CN112782577A - Multi-sense fusion coal mine large motor fault diagnosis system - Google Patents
Multi-sense fusion coal mine large motor fault diagnosis system Download PDFInfo
- Publication number
- CN112782577A CN112782577A CN202110109385.5A CN202110109385A CN112782577A CN 112782577 A CN112782577 A CN 112782577A CN 202110109385 A CN202110109385 A CN 202110109385A CN 112782577 A CN112782577 A CN 112782577A
- Authority
- CN
- China
- Prior art keywords
- source information
- microprocessor
- module
- coal mine
- sensor
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/34—Testing dynamo-electric machines
- G01R31/343—Testing dynamo-electric machines in operation
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D21/00—Measuring or testing not otherwise provided for
- G01D21/02—Measuring two or more variables by means not covered by a single other subclass
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Testing Of Devices, Machine Parts, Or Other Structures Thereof (AREA)
Abstract
The invention relates to a multi-sense fusion coal mine large motor fault diagnosis system which comprises a multi-source information monitoring node, a multi-source information aggregation node and an upper computer monitoring center. The multi-source information monitoring node comprises an acquisition unit and a processing unit, wherein the acquisition unit acquires multi-source information of a large motor during operation by using a sound sensor, a vibration sensor, a current transformer and the like, transmits the multi-source information to the processing unit through a serial port between microprocessors for analysis, processing and feature information extraction, and sends the feature information to the multi-source information aggregation node through an NB-IoT module; the multi-source information aggregation node sends the characteristic information to an upper computer monitoring center through a WiFi module; and the upper computer monitoring center displays the uploaded motor characteristic information. The system can diagnose the health condition of the coal mine large motor in real time, ensure the high-efficiency operation of the coal mine large motor, and realize the safety concept of unmanned and unmanned production of the coal mine.
Description
Technical Field
The invention relates to the technical field of application of the Internet of things and the technical field of motor monitoring, in particular to a multi-sense fusion coal mine large motor fault diagnosis system.
Background
With the continuous improvement of the mechanization and intellectualization level of coal mine production equipment, a coal mine large motor plays an increasingly important role in coal mine safety production, for example, a ventilator, a belt conveyor, a lifter and other large key equipment occupy an important position in the high-efficiency production of a coal mine, but the unplanned shutdown of the coal mine large equipment also brings potential safety hazards to the coal mine safety production. The core of the operation of various large-scale equipment in the coal mine is a large-scale motor, and the large-scale motor in the large-scale equipment meets the explosion-proof requirement due to the severe production environment of the coal mine, so that the fault diagnosis difficulty of the large-scale motor is increased to a certain extent.
At present, the fault diagnosis of the large motor in the coal mine mainly comprises the steps of collecting relevant information of the motor during working through a single vibration sensor or a current transformer, analyzing and processing the collected information, uploading the information to a data monitoring interface, and continuously checking data change by workers. The mode for detecting the fault of the large motor cannot obtain important information of other parameters when the motor works, is easy to cause mental fatigue of workers, and ignores important data; on the other hand, in order to avoid the safety accidents caused by the mistaken running of the personnel, the guardrails are arranged around the coal mine large-scale equipment, and the prompting effect cannot be achieved.
Therefore, a multi-sense fusion coal mine large motor fault diagnosis system is needed to solve the problems.
Disclosure of Invention
The invention aims to provide a multi-sensor fusion coal mine large motor fault diagnosis system, which utilizes a sound sensor, a vibration sensor, a current transformer, an infrared distance measurement sensor and a temperature sensor to collect multi-source information of a motor in real time during working, transmits the multi-source information to a processing unit in a serial port communication mode, obtains characteristic information after analysis and processing by the processing unit, transmits the obtained characteristic information to a multi-source information sink node through an NB-IoT (NB-IoT) module, and compresses and packages the characteristic information through a WiFi (wireless fidelity) module and sends the characteristic information to an upper computer monitoring center.
The invention adopts the following technical scheme for realizing the purpose:
a multi-sense fusion coal mine large motor fault diagnosis system is composed of multi-source information monitoring nodes, multi-source information aggregation nodes and an upper computer monitoring center. The multi-source information monitoring node comprises an acquisition unit and a processing unit, wherein the acquisition unit comprises: the system comprises a sound sensor, a vibration sensor, a current transformer, a temperature sensor, an infrared distance measuring sensor, a first microprocessor and a first power supply module; the processing unit includes: the second microprocessor, the first memory, the buzzer, the first NB-IoT module and the second power supply module; the multi-source information sink node comprises a third microprocessor, a third power supply module, a second NB-IoT module, a WiFi module and a second memory. Data transmission is completed between the acquisition unit and the processing unit in the multi-source information monitoring node in a serial port mode, the multi-source information monitoring node transmits the processed characteristic information to the multi-source information aggregation node through the NB-IoT module, the multi-source information aggregation node packs and compresses the received characteristic information data, the packed characteristic information data are sent to the upper computer monitoring center through the WiFi module, and the upper computer monitoring center displays the uploaded data.
The multi-source information monitoring node comprises an acquisition unit and a processing unit, wherein a microprocessor in the acquisition unit controls a sound sensor, a vibration sensor, a current transformer and a temperature sensor to acquire sound information, vibration information, current information and temperature information of the motor in real time when the motor works, meanwhile, a microprocessor in the acquisition unit controls an infrared distance measurement sensor to acquire information about whether people and distance between people and the motor exist around the motor in real time when the motor runs, corresponding pins of a sound sensor, a vibration sensor, a current transformer, a temperature sensor and the infrared distance measurement sensor are connected with an I/O (input/output) port of the microprocessor through wires, a power supply module supplies power to the sound sensor, the vibration sensor, the current transformer, the temperature sensor, the infrared distance measurement sensor and the microprocessor through the wires, and data collected by the acquisition unit is transmitted to the processing unit through a UART (universal asynchronous receiver/transmitter); the microprocessor in the processing unit controls the memory to store the multi-source information acquired by the acquisition unit and analyzes and processes the information data, the microprocessor controls the buzzer to give a voice alarm when a person approaches the motor, and the microprocessor controls the NB-IoT module to send the characteristic information obtained by processing and analyzing to the multi-source information sink node. The corresponding pins of the memory, the buzzer and the NB-IoT module in the processing unit are connected with the I/O port of the microprocessor through leads, and the power supply module supplies power to the microprocessor, the memory, the buzzer and the NB-IoT module through leads.
In the multi-source information aggregation node, a microprocessor controls an NB-IoT module to receive characteristic information obtained by analysis of a processing unit in a multi-source information monitoring node, a microprocessor controls a memory to store the characteristic information obtained by analysis of the processing unit in the multi-source information monitoring node, the characteristic information is packaged and compressed into a data packet, and the microprocessor controls a WiFi module to transmit the processed characteristic information data packet in real time; the corresponding pins of the NB-IoT module, the memory and the WiFi module are connected with an I/O port of the microprocessor through leads, the power supply module supplies power to the microprocessor, the memory and the WiFi module through leads, and the processed characteristic information data packet is sent to the upper computer monitoring center through the WiFi module.
The upper computer monitoring center receives the characteristic information data packet of the multi-source information sink node through the WiFi wireless network and displays the characteristic information data packet on a display interface of the upper computer to obtain the current state information of the motor in operation.
Compared with the prior art, the invention has the beneficial effects that:
1. the multi-sensor fusion technology is adopted, multi-source information of the motor during working is collected through various sensors, and the multi-source information is processed and analyzed to be used as a basis for judging whether the motor breaks down or not. Particularly, the sound sensor is added to collect the sound information of the motor during working, the sound sensor and the vibration information collected by the vibration sensor form information complementation, the information amount of the motor during working is increased, and the sound sensor is adopted to collect the sound information of the motor during working and is not restricted by the installation space.
2. By adopting the current transformer, on one hand, the uniqueness of data can be ensured, and the collected multisource information of the motor in different working states is labeled; on the other hand, the motor fault diagnosis method is used as a part of multi-source information in motor fault diagnosis under the same working state of the motor.
3. When the motor works, in order to reduce safety accidents caused by the fact that personnel are close to the motor, the infrared distance measuring sensor is adopted, whether personnel appear or not can be detected in real time, and the distance between the personnel and the motor can also be measured. And triggering a buzzer according to the set threshold value to remind people to keep away from the motor.
Drawings
Fig. 1 is a schematic diagram of the operation of the system of the present invention.
FIG. 2 is a diagram of an acquisition unit structure of a multi-source information monitoring node in the present invention.
FIG. 3 is a diagram of a processing unit structure of a multi-source information monitoring node in the present invention.
Fig. 4 is a structure diagram of a multi-source information sink node in the present invention.
Wherein, in fig. 2: the system comprises a sound sensor 1, a vibration sensor 2, a current transformer 3, an infrared distance measuring sensor 4, a temperature sensor 5, a first microprocessor 601 and a first power supply module 701. In fig. 3: 8-buzzer, 901-first memory, 1001-first NB-IoT module, 602-second microprocessor, 702-second power module. In fig. 4: 11-WiFi module, 1002-second NB-IoT module, 902-second memory, 603-third microprocessor, 703-third power supply module.
Detailed Description
The invention is further illustrated by the following specific examples.
As shown in fig. 1, the work flow diagram of the multi-sense fusion coal mine large motor fault diagnosis system is composed of a multi-source information monitoring node, a multi-source information aggregation node and an upper computer monitoring center, wherein the multi-source information monitoring node comprises an acquisition unit and a processing unit.
The specific implementation process comprises the following steps:
a first power module 701 in an acquisition unit of a multi-source information monitoring node supplies power to a first microprocessor 601, a sound sensor 1, a vibration sensor 2, a current transformer 3, a temperature sensor 4 and an infrared distance measuring sensor 5, so that the first microprocessor 601 is powered on and initialized. When the motor works, the sound sensors 1 are arranged at different positions about 1 meter away from the motor, and the first microprocessor 601 controls the sound sensors 1 to collect sound information; the vibration sensor 2 is arranged near the motor shell and the rotating shaft, and the first microprocessor 601 controls the vibration sensor 2 to acquire vibration information; the current transformer 3 is arranged in a circuit connection wire of the motor, and the first microprocessor 601 controls the current transformer to acquire current information of the motor in different states; the temperature sensor 4 is arranged on the motor shell, and the first microprocessor 601 controls the temperature sensor 4 to acquire temperature information; the infrared distance measuring sensors 5 are placed in different directions of the safety fence, and the first microprocessor 601 controls the infrared distance measuring sensors 5 to acquire information about whether people are around and the distance between people and the motor when the motor runs; the first microprocessor 601 transmits the multi-source information collected by the collection unit to the processing unit of the multi-source information monitoring node through the UART serial port.
In the processing unit of the multi-source information monitoring node, the second power module 702 supplies power to the second microprocessor 602, the memory 901 and the buzzer 8 through a conducting wire, so that the second microprocessor 602 is powered on and initialized. The second microprocessor 602 stores the multi-source data collected by the collection unit into the first memory 901 for analysis and processing; when the second microprocessor 602 analyzes that a person crosses the man-machine safety distance of the motor in work, the second microprocessor 602 controls the buzzer 8 to give an alarm sound to remind the person to get away from the motor; the second microprocessor 602 finally sends the feature information obtained by processing and analyzing to the multi-source information aggregation node by controlling the first NB-IoT module 1001
The multi-source information aggregation node is configured to receive the feature information analyzed by the processing unit from the multi-source information monitoring node, and store the feature information in the second memory 902. The third power module 703 firstly supplies power to the third microprocessor 603, the second NB-IoT module 1002, the second memory 902 and the WiFi module 11 through wires, the third microprocessor 603 controls the second NB-IoT module 1002 to receive information analyzed and processed by the processing unit in the multi-source information monitoring node, and the second memory 902 packages and compresses the characteristic information into a characteristic information data packet, and sends the characteristic information data packet to the upper computer monitoring center through the WiFi module 11.
The upper computer monitoring center receives the characteristic information data packet of the multi-source information sink node through the WiFi wireless network, displays the data on an upper computer interface through further processing, displays the condition information of the large motor in the coal mine production link during operation in real time, and facilitates later-stage checking and analysis.
The multi-sense fusion coal mine large motor fault diagnosis system adopts multi-sense fusion, NB-IoT and WiFi communication and artificial intelligence technologies, has the characteristics of comprehensive perception of multi-source information of the motor in different working states, high multi-source information transmission speed, low power consumption, high intelligence and the like, realizes fault diagnosis of the coal mine large motor by processing and analyzing the multi-source information, improves low fault diagnosis efficiency, and reduces the probability of casualty events.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood by those skilled in the art that the above-mentioned embodiments are merely exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalents, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (5)
1. The utility model provides a large-scale motor fault diagnostic system in colliery that multi-sense fuses which characterized in that: the fault diagnosis system comprises a multi-source information monitoring node, a multi-source information aggregation node and an upper computer monitoring center, wherein the multi-source information monitoring node comprises a collecting unit and a processing unit, and the collecting unit comprises a sound sensor (1), a vibration sensor (2), a current transformer (3), a temperature sensor (4), an infrared distance measuring sensor (5), a first microprocessor (601) and a first power module (701); the processing unit comprises a second microprocessor (602), a second power supply module (702), a buzzer (8), a first memory (901) and a first NB-IoT module (1001); the multi-source information aggregation node comprises a third microprocessor (603), a third power supply module (703), a second memory (902), a second NB-IoT module (1002) and a WiFi module (11); data transmission of an acquisition unit and a processing unit in the multi-source information monitoring node is completed through serial ports of a first microprocessor (601) and a second microprocessor (602); data transmission is carried out between the multi-source information monitoring node and the multi-source information aggregation node through a first NB-IoT module (1001) and a second NB-IoT module (1002); the multi-source information aggregation node sends data to an upper computer monitoring center through a WiFi module (11).
2. The multi-sense integrated coal mine large motor fault diagnosis system according to claim 1, characterized in that: multisource information monitoring node comprises acquisition unit and processing unit, acquisition unit includes sound sensor (1), vibration sensor (2), current transformer (3), temperature sensor (4), infrared distance measuring sensor (5), first microprocessor (601) and first power module (701), sound sensor (1), vibration sensor (2), current transformer (3), the corresponding pin of temperature sensor (4) and infrared distance measuring sensor (5) passes through the wire and links to each other with the IO mouth of first microprocessor (601), first power module (701) are sound sensor (1) through the wire, vibration sensor (2), current transformer (3), temperature sensor (4), infrared distance measuring sensor (5) and first microprocessor (601) power supply.
3. The multi-sense integrated coal mine large motor fault diagnosis system according to claim 1, characterized in that: the multi-source information monitoring node is composed of an acquisition unit and a processing unit, wherein the processing unit comprises a second microprocessor (602), a second power module (702), a buzzer (8), a first memory (901) and a first NB-IoT module (1001), corresponding pins of the buzzer (8), the first memory (901) and the first NB-IoT module (1001) are connected with an I/O port of the second microprocessor (602) through a lead, and the second power module (702) supplies power for the second microprocessor (602), the buzzer (8), the first memory (901) and the first NB-IoT module (1001) through leads.
4. The multi-sense integrated coal mine large motor fault diagnosis system according to claim 1, characterized in that: the multi-source information aggregation node is composed of a third microprocessor (603), a second NB-IoT module (1002), a WiFi module (11), a second memory (902) and a third power module (703), corresponding pins of the second NB-IoT module (1002), the WiFi module (11) and the second memory (902) are connected with an I/O port of the third microprocessor (603) through leads, and the third power module (703) supplies power to the third microprocessor (603), the buzzer (8), the second memory (902) and the second NB-IoT module (1002) through leads.
5. The multi-sense integrated coal mine large motor fault diagnosis system according to claim 1, characterized in that: and the upper computer monitoring center receives data sent by the multi-source information sink nodes through the WiFi network, obtains characteristic information processed and analyzed by the multi-source information sink nodes, and displays the characteristic information on an upper computer interface.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110109385.5A CN112782577A (en) | 2021-01-21 | 2021-01-21 | Multi-sense fusion coal mine large motor fault diagnosis system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110109385.5A CN112782577A (en) | 2021-01-21 | 2021-01-21 | Multi-sense fusion coal mine large motor fault diagnosis system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112782577A true CN112782577A (en) | 2021-05-11 |
Family
ID=75758173
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110109385.5A Pending CN112782577A (en) | 2021-01-21 | 2021-01-21 | Multi-sense fusion coal mine large motor fault diagnosis system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112782577A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113419492A (en) * | 2021-06-02 | 2021-09-21 | 安徽理工大学环境友好材料与职业健康研究院(芜湖) | NB-IoT industrial pollutant monitoring system based on multi-source heterogeneous sensor data fusion |
| CN113432741A (en) * | 2021-08-02 | 2021-09-24 | 龙口矿业集团有限公司 | Motor and bearing detection system of large-scale equipment for coal mine |
-
2021
- 2021-01-21 CN CN202110109385.5A patent/CN112782577A/en active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113419492A (en) * | 2021-06-02 | 2021-09-21 | 安徽理工大学环境友好材料与职业健康研究院(芜湖) | NB-IoT industrial pollutant monitoring system based on multi-source heterogeneous sensor data fusion |
| CN113432741A (en) * | 2021-08-02 | 2021-09-24 | 龙口矿业集团有限公司 | Motor and bearing detection system of large-scale equipment for coal mine |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105738809B (en) | A kind of motor temperature rise and vibration monitoring device and its implementation | |
| CN203229283U (en) | Elevator fault wireless pre-warning system | |
| CN201546759U (en) | ZigBee technology-based underground safety-monitoring system for coal mine | |
| CN112782577A (en) | Multi-sense fusion coal mine large motor fault diagnosis system | |
| CN201680923U (en) | Wireless temperature sensing device | |
| CN210405371U (en) | Air compression intelligent operation and maintenance system based on Internet of things | |
| CN211452846U (en) | Fan fault remote monitoring system based on current signal | |
| CN211062177U (en) | Special equipment monitoring system based on BIM technology | |
| CN114861540A (en) | Mine ventilator working state monitoring system based on WT-CNN and harmonic vibration feature fusion | |
| CN214278371U (en) | Multi-sense fusion coal mine large motor fault diagnosis system | |
| CN113888833A (en) | Remote early warning detection device for limited space operation | |
| CN206339257U (en) | A kind of self-powered bridge real-time radio health monitoring systems | |
| CN207319055U (en) | Combine harvester fault diagnosis system based on CAN bus | |
| CN206725730U (en) | A kind of AGV power supplies on-line monitoring system | |
| CN105863736A (en) | Coal mine gas monitoring system | |
| CN202771233U (en) | Computer-controlled wireless data acquisition system of oil pumping unit | |
| CN206639003U (en) | A kind of high voltage power cable connector temperature wireless checking control device | |
| CN205594139U (en) | Motor temperature rise and vibration monitoring devices | |
| CN210570822U (en) | Multimode communication temperature and humidity monitoring equipment | |
| CN206479821U (en) | A kind of pressure vessel operation monitoring system | |
| CN107065039A (en) | A kind of zero energy consumption field heavy rain monitoring device and monitoring method | |
| CN207231641U (en) | A kind of cable temperature data acquisition and transmission terminal | |
| CN202734864U (en) | Monitoring system for wind-generating set | |
| CN212893319U (en) | Elevator running acceleration acquisition and transmission device | |
| CN212893318U (en) | Elevator operation data acquisition and transmission device based on NB-IoT |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |