Temperature monitoring device for large-dip-angle slant monorail crane

Abstract

The invention discloses a temperature monitoring device of a monorail crane for large inclination angle inclination, which belongs to the technical field of monorail crane safety monitoring, and comprises a multi-dimensional sensing module which is arranged at a key heating part and a surrounding environment of the monorail crane and comprises a temperature sensor group, an environment sensor group and a working condition sensor group. And the data processing and decision-making module is fixedly mounted in the electric cabinet of the monorail crane, and an embedded industrial computer is adopted to operate a multi-parameter fusion monitoring model. A high-precision sensor is adopted, tiny temperature changes of all key components can be accurately captured, and the accuracy and reliability of monitoring data are ensured. Meanwhile, the special environment under the large-dip-angle oblique working condition is fully considered, so that monitoring is more comprehensive and free of omission, and a solid guarantee is provided for stable operation of the monorail crane. The device covers key heating components such as a diesel engine, a hydraulic system, a cooling system and an axle box, eliminates monitoring blind areas of a traditional device by combining exhaust and cooling water temperature monitoring, and achieves full-dimensional sensing of the thermal state.

Description

Technical Field

[0001] This invention belongs to the field of monorail safety monitoring technology, specifically relating to a temperature monitoring device for a monorail used at a large angle of inclination. Background Technology

[0002] The Huaibei Mining Group's transportation system reform adopted explosion-proof diesel-powered monorail cranes, significantly improving transportation efficiency compared to winch transport. As a core transportation device in coal mines, both for ascending and descending inclines and in horizontal roadways, monorail cranes offer advantages such as high mobility and large load capacity. However, when operating at steep angles, their power, transmission, and braking systems must withstand loads far exceeding those required for horizontal roadway operation, leading to a rapid temperature increase and becoming a major cause of safety accidents. Existing monorail crane temperature monitoring technology has the following key shortcomings:

[0003] The monitoring dimensions are limited and there are blind spots: existing devices mostly use single-bus digital temperature sensors to centrally monitor shaft temperature, which does not cover key heat-generating components such as diesel engines, main pump sets, and brake pump sets. Furthermore, the monitoring of key parameters such as cooling water temperature and exhaust temperature is lacking, making it impossible to fully reflect the thermal status of the equipment.

[0004] Poor anti-interference capability and insufficient reliability: The single-bus connection method has the risk of single point of failure. A short circuit in any sensor will cause the entire monitoring system to fail. Furthermore, it is not adapted to vibration and dust environments under large tilt angle conditions, resulting in low data transmission stability.

[0005] The early warning mechanism is rigid: alarms are triggered only based on fixed temperature thresholds, without dynamically adjusting the warning standards according to operating parameters such as inclination angle, operating speed, and load weight, which easily leads to false alarms or missed alarms. For example, when climbing at a steep inclination angle, the normal threshold for the surface temperature of the diesel engine should be lower than that under level roadway operation, but the existing device does not implement differentiated judgment.

[0006] Weak data interaction and traceability capabilities: Most devices only have local alarm functions, lack real-time data synchronization with the remote control center, and have no historical data storage and analysis functions, which is not conducive to fault tracing and preventive maintenance. Summary of the Invention

[0007] The purpose of this invention is to provide a temperature monitoring device for a monorail crane with a large inclination angle, so as to solve the problems mentioned in the background art.

[0008] To achieve the above objectives, the present invention provides the following technical solution: a temperature monitoring device for a monorail crane used at a large angle of inclination, comprising:

[0009] The multi-dimensional sensing module is installed at the key heat-generating components of the monorail and the surrounding environment, including a temperature sensor group, an environmental sensor group, and a working condition sensor group.

[0010] The data processing and decision-making module is fixedly installed inside the monorail crane's electrical control box and uses an embedded industrial computer to run a multi-parameter fusion monitoring model.

[0011] The early warning execution module is connected to the data processing and decision-making module and executes tiered early warnings.

[0012] The power supply module, connected to the multi-dimensional sensing module, data processing and decision-making module and early warning execution module, provides a stable power supply;

[0013] The remote interaction module connects to the data processing and decision-making module to enable remote data transmission and command interaction;

[0014] The self-diagnosis and historical analysis module is integrated into the data processing and decision-making module, supporting self-checking, fault tracing, and predictive maintenance.

[0015] Preferably, the temperature sensor group includes:

[0016] Explosion-proof K-type thermocouples are installed on the diesel engine cylinder block and exhaust manifold, with a measurement range of 0 to 400℃ and an accuracy of ±1℃.

[0017] The intrinsically safe PT100 sensor is installed on the main pump assembly and brake pump assembly, with a measurement range of -50 to 200℃ and an accuracy of ±0.5℃.

[0018] Waterproof NTC thermistors are installed in the cooling water tank and bearing housing, with a response time of ≤1s and a waterproof rating of IP68.

[0019] Preferably, the data processing and decision-making module uses an ARM Cortex-A9 processor, preprocesses the data through moving average filtering and Kalman filtering, evaluates the thermal state of the equipment based on a neural network algorithm, and dynamically adjusts the temperature threshold according to the tilt angle and load changes.

[0020] Preferably, the environmental sensor group includes:

[0021] Temperature and humidity sensor, installed 0.5 to 1m away from the heat-generating component, with a measurement range of -40℃ to 85℃ and 0% to 100%RH, and an accuracy of ±0.3℃ / ±2%RH;

[0022] The dust concentration sensor (GP2Y1010AU0F) has its sampling port facing the surrounding environment and a detection range of 0-500 μg / m³.

[0023] Preferably, the data processing and decision-making module is specifically used for:

[0024] It receives and integrates temperature data of key heat-generating components collected by the temperature sensor group, environmental data collected by the environmental sensor group, and tilt angle, load, and speed data collected by the operating condition sensor group;

[0025] Based on the multi-parameter fusion monitoring model, the current thermal status of the equipment is comprehensively evaluated, and graded early warning instructions are generated according to the evaluation results.

[0026] Preferably, the operating condition sensor group includes:

[0027] A three-axis tilt sensor is installed on the monorail crane's running mechanism, with a measurement range of ±90° and an accuracy of ±0.1°.

[0028] The load weight sensor is integrated into the hook or wire rope fixing point, with a range of 0 to 10 tons and an accuracy of ±0.5%FS.

[0029] The operating speed sensor is mounted on the drive wheel axle and has a resolution of 0.1 m / s.

[0030] Preferably, the ARM Cortex-A9 processor specifically includes the following functions:

[0031] Data fusion and preprocessing: The original data is smoothed and outliers are removed by moving average filtering, and the tilt angle and velocity data are corrected in real time by Kalman filtering algorithm;

[0032] Thermal state assessment model: Based on neural network algorithm, the input layer contains 12 nodes including temperature, humidity, dust, tilt angle, load and velocity, the hidden layer has 3 layers with 32 nodes each, and the output layer is a thermal state score of 0-100 points;

[0033] Dynamic adaptation to operating conditions: When the tilt angle is ≥15°, the threshold values ​​for diesel engine surface temperature, brake pump group temperature, etc. are automatically lowered. For every ton increase in load, the corresponding component temperature threshold is lowered by 0.5%.

[0034] Preferably, the early warning execution module includes:

[0035] Local early warning unit: intrinsically safe audible and visual alarm for mining, OLED display panel, installed on the instrument panel in the monitoring room;

[0036] Emergency intervention unit: connected to the electronic control valve of the monorail braking system, triggering emergency braking and cutting off power supply to the power system when a level 2 warning is triggered;

[0037] The power supply module adopts an intrinsically safe dual-redundancy design, including an explosion-proof switching power supply and a backup lithium battery pack.

[0038] Preferably, the remote interaction module accesses the coal mine ring network through an intrinsically safe wireless base station for mining, and its functions include uploading thermal status scores, early warning instructions and equipment operation data to the ground control center in real time, and receiving parameter configuration, threshold adjustment and data query instructions from the remote control center.

[0039] Preferably, the self-diagnosis and historical analysis module includes the following functions:

[0040] Self-diagnostic function: Periodically performs self-checks on the hardware and communication status of the multi-dimensional sensing module, early warning execution module, and power supply module. When an anomaly occurs, it generates diagnostic information containing the anomaly type and location and provides a prompt through the early warning execution module.

[0041] Historical analysis function: Long-term storage of raw data collected by multi-dimensional sensing modules, early warning event records generated by data processing and decision-making modules, and equipment operation status data, supporting trend analysis, fault tracing, and predictive maintenance analysis.

[0042] Compared with the prior art, the beneficial effects of the present invention are:

[0043] 1. This invention employs high-precision sensors, capable of accurately capturing minute temperature changes in key components, ensuring the accuracy and reliability of monitoring data. Simultaneously, its unique arrangement fully considers the special environment under large-angle inclined conditions, making monitoring more comprehensive and thorough, providing a solid guarantee for the stable operation of the monorail crane. It covers key heat-generating components such as the diesel engine, hydraulic system, cooling system, and axle box, and, combined with exhaust and cooling water temperature monitoring, eliminates monitoring blind spots of traditional devices, achieving full-dimensional perception of thermal status.

[0044] 2. This invention constructs a dynamic early warning model based on multiple parameters such as tilt angle and load. This model can adjust the early warning threshold in real time according to the tilt angle changes, load fluctuations, and other parameter information during the actual operation of the monorail. When the tilt angle increases or the load increases, the model automatically increases its sensitivity to temperature anomalies and issues an early warning signal. Conversely, when the tilt angle is small or the load is light, the warning standard is appropriately relaxed to reduce unnecessary false alarms. This intelligent early warning mechanism greatly improves the accuracy and reliability of the temperature monitoring device, effectively avoiding false alarms or missed alarms caused by unreasonable fixed threshold settings, and providing a more reliable guarantee for the safe operation of the monorail.

[0045] 3. This invention uses a tiered early warning system linked to emergency braking. It sets multiple warning thresholds. When an abnormal temperature is detected but has not yet reached an emergency danger level, a primary warning is triggered to alert operators and prompt initial inspection. If the temperature continues to rise and reaches the intermediate warning threshold, the device will issue a stronger alarm and advise operators to immediately stop the monorail operation for a detailed inspection. When the temperature rises sharply to the emergency warning threshold, the device will immediately activate the emergency braking system, forcing the monorail to stop operation, thereby effectively preventing serious safety accidents caused by thermal failures and ensuring the safety of personnel and equipment. Attached Figure Description

[0046] Figure 1This is a flowchart of the present invention. Detailed Implementation

[0047] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0048] Example 1

[0049] Please see Figure 1 This invention provides a temperature monitoring device for a monorail crane used at large inclination angles. The device comprises a multi-dimensional sensing module installed at key heat-generating components of the monorail crane and its surrounding environment, including a temperature sensor group, an environmental sensor group, and a working condition sensor group. The temperature sensor group includes: an explosion-proof K-type thermocouple installed on the diesel engine cylinder block and exhaust manifold, with a measurement range of 0–400℃ and an accuracy of ±1℃; an intrinsically safe PT100 sensor installed on the main pump assembly and brake pump assembly, with a measurement range of -50–200℃ and an accuracy of ±0.5℃; and a waterproof NTC thermistor installed at the coolant tank and axle box bearings, with a response time ≤1s and a waterproof rating of IP68. The environmental sensor group includes: a temperature and humidity sensor installed 0.5–1m away from the heat-generating components, with a measurement range of -40℃–85℃ and 0%–100%RH, and an accuracy of ±0.3℃ / ±2%RH. The dust concentration sensor (GP2Y1010AU0F) has its sampling port facing the surrounding environment and a detection range of 0-500 μg / m³.

[0050] The operating condition sensor group includes: a three-axis tilt sensor, installed on the monorail crane's running mechanism, with a measurement range of ±90° and an accuracy of ±0.1°; a load weight sensor, integrated into the hook or wire rope fixing point, with a measuring range of 0–10 tons and an accuracy of ±0.5%FS; and a running speed sensor, installed on the drive wheel axle, with a resolution of 0.1 m / s.

[0051] Furthermore, the multi-dimensional sensing module, through a combination of various types of sensors, achieves comprehensive monitoring of key components and the operating environment of the monorail crane. The temperature sensor group selects suitable models based on the characteristics of different equipment; the explosion-proof K-type thermocouples adopt an armored structure, capable of withstanding the high temperatures and vibrations on the diesel engine surface. The intrinsically safe PT100 sensor eliminates the influence of line resistance through a four-wire connection method, ensuring the stability of pump temperature measurement. The waterproof NTC thermistor uses epoxy resin sealing technology to meet the requirements of the cooling system under humid conditions. In the environmental sensor group, the temperature and humidity sensor integrates a PT1000 temperature sensing element and a polymer thin-film humidity-sensitive capacitor, transmitting signals through shielded cables. The dust concentration sensor uses the infrared scattering principle, with a built-in fan to form a stable airflow for sampling. Regarding the operating condition sensor group, the three-axis tilt sensor has a built-in gyroscope compensation mechanism, which can dynamically correct angular deviations during hoisting. The load weight sensor achieves force-to-electricity conversion through a strain gauge bridge circuit, and is equipped with an overload alarm function. The running speed sensor uses the Hall effect principle, calculating real-time speed by detecting the frequency of the drive wheel magnet signal, with a data output period of less than 50ms. All sensors synchronize data via a CAN bus, with a configurable sampling frequency of 1-10Hz, supporting both Modbus RTU and TCP dual-protocol communication. All sensors are connected to the data processing module inside the control box via CAN twisted-pair shielded cables.

[0052] The data processing and decision-making module uses an ARM Cortex-A9 processor. It preprocesses data using moving average filtering and Kalman filtering, evaluates the equipment's thermal state based on a neural network algorithm, and dynamically adjusts the temperature threshold according to tilt angle and load changes. It receives and fuses temperature data from key heat-generating components collected by the temperature sensor group, environmental data collected by the environmental sensor group, and tilt angle, load, and speed data collected by the operating condition sensor group. Based on a multi-parameter fusion monitoring model, it comprehensively evaluates the current equipment's thermal state and generates tiered early warning commands based on the evaluation results. The ARM Cortex-A9 processor's specific functions include: Data fusion and preprocessing: smoothing the raw data and removing outliers using moving average filtering, and using a Kalman filtering algorithm to correct tilt angle and speed data in real time. Thermal state evaluation model: based on a neural network algorithm, the input layer contains 12 nodes (temperature, humidity, dust, tilt angle, load, and speed), three hidden layers with 32 nodes each, and the output layer provides a thermal state score from 0 to 100. Dynamic adaptation to operating conditions: When the tilt angle is ≥15°, the threshold values ​​for diesel engine surface temperature, brake pump group temperature, etc. are automatically lowered. For every ton increase in load, the corresponding component temperature threshold is lowered by 0.5%.

[0053] Furthermore, four warning levels are established based on the thermal status score. A Level 1 warning is triggered when the score exceeds 80, and the system automatically reduces speed. A Level 2 warning is initiated when the score is between 60 and 80, prompting manual inspection. A Level 3 warning is executed when the score is between 40 and 60, recording abnormal data. Below 40, normal operation is maintained. Dynamic threshold adjustment strategy: A three-dimensional mapping table of tilt angle, load, and temperature is established. The safe temperature threshold under the current operating condition is quickly determined using a lookup method, while a temperature buffer zone is set to prevent frequent warning triggering. Multi-source data verification mechanism: When data from the temperature sensor and the operating condition sensor conflict, a cross-validation process is initiated. Tilt angle and speed data corrected by Kalman filtering are prioritized as the basis for judgment, ensuring the reliability of the warning decision.

[0054] The early warning execution module includes: a local early warning unit: an intrinsically safe audible and visual alarm and an OLED display panel, installed on the control room dashboard. An emergency intervention unit: connected to the electric control valve of the monorail braking system, triggering emergency braking and cutting off power to the power system upon a level-two early warning. The power supply module adopts an intrinsically safe dual-redundant design, including an explosion-proof switching power supply and a backup lithium battery pack.

[0055] Furthermore, the data transmission module adopts an industrial-grade Ethernet communication protocol and is equipped with a redundant fiber optic ring network link to ensure the stability of data transmission in the complex electromagnetic environment downhole. The sensor group includes a high-precision platinum resistance temperature probe, a triaxial accelerometer, and a Hall effect speed sensor. All probes are explosion-proof and have an IP68 protection rating. The control module is developed based on the ARM Cortex-M7 core and integrates a fuzzy PID control algorithm, which can dynamically adjust the sampling frequency according to real-time operating conditions and automatically switch to high-speed sampling mode when the tilt angle exceeds 25°.

[0056] The remote interaction module connects to the coal mine ring network through an intrinsically safe wireless base station for mining. Its functions include uploading thermal status scores, early warning instructions, and equipment operation data to the ground control center in real time, and receiving parameter configuration, threshold adjustment, and data query instructions from the remote control center.

[0057] Furthermore, this module supports concurrent communication between multiple nodes, employs AES-128 encryption to ensure data transmission security, and maintains a communication latency of less than 200ms. The ground control center can remotely configure parameters via a web interface or mobile app, and supports historical data curve playback and anomaly event tracing. The system reserves interfaces for industrial protocols such as OPCUA and ModbusTCP, enabling seamless integration with coal mine integrated automation platforms to achieve multi-system data sharing and collaborative control.

[0058] The self-diagnosis and historical analysis module includes the following functions: Self-diagnosis: Periodically checks the hardware and communication status of the multi-dimensional sensing module, early warning execution module, and power supply module. When an anomaly occurs, it generates diagnostic information including the anomaly type and location and alerts the system via the early warning execution module. Historical analysis: Long-term storage of raw data collected by the multi-dimensional sensing module, early warning event records generated by the data processing and decision-making module, and equipment operating status data. It supports trend analysis, fault tracing, and predictive maintenance analysis.

[0059] Furthermore, this module possesses intelligent data processing capabilities. Its self-diagnostic function can monitor the working status of each module in real time, ensuring stable system operation. Once an anomaly is detected, an early warning mechanism is immediately triggered, providing maintenance personnel with accurate fault location information. The historical analysis function, through big data storage technology, completely records all key data during equipment operation, providing strong data support for subsequent trend analysis, fault review, and preventative maintenance, effectively improving the level of intelligent equipment management.

[0060] Example 2

[0061] This device is installed on an explosion-proof diesel engine monorail crane in a transport roadway of a 35° inclined mining area in a coal mine. The specific configuration of each module is as follows:

[0062] Multi-dimensional sensing module: Two explosion-proof K-type thermocouples are installed in the diesel engine cylinder block, one thermocouple is installed in the exhaust manifold, one PT100 sensor is installed in each of the main pump assembly and brake pump assembly, one NTC thermistor is installed in the coolant tank, and two NTC thermistors are installed in each of the front and rear axle boxes. The tilt sensor is installed in the middle of the frame, the load sensor is installed on the connecting pin of the carrier vehicle, and the encoder is installed at the end of the right travel wheel axle.

[0063] Data processing and decision-making module: adopts STM32F407ZGT6 main controller, configured with 8GB industrial SD card, preset basic thresholds: diesel engine surface ≤150℃, exhaust temperature ≤70℃, cooling water temperature ≤95℃, shaft temperature ≤90℃.

[0064] Early warning execution module: The audible and visual alarm is model BBJ-36V, and the display panel is a 2.4-inch OLED screen.

[0065] Remote interaction module: Employs intrinsically safe mine-grade WiFi base stations, supporting IEEE 802.11b / g / n protocols, and networked with base stations deployed every 50m within the tunnel. The WiFi base stations connect to a signal converter via network cables, thus accessing the mine's ring network.

[0066] When a monorail crane with a load of 25t climbs a 35° inclined roadway, the operating process of the device is as follows: the temperature sensing unit collects the surface temperature of the diesel engine, the exhaust temperature and the temperature of the brake pump group in real time, and the working condition sensor group collects the inclination angle of 34.8°, the load of 24.7t and the speed of 1.2m / s.

[0067] The main controller, through a fusion algorithm, calculates that due to an inclination angle ≥30° and a load ≥20t, the safety threshold for the brake pump unit is lowered to 80℃. A level one warning is triggered when the current temperature exceeds the preset value. The audible and visual alarm flashes a yellow light every 2 seconds and sounds a buzzer, while the brake pump unit temperature parameter is highlighted on the display panel. Simultaneously, the data is synchronized to the ground control center. Upon receiving the warning, the control center reduces the operating speed to 0.8m / s. After 1 minute, the brake pump unit temperature drops below the threshold, the warning is automatically deactivated, and the device resumes normal monitoring.

[0068] In this embodiment, the device successfully achieved temperature anomaly warning under high tilt angle and high load conditions, with a response time of ≤2s and no data interruption or false alarms, verifying its reliability and practicality.

[0069] The working principle and usage process of this invention are as follows: When the monorail is in operation, the temperature sensor group continuously and in real time collects key data such as the surface temperature of the diesel engine, exhaust temperature, and brake pump group temperature. Simultaneously, the operating condition sensor group collects operating condition information such as the tunnel inclination angle, load weight, and operating speed. After receiving this collected data, the main controller performs comprehensive calculation and analysis using a fusion algorithm. Once an operating condition with an inclination angle greater than or equal to 30° and a load greater than or equal to 20t is detected, the main controller automatically lowers the safety threshold of the brake pump group. If the current brake pump group temperature is found to be greater than this preset value during monitoring, a first-level early warning mechanism will be immediately triggered. At this time, the audible and visual alarm will start working, with a yellow light flashing at 2-second intervals and a buzzer sounding simultaneously. The brake pump group temperature parameter will be highlighted on the display panel so that operators can quickly obtain key information. At the same time, the system will synchronously transmit relevant data to the ground control center. Upon receiving the early warning information, the ground control center will promptly take measures to reduce the monorail's operating speed to 0.8m / s. After 1 minute of operation and adjustment, if the temperature of the brake pump group drops below the threshold, the warning will be automatically lifted, and the device will then resume normal monitoring and continue to monitor various temperature data during the operation of the monorail in real time.

[0070] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A temperature monitoring device for a monorail crane used at a large angle of inclination, characterized in that, include: The multi-dimensional sensing module is installed at the key heat-generating components of the monorail and the surrounding environment, including a temperature sensor group, an environmental sensor group, and a working condition sensor group. The data processing and decision-making module is fixedly installed inside the monorail crane's electrical control box and uses an embedded industrial computer to run a multi-parameter fusion monitoring model. The early warning execution module is connected to the data processing and decision-making module and executes tiered early warnings. The power supply module, connected to the multi-dimensional sensing module, data processing and decision-making module and early warning execution module, provides a stable power supply; The remote interaction module connects to the data processing and decision-making module to enable remote data transmission and command interaction; The self-diagnosis and historical analysis module is integrated into the data processing and decision-making module, supporting self-checking, fault tracing, and predictive maintenance.

2. The temperature monitoring device for a monorail crane with a large inclination angle according to claim 1, characterized in that, The temperature sensor group includes: Explosion-proof K-type thermocouples are installed on the diesel engine cylinder block and exhaust manifold, with a measurement range of 0 to 400℃ and an accuracy of ±1℃. The intrinsically safe PT100 sensor is installed on the main pump assembly and brake pump assembly, with a measurement range of -50 to 200℃ and an accuracy of ±0.5℃. Waterproof NTC thermistors are installed in the cooling water tank and bearing housing, with a response time of ≤1s and a waterproof rating of IP68.

3. The temperature monitoring device for a monorail crane with a large inclination angle according to claim 1, characterized in that, The data processing and decision-making module uses an ARM Cortex-A9 processor to preprocess the data through moving average filtering and Kalman filtering, evaluates the thermal state of the equipment based on a neural network algorithm, and dynamically adjusts the temperature threshold according to the tilt angle and load changes.

4. The temperature monitoring device for a monorail crane with a large inclination angle according to claim 1, characterized in that, The environmental sensor group includes: Temperature and humidity sensor, installed 0.5 to 1m away from the heat-generating component, with a measurement range of -40℃ to 85℃ and 0% to 100%RH, and an accuracy of ±0.3℃ / ±2%RH; The dust concentration sensor (GP2Y1010AU0F) has its sampling port facing the surrounding environment and a detection range of 0-500 μg / m³.

5. A temperature monitoring device for a monorail crane with a large inclination angle according to claim 3, characterized in that, The data processing and decision-making module is specifically used for: It receives and integrates temperature data of key heat-generating components collected by the temperature sensor group, environmental data collected by the environmental sensor group, and tilt angle, load, and speed data collected by the operating condition sensor group; Based on the multi-parameter fusion monitoring model, the current thermal status of the equipment is comprehensively evaluated, and graded early warning instructions are generated according to the evaluation results.

6. The temperature monitoring device for a monorail crane with a large inclination angle according to claim 1, characterized in that, The operating condition sensor group includes: A three-axis tilt sensor is installed on the monorail crane's running mechanism, with a measurement range of ±90° and an accuracy of ±0.1°. The load weight sensor is integrated into the hook or wire rope fixing point, with a range of 0 to 10 tons and an accuracy of ±0.5%FS. The operating speed sensor is mounted on the drive wheel axle and has a resolution of 0.1 m / s.

7. A temperature monitoring device for a monorail crane with a large inclination angle according to claim 3, characterized in that, The specific functions of the ARM Cortex-A9 processor include: Data fusion and preprocessing: The original data is smoothed and outliers are removed by moving average filtering, and the tilt angle and velocity data are corrected in real time by Kalman filtering algorithm; Thermal state assessment model: Based on neural network algorithm, the input layer contains 12 nodes including temperature, humidity, dust, tilt angle, load and velocity, the hidden layer has 3 layers with 32 nodes each, and the output layer is a thermal state score of 0-100 points; Dynamic adaptation to operating conditions: When the tilt angle is ≥15°, the threshold values ​​of diesel engine surface temperature, brake pump group temperature, etc. are automatically lowered. For every ton increase in load, the corresponding component temperature threshold is lowered by 0.5%.

8. A temperature monitoring device for a monorail crane with a large inclination angle according to claim 1, characterized in that, The early warning execution module includes: Local early warning unit: intrinsically safe audible and visual alarm for mining, OLED display panel, installed on the instrument panel in the monitoring room; Emergency intervention unit: connected to the electronic control valve of the monorail braking system, triggering emergency braking and cutting off power supply to the power system when a level 2 warning is issued; The power supply module adopts an intrinsically safe dual-redundancy design, including an explosion-proof switching power supply and a backup lithium battery pack.

9. A temperature monitoring device for a monorail crane with a large inclination angle according to claim 1, characterized in that, The remote interaction module connects to the coal mine ring network through an intrinsically safe wireless base station for mining. Its functions include uploading thermal status scores, early warning instructions, and equipment operation data to the ground control center in real time, and receiving parameter configuration, threshold adjustment, and data query instructions from the remote control center.

10. A temperature monitoring device for a monorail crane with a large inclination angle according to claim 1, characterized in that, The self-diagnosis and historical analysis module includes the following functions: Self-diagnostic function: Periodically performs self-checks on the hardware and communication status of the multi-dimensional sensing module, early warning execution module, and power supply module. When an anomaly occurs, it generates diagnostic information containing the anomaly type and location and provides a prompt through the early warning execution module. Historical analysis function: Long-term storage of raw data collected by multi-dimensional sensing modules, early warning event records generated by data processing and decision-making modules, and equipment operation status data, supporting trend analysis, fault tracing, and predictive maintenance analysis.

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