Intelligent monitoring method, device and system for mountain transportation system

Abstract

The present invention discloses an intelligent monitoring method, device, and system for a mountain transport system. The method acquires operating status data of the mountain transport system, preprocesses and calibrates the operating status data to obtain processed operating status data, compares the processed operating status data with a corresponding first preset threshold value, and obtains a first comparison result. Based on the first comparison result, the method determines whether an abnormality exists in the mountain transport system. If an abnormality exists, a first alarm message is sent to an intelligent monitoring platform. If no abnormality exists, the processed operating status data is sent to the intelligent monitoring platform for storage and identification to determine whether an abnormality exists. This method improves the reliability of emergency monitoring and early warning in mountain transport systems.

Description

Technical Field

[0001] The present invention relates to the technical field of mountain transport monitoring, and in particular to an intelligent monitoring method, device and system for a mountain transport system. Background Art

[0002] With rapid economic development, the demand for electricity in people's daily lives is increasing. The workload for power transmission line construction is increasing year by year, and construction deadlines are shrinking. The ability to conveniently and quickly transport power supplies (transmission line tower materials, sand and gravel, and construction equipment) to the construction site is paramount to ensuring the construction schedule. However, most power transmission line projects are located in mountainous areas. Furthermore, rainy days can cause muddy roads, and the often harsh transportation conditions of high mountains, steep slopes, narrow bends, dangerous roads, and slippery roads often hinder construction progress. This often results in delayed material supply, or even the inability to transport them, severely hindering project progress.

[0003] Currently, transportation for power transmission line projects in mountainous areas still relies primarily on human (and animal) labor, supplemented by machinery, resulting in a low level of mechanization. With rapid economic and social development, traditional animal power, such as mules and horses, is in short supply, driving up transportation costs and increasing labor costs. This labor-intensive construction method is becoming unsustainable. Furthermore, the few mechanized transportation systems currently available lack sufficient on-site monitoring capabilities. Equipment status monitoring and system control rely heavily on the experience of technicians, making them incapable of accurately monitoring the status of the transportation system and emergency situations, or providing early warnings of failures, resulting in low reliability. Summary of the Invention

[0004] In order to solve the above technical problems, the embodiments of the present invention provide an intelligent monitoring method, device and system for a mountain transportation system to solve the technical problem of low reliability of emergency monitoring and early warning in mountain transportation systems in the prior art.

[0005] A first aspect of an embodiment of the present invention provides an intelligent monitoring method for a mountain transportation system, the method comprising:

[0006] Obtaining operational status data of mountain transport systems;

[0007] preprocessing and calibrating the operating status data to obtain processed operating status data, comparing the processed operating status data with a corresponding first preset threshold value to obtain a first comparison result, and determining whether there is an abnormality in the mountain transport system based on the first comparison result; if there is an abnormality, sending a first alarm message to the intelligent monitoring platform; if there is no abnormality, sending the processed operating status data to the intelligent monitoring platform for storage;

[0008] The processed operating status data is sent to the intelligent monitoring platform for identification, so that the intelligent monitoring platform uses the intelligent identification model to identify the processed operating status data to obtain an identification result, and compares the identification result with the corresponding second preset threshold to obtain a second comparison result. According to the second comparison result, it is determined whether there is an abnormality in the mountain transportation system. If so, a second alarm message is issued, so that the monitoring personnel can adjust the mountain transportation system according to the second alarm message or the first alarm message.

[0009] In a possible implementation of the first aspect, obtaining operating status data of the mountain transportation system includes:

[0010] Receive operating status data collected by sensor units installed on each transport vehicle, wherein the operating status data includes operating speed data, load data, tilt angle data, driving route data, wind speed data and cargo status data.

[0011] In a possible implementation of the first aspect, the inclination angle data is obtained by a sensor unit provided at the center of the bottom of the transport vehicle, and the calculation formula of the inclination angle data is:

[0012]

[0013]

[0014] in, is the angle, is the output voltage, is the zero point voltage, is the angular sensitivity, is the output voltage range, is the angle measurement range;

[0015] The wind speed data is obtained through the wind speed sensor installed on the cableway support. The calculation formula of the wind speed data is:

[0016]

[0017] in, is the wind speed at the location of the basket, is the wind speed at the cargo basket station, The wind speed under the cargo basket, is the distance between the basket and the upper station, which is obtained by integrating the speed of the basket after it leaves the upper station. is the span length of the upper station and the lower station;

[0018] The load data is obtained through the sensor installed on the cargo basket rope of the transport vehicle. The calculation formula of the load data is:

[0019]

[0020] in, is the angle between the suspension rope and the horizontal plane, For tension.

[0021] In a possible implementation of the first aspect, preprocessing and calibrating the operating status data to obtain processed operating status data includes:

[0022] Filtering and denoising the operating status data by calculating the average value of the operating status data within a preset sliding window to obtain denoised data;

[0023] Perform linear calibration on the denoised data to obtain the processed operating status data.

[0024] In a possible implementation of the first aspect, enabling monitoring personnel to adjust the mountain transportation system according to the second alarm information or the first alarm information includes:

[0025] When the first alarm information and the second alarm information are generated at the same time, the intelligent monitoring platform sends an emergency braking instruction and generates an abnormality report;

[0026] When either the first alarm information or the second alarm information is generated, the manual review process is started, the corresponding control strategy is implemented and the corresponding decision result is recorded.

[0027] In a possible implementation of the first aspect, after the operating status data is sent to the intelligent monitoring platform for storage, the method further includes:

[0028] Extracting features from the stored operating status data to obtain time domain feature data, frequency domain feature data, and correlation feature data;

[0029] Based on the time domain feature data, frequency domain feature data and correlation feature data, the initial recognition model is trained to obtain an intelligent recognition model.

[0030] To solve the same technical problem, a second aspect of an embodiment of the present invention provides an intelligent monitoring device for a mountain transportation system, comprising:

[0031] An acquisition module is used to obtain the operating status data of the mountain transportation system;

[0032] a first judgment module, configured to preprocess and calibrate the operating status data to obtain processed operating status data, compare the processed operating status data with a corresponding first preset threshold value to obtain a first comparison result, and determine whether there is an abnormality in the mountain transport system based on the first comparison result; if there is an abnormality, send a first alarm message to the intelligent monitoring platform; if there is no abnormality, send the processed operating status data to the intelligent monitoring platform for storage;

[0033] The second judgment module is used to send the processed operating status data to the intelligent monitoring platform for identification, so that the intelligent monitoring platform uses the intelligent recognition model to identify the processed operating status data to obtain an identification result, compare the identification result with the corresponding second preset threshold value to obtain a second comparison result, and judge whether there is an abnormality in the mountain transportation system based on the second comparison result. If so, a second alarm message is issued to enable the monitoring personnel to adjust the mountain transportation system based on the second alarm message or the first alarm message.

[0034] In a possible implementation manner of the second aspect, the acquisition module includes a receiving unit, wherein:

[0035] The receiving unit is used to receive the operating status data collected by the sensor units installed on each transport vehicle, wherein the operating status data includes operating speed data, load data, tilt angle data, driving route data, wind speed data and cargo status data.

[0036] To solve the same technical problem, a third aspect of an embodiment of the present invention provides an intelligent monitoring system for a mountain transportation system, comprising:

[0037] A sensor network, an intelligent monitoring device for a mountain transport system, and an intelligent monitoring platform, wherein the intelligent monitoring device for a mountain transport system is used to perform the intelligent monitoring device method for a mountain transport system according to the first aspect of the embodiments of the present invention;

[0038] The sensor network is connected to the intelligent monitoring device of the mountain transportation system, and the intelligent monitoring device of the mountain transportation system is connected to the intelligent monitoring platform.

[0039] In a possible implementation of the third aspect, the sensor network is used to send the collected operating status data to an intelligent monitoring device of the mountain transport system;

[0040] The intelligent monitoring device of the mountain transport system is used to obtain operating status data of the mountain transport system; preprocess and calibrate the operating status data to obtain processed operating status data; compare the processed operating status data with a corresponding first preset threshold value to obtain a first comparison result; determine whether there is an abnormality in the mountain transport system based on the first comparison result; if there is an abnormality, send a first alarm message to the intelligent monitoring platform; if there is no abnormality, send the processed operating status data to the intelligent monitoring platform for storage and identification;

[0041] The intelligent monitoring platform is used to receive the first alarm information and the processed operating status data, use the intelligent recognition model to identify the processed data to obtain an identification result, compare the identification result with the corresponding second preset threshold to obtain a second comparison result, and determine whether there is an abnormality in the mountain transportation system based on the second comparison result. If so, a second alarm information is issued, so that the monitoring personnel can adjust the mountain transportation system according to the second alarm information or the first alarm information.

[0042] The technical solution of the present invention has the following advantages:

[0043] The intelligent monitoring method for a mountain transport system provided by an embodiment of the present invention obtains operating status data of the mountain transport system, preprocesses and calibrates the operating status data to obtain processed operating status data, compares the processed operating status data with a corresponding first preset threshold value to obtain a first comparison result, determines whether the mountain transport system has an abnormality based on the first comparison result, and if so, sends a first alarm message to an intelligent monitoring platform; if not, sends the processed operating status data to the intelligent monitoring platform for storage; sends the processed operating status data to the intelligent monitoring platform for identification, so that the intelligent monitoring platform uses an intelligent recognition model to identify the processed operating status data and obtains an identification result; compares the identification result with a corresponding second preset threshold value to obtain a second comparison result, determines whether the mountain transport system has an abnormality based on the second comparison result, and if so, issues a second alarm message, allowing monitoring personnel to adjust the mountain transport system based on the second alarm message or the first alarm message. The above method improves the reliability of emergency monitoring and early warning in mountain transport systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific implementation methods or the description of the prior art. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0045] Figure 1 1. A monitoring flow chart of an intelligent monitoring method for a mountain transportation system according to an embodiment of the present invention;

[0046] Figure 2 A block diagram of a sensor network structure of an intelligent monitoring method for a mountain transportation system according to an embodiment of the present invention;

[0047] Figure 3 A distribution diagram of sensors on a double-track vehicle in an intelligent monitoring method for a mountain transportation system according to an embodiment of the present invention;

[0048] Figure 4 A distribution diagram of sensors on an all-terrain transport vehicle in an intelligent monitoring method for a mountain transport system according to an embodiment of the present invention;

[0049] Figure 5 A distribution diagram of cableway sensors in an intelligent monitoring method for a mountain transportation system according to an embodiment of the present invention;

[0050] Figure 6 This is a device block diagram of an intelligent monitoring device for a mountain transportation system according to an embodiment of the present invention;

[0051] Figure 7 This is a structural block diagram of a data processing center of an intelligent monitoring device for a mountain transportation system according to an embodiment of the present invention;

[0052] Figure 8 Flowchart of data processing of the intelligent monitoring system of the mountain transportation system in an embodiment of the present invention;

[0053] Reference numerals:

[0054] Among them, 101, double-track vehicle speed sensor; 111, double-track vehicle load sensor; 121, double-track vehicle tilt sensor; 131, double-track vehicle front end camera; 132, double-track vehicle rear end camera; 133, double-track vehicle side camera; 201, all-terrain transport vehicle speed sensor; 211, longitudinal beam vibration sensor; 212, cross beam vibration sensor; 213, motor vibration sensor; 221, all-terrain transport vehicle load sensor; 231, all-terrain transport vehicle tilt sensor; 2 41. External surveillance camera of all-terrain transport vehicle; 242. Internal surveillance camera of all-terrain transport vehicle; 301. Tension sensor at the first end of the cableway; 302. Tension sensor at the second end of the cableway; 311. Wind speed sensor at the first end of the cableway; 312. Wind speed sensor at the second end of the cableway; 321. Cableway speed sensor; 331. Cableway load sensor; 341. Cableway inclination sensor; 351. Cableway middle surveillance camera; 352. Cableway external surveillance camera; 353. Cableway internal surveillance camera. DETAILED DESCRIPTION

[0055] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0056] In the description of the present invention, it should be noted that the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance.

[0057] The embodiment of the present invention provides an intelligent monitoring method for a mountain transport system, such as Figure 1 As shown, Figure 1 This is a flow chart of the intelligent monitoring method for a mountain transport system, including steps S101 to S103. The details of each step are as follows:

[0058] S101. Obtaining operating status data of a mountain transportation system.

[0059] In this embodiment, the mountain transport system includes three transport units: a double-track vehicle, an all-terrain transport vehicle, and a cableway. According to the actual terrain and environment of the construction, a combination of the three transport modes can be selected to meet the transportation needs.

[0060] The cargo was transported from the flat areas outside the mountainous area to the hilly areas inside the mountainous area. Therefore, it was first transported by double-track vehicles, then by all-terrain transport vehicles, and finally by cableway to the construction site. First, the various sensor units installed on the transport vehicles collected operating status information of the transport units.

[0061] In one embodiment, obtaining the operating status data of the mountain transportation system includes:

[0062] Receive operating status data collected by sensor units installed on each transport vehicle, wherein the operating status data includes operating speed data, load data, tilt angle data, driving route data, wind speed data and cargo status data.

[0063] In this embodiment, the mountain transport system includes three transport units: a double-track vehicle, an all-terrain transport vehicle, and a cableway. Each transport vehicle includes a double-track vehicle, an all-terrain transport vehicle, and a cableway. Figure 2 As shown, the sensor units include a dual-track vehicle sensor unit, an all-terrain transport vehicle sensor unit, and a cableway sensor unit. The dual-track vehicle sensor unit is used to monitor the operating status of the dual-track vehicle in the mountain transport system and includes a speed sensor, a load sensor, an inclination sensor, and a surveillance camera. The all-terrain transport vehicle sensor unit is used to monitor the operating status of the all-terrain transport vehicle in the mountain transport system and includes a speed sensor, a vibration sensor, a load sensor, an inclination sensor, and a surveillance camera. The cableway sensor unit is used to monitor the operating status of the cableway in the mountain transport system and includes a tension sensor, a wind speed sensor, a speed sensor, a load sensor, an inclination sensor, and a surveillance camera.

[0064] In the double-track vehicle sensor unit, a speed sensor is set on the driving wheel hub of the double-track vehicle to measure the rotation speed of the driving wheel, and the actual running speed of the double-track vehicle is indirectly calculated; a load sensor is set in the middle part of the double-track vehicle chassis and the cargo rack. This installation can minimize the impact of uneven roads on the measurement and ensure that the sensor can accurately measure the load borne by the vehicle; an inclination sensor is set in the center of the bottom of the double-track vehicle. Its location at the center of gravity can ensure that the measured data can more accurately reflect the overall inclination state of the vehicle, that is, collect inclination angle data; monitoring cameras are set at the front and rear ends of the double-track vehicle to monitor the vehicle's driving route, the road conditions ahead, and the conditions of the vehicle behind. A monitoring camera is also set on the side of the internal freight stacking area of the vehicle to monitor the status of the cargo in real time, ensure that the cargo remains stable during transportation, and prevent safety accidents caused by cargo shifting or tipping.

[0065] In the sensor unit of the all-terrain transport vehicle, a speed sensor is set on the drive wheel hub of the all-terrain transport vehicle to measure the rotation speed of the drive wheel, and the actual operating speed of the double-track vehicle is indirectly calculated; by setting vibration sensors on the longitudinal beams, cross beams and near the motor of the all-terrain transport vehicle chassis, the vehicle operation smoothness and potential mechanical problems, namely vibration data, are evaluated; by setting a load sensor in the middle part of the all-terrain transport vehicle chassis and the cargo rack, it can be ensured that the sensor can accurately measure the load borne by the vehicle; by setting an inclination sensor at the center of the bottom of the all-terrain transport vehicle, its location at the center of gravity can ensure that the measured data can more accurately reflect the overall tilt state of the vehicle, namely the tilt angle data; by setting surveillance cameras at the front end of the all-terrain transport vehicle and on the side of the freight stacking area inside the vehicle, the road conditions in front of the vehicle and the internal cargo status are monitored in real time.

[0066] In the cableway sensor unit, by setting tension sensors at the anchor points at both ends of the cableway, the monitoring personnel can ensure the safe operation of the cableway based on the monitored tension status of the cableway; by setting wind speed sensors on the support frames at both ends of the cableway, the running speed of the cableway can be adjusted according to the real-time wind speed data, thereby ensuring the safe operation of the cableway; by setting a speed sensor near the roller on the cargo basket carrying rope, the running speed of the cargo basket can be indirectly calculated by measuring the rotation speed of the roller; by setting a load sensor on the lifting rope of the cargo basket, it is used to ensure that the cableway operates within the permitted load; by setting an inclination sensor at the bottom center of the cargo basket, it can be ensured that the measured data can more accurately reflect the overall tilt state of the vehicle; by setting surveillance cameras on the middle support frame of the cableway, as well as on the outer and inner walls of the cargo basket, it is used to monitor the operating status along the cableway and the safety status of the cargo in the cargo basket.

[0067] In one embodiment, the tilt angle data is obtained by a sensor unit disposed at the center of the bottom of the transport vehicle. The calculation formula for the tilt angle data is:

[0068]

[0069]

[0070] in, is the angle, is the output voltage, is the zero point voltage, is the angular sensitivity, is the output voltage range, is the angle measurement range;

[0071] The wind speed data is obtained through the wind speed sensor installed on the cableway support. The calculation formula of the wind speed data is:

[0072]

[0073] in, is the wind speed at the location of the basket, is the wind speed at the cargo basket station, The wind speed under the cargo basket, is the distance between the basket and the upper station, which is obtained by integrating the speed of the basket after it leaves the upper station. is the span length of the upper station and the lower station;

[0074] The load data is obtained through the sensor installed on the cargo basket rope of the transport vehicle. The calculation formula of the load data is:

[0075]

[0076] in, is the angle between the suspension rope and the horizontal plane, For tension.

[0077] In this embodiment, the sensors of the double-track vehicle sensor unit are distributed as follows: Figure 3 When sensors are installed on a dual-track vehicle, the dual-track vehicle speed sensor 101 is installed on the hub of the dual-track vehicle's drive wheel. A photoelectric speed sensor is used. When the wheel rotates, the teeth on the wheel ring gear sequentially block the light emitted by the light-emitting diode, causing the light intensity irradiated on the phototransistor to show periodic changes. Consequently, the output current of the phototransistor also generates a pulse signal. By measuring the rotational speed of the drive wheel, the actual running speed of the dual-track vehicle is indirectly calculated. At the same time, the photoelectric speed sensor uses a dual-path photoelectric device to generate two sets of pulse signals with a certain phase difference, thereby identifying the running direction of the dual-track vehicle.

[0078] The double-track vehicle load sensor 111 is arranged in the middle of the double-track vehicle chassis and the load rack, and adopts a piezoelectric load sensor to measure the vehicle load based on the piezoelectric effect of the crystal.

[0079] The double-track vehicle inclination sensor 121 is set at the bottom center of the double-track vehicle. It uses a dual-axis inclination sensor to measure the inclination change within the range of ±30 degrees on the X and Y axes. The dual-axis inclination sensor outputs a voltage within the range of 0 to 5V. In the data processing center, the inclination calculation formula can be used:

[0080]

[0081]

[0082] in, is the angle, is the output voltage, is the zero point voltage, is the angular sensitivity, is the output voltage range, is the angle measurement range.

[0083] Surveillance cameras are installed at the front and rear ends of the double-track vehicle to monitor the vehicle's route, the road conditions ahead, and the conditions of vehicles behind. A surveillance camera is also installed on the side of the internal freight storage area of the vehicle, namely the double-track vehicle side camera 133, the double-track vehicle front camera 131 and the double-track vehicle rear camera 132. They can select the main monitoring direction of the double-track vehicle according to the vehicle's running direction identified by the double-track vehicle speed sensor 101. The other camera facing away from the running direction enters sleep mode to reduce power consumption.

[0084] The sensor distribution of the all-terrain transport vehicle is as follows Figure 4 When setting sensors on the all-terrain transport vehicle, the all-terrain transport vehicle speed sensor 201 is set on the driving wheel hub; the vibration sensors of the all-terrain transport vehicle are respectively set on the longitudinal beams and cross beams of the chassis, and near the motor, as shown in FIG. Figure 4 The center longitudinal beam vibration sensor 211, the cross beam vibration sensor 212, and the motor vibration sensor 213 utilize piezoelectric vibration sensors. Vibration signals are filtered and de-noised at the data processing center, then wirelessly transmitted to the intelligent monitoring platform. Spectral analysis is performed using a Fast Fourier Transform (FFT), and a machine learning algorithm is trained to identify abnormal frequency components. The ATV load sensor 221 is located between the chassis and the cargo rack. The ATV tilt sensor 231 is located at the center of the ATV's bottom. External and internal surveillance cameras 241 and 242 monitor the vehicle's environmental conditions and the status of the cargo inside, respectively.

[0085] The distribution of sensors on the cableway is as follows Figure 5 When setting sensors on the cableway, the tension sensor 301 at the first end of the cableway and the tension sensor 302 at the second end of the cableway are set at the anchor points at both ends of the cableway. The lateral pressure tension sensor is used, and the monitoring personnel can adjust the cableway tensioning device according to the monitored tension.

[0086] The wind speed sensor 311 at the first end of the cableway and the wind speed sensor 312 at the second end of the cableway are installed on the support frames at both ends of the cableway. Using three-cup wind speed sensors, monitoring personnel can adjust the operating speed of the cableway according to real-time wind speed data to ensure the safe operation of the cableway. In this embodiment, the wind speed at the location can be obtained based on the wind speed at both ends of the support frame and the location of the cargo basket. According to the formula:

[0087]

[0088] in, is the wind speed at the location of the basket, is the wind speed at the cargo basket station, The wind speed under the cargo basket, is the distance between the basket and the upper station, is the span between the upper station and the lower station, where the distance between the basket and the upper station is It can be obtained by integrating the speed of the cargo basket after it leaves the upper station;

[0089] The cableway speed sensor 321 is set near the roller on the cargo basket carrying cable, and the running speed of the cargo basket is indirectly calculated by measuring the rotation speed of the roller;

[0090] The cableway load sensor 331 is installed on the hanging rope of the cargo basket and uses a strain gauge to measure the tension on the hanging rope. According to the formula:

[0091]

[0092] in, is the angle between the suspension rope and the horizontal plane, For tension.

[0093] A cableway inclination sensor 341 is located at the bottom center of the cargo basket, ensuring that the measured data more accurately reflects the vehicle's overall tilt. Cableway center surveillance camera 351, cableway exterior surveillance camera 352, and cableway interior surveillance camera 353 are located on the cableway's center support frame, as well as on the outer and inner walls of the cargo basket, to monitor the status of the cableway and the cargo within.

[0094] It should be noted that the surveillance camera includes a camera and a wireless image transmission module, and the wireless image transmission module can transmit the captured video directly to the intelligent monitoring platform.

[0095] S102. Preprocess and calibrate the operating status data to obtain processed operating status data, compare the processed operating status data with a corresponding first preset threshold value to obtain a first comparison result, and determine whether there is an abnormality in the mountain transportation system based on the first comparison result. If there is an abnormality, send a first alarm message to the intelligent monitoring platform; if there is no abnormality, send the processed operating status data to the intelligent monitoring platform for storage.

[0096] In this embodiment, a data processing center is required for each sensor unit in the mountain transport system, including the dual-track vehicle sensor unit, the all-terrain transport vehicle sensor unit, and the cableway sensor unit. The cableway sensor unit requires two data processing centers: one for collecting and processing sensor data from the cargo basket, and the other for collecting and processing sensor data from the cableway support frame.

[0097] The STM32 microcontroller in the data processing center obtains operating status data from its sensor unit, first performing preliminary processing on the operating status data and then comparing the data with a first preset threshold. If there are no abnormalities, the transportation system is in a safe state. The microcontroller transmits the pre-processed and calibrated data to the intelligent monitoring platform via a wireless transmission module for display and storage. If the threshold is exceeded, an abnormality has occurred. The microcontroller also sends an alarm message, namely the first alarm message, to the intelligent monitoring platform at the same time as sending the data. The first alarm message includes at least three pieces of information: location information, time information, and alarm content information. The location information indicates which sensor issued the alarm and which sensor unit the sensor is located in, the time information indicates the time the alarm occurred, and the content information includes the threshold value exceeded.

[0098] It should be noted that the threshold for monitoring physical quantities, namely the first preset threshold, is not fixed. Changes in the measured values of certain sensors will dynamically adjust the thresholds of other sensors to achieve a coordinated monitoring effect. For example, when the load detected in the transport unit exceeds a certain value, the comparison threshold of the inclination sensor in the unit will be dynamically adjusted to prevent the vehicle or cargo basket from overturning due to changes in the center of gravity caused by the increased load. The comparison threshold of the speed sensor in the unit will also be appropriately lowered to increase the dynamic stability of the system. When the wind speed detected in the cableway sensor unit exceeds a certain value, the comparison threshold of the cargo basket speed sensor will be appropriately lowered to ensure the safe operation of the cableway.

[0099] It should be noted that the STM32 microcontroller is a 32-bit ARM architecture microcontroller with built-in multiple peripheral circuits, including TIM, ADC, USART, IIC, etc. It has the advantages of low power consumption, low cost, and high performance, which just meets the design requirements and design principles of the intelligent monitoring platform of the mountain transportation system.

[0100] In one embodiment, preprocessing and calibrating the operating status data to obtain processed operating status data includes:

[0101] Filtering and denoising the operating status data by calculating the average value of the operating status data within a preset sliding window to obtain denoised data;

[0102] Perform linear calibration on the denoised data to obtain the processed operating status data.

[0103] In this embodiment, after the STM32 microcontroller receives the data sent by the sensor, it performs filtering and denoising by calculating the average value of the data in a set sliding window in real time, and then converts the original value into the corresponding physical quantity through linear calibration.

[0104] S103. Send the processed operating status data to the intelligent monitoring platform for identification, so that the intelligent monitoring platform uses the intelligent identification model to identify the processed operating status data to obtain an identification result, compare the identification result with the corresponding second preset threshold to obtain a second comparison result, and determine whether there is an abnormality in the mountain transportation system based on the second comparison result. If so, issue a second alarm message, so that the monitoring personnel adjust the mountain transportation system according to the second alarm message or the first alarm message.

[0105] In this embodiment, the intelligent monitoring platform is a host computer located in a remote monitoring room. After receiving data and video from the data processing center and the sensor network, the host computer first displays and stores the data and video, then extracts features from the data, and trains the model based on the extracted features. After real-time data is input into the model, the output value will be used to compare with the set second preset threshold. If the comparison is abnormal, a second alarm message will be issued.

[0106] The intelligent monitoring platform will judge the alarm information after each model output comparison. If only one of the models in the data processing center and the intelligent monitoring platform issues an alarm, a manual review will be initiated, and the manual review results will be reverse-annotated to the database to dynamically correct the model prediction deviation; if both issue an alarm, it means a dangerous situation has occurred, and the intelligent monitoring platform will send an emergency braking command.

[0107] If only the data processing center issues an alarm, monitoring personnel only need to implement the corresponding control strategy based on the alarm information. When an alarm information is received by the intelligent monitoring platform, the monitoring video of the corresponding unit will be retrieved for monitoring personnel to assist in judgment and determine the source of the abnormality.

[0108] In one embodiment, enabling monitoring personnel to adjust the mountain transportation system according to the second alarm information or the first alarm information includes:

[0109] When the first alarm information and the second alarm information are generated at the same time, the intelligent monitoring platform sends an emergency braking instruction and generates an abnormality report;

[0110] When either the first alarm information or the second alarm information is generated, the manual review process is started, the corresponding control strategy is implemented and the corresponding decision result is recorded.

[0111] In this embodiment, if the primary threshold alarm of the data processing center and the alarm of the intelligent monitoring platform are triggered at the same time and it is determined to be a dangerous situation, the intelligent monitoring platform can send an emergency braking instruction to the transport unit in the abnormal condition while issuing an alarm to the monitoring personnel, and generate an abnormality report; if only one of the data processing center or the intelligent monitoring platform triggers an alarm and it is determined that an abnormal situation has occurred, the manual review process is started, the corresponding control strategy is implemented, and the decision results are recorded at the same time. The manual review results are then reverse-annotated to the database to dynamically correct the model prediction deviation.

[0112] The video transmitted to the intelligent monitoring platform is displayed in real time. Image recognition algorithms are also used to identify cargo within the transport unit, preventing it from falling out due to vibration or tilt. If cargo falls out, an alarm is triggered. When the intelligent monitoring platform detects an alarm signal, it retrieves the video data from the corresponding sensor unit to assist monitoring personnel in troubleshooting the source of the anomaly.

[0113] It should be noted that the primary threshold alarm refers to the first alarm information, and the model alarm of the intelligent monitoring platform refers to the second alarm information.

[0114] In one embodiment, after the operating status data is sent to the intelligent monitoring platform for storage, the process further includes:

[0115] Extracting features from the stored operating status data to obtain time domain feature data, frequency domain feature data, and correlation feature data;

[0116] Based on the time domain feature data, frequency domain feature data and correlation feature data, the initial recognition model is trained to obtain an intelligent recognition model.

[0117] In this embodiment, the intelligent monitoring platform includes a host computer, which receives data transmitted from the single-chip microcomputer through the TCP / IP protocol, and then performs graphical display and local storage; features are extracted from the stored data, including time domain features, frequency domain features and correlation features, where the correlation features include the correlation coefficients of different sensors in different sensor units, including covariance and linear regression residuals; the extracted features are trained using a machine learning algorithm to establish an intelligent recognition model; after the training is completed, the model is used to identify and classify real-time data, and by comparing the output of the model with the set threshold, it is determined whether there is an abnormal condition. If there is an abnormal condition, the intelligent monitoring platform will issue an alarm.

[0118] The intelligent monitoring device for mountain transportation system provided by the embodiment of the present invention is as follows: Figure 6 As shown, Figure 6 The device block diagram of the intelligent monitoring system for mountain transportation system includes:

[0119] Acquisition module 601, used to obtain the operating status data of the mountain transportation system;

[0120] A first judgment module 602 is configured to preprocess and calibrate the operating status data to obtain processed operating status data, compare the processed operating status data with a corresponding first preset threshold value to obtain a first comparison result, and determine whether there is an abnormality in the mountain transport system based on the first comparison result. If an abnormality is present, a first alarm message is sent to the intelligent monitoring platform; if no abnormality is present, the processed operating status data is sent to the intelligent monitoring platform for storage;

[0121] The second judgment module 603 is used to send the processed operating status data to the intelligent monitoring platform for identification, so that the intelligent monitoring platform uses the intelligent recognition model to identify the processed operating status data, obtain an identification result, compare the identification result with the corresponding second preset threshold, obtain a second comparison result, and judge whether there is an abnormality in the mountain transportation system based on the second comparison result. If so, a second alarm message is issued, so that the monitoring personnel can adjust the mountain transportation system according to the second alarm message or the first alarm message.

[0122] In one embodiment, the acquisition module 601 includes a receiving unit, wherein:

[0123] The receiving unit is used to receive the operating status data collected by several sensor units installed on the transport vehicle, wherein the operating status data includes operating speed data, load data, tilt angle data, driving route data, wind speed data and cargo status data.

[0124] The specific implementation of the intelligent monitoring device for a mountain transport system is substantially the same as the specific embodiment of the intelligent monitoring method for a mountain transport system described above, and will not be described in detail herein.

[0125] The intelligent monitoring system for a mountain transport system provided by an embodiment of the present invention includes:

[0126] A sensor network, an intelligent monitoring device for a mountain transport system, and an intelligent monitoring platform, wherein the intelligent monitoring device for a mountain transport system is used to execute the intelligent monitoring device method for a mountain transport system provided by an embodiment of the invention;

[0127] The sensor network is connected to the intelligent monitoring device of the mountain transportation system, and the intelligent monitoring device of the mountain transportation system is connected to the intelligent monitoring platform.

[0128] In this embodiment, in the intelligent monitoring system of the mountain transportation system, as Figure 7 As shown, the data processing center, that is, the intelligent monitoring device of the mountain transportation system, includes an STM32 microcontroller, a power supply module and a wireless transmission module. The power supply module includes a DC / DC buck module and a battery. The voltage at the output end of the DC / DC buck module is 3-12V. The wireless transmission module is a 4G / 5G wireless network unit.

[0129] The sensor network is distributed at key locations on the double-track vehicles, all-terrain transport vehicles and cableways in the mountain transport system, and is used to collect the operating status of the transport system in real time, including physical information and monitoring videos; the data processing center is a single-chip microcomputer, which is responsible for preliminary processing of the physical information collected by the sensors, then comparing it with the set threshold, and then transmitting the data to the intelligent monitoring platform. If the threshold comparison is abnormal, the data processing center will send an alarm to the intelligent monitoring platform; the intelligent monitoring platform receives monitoring videos from the sensor network and data from the data processing center, and is responsible for displaying, storing the data and videos and issuing early warnings of possible faults.

[0130] In one embodiment, the sensor network is used to send the collected operating status data to an intelligent monitoring device of the mountain transport system;

[0131] The intelligent monitoring device of the mountain transport system is used to obtain operating status data of the mountain transport system; preprocess and calibrate the operating status data to obtain processed operating status data; compare the processed operating status data with a corresponding first preset threshold value to obtain a first comparison result; determine whether there is an abnormality in the mountain transport system based on the first comparison result; if there is an abnormality, send a first alarm message to the intelligent monitoring platform; if there is no abnormality, send the processed operating status data to the intelligent monitoring platform for storage and identification;

[0132] The intelligent monitoring platform is used to receive the first alarm information and the processed operating status data, use the intelligent recognition model to identify the processed data to obtain an identification result, compare the identification result with the corresponding second preset threshold to obtain a second comparison result, and determine whether there is an abnormality in the mountain transportation system based on the second comparison result. If so, a second alarm information is issued, so that the monitoring personnel can adjust the mountain transportation system according to the second alarm information or the first alarm information.

[0133] In this embodiment, the sensor network collects the operating status of the transport unit in real time, including physical information and monitoring videos; the data processing center, that is, the intelligent monitoring device of the mountain transport system is a single-chip microcomputer, which is responsible for preliminary processing of the physical information collected by the sensor, and then compares it with the set threshold, and then transmits the data to the intelligent monitoring platform. If the threshold comparison is abnormal, the data processing center will send an alarm to the intelligent monitoring platform; the intelligent monitoring platform receives the monitoring video from the sensor network and the data from the data processing center, and is responsible for displaying and storing the data and video and issuing early warnings for possible faults.

[0134] Specifically, if Figure 8 As shown in the figure, the workflow of the system is as follows: first, the sensor network collects data, and then the data is pre-processed in the single-chip microcomputer, including filtering, denoising and calibration. The data is then compared with the set threshold and sent to the intelligent monitoring platform. If the threshold judgment is abnormal, an alarm will be issued to the intelligent monitoring platform, waiting for further processing by the intelligent monitoring platform; the data sent to the intelligent monitoring platform will be displayed in real time and stored locally. The stored data will be subjected to multimodal feature extraction and model training based on the machine learning algorithm. After the real-time data is input, the output of the model will be compared with the set threshold. If an abnormality occurs, an alarm will be issued. The intelligent monitoring platform will perform a two-level abnormality verification based on the model alarm and the alarm result of the data processing center, and generate the final control instruction. If only one alarm is triggered, a manual review will be carried out, the corresponding control strategy will be implemented, and the model will be updated to realize a complete monitoring closed-loop process. If a two-level alarm is triggered, the monitoring system will issue an emergency braking command and wait for the staff to eliminate the dangerous situation before resuming the transportation of the transport unit.

[0135] Compared with the existing technology, the mountain transportation system intelligent monitoring platform of the present invention has the following advantages and benefits:

[0136] By integrating multiple sensor technologies, this invention enables real-time monitoring of the operating status of a mountain transport system consisting of dual-track vehicles, all-terrain transport vehicles, and cableways, covering multiple physical quantities such as speed, load, inclination, and vibration. Based on this data, monitoring personnel can dynamically adjust operating parameters to ensure the system's proper operation.

[0137] The system has an intelligent fault warning function. Through the collaborative work of the data processing center and the intelligent monitoring platform, it can quickly identify abnormal situations and issue alarms. In addition, the system also supports manual review and the sending of emergency braking commands to ensure that timely measures can be taken in dangerous situations.

[0138] The intelligent monitoring platform also supports real-time display and storage of data and video, and provides managers with intuitive monitoring information through a visual interface. This remote monitoring capability enables managers to understand the operating status of the transportation system anytime and anywhere, improving management efficiency.

[0139] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0140] The specific embodiments described above further illustrate the objectives, technical solutions, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. In particular, it should be noted that any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included within the scope of protection of the present invention for those skilled in the art.

Claims

1. An intelligent monitoring method for a mountain transport system, characterized in that: include: Obtaining operational status data of mountain transport systems; preprocessing and calibrating the operating status data to obtain processed operating status data, comparing the processed operating status data with a corresponding first preset threshold value to obtain a first comparison result, and determining whether there is an abnormality in the mountain transport system based on the first comparison result; if there is an abnormality, sending a first alarm message to an intelligent monitoring platform; if there is no abnormality, sending the processed operating status data to the intelligent monitoring platform for storage; Sending the processed operating status data to the intelligent monitoring platform for identification, so that the intelligent monitoring platform uses an intelligent recognition model to identify the processed operating status data to obtain an identification result, comparing the identification result with a corresponding second preset threshold to obtain a second comparison result, and judging whether there is an abnormality in the mountain transportation system according to the second comparison result. If so, issuing a second alarm message so that monitoring personnel adjust the mountain transportation system according to the second alarm message or the first alarm message, wherein, when either the first alarm message or the second alarm message is generated, a manual review process is initiated to obtain a manual review result, and the manual review result is reversely annotated to a database to correct the prediction deviation of the intelligent recognition model; The obtaining of the operating status data of the mountain transportation system includes: Receive operating status data collected by sensor units installed on each transport vehicle, wherein the operating status data includes operating speed data, load data, inclination angle data, vibration data, tension data, driving route data, wind speed data, and cargo status data; After the operating status data is sent to the intelligent monitoring platform for storage, the method further includes: Extracting features from the stored operating status data to obtain time domain feature data, frequency domain feature data, and correlation feature data; Based on the time domain feature data, the frequency domain feature data and the associated feature data, an initial recognition model is trained to obtain an intelligent recognition model.

2. The intelligent monitoring method for mountain transportation system according to claim 1, characterized in that: The tilt angle data is obtained by a sensor unit provided at the center of the bottom of the transport vehicle. The calculation formula of the tilt angle data is: in, is the angle, is the output voltage, is the zero point voltage, is the angular sensitivity, is the output voltage range, is the angle measurement range; The wind speed data is obtained by a wind speed sensor provided on the cableway support, wherein the calculation formula of the wind speed data is: in, is the wind speed at the location of the basket, is the wind speed at the cargo basket station, The wind speed under the cargo basket, is the distance between the basket and the upper station, which is obtained by integrating the speed of the basket after it leaves the upper station. is the span length of the upper station and the lower station; The load data is obtained by a sensor installed on the cargo basket sling of the transport vehicle, wherein the calculation formula of the load data is: in, is the angle between the suspension rope and the horizontal plane, For tension.

3. The intelligent monitoring method for mountain transportation system according to claim 1, characterized in that: The preprocessing and calibrating the operating status data to obtain processed operating status data includes: Filtering and denoising the operating status data according to the average value of the operating status data within the preset sliding window to obtain denoised data; Linear calibration is performed on the denoised data to obtain processed operating status data.

4. The intelligent monitoring method for mountain transportation system according to claim 1, characterized in that: The step of enabling the monitoring personnel to adjust the mountain transportation system according to the second alarm information or the first alarm information includes: When the first alarm information and the second alarm information are generated at the same time, the intelligent monitoring platform sends an emergency braking instruction and generates an abnormality report; When either the first alarm information or the second alarm information is generated, a manual review process is started, a corresponding control strategy is implemented, and a corresponding decision result is recorded.

5. An intelligent monitoring device for a mountain transport system, characterized in that: include: An acquisition module is used to obtain the operating status data of the mountain transportation system; a first judgment module, configured to preprocess and calibrate the operating status data to obtain processed operating status data, compare the processed operating status data with a corresponding first preset threshold value to obtain a first comparison result, and determine whether there is an abnormality in the mountain transport system based on the first comparison result; if so, send a first alarm message to the intelligent monitoring platform; if not, send the processed operating status data to the intelligent monitoring platform for storage; a second judgment module, configured to send the processed operating status data to the intelligent monitoring platform for identification, so that the intelligent monitoring platform identifies the processed operating status data using an intelligent recognition model to obtain an identification result, compares the identification result with a corresponding second preset threshold value to obtain a second comparison result, and determines whether there is an abnormality in the mountain transportation system based on the second comparison result; if so, issues a second alarm message, so that monitoring personnel adjust the mountain transportation system based on the second alarm message or the first alarm message; wherein, when either the first alarm message or the second alarm message is generated, a manual review process is initiated to obtain a manual review result, which is reversely annotated to a database to correct the prediction deviation of the intelligent recognition model; The acquisition module includes a receiving unit, wherein: The receiving unit is used to receive the operating status data collected by the sensor unit installed on each transport vehicle, wherein the operating status data includes operating speed data, load data, tilt angle data, driving route data, wind speed data and cargo status data; After the operating status data is sent to the intelligent monitoring platform for storage, the method further includes: Extracting features from the stored operating status data to obtain time domain feature data, frequency domain feature data, and correlation feature data; Based on the time domain feature data, the frequency domain feature data and the associated feature data, an initial recognition model is trained to obtain an intelligent recognition model.

6. An intelligent monitoring system for mountain transportation system, characterized in that: The method comprises a sensor network, an intelligent monitoring device for a mountain transport system and an intelligent monitoring platform, wherein the intelligent monitoring device for a mountain transport system is used to execute the method for the intelligent monitoring device for a mountain transport system according to any one of claims 1 to 4; The sensor network is connected to the intelligent monitoring device of the mountain transportation system, and the intelligent monitoring device of the mountain transportation system is connected to the intelligent monitoring platform.

7. The intelligent monitoring system for mountain transportation system according to claim 6, characterized in that: The sensor network is used to send the collected operating status data to the intelligent monitoring device of the mountain transport system; The intelligent monitoring device of the mountain transport system is used to obtain the operating status data of the mountain transport system; preprocessing and calibrating the operating status data to obtain processed operating status data, comparing the processed operating status data with a corresponding first preset threshold to obtain a first comparison result, and determining whether there is an abnormality in the mountain transportation system based on the first comparison result; if there is an abnormality, sending a first alarm message to an intelligent monitoring platform; if there is no abnormality, sending the processed operating status data to the intelligent monitoring platform for storage and identification; The intelligent monitoring platform is used to receive the first alarm information and the processed operating status data, use the intelligent recognition model to identify the processed data to obtain an identification result, compare the identification result with the corresponding second preset threshold to obtain a second comparison result, and determine whether there is an abnormality in the mountain transportation system based on the second comparison result. If so, a second alarm information is issued, so that the monitoring personnel can adjust the mountain transportation system according to the second alarm information or the first alarm information; wherein, when either the first alarm information or the second alarm information is generated, a manual review process is started to obtain a manual review result, and the manual review result is reversely annotated to the database to correct the prediction deviation of the intelligent recognition model; and receive the operating status data collected by the sensor unit installed on each transport vehicle, wherein the operating status data includes operating speed data, load data, inclination angle data, driving route data, wind speed data and cargo status data; and perform feature extraction on the stored operating status data to obtain time domain feature data, frequency domain feature data and correlation feature data; based on the time domain feature data, the frequency domain feature data and the correlation feature data, the initial recognition model is trained to obtain an intelligent recognition model.

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