CN114877935A - Multi-source sensor integrated monitoring method and device and inspection robot - Google Patents

Abstract

The invention relates to the technical field of transportation equipment, in particular to an integrated monitoring method and device for a multi-source sensor and an inspection robot. The method is based on the real-time monitoring of the running state and the acquisition of signal data by a multi-source sensor installed at each monitoring point on a transport vehicle; and transmitting and storing the fault characteristic parameters to a control management system in real time, analyzing the fault characteristic parameters, if the fault characteristic parameters exceed a preset normal range, sending an alarm by the control management system, stopping the operation of the transport vehicle inspection platform, marking fault coordinate position information, and performing online fault positioning and fault diagnosis on the transport vehicle. Through detection and information fusion, the autonomous environment perception capability of the vehicle is enhanced, the running safety is improved, real-time monitoring of the running state of the main transportation system is realized, fault hidden danger is diagnosed, early warning is timely performed, unattended detection and fault diagnosis of the state of the conveying belt can be realized through intelligent modification, and the purpose of saving labor cost is achieved.

Description

A multi-source sensor integrated monitoring method, device and inspection robot

technical field

The invention relates to the technical field of transportation equipment, in particular to a multi-source sensor integrated monitoring method, device and inspection robot.

Background technique

Mining electric locomotives are mainly used for long-distance transportation of underground transportation alleys and ground. At present, in order to strengthen the vehicle's autonomous environment perception ability and improve driving safety, the intelligent transformation of underground electric locomotives is gradually carried out. At present, most of the inspection work is done manually. The whole inspection process mainly relies on the inspection staff with years of work experience to complete the maintenance work through basic methods such as beating, inspection, and listening. However, during the whole transportation process, there is a lack of fault location, diagnosis and condition monitoring of the key components of the main transportation system, and it is impossible to implement lightweight, intelligent, and highly reliable autonomous inspections for the main transportation system.

SUMMARY OF THE INVENTION

In order to solve the problems of fault location, diagnosis and state monitoring of the key components of the current main transportation system, the present invention provides a multi-source sensor integrated monitoring method, device and inspection robot, which can realize unattended operation by implementing intelligent transformation. Conveyor belt status detection, fault diagnosis, to achieve the purpose of saving labor costs.

To achieve the above purpose, the embodiments of the present invention provide the following technical solutions:

In a first aspect, in an embodiment provided by the present invention, a multi-source sensor integrated monitoring method is provided, comprising the following steps:

Based on the multi-source sensors installed at each monitoring point on the transport vehicle, the running status is monitored in real time and the signal data is collected;

Preprocessing the collected signal data, using the fault feature parameters used to identify the fault as the fault evidence body, and extracting the data features;

The fault characteristic parameters are transmitted and saved to the control management system in real time, and the fault characteristic parameters are analyzed. If the fault characteristic parameters exceed the preset normal range, the control management system will issue an alarm, the transportation vehicle inspection platform will stop running, and The fault coordinate position information is marked, and the online fault location and fault diagnosis are carried out for the transport vehicle.

As a further solution of the present invention, the multi-source sensors installed at each monitoring point on the transport vehicle are used for real-time monitoring of the monitoring data of the conveyor head and the belt portion, and the signal data collected by the multi-source sensors is in the form of message queues arrangement.

As a further solution of the present invention, the monitoring data is sent to an online monitoring platform through an industrial Ethernet or 5G network, and the online monitoring platform remotely synchronizes historical data, the monitoring data is subjected to feature extraction after data preprocessing, and after feature extraction, DS Decision fusion, the final decision is made based on the results obtained.

As a further solution of the present invention, the multi-source sensor monitors and collects signal data in real time, including material accumulation signal, noise detection signal, thermal imaging detection signal and drive motor temperature signal of the belt conveyor.

In a second aspect, in an embodiment provided by the present invention, a multi-source sensor integrated monitoring device is provided, including:

a data collection module, which is used for real-time monitoring of the running state and collection of signal data based on the multi-source sensors installed at each monitoring point on the transport vehicle;

a data control module, the data control module is used for preprocessing the collected signal data, using the fault feature parameter used to identify the fault as the fault evidence body, and extracting the data feature;

An early warning control module, which is used to transmit and save the fault characteristic parameters to the control management system in real time, and analyze the fault characteristic parameters. If the fault characteristic parameters exceed the preset normal range, the control management system sends out Alarm, the transportation vehicle inspection platform stops running, and marks the fault coordinate position information, and conducts online fault location and fault diagnosis for the transportation vehicle.

As a further solution of the present invention, the multi-source sensor is a perception sensor installed on a transportation vehicle for environmental perception, and the perception sensor includes a camera, a millimeter-wave radar, and a lidar sensor for real-time identification of vehicle transportation road conditions.

As a further solution of the present invention, the transportation vehicle is an underground electric locomotive, and the monitoring data of the head and the belt part of the underground electric locomotive are monitored in real time, and the monitoring data is sent to the online through the industrial Ethernet or 5G network. monitoring platform.

As a further solution of the present invention, the multi-source sensor installed at the monitoring point of the nose further includes a thermal imager, and the thermal imager is used for coal stack temperature detection, conveyor belt deviation detection, conveyor belt electrical and power equipment Accident hidden danger, intrusion detection; used to monitor the fire hidden danger in the equipment, and alarm when the temperature of each target object exceeds the set temperature; used to confirm that an abnormal situation occurs to the staff, and immediately alarm.

As a further solution of the present invention, the multi-source sensor installed at the monitoring point of the nose further includes:

The smoke detection sensor is used to detect whether the belt of the belt conveyor in the coal mine produces smoke or not, and generate a smoke detection signal;

The infrared temperature sensor is used to measure the temperature of the measured target in the sensor's field of view.

As a further solution of the present invention, the temperature detection of the coal heap is based on image detection and detection by using a coal heap sensor to generate a material accumulation signal, and extract the accumulation characteristic parameters in the material accumulation signal.

In a third aspect, in an embodiment provided by the present invention, an inspection robot is provided, the inspection robot includes a multi-source sensor integrated monitoring device, and the inspection robot further includes:

The machine head inspection platform, the machine head inspection platform is installed above the conveyor belt head, the machine head inspection platform is inspected along the circular guide rail installed above the conveyor belt head, and the machine head inspection platform is installed on the conveyor belt. An explosion-proof spherical camera is installed on the telescopic rod, which is used to adjust the length of the telescopic rod, adjust the field of view of the spherical camera, and obtain the collected signal data of the nose and the transmission system in real time;

A belt inspection platform, the belt inspection platform independently walks along the track of the belt and the idler, a proximity switch is installed on the belt inspection platform, and a proximity switch sensing hole is installed on the track, and the belt inspection platform It is used to automatically calculate the position for positioning according to the number of proximity switch sensing holes sensed by the proximity switch. The detection layer of the belt inspection platform is equipped with a thermal imager and a sensor of a noise detection device, which detects the signal data of the idler in real time and corrects the movement. Real-time monitoring of conveyor belt faults.

In a fourth aspect, in yet another embodiment provided by the present invention, a computer device is provided, including a memory and a processor, the memory stores a computer program, and the processor loads and executes the computer program to implement multiple Steps of a source sensor integrated monitoring method.

In a fifth aspect, in yet another embodiment provided by the present invention, a storage medium is provided, storing a computer program, and when the computer program is loaded and executed by a processor, the steps of the multi-source sensor integrated monitoring method are implemented .

The technical scheme provided by the invention has the following beneficial effects:

The multi-source sensor integrated monitoring method, device and inspection robot provided by the present invention can replace the traditional manual inspection and remote monitoring of safety prevention inspection tasks, and use a high-definition camera to confirm the operation status of the target (conveyor belt)/when abnormal conditions occur (eg : deviation, slip) immediately alarm; use ultrasonic sensors to accurately locate when abnormal conditions occur on the conveyor belt (coal clipping/conveyor belt tear, bulge, wear); use thermal imaging cameras to monitor fire hazards in the equipment, each target When the temperature of the object exceeds the set temperature, it will give an alarm or when it is confirmed that the staff has an abnormal situation, the alarm will be issued immediately; use the environmental sensor to monitor various environmental information (including gas, smoke, etc.) in real time, and operate autonomously; use each inspection directory to accumulate data management And daily inspection reports are provided to achieve the level of intelligent data management; signal data is collected through multi-source sensors, and through the performance of lightweight, intelligent and high reliability, inspection and information fusion are carried out through the inspection robot system to strengthen The vehicle's autonomous environmental perception capability improves driving safety, so as to realize real-time monitoring of the operating status of the main transportation system, diagnose hidden faults, and give early warnings.

These and other aspects of the invention will be more clearly understood from the description of the following embodiments. It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention.

Description of drawings

In order to illustrate the technical solutions in the embodiments of the present invention more clearly, the following briefly introduces the accompanying drawings that need to be used in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only for the present invention. some examples. In the attached image:

FIG. 1 is a flowchart of a multi-source sensor integrated monitoring method according to an embodiment of the present invention.

FIG. 2 is a flowchart of scheduling control in a multi-source sensor integrated monitoring method according to an embodiment of the present invention.

3 is a structural diagram of a beam-mounted autonomous inspection robot in a multi-source sensor integrated monitoring device according to an embodiment of the present invention.

FIG. 4 is a schematic structural diagram of stacking detection in a multi-source sensor integrated monitoring device according to an embodiment of the present invention.

FIG. 5 is a flowchart of a monitoring and inspection platform in a multi-source sensor integrated monitoring device according to an embodiment of the present invention.

FIG. 6 is a schematic diagram of a coal pile detection and alarm based on image processing in a multi-source sensor integrated monitoring device according to an embodiment of the present invention.

FIG. 7 is a flowchart of a fault decision in a multi-source sensor integrated monitoring device according to an embodiment of the present invention.

Detailed ways

In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention, but not to limit the present invention.

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

At present, in the whole transportation process of long-distance transportation between underground transportation alleys and ground, there is a lack of fault location, diagnosis and condition monitoring of key components of the main transportation system, and it is impossible to implement lightweight, intelligent, High reliability autonomous inspection.

In view of the above problems, the multi-source sensor integrated monitoring method, device and inspection robot provided by the present invention can realize unattended conveyor belt status detection and fault diagnosis by implementing intelligent transformation, and achieve the purpose of saving labor costs.

Specifically, the embodiments of the present application are further described below with reference to the accompanying drawings.

Referring to FIG. 1 , an embodiment of the present invention provides an integrated monitoring method for multi-source sensors. The integrated monitoring method for multi-source sensors specifically includes the following steps:

S1. Real-time monitoring of the running state and collection of signal data based on multi-source sensors installed at each monitoring point on the transport vehicle;

S2, preprocessing the collected signal data, using the fault feature parameters used to identify the fault as the fault evidence body, and extracting the data features;

S3. Real-time transmission and storage of the fault characteristic parameters to the control management system, and analysis of the fault characteristic parameters. If the fault characteristic parameters exceed the preset normal range, the control management system issues an alarm, and the transportation vehicle inspection platform stops running , and mark the fault coordinate position information, and carry out online fault location and fault diagnosis for the transport vehicle.

In this embodiment, intelligent algorithms are used to achieve engineering requirements such as fault location, diagnosis, and condition monitoring of key components of the main transportation system, and a lightweight, intelligent, and highly reliable inspection robot system is developed. The integrated detection structure and information fusion method realize the acquisition of signal data through multi-source sensors, and through the performance of light weight, intelligence and high reliability, it can replace the traditional manual inspection and remote monitoring of safety prevention inspection tasks. Integrate, strengthen the vehicle's autonomous environment perception ability and improve driving safety, so as to realize real-time monitoring of the operation status of the main transportation system, diagnose hidden faults, and give early warning in time.

In the embodiment of the present application, the multi-source sensors installed at each monitoring point on the transport vehicle are used to monitor the monitoring data of the head part 1 and the belt part of the conveyor belt in real time, and the signal data collected by the multi-source sensors are queued in messages. arranged in the form of.

Referring to FIG. 7 , in the embodiment of the present application, the monitoring data is sent to an online monitoring platform through an industrial Ethernet or 5G network, and the online monitoring platform remotely synchronizes historical data, and the monitoring data is characterized after data preprocessing. Extraction. After feature extraction, DS decision fusion is performed, and the final decision is made according to the obtained results.

In the embodiment of the present application, the multi-source sensor monitors and collects signal data in real time, including material accumulation signal, noise detection signal, thermal imaging detection signal and driving motor temperature signal of the belt conveyor, wherein the driving motor temperature signal passes through the motor temperature The monitoring device 11 collects and collects the signal data on each monitoring point of the belt conveyor in real time through the thermal imaging sensor, noise sensor and limit sensor for common faults such as slippage, noise and accumulation in the operation of the mining belt conveyor, and A series of signal analysis and processing technologies such as filtering and denoising are performed on the collected signals to realize data preprocessing, and the fault characteristic parameters that can identify the fault are selected as the evidence subject in the identification framework, and the basic probability distribution of each fault evidence body is obtained. , realize data feature extraction, and finally make the final decision by the result obtained by the improved D-S information fusion technology.

Among them, the information fusion control algorithm D-S evidence theory is to judge the cause of the event according to the result of the event. First of all, it is necessary to make a series of assumptions about the cause of the event to form an identification framework, and make each assumed cause have an independent basic probability distribution, and then fuse these probability distributions by fusion rules, and obtain the fusion result for probability analysis. Thus, the one with the highest probability is the main reason for the occurrence of the event. By establishing the relationship between propositions and sets, the problem of trust in propositions is transformed into a problem of set probability. As a reasoning algorithm for dealing with uncertain information, D-S evidence theory can organically combine different levels of information collected by multiple sensors through fusion rules, which improves the accuracy of diagnosis and decision-making to a certain extent.

The multi-source sensor integrated monitoring method of the present invention collects signal data through the multi-source sensors, and through the performance of light weight, intelligence and high reliability, performs detection and information fusion through the inspection robot system, and strengthens the vehicle's autonomous environment perception The ability to improve driving safety, so as to realize real-time monitoring of the operating status of the main transportation system, diagnosis of hidden faults, and timely early warning.

Referring to FIG. 1, an embodiment of the present invention provides a multi-source sensor integrated monitoring device, the multi-source sensor integrated monitoring device includes:

a data collection module, which is used for real-time monitoring of the running state and collection of signal data based on the multi-source sensors installed at each monitoring point on the transport vehicle;

a data control module, the data control module is used for preprocessing the collected signal data, using the fault feature parameter used to identify the fault as the fault evidence body, and extracting the data feature;

An early warning control module, which is used to transmit and save the fault characteristic parameters to the control management system in real time, and analyze the fault characteristic parameters. If the fault characteristic parameters exceed the preset normal range, the control management system sends out Alarm, the transportation vehicle inspection platform stops running, and marks the fault coordinate position information, and conducts online fault location and fault diagnosis for the transportation vehicle.

In the embodiment of the present application, the multi-source sensor is a perception sensor installed on a transportation vehicle for environmental perception, and the perception sensor includes a camera, a millimeter-wave radar, and a lidar sensor for real-time identification of vehicle transportation road conditions.

In the embodiment of the present application, the transport vehicle is an underground electric locomotive, and the monitoring data of the head part 1 and the belt part of the underground electric locomotive are monitored in real time, and the monitoring data is sent through an industrial Ethernet or 5G network to the online monitoring platform.

In the multi-source sensor integrated monitoring device of the embodiment of the present application, the monitoring data of the head part 1 and the belt part of the main transmission system will be aggregated to the online monitoring platform of the main transmission system through the industrial Ethernet or 5G network, so as to realize multiple Real-time monitoring of the running status of the belts, diagnosis of hidden troubles, and timely early warning.

In the embodiment of the present application, the multi-source sensor installed at the monitoring point on the first part of the machine head further includes a thermal imager 36, and the thermal imager 36 is used for coal stack temperature detection, conveyor belt deviation detection, conveyor belt deviation detection, etc. Electrical and power equipment accident hidden danger, intrusion detection; used to monitor the fire hidden danger in the equipment, alarm when the temperature of each target object exceeds the set temperature; used to confirm the abnormal situation of the staff, and immediately alarm.

In the embodiment of the present application, the multi-source sensor installed at the monitoring point of the first part of the machine head further includes:

The smoke detection sensor is used to detect whether the belt of the belt conveyor in the coal mine produces smoke, and generate a smoke detection signal; among them, whether the smoke detection refers to the smoke generated by the belt of the belt conveyor in the coal mine due to friction heating or other reasons. Can use explosion-proof type smoke sensor, voltage DC: 12--24V.

The infrared temperature sensor is used to measure the temperature of the measured target in the sensor's field of view; among them, for the infrared temperature sensor, when the temperature is measured, the area of the measured target should fill the sensor's field of view. According to the size of the measured area, choose to install the sensor at a distance of 15cm from the motor.

In the embodiment of the present application, when the multi-source sensor integrated monitoring device is applied to coal pile detection, since the coal pile is very harmful to the belt transportation system, the belt will deviate when the coal is piled up for many times, and the belt surface will wear out. Serious problems, which greatly reduce the service life of the belt and affect the stability of the belt transportation system. If the coal pile failure is not solved in time, the equipment will be shut down and the production will be affected. 1 and other equipment accidents, and even cause casualties. Detection schemes include image-based detection and detection using piled coal sensors.

Therefore, the temperature detection of the coal heap is based on image detection and detection by using a coal heap sensor to generate a material accumulation signal, and extract the accumulation characteristic parameters in the material accumulation signal.

In the embodiment of the present application, when the multi-source sensor integrated monitoring device is applied to the roller temperature and noise monitoring and inspection platform, the overall structure of the roller temperature and noise monitoring and inspection platform is shown in FIG. 5 , including the rope drive mechanism 32 , rope tensioning mechanism 32, electrical installation box 33, thermal imager 36, noise detector 35, warning light 34 and other devices, wherein the thermal imager 36, noise detector 35, warning light 34 are fixed on the electrical installation box 33, The electrical installation box 33 is fixed on the rope, and the motor at one end drives the rope to move, and drives the inspection platform to move, so as to realize the inspection of the idler state.

Referring to FIG. 2 , in the process of applying the multi-source sensor integrated monitoring device of the present application to the mining electric locomotive for the entire inspection process of the long-distance transportation of the underground transportation alley and the ground, through the multi-source sensor in the data collection module For material accumulation fault detection, driven wheel stuck fault thermal imaging detection, driven wheel rotation abnormal noise detection and belt drive wheel abnormal detection, the detected signal data is fused through multi-information fusion rules and then aggregated to the roadway centralized control platform. Through the underground industrial Ethernet or 5G network, it is transmitted to the centralized control platform of the dispatching room on the well, using a unified management platform, comprehensively using infrared thermal imaging technology, audio-based fault location technology, and multi-parameter sensing technology to realize the reliability of conveyor belts. promote.

Referring to FIG. 3 and FIG. 4 , an embodiment of the present invention provides an inspection robot, the inspection robot includes a multi-source sensor integrated monitoring device, and the inspection robot further includes:

The machine head inspection platform 21, the machine head inspection platform 21 is installed above the conveyor belt head 1, and the machine head inspection platform 21 is inspected along the circular guide rail installed above the conveyor belt head 1. An explosion-proof spherical camera 22 is installed on the head inspection platform 21 through a telescopic rod, and an explosion-proof charging station 10 is also provided on the head 1, which is used to adjust the length of the telescopic rod, adjust the field of view of the spherical camera, and obtain the head in real time. 1 and the acquisition signal data of the transmission system;

A belt inspection platform 13, the belt inspection platform 13 autonomously walks along the track of the belt and the idler, a proximity switch is installed on the belt inspection platform 13, and a proximity switch sensing hole is installed on the track, and the belt inspection platform 13 is installed with a proximity switch. The inspection platform 13 is used to automatically calculate the position for positioning according to the number of proximity switch sensing holes sensed by the proximity switch. Roller signal data, real-time monitoring of mobile conveyor belt faults.

When the inspection robot performs online fault location and fault diagnosis on the main motor and transmission system of the head 1, a circular guide rail is installed above the head 1 and the transmission system, and the head inspection platform 21 is inspected on the circular guide rail. , through the explosion-proof spherical camera 22 installed on the machine head inspection platform 21 by the telescopic rod, adjust the length of the telescopic rod, the spherical camera can see the various positions of the machine head 1, and obtain the temperature, noise, noise, etc. Smoke density and other information, and transmit and save these parameters to the control system in real time. If any parameter information exceeds the preset normal range, the system will issue an alarm, the nose inspection platform 21 will stop running, and the fault coordinate position information will be marked. Realize the online fault location and fault diagnosis of the main motor and transmission system of the head 1.

When the inspection robot detects and monitors the status of the belt, idler and coal pile in the belt transportation, the inspection of the belt and the idler is completed by the inspection platform, and the inspection platform walks along the track autonomously. Proximity switches are installed on the platform, and there are proximity switch sensing holes on the track. The inspection platform automatically calculates the position to achieve positioning according to the number of holes sensed by the proximity switch. Thermal imaging cameras 36 and noise detection devices are installed on the detection layer of the inspection platform. The sensor detects information such as roller damage, belt breakage, tearing, deviation, slippage, fire, etc., and realizes the comprehensive use of thermal infrared imaging technology, audio fault location technology, and multi-sensor data fusion technology to realize real-time monitoring of mobile conveyor belt faults. .

Referring to Fig. 6, the detection of coal pile state is completed by the coal pile detection sensor 12. The coal pile detection sensor 12 is installed at the joint of the parallel belt and the inclined belt, which can detect the height of the coal at this position in real time, and transmit and save the detection data in real time. To the control system, if the altitude information exceeds the preset normal range, the system will issue an alarm and the conveyor belt will stop working.

In the embodiment of the present application, the inspection robot is applied to the main transportation system hoisting autonomous inspection robot, so that the multi-sensor information such as "smell-sight-hearing" can be used when the research on the beam-hoisting autonomous inspection robot system is carried out. Intelligent algorithms are used to meet engineering requirements such as fault location, diagnosis and condition monitoring of key components of the main transportation system, and a lightweight, intelligent and highly reliable inspection robot system is developed.

Among them, the head inspection platform 21 is located in the core area of the conveyor head 1 for monitoring, and the hoisting circular rail inspection platform is used to perform online fault location and fault diagnosis for the main motor and transmission system of the head 1. The belt inspection platform 13 is used to monitor the long-distance belt transportation area. The long-rail inspection platform is used to detect and monitor the status of the belt, idler and coal pile in the belt transportation.

In the embodiment of the present application, the intelligent inspection robot can replace the traditional manual inspection to remotely monitor the safety prevention inspection task. The following inspection and monitoring operations can be implemented:

Use the high-definition camera to confirm the running status of the target (conveyor belt) / when an abnormal situation occurs (for example: deviation, slippage), it will immediately alarm;

Use ultrasonic sensors to accurately position the conveyor belt when abnormal conditions occur (coal clipping/conveyor belt tearing, bulging, abrasion);

Use a thermal imager to monitor fire hazards in the equipment, alarm when the temperature of each target object exceeds the set temperature, or when an abnormality is confirmed to the staff;

Use environmental sensors to monitor various environmental information (including gas, smoke, etc.) in real time and operate autonomously;

Use each inspection catalog to accumulate data management and provide daily inspection reports to achieve the level of intelligent data management.

When the inspection robot is used as a coal mine inspection robot, it is equipped with a variety of sensors to collect real-time production environment data such as image, sound, infrared thermal image temperature, smoke, and various gas concentrations. Using intelligent sensing key technology algorithm, it can accurately judge the operation status of the equipment, predict and give early warning to the operation failure of coal mine equipment, and reduce the downtime of failure.

Among them, the thermal imager 36 detected by the conveyor head part 1 can also be used for coal pile temperature detection, conveyor belt deviation detection, conveyor belt electrical and power equipment accident hidden dangers, personnel intrusion detection and other aspects. Realize coal pile temperature detection, conveyor belt deviation detection and cable temperature detection.

In the embodiment of the present application, the multi-source sensor installed at the monitoring point of the first part of the machine head further includes:

The smoke detection sensor is used to detect whether the belt of the belt conveyor in the coal mine produces smoke, and generate a smoke detection signal; among them, whether the smoke detection refers to the smoke generated by the belt of the belt conveyor in the coal mine due to friction heating or other reasons. Can use explosion-proof type smoke sensor, voltage DC: 12--24V.

The infrared temperature sensor is used to measure the temperature of the measured target in the sensor's field of view; among them, for the infrared temperature sensor, when the temperature is measured, the area of the measured target should fill the sensor's field of view. According to the size of the measured area, choose to install the sensor at a distance of 15cm from the motor.

It should be noted that the inspection robot adopts the steps of the above-mentioned integrated monitoring method of multi-source sensors. Therefore, the operation process of the inspection robot in this embodiment will not be described in detail.

In one embodiment, an embodiment of the present invention also provides a computer device, comprising at least one processor, and a memory communicatively connected to the at least one processor, the memory storing data that can be used by the at least one processor. An instruction executed by a processor, the instruction is executed by the at least one processor, so that the at least one processor executes the multi-source sensor integrated monitoring method, and the processor executes the instruction to implement the above methods. steps in the example.

In an embodiment of the present invention, a computer device is provided, the computer device comprising a memory and a processor having a computer program stored in the memory, the processor being configured to execute the computer program stored in the memory. The memory is used to store one or more computer instructions, wherein the one or more computer instructions are executed by the processor to implement the steps in the above method embodiments:

Based on the multi-source sensors installed at each monitoring point on the transport vehicle, the running status is monitored in real time and the signal data is collected;

Preprocessing the collected signal data, using the fault feature parameters used to identify the fault as the fault evidence body, and extracting the data features;

The fault characteristic parameters are transmitted and saved to the control management system in real time, and the fault characteristic parameters are analyzed. If the fault characteristic parameters exceed the preset normal range, the control management system will issue an alarm, the transportation vehicle inspection platform will stop running, and The fault coordinate position information is marked, and the online fault location and fault diagnosis are carried out for the transport vehicle.

An embodiment of the present invention also provides a storage medium on which a computer program is stored, and when the computer program is executed by a processor, implements the steps in the foregoing method embodiments:

Based on the multi-source sensors installed at each monitoring point on the transport vehicle, the running status is monitored in real time and the signal data is collected;

Preprocessing the collected signal data, using the fault feature parameters used to identify the fault as the fault evidence body, and extracting the data features;

The fault characteristic parameters are transmitted and saved to the control management system in real time, and the fault characteristic parameters are analyzed. If the fault characteristic parameters exceed the preset normal range, the control management system will issue an alarm, the transportation vehicle inspection platform will stop running, and The fault coordinate position information is marked, and the online fault location and fault diagnosis are carried out for the transport vehicle.

Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be implemented by instructing relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage In the medium, when the computer program is executed, it may include the processes of the above-mentioned method embodiments. Wherein, any reference to memory, storage, database or other media used in the various embodiments provided in this application may include at least one of non-volatile and volatile memory.

To sum up, the multi-source sensor integrated monitoring method, device and inspection robot provided by the present invention can replace traditional manual inspection and remote monitoring and safety prevention inspection tasks. , intelligent and high reliability performance, through the inspection robot system for detection and information fusion, strengthen the vehicle's autonomous environment perception ability and improve driving safety, so as to realize the real-time monitoring of the operating status of the main transportation system, diagnose hidden faults, and give timely warnings.

The above descriptions are only preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements and improvements made within the spirit and principles of the present invention shall be included in the protection of the present invention. within the range.

Claims (10)

1. The integrated monitoring method of the multisource sensor is characterized by comprising the following steps:

monitoring the running state in real time and acquiring signal data based on multi-source sensors installed at monitoring points on a transport vehicle;

preprocessing the acquired signal data, taking fault characteristic parameters for identifying faults as fault evidence bodies, and extracting data characteristics;

and transmitting and storing the fault characteristic parameters to a control management system in real time, analyzing the fault characteristic parameters, if the fault characteristic parameters exceed a preset normal range, sending an alarm by the control management system, stopping the operation of the transport vehicle inspection platform, marking fault coordinate position information, and performing online fault positioning and fault diagnosis on the transport vehicle.

2. The integrated monitoring method of the multisource sensor as claimed in claim 1, wherein the multisource sensors mounted at the monitoring points on the transport vehicle are used for monitoring the monitoring data of the head part and the belt part of the conveyor in real time, and the signal data collected by the multisource sensors are arranged in the form of a message queue.

3. The integrated multi-source sensor monitoring method according to claim 2, wherein the monitoring data is sent to an online monitoring platform through an industrial Ethernet or a 5G network, the online monitoring platform synchronizes historical data remotely, the monitoring data is subjected to feature extraction after data preprocessing, a DS decision fusion is performed after feature extraction, and a final decision is made according to an obtained result.

4. The integrated monitoring method for the multisource sensor according to claim 3, wherein the multisource sensor monitors and collects signal data in real time, and comprises a material accumulation signal, a noise detection signal, a thermal imaging detection signal and a driving motor temperature signal of a belt conveyor.

5. A multisource sensor integrated monitoring device is characterized in that the multisource sensor integrated monitoring device adopts the multisource sensor integrated monitoring method of any one of claims 1 to 4 to monitor the running state of a transport vehicle in real time; the integrated monitoring system of the multisource sensor comprises:

the data collection module is used for monitoring the running state in real time and collecting signal data based on multi-source sensors arranged at each monitoring point on the transport vehicle;

the data control module is used for preprocessing the acquired signal data, taking fault characteristic parameters for identifying faults as fault evidence bodies and extracting data characteristics;

and the early warning control module is used for transmitting and storing the fault characteristic parameters to the control management system in real time and analyzing the fault characteristic parameters, if the fault characteristic parameters exceed a preset normal range, the control management system gives an alarm, the transport vehicle inspection platform stops running, fault coordinate position information is marked, and online fault positioning and fault diagnosis are carried out on the transport vehicle.

6. The integrated monitoring device of claim 5, wherein the multi-source sensor is a sensor installed on a transportation vehicle for sensing the environment, and the sensor comprises a camera, a millimeter wave radar and a laser radar sensor for real-time determination of the transportation road condition of the vehicle.

7. The integrated multisource sensor monitoring device according to claim 6, wherein the transportation vehicle is a downhole rail electric locomotive, monitoring data of a nose part and a belt part of the downhole rail electric locomotive are monitored in real time, and the monitoring data are transmitted to an online monitoring platform through an industrial Ethernet or a 5G network.

8. The integrated monitoring device of the multisource sensor and the sensor as claimed in claim 7, wherein the multisource sensor installed at the monitoring point of the nose further comprises a thermal imager, and the thermal imager is used for coal piling temperature detection, conveying belt deviation detection, conveying belt electrical and power equipment accident potential and intrusion detection; the device is used for monitoring fire hazard in the equipment, and alarming when the temperature of each target object exceeds a set temperature; the alarm is used for immediately alarming when the abnormal condition of the staff is confirmed.

9. The integrated multisource sensor monitoring device of claim 8, wherein the nose unit monitoring point mounted multisource sensor further comprises:

the smoke detection sensor is used for detecting whether the belt of the belt conveyor under the coal mine generates smoke or not and generating a smoke detection signal;

and the infrared temperature sensor is used for measuring the temperature of the measured target in the sensor field of view.

10. An inspection robot, characterized in that the inspection robot comprises a multisource sensor integrated monitoring device according to any one of claims 1-7; patrol and examine robot still includes:

the system comprises a conveyor head inspection platform, a circular guide rail, an explosion-proof spherical camera, a transmission system and a control system, wherein the conveyor head inspection platform is arranged above a conveyor head, and is used for inspecting along the circular guide rail arranged above the conveyor head;

the platform is patrolled and examined to the belt, the belt is patrolled and examined the track of platform edge belt and bearing roller and is independently walked, the belt is patrolled and examined and is installed proximity switch on the platform, install proximity switch response hole on the track, the belt is patrolled and examined the platform and is used for sensing the quantity in proximity switch response hole according to proximity switch, and the automatic calculation position is fixed a position, thermal imager, noise detection device's sensor is installed on the detection layer that the platform was patrolled and examined to the belt, and real-time detection bearing roller signal data is to portable conveyer belt trouble real-time supervision.

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