Cableway safety distance monitoring control system based on multi-sensor fusion

Abstract

The invention discloses a cableway safety distance monitoring control system based on multi-sensor fusion, which relates to the technical field of aerial cableways, and comprises a lift car movement monitoring unit, an obstacle detection unit, an encrypted data transmission unit, an intelligent analysis host and linkage control unit and a hydraulic redundancy anchoring device, according to the cableway safety distance monitoring and control system based on multi-sensor fusion, by fusing ultrasonic waves, radar, the gyroscope and infrared grating array data and combining with an LSTM model, the swing track of a carriage in the next three seconds is predicted, the cableway safety distance is analyzed, and the safety distance of the cableway is obtained. The cableway safety distance is judged to belong to the type of three early warning levels, then a corresponding joint control mechanism is triggered, control actions are output, self-adaptive control of the cableway is achieved, a self-adaptive threshold model based on the Bayesian network is provided, dynamic adjustment of the safety distance along with environmental parameters is achieved, and the method is superior to a traditional fixed threshold.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of aerial ropeway, in particular to a ropeway safety distance monitoring control system based on multi-sensor fusion. BACKGROUND

[0002] The ropeway is a kind of transportation system for transporting people or goods by steel cable as track, which is erected on the support structure. Its core components include steel cable (load bearing cable / traction cable), driving and tensioning device, support structure (support / pressure cable wheel set), carrying tool (suspension cabin / chair / basket) and electrical system. The ropeway can be divided into fixed rope type (speed about 1 meter / second), off-hanging rope type (speed 5-6 meters / second) and reciprocating type (speed up to 8 meters / second, passenger capacity hundreds of people) according to the operation mode. The ropeway safety protection mainly involves three aspects of equipment maintenance, passenger behavior specification and emergency management, and real-time monitoring of the lateral swing of the suspension cabin is the core guarantee for the safe operation of the ropeway. The large swing will increase the risk of collision between the suspension cabin and the support or platform, and also cause panic among passengers. However, the existing technology has the following shortcomings: 1. There is no real-time monitoring means for the lateral swing of the suspension cabin, and the collision risk is only judged by manual observation or fixed limiting device, with a response delay of 5-10 seconds; 2. The false alarm rate of the traditional video monitoring system is as high as 40% in rainy, snowy and foggy weather, and the distance parameter cannot be quantitatively detected; 3. The ultrasonic sensor is easily disturbed in rainy and snowy weather, the millimeter wave radar has high cost, the infrared grating cannot penetrate obstacles, and the multi-sensor data is processed independently without forming collaborative optimization, which is difficult to cope with local wind speed mutation in complex terrain. SUMMARY

[0003] In view of the shortcomings of the prior art, the present application provides a ropeway safety distance monitoring control system based on multi-sensor fusion, which solves the problems raised in the background.

[0004] To achieve the above purpose, the present application realizes the following technical scheme: a ropeway safety distance monitoring control system based on multi-sensor fusion, comprising: a suspension cabin motion monitoring unit, an obstacle detection unit, an encrypted data transmission unit, an intelligent analysis host and a linkage control unit, and a hydraulic redundant anchoring device, the suspension cabin motion monitoring unit is composed of a three-axis MEMS gyroscope and a GPS positioning module, the obstacle detection unit is composed of an infrared grating array and a millimeter wave radar, an ultrasonic array; The encrypted data transmission unit adopts a hybrid networking architecture combining LORA wireless communication and fiber ring network; The intelligent analysis host: deploy swing trend prediction algorithm based on LSTM neural network and adaptive threshold model based on Bayesian network.

[0005] The linkage control unit: the output signal can directly intervene the frequency converter to realize four-stage speed regulation control, and the four-stage speed regulation control is sound-light warning, speed limiting, braking and anchoring.

[0006] Preferably, the three-axis MEMS gyroscope is installed at a vertical distance of not more than 20 cm from the center of gravity of the cage.

[0007] Preferably, the infrared grating array forms a cross-detection network on both sides of the cage, and the interval angle between adjacent beams is ≤5°.

[0008] Preferably, the millimeter wave radar is installed in the middle of the support beam, and the detection direction forms a 45° angle with the running direction of the cableway.

[0009] Preferably, the key nodes in the hybrid networking structure used for data transmission are provided with double-channel hot backup.

[0010] Preferably, the sensors used in the cage motion monitoring unit and the obstacle detection unit are fixed by using a fixed seat, and are protected by using a neodymium magnet and a shielding cover.

[0011] Preferably, the three-axis MEMS gyroscope uses an MPU-6050 chip to detect the roll angle at a sampling rate of 100 Hz, and the ultrasonic array: 4 groups of ultrasonic sensors are symmetrically installed on both sides of the support, covering horizontal and vertical direction detection of the cage.

[0012] Preferably, a waterproof sound-transparent film is installed on the ultrasonic sensor, and the detection error in rainy and snowy weather is reduced to ±3 cm.

[0013] The application provides a cableway safety distance monitoring control system based on multi-sensor fusion, which has the following beneficial effects: The cableway safety distance monitoring control system based on multi-sensor fusion fuses ultrasonic, radar and gyroscope and infrared grating array data, combines an LSTM model to predict the cage swing trajectory within 3 seconds in the future, analyzes the cableway safety distance, judges the type of the cableway safety distance in three types of early warning levels, and then triggers the corresponding linkage control mechanism, outputs the control action, realizes the adaptive control of the cableway, proposes an adaptive threshold model based on a Bayesian network, realizes the dynamic adjustment of the safety distance with the environmental parameters, and is superior to the traditional fixed threshold. BRIEF DESCRIPTION OF DRAWINGS

[0014] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description only represent some of the embodiments of the present application, and other drawings can be obtained by those of ordinary skill in the art without any creative effort based on these drawings.

[0015] Fig. 1 The system installation schematic diagram of the cableway safety distance monitoring control system based on multi-sensor fusion of the present application; Fig. 2 The early warning decision flowchart of the cableway safety distance monitoring control system based on multi-sensor fusion of the present application; Fig. 3 The system module schematic diagram of the cableway safety distance monitoring control system based on multi-sensor fusion of the present application.

[0016] In the figure: 1, cabin movement monitoring unit; 2, obstacle detection unit; 3, encrypted data transmission unit; 4, intelligent analysis host; 5, linkage control unit; 6, hydraulic redundant anchoring device; 7, three-axis MEMS gyroscope; 8, GPS positioning module; 9, infrared grating array; 10, millimeter wave radar; 11, ultrasonic array. DETAILED DESCRIPTION

[0017] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments only represent some of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without any creative effort belong to the scope of protection of the present application.

[0018] Please refer to Figs. 1-3 The present application provides a technical solution of a cableway safety distance monitoring control system based on multi-sensor fusion, which comprises: a cabin movement monitoring unit 1, an obstacle detection unit 2, an encrypted data transmission unit 3, an intelligent analysis host 4, a linkage control unit 5, and a hydraulic redundant anchoring device 6. The cabin movement monitoring unit 1 is composed of a three-axis MEMS gyroscope 7 and a GPS positioning module 8. The obstacle detection unit 2 is composed of an infrared grating array 9, a millimeter wave radar 10, and an ultrasonic array 11. The encrypted data transmission unit 3 adopts a hybrid networking architecture combining LORA wireless communication and fiber ring network. The hydraulic redundant anchoring device 6 and the encrypted data transmission unit 3 are adopted. Compared with the prior art, the system response speed is improved by 4 times, the false alarm rate is reduced to below 3%, and it is suitable for harsh environments such as mountainous areas and high altitudes. Intelligent analysis host 4: deploy swing trend prediction algorithm based on LSTM neural network and adaptive safety distance threshold algorithm based on Bayesian network; Adaptive safety distance threshold algorithm based on Bayesian network: train Bayesian network model based on historical data wind speed, car speed, swing amplitude, dynamically adjust safety distance threshold, propose adaptive threshold model based on Bayesian network, realize dynamic adjustment of safety distance with environmental parameters, better than traditional fixed threshold.

[0019] Multi-sensor data fusion: adopt Kalman filter to fuse ultrasonic, radar and gyroscope data, eliminate single sensor noise and improve detection accuracy to ±2cm.

[0020] Linkage control unit 5: output signal can directly intervene frequency converter to realize four-stage speed control, four-stage speed control for sound and light warning, speed limit, braking and anchoring.

[0021] Three-axis MEMS gyroscope 7, the vertical distance from the installation position to the center of gravity of the hanging car is not more than 20cm.

[0022] Those skilled in the art know that: infrared grating array 9 forms a cross detection network on both sides of the hanging car, the angle between adjacent beams is ≤5°.

[0023] Those skilled in the art know that: millimeter wave radar 10 is installed in the middle of the support beam, and the detection direction is at an angle of 45° with the direction of cableway operation.

[0024] Those skilled in the art know that: the key nodes in the hybrid networking structure used for data transmission are set with dual-channel hot standby.

[0025] Those skilled in the art know that: the sensors used in the hanging car motion monitoring unit 1 and the obstacle detection unit 2 are fixed by fixed seats, and are protected by neodymium magnets and shielding covers.

[0026] Those skilled in the art know that: three-axis MEMS gyroscope 7: uses MPU-6050 chip to detect roll angle at a sampling rate of 100Hz, ultrasonic array 11: 4 groups of ultrasonic sensors are symmetrically installed on both sides of the support, covering horizontal and vertical direction detection of the car.

[0027] Those skilled in the art know that: waterproof sound transmission film is installed on the ultrasonic sensor, and the detection error is reduced to ±3cm in rainy and snowy weather.

[0028] Example 1: sensor installation and calibration Ultrasonic array 11: each group contains 2 transceivers, horizontal spacing 50cm, vertical inclination 10°, forming a three-dimensional detection network; Millimeter wave radar 10: installed at the height of 1.2 m from the cableway cable 1.2 m, inclined downward by 5° to cover the bottom area of the car; Three-axis MEMS gyroscope 7 calibration: baseline data is collected when the car is stationary, and mechanical vibration interference is eliminated by acceleration compensation in dynamic mode; Three-axis MEMS gyroscope 7: MPU-6050 chip is used to detect the roll angle range of ±90° at a sampling rate of 100 Hz Infrared grating: transceiver pairs with a spacing of 30 cm are arranged on both sides of the hanging car, forming a 30°×5m fan-shaped detection area; Electromagnetic shielding: the sensor cables used by infrared grating array 9, millimeter wave radar 10, ultrasonic array 11, three-axis MEMS gyroscope 7, and GPS positioning module 8 all use double shielding structure (aluminum foil + copper mesh), and the signal-to-noise ratio is improved by 20 dB.

[0029] Example 2: Communication system: Hanging car→support: LORA communication is used, and data containing gyroscope data, GPS coordinates, and device ID is sent every 200 ms; Support→control room: a ring network is formed by single-mode optical fiber, and the communication delay is <50 ms; Modbus-RTU protocol is used, and a special data frame structure is defined: | Start code | Device address | Function code | Data segment (16 bytes) | CRC check | |--------|----------|--------|----------------|---------| Example 3: Algorithm deployment Data preprocessing: the original ultrasonic data is filtered by a sliding window with a window size of 10 ms, and abnormal pulses are removed. Radar wind speed data is compared with weather station data to correct local deviations caused by terrain.

[0030] Real-time prediction: based on the LSTM model to predict the car swing trajectory in the next 3 seconds, input parameters: roll angle, wind speed, and car speed.

[0031] Example 4: Control linkage When level III early warning is triggered, the system automatically starts: The response time of the frequency converter output braking signal is <0.2 s; The locking force of the hydraulic redundant anchoring device 6 is ≥5 kN; Send encrypted alarm signal AES-256 protocol to control center.

[0032] Four-level control strategy:

[0033] The standard parts used in the present application can be purchased from the market, and can be ordered according to the description and drawings, and the specific connection of each part adopts the conventional means such as bolt, rivet and welding in the prior art, the mechanical, parts and equipment adopt the conventional type in the prior art, the installation mode between the equipment is the same as the conventional installation mode in the prior art, such as the two ends of the shaft part are connected by bearings, the connection position of the valve part is provided with a leakage prevention rubber strip, the outer side of the threaded rod or screw rod is provided with a dust cover, the equipment can be driven by any one of built-in battery or external power supply, etc., the control mode is automatically controlled by the controller, the control circuit of the controller can be realized by simple programming of the person skilled in the art, which belongs to the common knowledge in the art, and the present application is mainly used for protecting the mechanical device, therefore, the control mode and circuit connection of the present application will not be explained in detail, and the external controller mentioned in the description can control the electrical elements mentioned herein, and the external controller is a conventional known device.

[0034] The above is only the preferred embodiment of the present application, but the protection scope of the present application is not limited to this, any person skilled in the art can make equivalent replacement or change according to the technical scheme and the inventive concept of the present application within the technical range disclosed by the present application, which should be covered in the protection scope of the present application.

Claims

1. A ropeway safety distance monitoring control system based on multi-sensor fusion, characterized in that: The application relates to a gondola car motion monitoring system, which comprises a gondola car motion monitoring unit (1), an obstacle detection unit (2), an encrypted data transmission unit (3), an intelligent analysis host (4), a linkage control unit (5) and a hydraulic redundancy anchoring device (6), wherein the gondola car motion monitoring unit (1) is composed of a three-axis MEMS gyroscope (7) and a GPS positioning module (8), the obstacle detection unit (2) is composed of an infrared grating array (9) and a millimeter wave radar (10), and an ultrasonic array (11). The encrypted data transmission unit (3) adopts a hybrid networking architecture combining LORA wireless communication and a fiber ring network. The intelligent analysis host (4) is provided with a swing trend prediction algorithm based on an LSTM neural network and an adaptive threshold model based on a Bayesian network. The linkage control unit (5) can directly intervene in a frequency converter to realize four-stage speed control, and the four-stage speed control is sound-light warning, speed limiting, braking and anchoring. The three-axis MEMS sensor is installed at a vertical distance of not more than 20 cm from the center of gravity of the gondola car.

2. The cableway safety distance monitoring control system based on multi-sensor fusion according to claim 1, characterized in that: The infrared grating array (9) forms a cross detection network on both sides of the gondola car, and the interval angle between adjacent beams is less than or equal to 5 degrees.

3. The cableway safety distance monitoring control system based on multi-sensor fusion according to claim 1, characterized in that: The millimeter wave radar (10) is installed in the middle of the support beam, and the detection direction forms a 45-degree angle with the running direction of the cableway.

4. The cableway safety distance monitoring control system based on multi-sensor fusion according to claim 1, characterized in that: The key nodes in the hybrid networking structure of the data transmission are provided with double-channel hot backup.

5. The cableway safety distance monitoring control system based on multi-sensor fusion according to claim 1, characterized in that: The sensors used in the gondola car motion monitoring unit (1) and the obstacle detection unit (2) are fixed by using fixed seats and protected by using neodymium magnets and shielding covers.

6. The ropeway safety distance monitoring control system based on multi-sensor fusion according to claim 1, characterized in that: The three-axis MEMS gyroscope (7) adopts an MPU-6050 chip to detect the roll angle at a sampling rate of 100 Hz.

7. The cableway safety distance monitoring control system based on multi-sensor fusion according to claim 1, characterized in that: The ultrasonic array (11) is symmetrically installed with four groups of ultrasonic sensors on both sides of the support, which covers the horizontal and vertical direction detection of the car.

8. The ropeway safety distance monitoring control system based on multi-sensor fusion according to claim 1, characterized in that: A waterproof sound transmission film is installed on the ultrasonic sensor, and the detection error is reduced to plus or minus 3 cm in rainy and snowy weather.

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