the machinery, changes in environmental parameters, and judgment of abnormal situations. Once the safety management subsystem finds an abnormal situation, it needs to issue early warnings and warnings in a timely manner. In addition to early warnings and warnings, the safety management subsystem also needs to have safety protection functions. For example, when the system detects that there is danger in a certain area, it can reduce risks by automatically controlling the start and stop of the machinery and restricting the entry and exit of personnel.

Embodiment 4 is different from the above embodiments in that the system further includes a user management subsystem, which is used to grant different data access and usage permissions to different users according to different roles and responsibilities.

The specific implementation process is as follows: First, clarify the different roles and responsibilities involved in the system, such as administrators, project managers, data analysts, and machine operators. These roles correspond to different responsibilities and functional requirements, so different data access and usage permissions need to be assigned to them.

Administrators have the highest authority and can access all functions and data of the entire system. Administrators can manage other users, assign different roles and permissions to them, and perform system configuration and adjustment operations.

Project managers are mainly concerned with project-related information and operations, so they can be assigned project-related permissions. For example, project managers can view project progress, manage project team members, and analyze project data.

Data analysts are mainly responsible for processing, analyzing, and visualizing data in the system. Therefore, data analysts can be assigned permissions related to data processing and analysis, such as data query, data export, chart generation, etc.

The machine operator is mainly responsible for the operation and maintenance of the machine, so he can be assigned permissions related to the operation and maintenance of the machine, such as remote control of the machine, operating status monitoring, maintenance record viewing, etc.

Through the implementation of the user management subsystem, different users can be given different data access and usage permissions according to their different roles and responsibilities. This helps to ensure the security and reliability of the system while improving the efficiency and effectiveness of the system. In actual applications, the user management subsystem also needs to be integrated and work in collaboration with other subsystems to ensure the smooth operation and effective management of the entire system.

In summary, the user management subsystem has beneficial effects in improving data security, improving work efficiency, simplifying management processes, enhancing system scalability and strengthening system reliability in the complete application analysis system of mining machinery based on BIM technology.

The above is only an embodiment of the present invention, and the common knowledge such as the known specific structure and/or characteristics in the scheme is not described in detail here. It should be pointed out that for those skilled in the art, several deformations and improvements can be made without departing from the structure of the present invention, which should also be regarded as the protection scope of the present invention, and these will not affect the effect of the implementation of the present invention and the practicality of the patent. The scope of protection required by this application shall be based on the content of its claims, and the specific implementation methods and other records in the specification can be used to interpret the content of the claims.

Claims (8)

1. A complete set of mining machinery application analysis system based on BIM technology, characterized by: including a model building subsystem, an information management subsystem, a data acquisition subsystem, a data analysis subsystem, a BIM model and visualization subsystem and a decision support subsystem; The model building subsystem is used to construct a three-dimensional model by inputting the original data of the complete set of mining machinery applications; The information management subsystem is used to process the model informatically; The data acquisition subsystem includes a sensor integration module, a data preprocessing module and a data transmission module. The sensor integration module is used to monitor the operating status, position and environmental parameters of mining machinery in real time. The data preprocessing module is used to clean, filter and format the raw data. The data transmission module is used to transmit the processed data to the data analysis subsystem or cloud storage platform. The data analysis subsystem is used to conduct in-depth analysis of the collected data and perform pipeline collision inspection; The BIM model and visualization subsystem is used to combine data analysis results with the BIM model and display them in an intuitive way; The decision support subsystem simulates and optimizes the construction plan based on the model's information data and data analysis results, provides optimization suggestions and decision support, and generates reports. 2. According to the BIM technology-based mining machinery complete application analysis system according to claim 1, it is characterized in that the input original data includes the physical information, attribute information and spatial relationship between the equipment. 3. According to the BIM technology-based mining machinery complete application analysis system of claim 1, it is characterized in that the information processing includes information entry, query and update of equipment procurement, transportation, installation and debugging. 4. According to the BIM technology-based mining machinery complete application analysis system according to claim 1, it is characterized in that the sensor integration module includes a speed sensor, a vibration sensor, an infrared sensor, a temperature sensor, a pressure sensor, an oil sensor, a GPS sensor, a mileage sensor, an angle sensor, a meteorological sensor, a soil moisture sensor, a soil quality sensor, a dust sensor, a noise sensor and a toxic gas sensor. 5. The complete application analysis system for mining machinery based on BIM technology according to claim 1 is characterized in that: when the data analysis subsystem determines that the received vibration sensor data is abnormal, the analysis process of the data analysis subsystem is: The data analysis subsystem determines whether there is abnormal vibration data caused by the passage of organisms based on the data from the infrared sensor; The data analysis subsystem determines whether there are abnormal vibration data caused by the passing of vehicles based on the transportation data of the information management subsystem; The data analysis subsystem determines whether the vibration data is abnormal due to geological disasters based on the vibration frequency and fluctuation in the vibration sensor data; At the same time, the data analysis subsystem determines whether the vibration data abnormality is caused by mechanical failure based on the historical data of the vibration sensor data. 6. According to the BIM-based mining machinery complete application analysis system of claim 1, it is characterized in that the system also includes an early warning subsystem, which is used to warn of abnormal situations based on the analysis results of the data analysis subsystem. 7. According to the BIM technology-based mining machinery complete application analysis system according to claim 1, it is characterized in that: the system also includes a safety management subsystem, which is used to monitor the operating status and environmental parameters of the mining machinery in real time, and to provide real-time warnings and protection for dangerous areas. 8. According to the BIM technology-based mining machinery complete application analysis system of claim 1, it is characterized in that the system also includes a user management subsystem, which is used to grant different data access and usage permissions to different users according to different roles and responsibilities.