Multi-working-condition data acquisition device applied to new energy mining equipment
By combining the MODBUS and CAN acquisition system with the host computer module and the adaptive unscented Kalman filter algorithm, the problems of incomplete parameters, inconsistent time axes, and poor adaptability of the data acquisition device for new energy mining equipment were solved, realizing comprehensive monitoring and high-precision speed measurement, and improving the safety of underground operations and the efficiency of data analysis.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- CHINA MINMETALS CHANGSHA MINING RES INST
- Filing Date
- 2026-04-22
- Publication Date
- 2026-07-21
AI Technical Summary
Existing data acquisition devices for new energy mining equipment suffer from incomplete data acquisition parameters, inconsistent data timelines, poor adaptability, low accuracy, and inflexible data transmission and storage methods. They cannot meet the monitoring needs under complex working conditions, and the underground environment is flammable and explosive, increasing safety risks.
The system employs a MODBUS and CAN acquisition system combined with a host computer module and a power supply module to achieve unified acquisition and recording of data from multiple types of sensors and CAN bus data. It combines GPS and millimeter-wave radar with an adaptive unscented Kalman filter algorithm for speed measurement, uses a mobile power supply, and supports flexible data transmission and storage.
It enables comprehensive parameter acquisition of new energy mining equipment, unifies the timeline, improves the accuracy and precision of data analysis, enhances the adaptability and safety of the equipment in complex underground environments, ensures accurate speed measurement in areas without GPS signals, and supports real-time analysis and long-term data storage.
Smart Images
Figure CN122432094A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of mining operation technology, and in particular to a multi-condition data acquisition device for new energy mining equipment. Background Technology
[0002] With the rapid development of new energy battery technology, the mining industry is gradually applying it to production practices. However, underground working environments are extreme, and mining equipment faces complex and diverse operating conditions. Therefore, it is necessary to collect operational data from new energy mining equipment from multiple perspectives. To ensure the stable operation of new energy mining equipment and guarantee safe mining operations, data acquisition devices not only help improve the reliability and stability of equipment operating in complex environments, but also effectively prevent major accidents and improve the level of mine safety management.
[0003] Currently, the operational data acquisition devices for new energy mining equipment still have the following shortcomings:
[0004] The collected parameters are not comprehensive enough to meet the comprehensive monitoring needs of complex operating conditions of new energy mining equipment; the inconsistent timelines of data collected from different parameters lead to difficulties in data analysis and make it difficult to accurately reflect the actual operating status of the equipment; the data acquisition device has poor adaptability to complex underground environments, low accuracy, and cannot accurately measure speed in areas without GPS signals; the data transmission and storage methods are not flexible and efficient enough, which is not conducive to real-time data analysis and long-term data preservation. These limitations may threaten the stability and safety of the equipment, thereby increasing the risks of underground operations. In addition, the excessive length of the cables increases the size of the acquisition equipment, making it inconvenient for personnel to carry. At the same time, the underground environment is filled with flammable and explosive dust and gases, and the normal operation of the battery greatly affects work safety. Summary of the Invention
[0005] This application proposes a multi-condition data acquisition device for new energy mining equipment, which can solve one of the problems existing in the background technology.
[0006] To achieve the above objectives, this application adopts the following technical solution:
[0007] A multi-condition data acquisition device for new energy mining equipment is provided. The multi-condition data acquisition device has a unified time axis and includes:
[0008] The MODBUS data acquisition system is used to collect sensor data from various types of sensors in the new energy mining equipment.
[0009] The CAN acquisition system is used to acquire CAN bus data in the new energy mining equipment.
[0010] The host computer module is used to obtain the sensing data and CAN bus data from the MODBUS acquisition system and the CAN acquisition system, and to record the obtained data; and,
[0011] The power supply module is used to supply power to the MODBUS acquisition system, the CAN acquisition system, and the host computer module.
[0012] Based on the above technical solution, this multi-condition data acquisition device has a unified timeline and includes: a MODBUS acquisition system for acquiring sensor data from various types of sensors in the new energy mining equipment; a CAN acquisition system for acquiring CAN bus data from the new energy mining equipment; a host computer module for obtaining sensor data and CAN bus data from the MODBUS and CAN acquisition systems and recording the acquired data; and a power supply module. This enables comprehensive acquisition of parameters from the new energy mining equipment, meeting the comprehensive monitoring needs of complex operating conditions. The unified data timeline facilitates data analysis and accurately reflects the actual operating status of the equipment. It exhibits high adaptability and accuracy in complex underground environments, and can accurately measure speed even in areas without GPS signals. The data transmission and storage methods are flexible and efficient, facilitating real-time data analysis and long-term data preservation. The use of a portable power supply makes it easy for data acquisition personnel to carry.
[0013] In one possible design, the MODBUS data acquisition system includes: a GPS for speed measurement and a millimeter-wave radar, and the host computer module is specifically used for:
[0014] When the GPS is valid, the first velocity measured by the GPS and the second velocity measured by the millimeter-wave radar are fused to obtain the final velocity.
[0015] When the GPS fails, the second speed shall be taken as the final speed.
[0016] In one possible design, the host computer module uses the first velocity as the input to the observation equation and the second velocity as the input to the state equation, and employs an adaptive unscented Kalman filter to obtain the final velocity.
[0017] In one possible design approach,
[0018] The state variable is defined as x=[v,a] T Where v is the equipment's operating speed, a is the acceleration, and T is the transpose.
[0019] State transition function f( )for:
[0020] Where F is the state transition matrix; The noise level is T, which represents the sampling period.
[0021] The host computer module is specifically used for:
[0022] Based on the state mean at time k-1 Covariance Generate the corresponding Sigma points:
[0023] Determine the mean weighting coefficient and the covariance weighting coefficient at the Sigma points:
[0024] Based on the state mean at time k-1 Covariance The state propagation prediction and mean-covariance prediction are performed using the Sigma point mean weighting coefficient and the Sigma point covariance weighting coefficient.
[0025] Where n is the state dimension; is the scaling factor; i is the i-th Sigma point; The weighting factor for the mean of the Sigma points; Sigma point covariance weighting coefficient; These are the distribution parameters; These are error parameters for higher-order terms.
[0026] In one possible design, the host computer module is further used for:
[0027] Based on a recursive estimation mechanism of the innovation sequence, the statistical properties of the process noise covariance matrix Q and the observation noise covariance matrix R are estimated and dynamically adjusted in real time online:
[0028] Among them, z k The value observed at time k is the first velocity measured by GPS; diag( ) is the operator for constructing diagonal matrices; α and β are forgetting factors; v k For the information at time k.
[0029] In one possible design, the MODBUS acquisition system includes: a Hall voltage sensor, a Hall current sensor, a temperature sensor, a pressure sensor, and a flow sensor. The sensor data acquired by each sensor is stored in a microSD card via a serial port acquisition unit. The host computer reads the sensor data from the microSD card via a USB bus.
[0030] In one possible design, the CAN acquisition system includes: a CAN data logger, which reads the CAN bus data through a CAN2.0 interface, and the host computer reads the CAN bus data from the CAN data logger via WIFI.
[0031] In one possible design, the power supply module uses a discrete mobile power supply.
[0032] In one possible design, the host computer module is also used to: compare and analyze the acquired data to obtain anomaly analysis results for the new energy mining equipment.
[0033] In one possible design, the host computer module is also used to: display the acquired data in charts. Attached Figure Description
[0034] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0035] Figure 1 This is a schematic diagram of the MODBUS acquisition system provided in the embodiments of this application;
[0036] Figure 2 This is a schematic diagram of the CAN acquisition system provided in the embodiments of this application;
[0037] Figure 3 This is a roadmap of the AUKF-based speed measurement algorithm provided in the embodiments of this application;
[0038] Figure 4 This is a power supply schematic diagram provided in an embodiment of this application;
[0039] Figure 5 This is a schematic diagram of the working condition data acquisition and reading software provided in the embodiments of this application. Detailed Implementation
[0040] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.
[0041] It should be noted that although functional modules are divided in the device schematic diagram and a logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the device or the order in the flowchart. The terms "first," "second," etc., in the specification, claims, and the aforementioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.
[0042] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.
[0043] This embodiment specifically relates to a portable multi-condition data acquisition device for new energy mining equipment, applied to the multi-directional condition data acquisition of new energy mining equipment operating in complex mine environments. The device features comprehensive parameter acquisition capabilities, a unified timeline, good underground adaptability, and efficient data transmission and storage methods.
[0044] like Figure 1-5 As shown, the technical solution for the data acquisition equipment is as follows:
[0045] The data acquisition device has a unified timeline and includes:
[0046] The MODBUS data acquisition system is used to collect sensor data from various types of sensors in the new energy mining equipment.
[0047] The CAN acquisition system is used to acquire CAN bus data in the new energy mining equipment.
[0048] The host computer module is used to obtain the sensing data and CAN bus data from the MODBUS acquisition system and the CAN acquisition system, and to record the obtained data; and,
[0049] The power supply module is used to supply power to the MODBUS acquisition system, the CAN acquisition system, and the host computer module.
[0050] Based on the above technical solution, this multi-condition data acquisition device has a unified timeline and includes: a MODBUS acquisition system for acquiring sensor data from various types of sensors in the new energy mining equipment; a CAN acquisition system for acquiring CAN bus data from the new energy mining equipment; a host computer module for obtaining sensor data and CAN bus data from the MODBUS and CAN acquisition systems and recording the acquired data; and a power supply module. This enables comprehensive acquisition of parameters from the new energy mining equipment, meeting the comprehensive monitoring needs of complex operating conditions. The unified data timeline facilitates data analysis and accurately reflects the actual operating status of the equipment. It exhibits high adaptability and accuracy in complex underground environments, and can accurately measure speed even in areas without GPS signals. The data transmission and storage methods are flexible and efficient, facilitating real-time data analysis and long-term data preservation. The use of a portable power supply makes it easy for data acquisition personnel to carry.
[0051] In one possible design, the MODBUS data acquisition system includes: a GPS for speed measurement and a millimeter-wave radar, and the host computer module is specifically used for:
[0052] When the GPS is valid, the first velocity measured by the GPS and the second velocity measured by the millimeter-wave radar are fused to obtain the final velocity.
[0053] When the GPS fails, the second speed shall be taken as the final speed.
[0054] In one possible design, the host computer module uses the first velocity as the input to the observation equation and the second velocity as the input to the state equation, and employs an adaptive unscented Kalman filter to obtain the final velocity.
[0055] In one possible design approach,
[0056] The state variable is defined as x=[v,a] T Where v is the equipment's operating speed, a is the acceleration, and T is the transpose.
[0057] State transition function f( )for:
[0058] Where F is the state transition matrix; denoted as process noise; T is the sampling period.
[0059] The host computer module is specifically used for:
[0060] Based on the state mean at time k-1 Covariance Generate the corresponding Sigma points:
[0061] Determine the mean weighting coefficient and the covariance weighting coefficient at the Sigma points:
[0062] Based on the state mean at time k-1 Covariance The state propagation prediction and mean-covariance prediction are performed using the Sigma point mean weighting coefficient and the Sigma point covariance weighting coefficient.
[0063] Where n is the state dimension; is the scaling factor; i is the i-th Sigma point; The weighting coefficients for the Sigma point mean are... Sigma point covariance weighting coefficient; These are the distribution parameters; These are error parameters for higher-order terms.
[0064] In one possible design, the host computer module is further used for:
[0065] Based on a recursive estimation mechanism of the innovation sequence, the statistical properties of the process noise covariance matrix Q and the observation noise covariance matrix R are estimated and dynamically adjusted in real time online:
[0066] Among them, z k The value observed at time k is the first velocity measured by GPS; diag( ) is the operator for constructing diagonal matrices; α and β are forgetting factors; v k For the information at time k.
[0067] In one possible design, the MODBUS acquisition system includes: a Hall voltage sensor, a Hall current sensor, a temperature sensor, a pressure sensor, and a flow sensor. The sensor data acquired by each sensor is stored in a microSD card via a serial port acquisition unit. The host computer reads the sensor data from the microSD card via a USB bus.
[0068] In one possible design, the CAN acquisition system includes: a CAN data logger, which reads the CAN bus data through a CAN2.0 interface, and the host computer reads the CAN bus data from the CAN data logger via WIFI.
[0069] In one possible design, the power supply module uses a discrete mobile power supply.
[0070] In one possible design, the host computer module is also used to: compare and analyze the acquired data to obtain anomaly analysis results for the new energy mining equipment.
[0071] In one possible design, the host computer module is also used to: display the acquired data in charts.
[0072] Specifically:
[0073] Power Data Acquisition Unit Structure: The power data acquisition unit consists of two parts: a MODBUS acquisition system and a CAN acquisition system. The MODBUS acquisition system is as follows... Figure 1 As shown: The physical layer uses a 485 bus for transmission and adopts the MODBUS RTU protocol. This system primarily records parameters acquired by the acquisition device itself, including mining equipment speed, total voltage, total current, operating device status, hydraulic system pressure, hydraulic system flow, and hydraulic system temperature. Data collected by various sensors is transmitted to the MODBUS acquisition system via the 485 bus, enabling centralized acquisition of multiple key parameters. The CAN acquisition system is shown below. Figure 2 As shown: Connected to the CAN bus of the mining equipment, the system listens for and records data transmitted on the bus, including bus voltage, bus current, and individual battery temperature. The CAN acquisition system monitors the data signals on the CAN bus in real time, collects and processes the data, and finally uses a host computer to parse the collected data to obtain accurate equipment operating parameters.
[0074] Data transmission:
[0075] Serial port data acquisition unit: Powered by a wide 9-30V supply with a power consumption of 0.5W, and supporting baud rates from 1.92Kbps to 961.2Kbps, making it ideal for portable systems. Configured via a host computer, it can communicate with devices using the standard Modbus-RTU protocol and store the parsed data in CSV format on a microSD card. This wide power supply design ensures stable operation under varying power conditions, while the flexible baud rate settings meet the data transmission needs of different devices, and the CSV format storage facilitates subsequent data processing and analysis.
[0076] CAN Bus Recorder: Supports real-time Wi-Fi transmission and features built-in long-term message storage. It can independently record data via two CAN / CAN FD bus channels, operating without a PC. Data is transmitted to the PC in real-time via Wi-Fi, facilitating data analysis and recording. The independent operation and real-time transmission capabilities of the CAN bus recorder allow for continuous data acquisition and timely transmission to the PC for analysis and processing even without a PC connection. Acquisition Card: With a sampling frequency of 500Hz and a maximum baud rate of 115.2Kbps, it meets high-speed sampling and transmission requirements. The device also features wide-range power supply with a power consumption of 0.8W. The acquisition card's high-speed sampling and transmission capabilities ensure accurate acquisition and timely transmission of rapidly changing operating condition data.
[0077] Speed measurement module based on adaptive unscented Kalman filter (AUKF): The process is as follows Figure 3 As shown, the system simultaneously utilizes GPS and millimeter-wave radar for fusion speed measurement. The design explicitly uses the millimeter-wave radar output speed as the input to the AUKF state equation, while GPS speed measurement data serves as the input to the AUKF observation equation. Considering the reality that new energy mining equipment cannot receive GPS signals during underground operations, the system adopts a "GPS module retention + millimeter-wave radar switching" design strategy. In underground environments where GPS signals are unavailable, the millimeter-wave radar independently completes the speed measurement task. This millimeter-wave radar speed measurement module, based on the transmission and reception principles of millimeter-wave signals, can capture the equipment's operating speed in real time, forming a highly efficient complement to the GPS speed measurement module, ultimately ensuring accurate acquisition of equipment speed information across all operational scenarios. The specific steps of the AUKF estimation are as follows:
[0078] (1) Based on the state mean at time k-1 Covariance Generate the corresponding Sigma points: (1)
[0079] In the formula: n — state dimension; — Scaling factor; i — The i-th Sigma point.
[0080] (2) Weight determination: (2)
[0081] In the formula: —Sigma point mean weighting coefficient; —Sigma point covariance weighting coefficient; —— ——
[0082] (3) State propagation and prediction: (3)
[0083] (4) Mean covariance prediction: (4)
[0084] Meanwhile, traditional Kalman filtering algorithms typically pre-set the process noise covariance matrix Q and the observation noise covariance matrix R as fixed constants, making it difficult to match the dynamic evolution of noise characteristics in real time, thus leading to decreased filtering accuracy or even divergence. In contrast, the improved Sage-Husa adaptive filtering algorithm, by constructing a recursive estimation mechanism based on innovation sequences, can estimate and dynamically adjust the statistical characteristics of Q and R in real time, thereby compensating for the effects of model parameter uncertainty and time-varying noise, significantly improving the adaptability and robustness of the filtering algorithm in complex dynamic scenarios. The adaptive parameter update formula is as follows: (5)
[0085] In the formula: α, β—forgetting factors; v k —New information at moment k.
[0086] Sensors: Both voltage and current sensors utilize the Hall effect, offering high measurement accuracy and resolution. The current sensor features an open design for easy installation. Hall effect sensors convert voltage and current signals into electrical signals for measurement using the Hall effect, offering advantages such as high accuracy and high resolution. The open design of the current sensor allows for installation without disassembling the equipment, significantly improving installation convenience.
[0087] Power Supply: Considering that the new energy mining equipment needs to be moved around and requires power during data collection, the power data acquisition instrument is powered by a 12V 20000mAh portable power bank, which is compact and easy to carry. Figure 4 As shown, there are two power supplies. One supplies power to the sensor, and the other supplies power to the serial port data acquisition unit and the CAN vehicle recorder. This is to ensure load balancing and allow the power data acquisition unit to have a longer operating time. This dual-power supply method rationally distributes the load, extends the overall operating time of the data acquisition unit, and meets the power supply requirements of mining equipment during mobile operations.
[0088] Host computer software: The developed host computer software has charting and data analysis / statistics functions. It can analyze the collected data and simultaneously compare parameters such as bus voltage and current, and battery temperature. Specifically, for example... Figure 5As shown, the host computer software displays the collected data in intuitive charts, facilitating viewing and analysis by operators. Simultaneously, by comparing and analyzing key parameters such as bus voltage and current, battery temperature, and CAN messages, abnormal situations during equipment operation can be detected promptly.
[0089] The portable new energy mining equipment multi-condition data acquisition device involved in this embodiment has the following advantages:
[0090] 1. Currently, most mining equipment condition data acquisition devices may only focus on collecting some key parameters, such as basic parameters like voltage and current. The device of this invention can simultaneously collect multiple data points, including speed, control device status, and hydraulic system parameters, and has a unified timeline and CAN message monitoring function, providing more comprehensive equipment condition information.
[0091] 2. Traditional downhole speed measurement methods suffer from drawbacks such as limited versatility and poor accuracy, making it difficult to meet the precise speed measurement requirements under complex operating conditions without GPS signals. This device innovatively adopts a GPS-millimeter-wave radar dual-mode speed measurement architecture based on adaptive unscented Kalman filtering (AUKF). When downhole GPS signals are missing, it automatically switches to independent millimeter-wave radar speed measurement mode; when GPS signals are stable, it fuses the dual-mode speed measurement data through the AUKF algorithm, significantly improving the accuracy and robustness of the speed measurement system. Previous data acquisition devices may not have considered the impact of load balancing on the power module.
[0092] 3. By rationally allocating power from two mobile power sources, the working time is extended while ensuring the normal operation of the equipment, thus improving the applicability of the data collection device in long-term field operations.
[0093] The above description is the preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications are also considered to be within the scope of protection of this application.
Claims
1. A multi-condition data acquisition device for new energy mining equipment, characterized in that, The multi-condition data acquisition device has a unified time axis and includes: The MODBUS data acquisition system is used to collect sensor data from various types of sensors in the new energy mining equipment. The CAN acquisition system is used to acquire CAN bus data in the new energy mining equipment. The host computer module is used to obtain the sensing data and CAN bus data from the MODBUS acquisition system and the CAN acquisition system, and to record the obtained data; and, The power supply module is used to supply power to the MODBUS acquisition system, the CAN acquisition system, and the host computer module.
2. The multi-condition data acquisition device for new energy mining equipment as described in claim 1, characterized in that, The MODBUS data acquisition system includes: a GPS for speed measurement and a millimeter-wave radar. The host computer module is specifically used for: When the GPS is valid, the first velocity measured by the GPS and the second velocity measured by the millimeter-wave radar are fused to obtain the final velocity. When the GPS fails, the second speed shall be taken as the final speed.
3. The multi-condition data acquisition device for new energy mining equipment as described in claim 2, characterized in that, The host computer module uses the first speed as the observation quantity and the second speed as the state quantity, and employs an adaptive unscented Kalman filter to obtain the final speed.
4. The multi-condition data acquisition device for new energy mining equipment as described in claim 3, characterized in that, The state variable is defined as x=[v,a] T Where v is the equipment's operating speed, a is the acceleration, and T is the transpose. State transition function f( )for: Where F is the state transition matrix; The noise level is T, which represents the sampling period. The host computer module is specifically used for: Based on the state mean at time k-1 Covariance Generate the corresponding Sigma points: Determine the mean weighting coefficient and the covariance weighting coefficient at the Sigma points: Based on the state mean at time k-1 Covariance The state propagation prediction and mean-covariance prediction are performed using the Sigma point mean weighting coefficient and the Sigma point covariance weighting coefficient. Where n is the state dimension; is the scaling factor; i is the i-th Sigma point; The weighting factor for the mean of the Sigma points; Sigma point covariance weighting coefficient; These are the distribution parameters; These are error parameters for higher-order terms.
5. The multi-condition data acquisition device for new energy mining equipment as described in claim 4, characterized in that, The host computer module is also specifically used for: Based on a recursive estimation mechanism of the innovation sequence, the statistical properties of the process noise covariance matrix Q and the observation noise covariance matrix R are estimated and dynamically adjusted in real time online: Among them, z k The value observed at time k is the first velocity measured by GPS; diag( ) is the operator for constructing diagonal matrices; α and β are forgetting factors; v k For the information at time k.
6. The multi-condition data acquisition device for new energy mining equipment as described in claim 1, characterized in that, The MODBUS data acquisition system includes: a Hall voltage sensor, a Hall current sensor, a temperature sensor, a pressure sensor, and a flow sensor. The sensor data acquired by each sensor is stored in a microSD card via a serial port acquisition device. The host computer reads the sensor data from the microSD card via a USB bus.
7. The multi-condition data acquisition device for new energy mining equipment as described in claim 1, characterized in that, The CAN acquisition system includes a CAN data logger, which reads the CAN bus data through a CAN2.0 interface, and the host computer reads the CAN bus data from the CAN data logger via WIFI.
8. The multi-condition data acquisition device for new energy mining equipment as described in claim 1, characterized in that, The power supply module uses a separate mobile power supply.
9. The multi-condition data acquisition device for new energy mining equipment as described in claim 1, characterized in that, The host computer module is also used to: compare and analyze the acquired data to obtain anomaly analysis results for new energy mining equipment.
10. The multi-condition data acquisition device for new energy mining equipment as described in claim 1, characterized in that, The host computer module is also used to: display the obtained data in charts.