Intelligent monitoring method, device and system for mountain transportation system

Abstract

The invention discloses an intelligent monitoring method, device and system for a mountain transportation system, and the method comprises the steps: obtaining the operation state data of the mountain transportation system, carrying out the preprocessing and calibration of the operation state data, obtaining the processed operation state data, comparing the processed operation state data with a corresponding first preset threshold value, and carrying out the recognition of the operation state data. And obtaining a first comparison result, judging whether the mountain transportation system is abnormal or not according to the first comparison result, if yes, sending first alarm information to an intelligent monitoring platform, and if not, sending the processed operation state data to the intelligent monitoring platform for storage and identification, and judging whether the mountain transportation system is abnormal or not. According to the method, the emergency monitoring and early warning reliability in the mountain transportation system is improved.

Description

Technical Field

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

[0002] With the rapid economic development, the demand for electric energy in the daily production and life of the people is increasing. The task volume of transmission line erection increases year by year, and the construction period is getting shorter and shorter. How to conveniently and quickly transport electric power materials (transmission line tower materials, sand and stones, construction tools) to the construction site is the primary condition for ensuring the construction period. However, most of the transmission line projects are located in mountainous areas with continuous mountains. Coupled with the muddy roads caused by rain, there are often harsh transportation environments such as high mountains, steep slopes, small bends, dangerous roads, and slippery roads, which often result in untimely supply of engineering materials or even inability to transport, seriously restricting the progress of engineering construction.

[0003] At present, the mountain transportation of transmission line projects still remains in the state of mainly relying on human (animal) power and supplemented by machinery, and the degree of construction mechanization is relatively low. With the rapid development of the economic society, traditional animal power such as mules and horses is in short supply, the transportation cost is continuously increasing, and the investment in human cost is continuously increasing. The labor-intensive construction method will be difficult to sustain. At the same time, the on-site monitoring means of the few existing mechanized transportation systems are insufficient, and they rely too much on the experience of technical personnel in equipment status monitoring and system control, and cannot accurately monitor the status and emergency situations of the transportation system and give fault warnings, with 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 in monitoring and warning of emergency situations in the existing mountain transportation system.

[0005] The first aspect of the embodiments of the present invention provides an intelligent monitoring method for a mountain transportation system, and the method includes: Obtain the operation status data of the mountain transportation system; Preprocess and calibrate the operation status data to obtain the processed operation status data, compare the processed operation status data with the corresponding first preset threshold to obtain a first comparison result, and judge whether there is an abnormality in the mountain transportation system according to 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 operation status data to the intelligent monitoring platform for storage; Send the processed operation status data to the intelligent monitoring platform for identification, so that the intelligent monitoring platform uses the intelligent recognition model to identify the processed operation status data, obtain the recognition result, compare the recognition result with the corresponding second preset threshold to obtain the second comparison result, and judge whether there is an abnormal situation in the mountain transportation system according to the second comparison result. If so, send the second alarm message, so that the monitoring personnel can adjust the mountain transportation system according to the second alarm message or the first alarm message.

[0006] In a possible implementation manner of the first aspect, obtaining the operation status data of the mountain transportation system includes: Receive the operation status data collected by the sensor units set on each transport vehicle, where the operation status data includes operation speed data, load data, tilt angle data, driving route data, wind speed data, and cargo status data.

[0007] In a possible implementation manner of the first aspect, the tilt angle data is obtained by the sensor unit set at the center of the bottom of the transport vehicle, and the calculation formula of the tilt angle data is: Where is the angle, is the output voltage, is the zero-point voltage, is the angle sensitivity, is the output voltage range, is the angle measurement range; The wind speed data is obtained by the wind speed sensor set on the cableway support. Among them, the calculation formula of the wind speed data is: Where is the wind speed at the position where the cargo basket is located, is the wind speed on the cargo basket at the upper station, is the wind speed on the cargo basket at the lower station, is the distance between the cargo basket and the upper station, obtained by integrating the speed of the cargo basket after it departs from the upper station, is the span between the upper station and the lower station; The load data is obtained by the sensor set on the suspension rope of the cargo basket of the transport vehicle. Among them, the calculation formula of the load data is: Where is the angle between the suspension rope and the horizontal plane, is the tension.

[0008] In a possible implementation of the first aspect, preprocess and calibrate the operation status data to obtain the processed operation status data, including: Filter and denoise the operation status data according to calculating the average value of the operation status data within a preset sliding window to obtain the denoised data; Perform linear calibration on the denoised data to obtain the processed operation status data.

[0009] In a possible implementation of the first aspect, enable the monitoring personnel to adjust the mountain transportation system according to the second alarm information or the first alarm information, including: When the first alarm information and the second alarm information are generated simultaneously, enable the intelligent monitoring platform to send an emergency braking instruction and generate an exception report; When either the first alarm information or the second alarm information is generated, start the manual review process, implement the corresponding control strategy and record the corresponding decision result.

[0010] In a possible implementation of the first aspect, after sending the operation status data to the intelligent monitoring platform for storage, it further includes: Extract features from the stored operation status data to obtain time-domain feature data, frequency-domain feature data and correlation feature data; Train the initial recognition model based on the time-domain feature data, frequency-domain feature data and correlation feature data to obtain the intelligent recognition model.

[0011] To solve the same technical problem, the second aspect of the embodiments of the present invention provides an intelligent monitoring device for a mountain transportation system, including: An acquisition module for acquiring the operation status data of the mountain transportation system; A first judgment module for preprocessing and calibrating the operation status data to obtain the processed operation status data, comparing the processed operation status data with the corresponding first preset threshold to obtain a first comparison result, and judging whether there is an abnormality in the mountain transportation system according to the first comparison result. If there is an abnormality, send the first alarm information to the intelligent monitoring platform. If there is no abnormality, send the processed operation status data to the intelligent monitoring platform for storage; A second judgment module for sending the processed operation status data to the intelligent monitoring platform for recognition, so that the intelligent monitoring platform uses the intelligent recognition model to recognize the processed operation status data to obtain a recognition result, comparing the recognition result with the corresponding second preset threshold to obtain a second comparison result, and judging whether there is an abnormal situation in the mountain transportation system according to the second comparison result. If so, send out the second alarm information to enable the monitoring personnel to adjust the mountain transportation system according to the second alarm information or the first alarm information.

[0012] In a possible implementation of the second aspect, the acquisition module includes a receiving unit, where the receiving unit is configured to receive the operation status data collected by the sensor units arranged on each transport vehicle, where the operation status data includes operation speed data, load data, tilt angle data, driving route data, wind speed data, and cargo status data.

[0013] To solve the same technical problem, a third aspect of the embodiments of the present invention provides an intelligent monitoring system for a mountain transportation system, including: a sensor network, an intelligent monitoring device for the mountain transportation system, and an intelligent monitoring platform, where the intelligent monitoring device for the mountain transportation system is configured to execute the method of the intelligent monitoring device for the mountain transportation system in the first aspect of the embodiments of the present invention; wherein, the sensor network is connected to the intelligent monitoring device for the mountain transportation system, and the intelligent monitoring device for the mountain transportation system is connected to the intelligent monitoring platform.

[0014] In a possible implementation of the third aspect, the sensor network is configured to send the collected operation status data to the intelligent monitoring device for the mountain transportation system; the intelligent monitoring device for the mountain transportation system is configured to obtain the operation status data of the mountain transportation system; preprocess and calibrate the operation status data to obtain the processed operation status data, compare the processed operation status data with the corresponding first preset threshold to obtain a first comparison result, and determine whether there is an abnormality in the mountain transportation system according to 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 operation status data to the intelligent monitoring platform for storage and identification; the intelligent monitoring platform is configured to receive the first alarm message and the processed operation status data, identify the processed data using the intelligent recognition model 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 abnormal situation in the mountain transportation system according to the second comparison result. If so, send a second alarm message, so that the monitoring personnel can adjust the mountain transportation system according to the second alarm message or the first alarm message.

[0015] The technical solution of the present invention has the following advantages: The intelligent monitoring method of the mountain transportation system provided by the embodiment of the present invention obtains the operation status data of the mountain transportation system, preprocesses and calibrates the operation status data to obtain the processed operation status data, compares the processed operation status data with the corresponding first preset threshold to obtain a first comparison result, and determines whether there is an abnormality in the mountain transportation system according to the first comparison result. If there is an abnormality, a first alarm message is sent to the intelligent monitoring platform. If there is no abnormality, the processed operation status data is sent to the intelligent monitoring platform for storage; the processed operation status data is sent to the intelligent monitoring platform for identification, so that the intelligent monitoring platform uses an intelligent identification model to identify the processed operation status data to obtain an identification result, compares the identification result with the corresponding second preset threshold to obtain a second comparison result, and determines whether there is an abnormal situation in the mountain transportation system according to the second comparison result. If so, a second alarm message is sent, enabling the monitoring personnel to adjust the mountain transportation system according to the second alarm message or the first alarm message. Through the above method, the reliability of emergency monitoring and early warning in the mountain transportation system is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for the description of the specific embodiments or the prior art. Obviously, the following drawings are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0017] Figure 1 It is the monitoring flowchart of the intelligent monitoring method of the mountain transportation system in the embodiment of the present invention; Figure 2 It is the block diagram of the sensor network structure of the intelligent monitoring method of the mountain transportation system in the embodiment of the present invention; Figure 3 It is the distribution diagram of the sensors of the double-track vehicle in the intelligent monitoring method of the mountain transportation system in the embodiment of the present invention; Figure 4 It is the distribution diagram of the sensors of the all-terrain vehicle in the intelligent monitoring method of the mountain transportation system in the embodiment of the present invention; Figure 5 It is the distribution diagram of the sensors of the cableway in the intelligent monitoring method of the mountain transportation system in the embodiment of the present invention; Figure 6 It is the block diagram of the intelligent monitoring device of the mountain transportation system in the embodiment of the present invention; Figure 7 It is the block diagram of the data processing center of the intelligent monitoring device of the mountain transportation system in the embodiment of the present invention; Figure 8Data processing flowchart of the intelligent monitoring system of the mountain transportation system in the embodiment of the present invention; Reference numerals: Among them, 101, double-track vehicle speed sensor; 111, double-track vehicle load sensor; 121, double-track vehicle inclination sensor; 131, front-end camera of the double-track vehicle carriage; 132, rear-end camera of the double-track vehicle carriage; 133, side camera of the double-track vehicle; 201, all-terrain vehicle speed sensor; 211, longitudinal beam vibration sensor; 212, cross beam vibration sensor; 213, vibration sensor at the motor; 221, all-terrain vehicle load sensor; 231, all-terrain vehicle inclination sensor; 241, external monitoring camera of the all-terrain vehicle; 242, internal monitoring camera of the all-terrain vehicle; 301, first-end tension sensor of the cableway; 302, second-end tension sensor of the cableway; 311, first-end wind speed sensor of the cableway; 312, second-end wind speed sensor of the cableway; 321, cableway speed sensor; 331, cableway load sensor; 341, cableway inclination sensor; 351, middle monitoring camera of the cableway; 352, external monitoring camera of the cableway; 353, internal monitoring camera of the cableway. Detailed implementation manners

[0018] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0019] In the description of the present invention, it should be noted that the terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0020] The intelligent monitoring method of the mountain transportation system provided by the embodiment of the present invention is as Figure 1 shown Figure 1 It is a flowchart of the intelligent monitoring method of the mountain transportation system, including steps S101 to S103, and the specific steps are as follows: S101. Obtain the operation status data of the mountain transportation system.

[0021] In this embodiment, the mountain transportation system includes three transportation units: double-track vehicles, all-terrain vehicles, and cableways. According to the actual terrain and environment of the construction, a combination of these three transportation methods, namely double-track vehicles, all-terrain vehicles, and cableways, can be selected to meet the transportation needs.

[0022] The goods are transported from the flat areas outside the mountainous area to the hills inside the mountainous area, so they are first transported by double-track vehicles, then by all-terrain transport vehicles, and finally by cableways to the construction site. First, the operating status information of the transport units is collected using the various sensor units installed on the transport vehicles.

[0023] In one embodiment, obtaining the operating status data of the mountain transportation system includes: 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.

[0024] 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 unit includes a double-track vehicle sensor unit, an all-terrain transport vehicle sensor unit and a cableway sensor unit. The double-track vehicle sensor unit is used to monitor the operating status of the double-track vehicle in the mountain transportation system, including a speed sensor, a load sensor, an inclination sensor and a monitoring camera; the all-terrain transport vehicle sensor unit is used to monitor the operating status of the all-terrain transport vehicle in the mountain transportation system, including a speed sensor, a vibration sensor, a load sensor, an inclination sensor and a monitoring camera; the cableway sensor unit is used to monitor the operating status of the cableway in the mountain transportation system, including a tension sensor, a wind speed sensor, a speed sensor, a load sensor, an inclination sensor and a monitoring camera.

[0025] In the sensor unit of the double-track vehicle, 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, so that the influence of uneven roads on the measurement can be avoided as much as possible, and it is ensured that the sensor can accurately measure the load borne by the vehicle; an inclination sensor is set at the bottom center of the double-track vehicle, and 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 vehicles behind, and a monitoring camera is also set on the side of the internal freight stacking area of ​​the vehicle to monitor the status of the goods in real time, to ensure that the goods remain stable during transportation, and to prevent safety accidents caused by the displacement or dumping of goods.

[0026] In the sensor unit of an all-terrain transport vehicle, the rotational speed of the drive wheel is measured by setting a speed sensor on the hub of the drive wheel of the all-terrain transport vehicle, and the actual running speed of the double-track vehicle is indirectly calculated; vibration sensors are set on the longitudinal beams, cross beams of the chassis of the all-terrain transport vehicle and near the motor to evaluate the running smoothness and potential mechanical problems of the vehicle, that is, vibration data; a load sensor is set in the middle part between the chassis and the cargo rack of the all-terrain transport vehicle to ensure that the sensor can accurately measure the load borne by the vehicle; an inclination sensor is set at the center of the bottom of the all-terrain transport vehicle, and its position at the center of gravity can ensure that the measured data can more accurately reflect the overall inclination state of the vehicle, that is, inclination angle data; monitoring cameras are set at the front end of the all-terrain transport vehicle and on the side of the internal cargo stacking area of the vehicle to monitor the road conditions in front of the vehicle during operation and the state of the internal cargo in real time.

[0027] In the cableway sensor unit, by setting tension sensors at the anchoring points at both ends of the cableway, the monitoring personnel can ensure the safe operation of the cableway according to the monitored cableway tension state; 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 bearing cable, the running speed of the cargo basket is indirectly calculated by measuring the rotational speed of the roller; a load sensor is set on the suspension rope of the cargo basket to ensure that the cableway works within the permitted load; by setting an inclination sensor at the center of the bottom inside the cargo basket, it can ensure that the measured data can more accurately reflect the overall inclination state of the vehicle; monitoring cameras are set on the middle support frame of the cableway, on the outer wall and inner wall of the cargo basket to monitor the running state along the cableway and the safety state of the cargo inside the cargo basket.

[0028] In one embodiment, the inclination angle data is obtained through the sensor unit set at the center of the bottom of the transport vehicle, and the calculation formula of the inclination angle data is: Where is the angle, is the output voltage, is the zero-point voltage, is the angle sensitivity, is the output voltage range, is the angle measurement range; The wind speed data is obtained through the wind speed sensor set on the cableway support, and the calculation formula of the wind speed data is: Where is the wind speed at the position where the cargo basket is located, is the wind speed at the upper station of the cargo basket, is the wind speed at the lower station of the cargo basket, is the distance between the cargo basket and the upper station, which is obtained by integrating the speed of the cargo basket after it departs from the upper station, is the span between the upper station and the lower station; The load data is obtained by sensors set on the suspension ropes of the cargo basket of the transport vehicle. Among them, the calculation formula for the load data is: Among them, is the angle between the suspension rope and the horizontal plane, is the tensile force.

[0029] In this embodiment, the sensors of the double-rail vehicle sensor unit are distributed as Figure 3 shown. When setting sensors on the double-rail vehicle, the double-rail vehicle speed sensor 101 is set on the hub of the driving wheel of the double-rail vehicle. An optoelectronic speed sensor is adopted. When the wheel rotates, the teeth on the wheel gear ring sequentially block the light emitted by the light-emitting diode, making the light intensity irradiated on the phototransistor present a periodic change. Furthermore, the output current of the phototransistor also generates a pulse signal accordingly. By measuring the rotational speed of the driving wheel, the actual running speed of the double-rail vehicle is indirectly calculated. At the same time, the optoelectronic speed sensor adopts a dual-channel optoelectronic device, which can generate two groups of pulse signals with a certain phase difference, thereby identifying the running direction of the double-rail vehicle.

[0030] The double-rail vehicle load sensor 111 is set at the middle part between the chassis and the load rack of the double-rail vehicle. A piezoelectric load sensor is adopted to measure the load of the vehicle according to the piezoelectric effect of the crystal.

[0031] The double-rail vehicle inclination sensor 121 is set at the center of the bottom of the double-rail vehicle. A biaxial inclination sensor is adopted, which can measure the inclination change within the range of ±30 degrees of the X and Y axes. The biaxial inclination sensor outputs a voltage within the range of 0 - 5V. In the data processing center, according to the inclination calculation formula: Among them, is the angle, is the output voltage, is the zero-point voltage, is the angle sensitivity, is the output voltage range, is the angle measurement range.

[0032] Surveillance cameras are installed at the front and rear ends of the double-track vehicle's carriage to monitor the vehicle's driving route, the road conditions ahead, and the situation of the vehicles behind. A surveillance camera is also installed on the side of the internal freight stacking area of the carriage, namely the side camera 133 of the double-track vehicle, the front camera 131 of the double-track vehicle's carriage, and the rear camera 132 of the double-track vehicle's carriage. It can select the main monitoring direction of the double-track vehicle according to the vehicle running direction identified by the double-track vehicle speed sensor 101, and the other camera facing away from the running direction enters sleep to reduce power consumption.

[0033] The sensor distribution of the all-terrain vehicle is as Figure 4 shown. When setting sensors on the all-terrain vehicle, the all-terrain vehicle speed sensor 201 is installed on the hub of the drive wheel; the vibration sensors of the all-terrain vehicle are respectively installed on the longitudinal beam, cross beam of the chassis, and near the motor, such as Figure 4 the longitudinal beam vibration sensor 211, the cross beam vibration sensor 212, and the vibration sensor 213 at the motor. Piezoelectric vibration sensors are used. After the vibration signals are filtered and denoised in the data processing center, they are wirelessly transmitted to the intelligent monitoring platform, and spectrum analysis is performed by fast Fourier transform (FFT). After being trained by machine learning algorithms, abnormal frequency components are found; the all-terrain vehicle load sensor 221 is installed in the middle part between the chassis and the cargo rack; the all-terrain vehicle tilt sensor 231 is installed at the center of the bottom of the all-terrain vehicle; the all-terrain vehicle external surveillance camera 241 and the all-terrain vehicle internal surveillance camera 242 are respectively used to monitor the environmental status in the vehicle running direction and the status of the internal goods.

[0034] The sensor distribution of the cableway is as Figure 5 shown. When setting sensors on the cableway, the cableway first-end tension sensor 301 and the cableway second-end tension sensor 302 are installed at the anchoring points at both ends of the cableway. Side pressure type tension sensors are used, and the monitoring personnel can adjust the cableway tensioning device according to the monitored tension magnitude.

[0035] The cableway first-end wind speed sensor 311 and the cableway second-end wind speed sensor 312 are installed on the support frames at both ends of the cableway. Three-cup anemometers are used. The monitoring personnel can adjust the running speed of the cableway according to the real-time wind speed data, thereby ensuring the safe operation of the cableway. In this embodiment, the wind speed at the location can be obtained according to the wind speed at both ends of the support frame and the position of the gondola. According to the formula: where, is the wind speed at the position of the gondola, is the wind speed at the upper station of the gondola, is the wind speed at the lower station of the gondola, is the distance between the gondola and the upper station, is the span length between the upper station and the lower station, where the distance between the cargo basket and the upper station can be obtained by integrating the speed of the cargo basket after it departs from the upper station; The cableway speed sensor 321 is arranged near the roller on the cargo basket's load-bearing cable. By measuring the rotation speed of the roller, the running speed of the cargo basket is indirectly calculated; The cableway load sensor 331 is arranged on the suspension rope of the cargo basket. A strain gauge is used to measure the tension on the suspension rope. According to the formula: where, is the angle between the suspension rope and the horizontal plane, is the tension.

[0036] The cableway inclination sensor 341 is arranged at the center position of the bottom inside the cargo basket, which can ensure that the measured data can more accurately reflect the overall inclination state of the vehicle. The cableway middle monitoring camera 351, the cableway external monitoring camera 352, and the cableway internal monitoring camera 353 are arranged on the middle support frame of the cableway, as well as the outer wall and inner wall of the cargo basket, for monitoring the state along the cableway and the state of the goods inside the cargo basket.

[0037] It should be noted that the monitoring camera includes a camera and a wireless video transmission module, and the wireless video transmission module can directly transmit the captured video to the intelligent monitoring platform.

[0038] S102. Preprocess and calibrate the operation state data to obtain the processed operation state data. Compare the processed operation state data with the corresponding first preset threshold to obtain the first comparison result. Judge whether there is an abnormality in the mountain transportation system according to the first comparison result. If there is an abnormality, send the first alarm information to the intelligent monitoring platform. If there is no abnormality, send the processed operation state data to the intelligent monitoring platform for storage.

[0039] In this embodiment, in the mountain transportation system, a data processing center needs to be equipped for each sensor unit, including the double-track vehicle sensor unit, the all-terrain vehicle sensor unit, and the cableway sensor unit. Among them, two data processing centers need to be configured for the cableway sensor unit. One data processing center is used to collect and process the sensor data on the cargo basket, and the other data processing center is used to collect and process the sensor data on the cableway support frame.

[0040] The STM32 single-chip microcomputer in the data processing center obtains the operation status data from the affiliated sensor unit. First, it preliminarily processes the operation status data, and then compares the data with the first preset threshold. If there is no abnormality, the transportation system is in a safe state, and the single-chip microcomputer will transmit the preprocessed and calibrated data to the intelligent monitoring platform through the wireless transmission module for display and storage; if it exceeds the threshold, there is an abnormal situation, and the single-chip microcomputer will send an alarm message while sending data to the intelligent monitoring platform, that is, the first alarm message. The first alarm message includes at least three pieces of information, namely location information, time information, and alarm content information. Among them, the location information is which sensor sent the alarm and which sensor unit the sensor is in, the time information is the time when the alarm occurred, and the content information includes how much the threshold has been exceeded.

[0041] It should be noted that the threshold for monitoring physical quantities, that is, the first preset threshold, is not fixed. It will dynamically adjust the thresholds of other sensors according to the changes in the measured values of some specific sensors to achieve the effect of collaborative monitoring. For example, when the load monitored in the transportation unit exceeds a certain value, the comparison threshold of the inclination sensor in the unit will be dynamically adjusted to prevent the vehicle or the cargo basket from tipping over due to the change in the center of gravity caused by the increase in the load; the comparison threshold of the speed sensor in the unit will also be appropriately reduced to increase the dynamic stability of the system; when the wind speed monitored in the cableway sensor unit exceeds a certain value, the comparison threshold of the cargo basket speed sensor will be appropriately reduced to ensure the safe operation of the cableway.

[0042] It should be noted that the STM32 single-chip microcomputer is a 32-bit ARM architecture microcontroller with a variety of built-in peripheral circuits, including TIM, ADC, USART, IIC, etc. It has the advantages of low power consumption, low cost, and high performance, which just meet the design requirements and design principles of the intelligent monitoring platform for the mountain transportation system.

[0043] In an embodiment, the operation status data is preprocessed and calibrated to obtain the processed operation status data, including: Filter and denoise the operation status data according to the calculated average value of the operation status data within the preset sliding window to obtain the denoised data; Perform linear calibration on the denoised data to obtain the processed operation status data.

[0044] In this embodiment, after the STM32 single-chip microcomputer receives the data sent by the sensor, it filters and denoises by calculating the average value of the data within the set sliding window in real time, and then through linear calibration, converts the original value into the corresponding physical quantity.

[0045] S103. Send the processed operation status data to the intelligent monitoring platform for identification, so that the intelligent monitoring platform uses the intelligent identification model to identify the processed operation status data, obtain the identification result, compare the identification result with the corresponding second preset threshold to obtain the second comparison result, and determine whether there is an abnormal situation in the mountain transportation system according to the second comparison result. If so, send the second alarm message, so that the monitoring personnel can adjust the mountain transportation system according to the second alarm message or the first alarm message.

[0046] In this embodiment, the intelligent monitoring platform is a host computer located in the remote monitoring room. After receiving the data and video from the data processing center and the sensor network, the host computer first displays and stores the data and video, and then extracts the features of the data. After training the model according to the extracted features, when the 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 shows an abnormality, the second alarm message will be sent.

[0047] The intelligent monitoring platform will judge the alarm message after each model output comparison. If only one of the models in the data processing center and the intelligent monitoring platform sends an alarm, the manual review will be started, and then the manual review result will be reversely marked to the database to dynamically correct the model prediction deviation. If both send alarms, it means that a dangerous situation has occurred, and the intelligent monitoring platform will send an emergency braking instruction.

[0048] If only the data processing center sends an alarm, the monitoring personnel only need to implement the corresponding control strategy according to the alarm message. When an alarm message is received by the intelligent monitoring platform, the monitoring video of the corresponding unit will be retrieved for the monitoring personnel to make an auxiliary judgment to determine the abnormal source.

[0049] In one embodiment, enabling the monitoring personnel to adjust the mountain transportation system according to the second alarm message or the first alarm message includes: When the first alarm message and the second alarm message are generated simultaneously, the intelligent monitoring platform is enabled to send an emergency braking instruction and generate an abnormality report; When either the first alarm message or the second alarm message is generated, start the manual review process, implement the corresponding control strategy and record the corresponding decision result.

[0050] In this embodiment, if the primary threshold alarm of the data processing center and the alarm of the intelligent monitoring platform are triggered simultaneously, it is determined as a dangerous situation. While sending an alarm to the monitoring personnel, the intelligent monitoring platform can send an emergency braking instruction to the transportation unit in an abnormal condition and generate an abnormal report. If only one of the data processing center or the intelligent monitoring platform triggers an alarm, it is determined that an abnormal situation has occurred, then the manual review process is started, the corresponding control strategy is implemented, the decision result is recorded, and then the manual review result is reversely marked to the database to dynamically correct the model prediction deviation.

[0051] Among them, the video transmitted to the intelligent monitoring platform will be displayed in real time. At the same time, an image recognition algorithm can be used to identify the goods in the transportation unit to prevent the goods from falling out due to the vibration and tilt of the transportation unit. An alarm will also be issued if the goods fall out. When the intelligent monitoring platform detects an alarm signal, it will retrieve the video data in the corresponding sensor unit to assist the monitoring personnel in investigating the source of the abnormality.

[0052] 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.

[0053] In one embodiment, after sending the operation status data to the intelligent monitoring platform for storage, it further includes: Extracting features from the stored operation status data to obtain time-domain feature data, frequency-domain feature data, and correlation feature data; Based on the time-domain feature data, frequency-domain feature data, and correlation feature data, training the initial recognition model to obtain an intelligent recognition model.

[0054] In this embodiment, the intelligent monitoring platform includes a host computer. The host computer receives the data transmitted from the single-chip microcomputer through the TCP / IP protocol, and then performs graphical display and local storage. By extracting features 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; using machine learning algorithms to train the extracted features to establish an intelligent recognition model; after training is completed, the model is used for the recognition and classification of real-time data. By comparing the output of the model with the set threshold, it is determined whether there is an abnormal situation. If there is an abnormal situation, the intelligent monitoring platform will issue an alarm.

[0055] The intelligent monitoring device of the mountain transportation system provided by the embodiment of the present invention, as Figure 6 shown, Figure 6 is a device block diagram of the intelligent monitoring system of the mountain transportation system, including: An acquisition module 601, configured to acquire the operation status data of the mountain transportation system; The first judgment module 602 is used to preprocess and calibrate the operation status data to obtain the processed operation status data, compare the processed operation status data with the corresponding first preset threshold to obtain a first comparison result, and judge whether there is an abnormality in the mountain transportation system according to the first comparison result. If there is an abnormality, a first alarm message is sent to the intelligent monitoring platform. If there is no abnormality, the processed operation status data is sent to the intelligent monitoring platform for storage; The second judgment module 603 is used to send the processed operation status data to the intelligent monitoring platform for identification, so that the intelligent monitoring platform uses the intelligent identification model to identify the processed operation status data to obtain an identification result, compare the identification result with the corresponding second preset threshold to obtain a second comparison result, and judge whether there is an abnormal situation in the mountain transportation system according to the second comparison result. If so, a second alarm message is sent, so that the monitoring personnel can adjust the mountain transportation system according to the second alarm message or the first alarm message.

[0056] In one embodiment, the acquisition module 601 includes a receiving unit, wherein, The receiving unit is used to receive the operation status data collected by a plurality of sensor units arranged on the transport vehicle. The operation status data includes operation speed data, load data, inclination angle data, driving route data, wind speed data and cargo status data.

[0057] The specific implementation manner of the intelligent monitoring device for the mountain transportation system is basically the same as the specific embodiments of the above-mentioned intelligent monitoring method for the mountain transportation system, and will not be elaborated here.

[0058] The intelligent monitoring system of the mountain transportation system provided by the embodiment of the present invention includes: A sensor network, an intelligent monitoring device for the mountain transportation system, and an intelligent monitoring platform. The intelligent monitoring device for the mountain transportation system is used to execute the intelligent monitoring device method for the mountain transportation system provided by the embodiment of the invention; Among them, 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.

[0059] In this embodiment, in the intelligent monitoring system of the mountain transportation system, as Figure 7 shown, the data processing center, that is, the intelligent monitoring device of the mountain transportation system includes an STM32 single-chip microcomputer, a power supply module and a wireless transmission module. The power supply module includes a DC / DC buck module and a storage battery. The voltage magnitude at the output end of the DC / DC buck module is 3 - 12V, and the wireless transmission module is a 4G / 5G wireless network unit.

[0060] The sensor network is distributed at key positions on the double-track vehicle, all-terrain vehicle, and cableway in the mountain transportation system, and is used to collect the operating status of the transportation system in real time, including physical information and monitoring videos; the data processing center is a single-chip microcomputer, which is responsible for preliminarily processing the physical information collected by the sensor, then comparing it with the set threshold, and then transmitting the data to the intelligent monitoring platform. If an abnormality occurs in the threshold comparison, the data processing center will send an alarm to the intelligent monitoring platform; the intelligent monitoring platform receives the monitoring videos and data from the sensor network, and is responsible for displaying, storing the data and videos, and warning of possible faults.

[0061] In one embodiment, the sensor network is used to send the collected operating status data to the intelligent monitoring device of the mountain transportation system; The intelligent monitoring device of the mountain transportation system is used to obtain the operating status data of the mountain transportation system; preprocess and calibrate the operating status data to obtain the processed operating status data, compare the processed operating status data with the corresponding first preset threshold to obtain a first comparison result, and judge whether there is an abnormality in the mountain transportation system according to 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; The intelligent monitoring platform is used to receive the first alarm message and the processed operating status data, identify the processed data using the intelligent recognition model to obtain an identification result, compare the identification result with the corresponding second preset threshold to obtain a second comparison result, and judge whether there is an abnormality in the mountain transportation system according to the second comparison result. If there is, send a second alarm message to enable the monitoring personnel to adjust the mountain transportation system according to the second alarm message or the first alarm message.

[0062] In this embodiment, the sensor network collects the operating status of the transportation unit in real time, including physical information and monitoring videos; the data processing center, that is, the intelligent monitoring device of the mountain transportation system, is a single-chip microcomputer, which is responsible for preliminarily processing the physical information collected by the sensor, then comparing it with the set threshold, and then transmitting the data to the intelligent monitoring platform. If an abnormality occurs in the threshold comparison, the data processing center will send an alarm to the intelligent monitoring platform; the intelligent monitoring platform receives the monitoring videos and data from the sensor network, and is responsible for displaying, storing the data and videos, and warning of possible faults.

[0063] Specifically, such as Figure 8As shown in the figure, the working process of the system is as follows: First, the sensor network collects data, and then the data is preprocessed in the single-chip microcomputer, including filtering, denoising, and calibration. Then, the data is compared with the set threshold and sent to the intelligent monitoring platform at the same time. If the threshold determination shows an anomaly, an alarm will be sent 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 at the same time. The data stored locally will be subjected to multi-modal feature extraction, and model training will be carried out according to machine learning algorithms. After the real-time data is input, the output of the model will be compared with the set threshold. If an anomaly occurs, an alarm will be sent. The intelligent monitoring platform will conduct double-level anomaly verification based on the model alarm and the alarm result of the data processing center to generate the final control instruction. If only one alarm is triggered, manual review will be carried out, the corresponding control strategy will be implemented, and the model will be updated at the same time to achieve a complete monitoring closed-loop process. If a double-level alarm is triggered, the monitoring system will send an emergency braking instruction and wait for the staff to eliminate the dangerous situation before resuming the transportation of the transportation unit.

[0064] Compared with the prior art, the intelligent monitoring platform of the mountain transportation system of the present invention has the following advantages and benefits: By integrating a variety of sensor technologies, the present invention can monitor the operating status of the mountain transportation system composed of double-track vehicles, all-terrain transport vehicles, and cableways in real time, covering multiple physical quantities such as speed, load, inclination, and vibration. According to the monitored data, the monitoring personnel can dynamically adjust the operating parameters to ensure the normal operation of the system.

[0065] 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 send out alarms. In addition, the system also supports manual review and the sending of emergency braking instructions to ensure that measures can be taken in a timely manner in case of danger.

[0066] The intelligent monitoring platform also supports the real-time display and storage of data and videos, and provides intuitive monitoring information for managers through a visual interface. This remote monitoring ability enables managers to master the operating status of the transportation system at any time and improve management efficiency.

[0067] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as the combinations of these technical features do not conflict, they should all be considered as the scope described in this specification.

[0068] The specific embodiments described above further elaborate on the object, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only for the specific embodiments of the present invention and is not used to limit the protection scope of the present invention. In particular, it is pointed out that for those skilled in the art, any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. An intelligent monitoring method for a mountain transport system, characterized in that: include: Obtaining the operating status data of mountain transportation systems; Preprocessing and calibrating the operation status data to obtain processed operation status data, comparing the processed operation status data with a corresponding first preset threshold value to obtain a first comparison result, judging whether the mountain transportation system has an abnormality according to the first comparison result, and if so, sending a first alarm message to an intelligent monitoring platform, and if not, sending the processed operation status data to the intelligent monitoring platform for storage; The processed operating status data is sent to the intelligent monitoring platform for identification, so that the intelligent monitoring platform uses an intelligent identification model to identify the processed operating status data to obtain an identification result, and the identification result is compared with a 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.

2. The intelligent monitoring method for mountain transportation system according to claim 1, characterized in that: 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.

3. The intelligent monitoring method for mountain transportation system according to claim 2, characterized in that: The inclination angle data is obtained by a sensor unit arranged at the center of the bottom of the transport vehicle, and the calculation formula of the inclination angle data is: in, is the angle, is the output voltage, is the zero voltage, is the angle sensitivity, is the output voltage range, is the angle measurement range; The wind speed data is obtained by a wind speed sensor arranged on the cableway support, wherein the calculation formula of the wind speed data is: in, is the wind speed at the location of the cargo 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 arranged 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.

4. 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: According to calculating the average value of the running status data in the preset sliding window, filtering and denoising the running status data to obtain denoised data; The denoised data is linearly calibrated to obtain processed operating status data.

5. 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 initiated, a corresponding control strategy is implemented, and a corresponding decision result is recorded.

6. The intelligent monitoring method for mountain transportation system according to claim 1, characterized in that: After sending the operating status data 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 associated feature data; Based on the time domain feature data, the frequency domain feature data and the associated feature data, the initial recognition model is trained to obtain an intelligent recognition model.

7. An intelligent monitoring device for a mountain transport system, characterized in that: include: An acquisition module, used to acquire the operation status data of the mountain transportation system; A first judgment module is used to pre-process and calibrate the operation status data to obtain processed operation status data, compare the processed operation status data with a corresponding first preset threshold value to obtain a first comparison result, and judge whether there is an abnormality in the mountain transportation system according to the first comparison result. If there is an abnormality, a first alarm message is sent to the intelligent monitoring platform; if there is no abnormality, the processed operation status data is sent to the intelligent monitoring platform for storage; 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 an intelligent recognition model to identify the processed operating status data to obtain an identification result, compare the identification result with a 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 according to the second alarm message or the first alarm message.

8. The intelligent monitoring device for mountain transportation system according to claim 7, characterized in that: The acquisition module includes a receiving unit, wherein: The receiving unit is used to receive the operating status data collected by the sensor unit arranged 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.

9. An intelligent monitoring system for a mountain transport system, characterized in that: It 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 intelligent monitoring device method for a mountain transport system as claimed in any one of claims 1 to 6; Wherein, 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.

10. The intelligent monitoring system for mountain transportation system according to claim 9, characterized in that: The sensor network is used to send the collected operation status data to the intelligent monitoring device of the mountain transportation system; The intelligent monitoring device of the mountain transport system is used to obtain the operation status data of the mountain transport system; Preprocessing and calibrating the operation status data to obtain processed operation status data, comparing the processed operation status data with a corresponding first preset threshold value to obtain a first comparison result, judging whether the mountain transportation system has an abnormality according to the first comparison result, and if so, sending a first alarm message to an intelligent monitoring platform; if not, sending the processed operation status data to the intelligent monitoring platform for storage and identification; The intelligent monitoring platform is used to receive the first alarm information and processed operating status data, use an intelligent recognition model to identify the processed data to obtain a recognition result, compare the recognition result with a 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 message is issued to enable monitoring personnel to adjust the mountain transportation system based on the second alarm information or the first alarm information.

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