CN115096630A - Smoke exhaust system fault detection device and fault identification method based on Internet of things - Google Patents
Smoke exhaust system fault detection device and fault identification method based on Internet of things Download PDFInfo
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- CN115096630A CN115096630A CN202210748474.9A CN202210748474A CN115096630A CN 115096630 A CN115096630 A CN 115096630A CN 202210748474 A CN202210748474 A CN 202210748474A CN 115096630 A CN115096630 A CN 115096630A
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- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
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Abstract
The invention provides a smoke exhaust system fault detection device and a fault identification method based on the Internet of things, wherein the fault detection device comprises: the system comprises an oil smoke sensor, an ozone concentration sensor, a smoke exhaust fan sensor, a microprocessor, an Internet of things communication unit and a power supply module; the oil smoke sensor is used for monitoring the oil smoke concentration of the smoke exhaust device; an ozone concentration sensor for monitoring the concentration of ozone generated by the purification device after purifying the exhaust gas; the smoke exhaust fan sensor is used for monitoring the state information of the smoke exhaust fan; the microprocessor is used for detecting whether the smoke exhaust system breaks down or not based on the oil smoke concentration, the ozone concentration and the state information of the smoke exhaust fan; the Internet of things communication unit is used for establishing communication connection between the fault detection device and the cloud server through a target Internet of things communication protocol; and the power supply module is used for independently supplying power for the fault detection device. The invention solves the technical problem that the fault of the smoke exhaust system can not be comprehensively detected in the prior art.
Description
Technical Field
The invention relates to the technical field of fault detection of a smoke exhaust system, in particular to a smoke exhaust system fault detection device and a fault identification method based on the Internet of things.
Background
Commercial fume extraction systems typically consist of a fume extractor and a purifier. The smoke exhaust device is a mechanical electronic system consisting of a fan system and an electric control system, and discharges oil smoke waste gas to the high altitude by virtue of a smoke exhaust pipeline; the fan system comprises a motor, a bearing component, a transmission component and the like. The purification device is arranged in front of the smoke exhaust device, and the oil smoke waste gas is purified by the purification system and then is exhausted to the high altitude; the purification is generally performed by techniques such as electrostatic purification, plasma purification, and UV purification.
The fault detection of the existing commercial smoke exhaust system only has the monitoring of fan current and purification current: the monitoring of the fan current is used for reducing the frequency of the fan when the fan has overcurrent faults, and the fan current is reduced so as to prevent the fan from being damaged by overheating; the monitoring of the purification current is used for fault recognition when the purification device is shut down or the purification effect is weakened. However, the existing commercial smoke exhaust system does not systematically monitor the oil smoke concentration and the ozone concentration and perform fault early warning, and also does not systematically monitor the noise, the vibration and the looseness of a conveyor belt of a fan, and generally carries out maintenance after complaints are received, and the failure cannot be predicted to carry out maintenance on equipment in advance.
Disclosure of Invention
In view of this, the present invention provides a smoke exhaust system fault detection apparatus and a fault identification method based on the internet of things, so as to alleviate the technical problem that the smoke exhaust system fault cannot be detected comprehensively in the prior art.
In a first aspect, the embodiment of the invention provides a smoke exhaust system fault detection device based on the internet of things, which is applied to a smoke exhaust system, wherein the smoke exhaust system comprises a smoke exhaust device and a purification device, and the smoke exhaust device comprises a smoke exhaust fan; the fault detection device is arranged at a position between the purification device and the smoke exhaust device; the failure detection device includes: the system comprises an oil smoke sensor, an ozone concentration sensor, a smoke exhaust fan sensor, a microprocessor, an Internet of things communication unit and a power supply module; the oil smoke sensor, the ozone concentration sensor, the smoke exhaust fan sensor and the internet of things communication unit are all in communication connection with the microprocessor; the oil fume sensor and the ozone concentration sensor are connected with the air filter element through a flow guide pipe to form an air inlet and outlet pipeline system; the oil smoke sensor is used for monitoring the oil smoke concentration of the smoke exhaust device; the ozone concentration sensor is used for monitoring the concentration of ozone generated after the exhaust gas is purified by the purification device; the smoke exhaust fan sensor is used for monitoring the state information of the smoke exhaust fan; the microprocessor is used for detecting whether the smoke exhaust system breaks down or not based on the oil smoke concentration, the ozone concentration and the state information of the smoke exhaust fan; the Internet of things communication unit is used for establishing communication connection between the fault detection device and the cloud server through a target Internet of things communication protocol; and the power supply module is used for independently supplying power to the fault detection device.
Further, the smoke exhaust fan sensor includes: a noise sensor, a vibration sensor and a current detection circuit; the noise sensor is used for monitoring noise information of the smoke exhaust fan; the vibration sensor is used for monitoring vibration information of the smoke exhaust fan; and the current detection circuit is used for monitoring the current information of the smoke exhaust fan.
Further, the current detection circuit is also used for monitoring the purifying current of the purifying device.
Furthermore, from one end of the air inlet pipe of the flow guide pipe to one end of the air outlet pipe, the oil fume sensor, the air filter element, the ozone concentration sensor and the smoke exhaust fan are sequentially arranged.
Further, the target internet of things communication protocol comprises an MQTT protocol.
In a second aspect, an embodiment of the present invention further provides a smoke exhaust system fault identification method based on the internet of things, which is applied to the fault detection device in the first aspect; the method comprises the following steps: acquiring actual working condition information of the smoke exhaust system during operation at preset time intervals; the actual working condition information comprises: the purification current value of the purification device, the oil smoke concentration, the ozone concentration and the state information of the smoke exhaust fan; identifying the fault of the smoke exhaust system based on the actual working condition information and the preset working condition information; the preset working condition information is the working condition information when the smoke exhaust system operates in a fault-free state.
Further, the state information of the smoke exhaust fan comprises a fan current value; the preset working condition information comprises: presetting a fan current range, a purification current range and an ozone concentration range; based on actual operating condition information and preset operating condition information, the fault of the smoke exhaust system is identified, and the method comprises the following steps of: if the fan current value is within the preset fan current range and the purification current value is smaller than the lower limit threshold of the preset purification current range, determining that the purification device has a shutdown fault; if the fan current value is within the preset fan current range and the ozone concentration is greater than the upper limit threshold value of the preset ozone concentration range, determining that the purifying device breaks down; if the purification current value is within the preset purification current range and the fan current value is smaller than the lower limit threshold of the preset fan current range, determining that a terminal air valve of the smoke exhaust system has a fault; and if the purification current value is within the preset purification current range and the fan current value is larger than the upper limit threshold value of the preset fan current range, determining that the belt of the smoke exhaust fan is loose or the air duct of the smoke exhaust system has air leakage fault.
Further, the state information of the smoke exhaust fan comprises: vibration amplitude and noise amplitude; based on actual operating condition information and preset operating condition information, the fault of the smoke exhaust system is identified, and the method comprises the following steps of: calculating the average value of the vibration amplitude and the noise amplitude of the smoke exhaust fan in a preset time period and every day; if the variation trend of the average value of the vibration amplitude and the noise amplitude is an increasing trend, determining that the smoke exhaust fan has bearing wear failure or fastener loosening failure; calculating the average value of the daily oil smoke concentration of the smoke exhaust fan in a preset time period; and if the change trend of the average value of the oil smoke concentration is an increasing trend and the purification current value is within the preset purification current range, determining that dirt exists in the purification device.
In a third aspect, an embodiment of the present invention further provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the steps of the method according to the second aspect when executing the computer program.
In a fourth aspect, the present invention further provides a computer-readable medium having non-volatile program code executable by a processor, where the program code causes the processor to execute the method according to the second aspect.
The invention provides a smoke exhaust system fault detection device and a fault identification method based on the Internet of things.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a schematic diagram of a smoke exhaust system fault detection device based on the internet of things according to an embodiment of the present invention;
fig. 2 is a schematic diagram of another smoke exhaust system fault detection device based on the internet of things according to an embodiment of the present invention;
fig. 3 is a schematic diagram of a smoke exhaust system according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a communication interaction provided in an embodiment of the present invention;
fig. 5 is a flowchart of a smoke exhaust system fault identification method based on the internet of things according to an embodiment of the present invention;
fig. 6 is a flowchart of another smoke exhaust system fault identification method based on the internet of things according to the embodiment of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it should be understood that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The first embodiment is as follows:
fig. 1 is a schematic diagram of a smoke exhaust system fault detection device based on the internet of things, which is applied to a smoke exhaust system, wherein the smoke exhaust system comprises a smoke exhaust device and a purification device, and the smoke exhaust device comprises a smoke exhaust fan. In an embodiment of the invention, the fault detection means is arranged at a position between the purification device and the fume extraction device.
As shown in fig. 1, the fault detection apparatus includes: the system comprises an oil smoke sensor 10, an ozone concentration sensor 20, a smoke exhaust fan sensor 30, a microprocessor 40, an internet of things communication unit 50 and a power supply module 60. The oil smoke sensor 10, the ozone concentration sensor 20, the smoke exhaust fan sensor 30 and the internet of things communication unit 50 are all in communication connection with the microprocessor 40; the oil smoke sensor 10 and the ozone concentration sensor 20 are connected with the air filter element through the flow guide pipe to form an air inlet and outlet pipeline system, and the flow rate of the air pump is adjusted by detecting the flow rate of the pipeline system, so that the sensor for monitoring oil smoke components works in an optimal mode.
Specifically, the smoke sensor 10 is used for monitoring the smoke concentration of the smoke exhaust device.
And an ozone concentration sensor 20 for monitoring the concentration of ozone generated after the exhaust gas is purified by the purification apparatus.
And a smoke exhaust fan sensor 30 for monitoring the state information of the smoke exhaust fan.
And the microprocessor 40 is used for detecting whether the smoke exhaust system breaks down or not based on the oil smoke concentration, the ozone concentration and the state information of the smoke exhaust fan.
And the internet of things communication unit 50 is used for establishing communication connection between the fault detection device and the cloud server through a target internet of things communication protocol.
Optionally, in the embodiment of the present invention, the target internet of things communication protocol includes an MQTT protocol.
And a power supply module 60 for independently supplying power to the fault detection device.
The invention provides a smoke exhaust system fault detection device based on the Internet of things, which is characterized in that an independent fault detection device is arranged to independently supply power to operate, so that the smoke exhaust device and a purification device are not influenced by the work of the smoke exhaust device and the purification device, meanwhile, a plurality of sensors are used for carrying out all-around monitoring on the smoke exhaust device and the purification device, and fault identification is carried out according to sensor data, so that the technical problem that the smoke exhaust system fault cannot be comprehensively detected in the prior art is solved.
Fig. 2 is a schematic diagram of another smoke exhaust system fault detection device based on the internet of things according to an embodiment of the invention. As shown in fig. 2, the smoke exhaust fan sensor 30 includes: a noise sensor 31, a vibration sensor 32, and a current detection circuit 33.
Specifically, the noise sensor 31 is configured to monitor noise information of the smoke exhaust fan.
And the vibration sensor 32 is used for monitoring vibration information of the smoke exhaust fan.
And a current detection circuit 33 for monitoring current information of the smoke exhaust fan.
Alternatively, in the embodiment of the present invention, the number of the current detection circuits 33 is plural. As shown in fig. 2, the current detection circuit 33 is also used to monitor the purge current of the purge device.
Optionally, as shown in fig. 2, the cooking fume sensor 10, the air filter, the ozone concentration sensor 20 and the smoke exhaust fan are sequentially arranged from one end of the air inlet pipe to one end of the air outlet pipe of the flow guide pipe.
In the embodiment of the invention, the smoke exhaust system consists of a smoke exhaust device and a purification device. Fig. 3 is a schematic view of a smoke exhausting system according to an embodiment of the present invention, as shown in fig. 3, the smoke exhausting device includes a host and a terminal, and the purifying device is installed in front of the smoke exhausting system to purify the smoke exhaust gas. The main machine is a smoke exhaust fan which is arranged at the outlet of the main pipe of the roof and plays a smoke exhaust role in the smoke exhaust flue, and the main machine is provided with an internet of things control device; the terminal refers to a power distribution valve and an internet of things control device which are arranged at the outlet of the kitchen branch pipe. The system comprises a host, an Internet of things control device, a terminal and an air valve, wherein the Internet of things control device of the host realizes air volume adjustment of the host, the Internet of things control device of the terminal realizes angle adjustment of the air valve, and the host and the terminal realize information interaction through bidirectional communication through the Internet of things control device, so that dynamic linkage adjustment of the air volume of the host and the angle of the air valve is realized; the internet of things control device can communicate in a wireless mode or a wired mode. As shown in fig. 3, the smoke exhausting system connects the smoke stoves and the air valves in the kitchens of each floor through the transverse branch pipes, and the smoke stoves and the air valves are gathered to a longitudinal main pipe and exhausted to the high altitude through the smoke exhausting fan.
The fault detection device provided by the embodiment of the invention is a real-time online monitoring device which is installed between a purification device and a smoke exhaust device, operates independently and has the communication function of the Internet of things. The mounting position is the position of the monitoring device shown in fig. 3.
The fault detection device provided by the embodiment of the invention can realize the following functions:
1. monitoring the concentration of the oil smoke in the oil smoke gas, and prejudging whether the purification device is lack of cleaning and maintenance after long-time operation, so that the exhaust concentration of the oil smoke is overproof due to incomplete purification;
2. monitoring the purification current, and prejudging whether the purification device is shut down due to fault protection;
3. monitoring the concentration of ozone generated after the oil fume gas is purified, and prejudging whether the purifying device is lack of cleaning and maintenance after long-time operation, so as to cause arc discharge of an electric field;
4. monitoring the current of the smoke exhaust fan, and pre-judging whether the power transmission changes due to the fact that a belt is loosened after the smoke exhaust fan runs for a long time;
5. noise and vibration of the smoke exhaust fan are monitored, and whether the smoke exhaust fan runs for a long time or not is judged in advance, so that the fastener is loosened and the bearing is abraded.
The fault detection device provided by the embodiment of the invention adopts a lightweight Internet of things communication protocol MQTT, can perform two-way data communication with a smoke discharge control system by means of an MQTT message server, and acquires fan operation information or controls the fan to operate through a cloud platform. Similarly, the fault detection device can report the detected fault state to the cloud platform in real time through a fault code, and can also remotely control the fault detection device to self-learn through the cloud platform. After the operation and maintenance personnel pay attention to the WeChat public number, the fault information can be pushed in real time, the operation and maintenance personnel can maintain the system conveniently in time, and the intelligent degree of the system is improved. Communication interaction as shown in fig. 4, the fault detection device performs message communication with the cloud platform through the MQTT message server, and the smoke exhaust control system also performs message communication with the cloud platform through the MQTT message server.
Example two:
fig. 5 is a flowchart of a smoke exhaust system fault identification method based on the internet of things according to an embodiment of the present invention, and is applied to the fault detection device in the first embodiment. As shown in fig. 5, the method specifically includes the following steps:
step S502, acquiring actual working condition information of the smoke exhaust system during operation at preset time intervals; the actual working condition information comprises: the purification current value, the oil smoke concentration, the ozone concentration and the state information of the smoke exhaust fan of the purification device;
step S504, based on the actual working condition information and the preset working condition information, identifying the fault of the smoke exhaust system; the preset working condition information is the working condition information when the smoke exhaust system operates in a fault-free state.
Optionally, the preset condition message is obtained by learning, by the fault detection device, an operation condition of the fault detection device in a fault-free state.
The invention provides a smoke exhaust system fault identification method based on the Internet of things, which is characterized in that an independent fault detection device is arranged to independently supply power to operate, so that the smoke exhaust device and a purification device are not influenced by the work of the smoke exhaust device and the purification device, meanwhile, a plurality of sensors are applied to comprehensively monitor the smoke exhaust device and the purification device, and fault identification is carried out according to sensor data, so that the technical problem that the smoke exhaust system fault cannot be comprehensively detected in the prior art is solved.
Optionally, the state information of the smoke exhaust fan includes a fan current value; the preset working condition information comprises: presetting a fan current range, a purification current range and an ozone concentration range; step S504 specifically includes:
if the current value of the fan is within the preset fan current range and the purification current value is smaller than the lower limit threshold value of the preset purification current range, determining that the purification device has a shutdown fault;
if the current value of the fan is within the preset fan current range and the ozone concentration is greater than the upper limit threshold value of the preset ozone concentration range, determining that the purifying device breaks down;
if the purification current value is within the preset purification current range and the fan current value is smaller than the lower limit threshold of the preset fan current range, determining that a terminal air valve of the smoke exhaust system has a fault;
and if the purification current value is within the preset purification current range and the fan current value is greater than the upper limit threshold value of the preset fan current range, determining that the belt of the smoke exhaust fan is loose or the air duct air leakage fault of the smoke exhaust system occurs.
Optionally, the state information of the smoke exhaust fan includes: vibration amplitude and noise amplitude; step S504 further includes:
calculating the average value of the vibration amplitude and the noise amplitude of the smoke exhaust fan in a preset time period every day;
if the variation trend of the average values of the vibration amplitude and the noise amplitude is an increasing trend, determining that the smoke exhaust fan has bearing wear failure or fastener loosening failure;
calculating the average value of the daily oil smoke concentration of the smoke exhaust fan in a preset time period;
and if the change trend of the average value of the oil smoke concentration is an increasing trend and the purification current value is within a preset purification current range, determining that dirt exists in the purification device.
Optionally, fig. 6 is a flowchart of another smoke exhaust system fault identification method based on the internet of things according to an embodiment of the present invention. As shown in fig. 6, the method includes the steps of:
s1, after the fault detection system is installed and debugged, sending a control command to the smoke discharge control system through the cloud platform, controlling the fans and all terminal air valves to be started to the frequency and angle calculated by the power distribution algorithm, and linking the purification device to start working so that the system enters the self-learning working condition of the device;
s2, issuing a self-learning command to the fault detection device through the cloud platform;
s3, reading the fan current, the purifying current, the oil smoke concentration, the ozone concentration, the noise amplitude and the vibration amplitude at intervals of fixed time (such as 1 minute) by the fault detection device, removing the maximum value and the minimum value through a software filtering algorithm after learning time T, taking the maximum value and the minimum value out of the residual data, and calculating an average value;
s4, the fault detection device stores the calculated fan current, the calculated purification current, the calculated oil smoke concentration, the calculated ozone concentration, the calculated noise amplitude and the calculated maximum value, minimum value and average value of the vibration amplitude into a memory, and exits from the self-learning process;
s5, reading the current, the purification current, the ozone concentration, the noise amplitude and the vibration amplitude of the fan at fixed intervals (such as 1 minute) by the fault detection device;
s6, if the fan current is normal and the purifying current is not or less than the lower threshold, judging that the purifying device has a shutdown fault;
s7, if the purifying current is normal and the fan current is smaller than the current of the device under the self-learning working condition, judging that the terminal air valve is not opened in place;
s8, if the purifying current is normal and the fan current is larger than the current under the self-learning working condition of the device, judging that the fan belt is loose or the air leakage phenomenon exists in the flue;
s9, if the current of the fan is normal and the ozone concentration is greater than the concentration of the device under the self-learning working condition, judging that the purifying device has frequent sparking or arc discharge and needs to be overhauled in time;
s10, calculating daily noise amplitude and vibration amplitude average values, analyzing the daily average values and the amplitude average values, the maximum values and the minimum value variation trends of the device under the self-learning working condition, and judging that the bearing abrasion or the fastener loosening phenomenon of the fan needs to be overhauled in time if the gradual increase trend exists;
and S11, calculating the average value of the daily oil smoke concentration, analyzing the variation trend of the average value of the daily oil smoke concentration, and if the purification current is normal and the average value of the oil smoke concentration has an increasing trend, judging that the purification device needs to be cleaned and maintained.
The embodiment of the present invention further provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and capable of running on the processor, and when the processor executes the computer program, the steps of the method provided in the embodiment of the present invention are implemented.
Embodiments of the present invention also provide a computer readable medium having non-volatile program code executable by a processor, where the program code causes the processor to execute the method provided by the embodiments of the present invention.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. A fault detection device of a smoke exhaust system based on the Internet of things is applied to the smoke exhaust system, the smoke exhaust system comprises a smoke exhaust device and a purification device, and the smoke exhaust device comprises a smoke exhaust fan; characterized in that the fault detection device is arranged at a position between the purification device and the fume extractor; the failure detection device includes: the system comprises an oil smoke sensor, an ozone concentration sensor, a smoke exhaust fan sensor, a microprocessor, an Internet of things communication unit and a power supply module; the oil fume sensor, the ozone concentration sensor, the smoke exhaust fan sensor and the internet of things communication unit are all in communication connection with the microprocessor; the oil fume sensor and the ozone concentration sensor are connected with the air filter element through the flow guide pipe to form an air inlet pipeline system and an air outlet pipeline system;
the oil smoke sensor is used for monitoring the oil smoke concentration of the smoke exhaust device;
the ozone concentration sensor is used for monitoring the concentration of ozone generated after the purification device purifies the exhaust gas;
the smoke exhaust fan sensor is used for monitoring the state information of the smoke exhaust fan;
the microprocessor is used for detecting whether the smoke exhaust system breaks down or not based on the oil smoke concentration, the ozone concentration and the state information of the smoke exhaust fan;
the Internet of things communication unit is used for establishing communication connection between the fault detection device and the cloud server through a target Internet of things communication protocol;
and the power supply module is used for independently supplying power to the fault detection device.
2. The fault detection device of claim 1, wherein the smoke exhaust fan sensor comprises: a noise sensor, a vibration sensor and a current detection circuit;
the noise sensor is used for monitoring noise information of the smoke exhaust fan;
the vibration sensor is used for monitoring vibration information of the smoke exhaust fan;
and the current detection circuit is used for monitoring the current information of the smoke exhaust fan.
3. The fault detection device of claim 2, wherein the current detection circuit is further configured to monitor a purge current of the purge device.
4. The apparatus according to claim 1, wherein the soot sensor, the air filter, the ozone concentration sensor, and the smoke exhaust fan are provided in this order from an end of the air inlet pipe to an end of the air outlet pipe of the draft tube.
5. The fault detection device of claim 1, wherein the target internet of things communication protocol comprises an MQTT protocol.
6. An Internet of things-based smoke exhaust system fault identification method is applied to the fault detection device of any one of claims 1-5; the method comprises the following steps:
acquiring actual working condition information of the smoke exhaust system during operation at preset time intervals; the actual working condition information comprises: the purification current value of the purification device, the oil smoke concentration, the ozone concentration and the state information of the smoke exhaust fan;
identifying the fault of the smoke exhaust system based on the actual working condition information and the preset working condition information; the preset working condition information is the working condition information when the smoke exhaust system operates in a fault-free state.
7. The method of claim 6, wherein the status information of the exhaust fan comprises a fan current value; the preset working condition information comprises: presetting a fan current range, a purification current range and an ozone concentration range; based on the actual working condition information and the preset working condition information, the fault of the smoke exhaust system is identified, and the method comprises the following steps of:
if the fan current value is within the preset fan current range and the purification current value is smaller than the lower limit threshold of the preset purification current range, determining that the purification device has a shutdown fault;
if the fan current value is within the preset fan current range and the ozone concentration is greater than the upper limit threshold value of the preset ozone concentration range, determining that the purification device breaks down;
if the purification current value is within the preset purification current range and the fan current value is smaller than the lower limit threshold of the preset fan current range, determining that a terminal air valve of the smoke exhaust system has a fault;
and if the purification current value is within the preset purification current range and the fan current value is greater than the upper limit threshold value of the preset fan current range, determining that the belt of the smoke exhaust fan is loose or the air duct of the smoke exhaust system has air leakage fault.
8. The method of claim 7, wherein the state information of the smoke exhaust fan comprises: vibration amplitude and noise amplitude; based on actual operating condition information and preset operating condition information, the fault of the smoke exhaust system is identified, and the method comprises the following steps of:
calculating the average value of the vibration amplitude and the noise amplitude of the smoke exhaust fan in a preset time period and every day;
if the variation trend of the average values of the vibration amplitude and the noise amplitude is an increasing trend, determining that the smoke exhaust fan has bearing wear failure or fastener loosening failure;
calculating the average value of the daily oil smoke concentration of the smoke exhaust fan in a preset time period;
and if the variation trend of the average value of the oil fume concentration is an increasing trend, and the purification current value is within the preset purification current range, determining that dirt exists in the purification device.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the steps of the method of any of the preceding claims 6 to 8 are implemented when the computer program is executed by the processor.
10. A computer-readable medium having non-transitory program code executable by a processor, wherein the program code causes the processor to perform the method of any of claims 6-8.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202210748474.9A CN115096630A (en) | 2022-06-28 | 2022-06-28 | Smoke exhaust system fault detection device and fault identification method based on Internet of things |
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| CN202210748474.9A CN115096630A (en) | 2022-06-28 | 2022-06-28 | Smoke exhaust system fault detection device and fault identification method based on Internet of things |
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