Fuel system intelligent monitoring and early warning system

Abstract

The present invention discloses an intelligent monitoring and early warning system for a fuel system, and relates to the technical field of intelligent monitoring. The present invention comprises a coal conveyor monitoring module, an environmental area monitoring module, a fixed-point monitoring module, a personnel safety protection module, an early warning terminal and a database. By real-time monitoring and analysis of the coal conveyor and the coal conveyor area, immediate, reliable, stable and all-day uninterrupted coal conveyor belt inspection can be achieved, and hidden dangers such as coal drop pipe blockage, coal conveyor belt tearing and coal conveyor belt deviation can be monitored in real time, thereby comprehensively improving the safety, reliability and timeliness of the coal conveying system, not only reducing the workload of on-site inspection personnel, but also ensuring their life safety, improving the inherent safety level of the production site, and improving the intelligent detection level of the coal conveying system. At the same time, it creates underlying data conditions and application foundation for more comprehensive intelligence of the overall coal conveying system of a thermal power plant.

Description

Technical Field

[0001] The present invention relates to the field of intelligent monitoring technology, and in particular to an intelligent monitoring and early warning system for a fuel system. Background Art

[0002] Thermal power plants are the core places for energy conversion. They convert coal into electricity through power generation equipment to provide a stable and reliable power supply for society. Electricity is an indispensable infrastructure for the operation of modern society. At the same time, as an important support for economic growth, the construction and operation of thermal power plants are crucial to the economic development of countries and regions. The stability and reliability of power supply directly affect the sustainability and efficiency of industrial production, and are also related to the development of commerce, services and agriculture. The construction and operation of thermal power plants can not only provide employment opportunities, but also drive the development of related industries and promote economic growth. Therefore, it is crucial to ensure the normal operation of thermal power plants. Thermal power generation depends on the stable operation of coal supply and coal transportation systems. However, the monitoring of coal supply and coal transportation systems in thermal power plants is still mainly manual inspection, which not only requires a lot of human resources, but also due to the increasing danger of thermal power plants and the increasing power consumption, the current manual inspection mode is in urgent need of upgrading. Once there is a problem with the coal supply chain, it may lead to serious consequences such as power outages. In addition, there may be safety hazards such as fire and explosion during the combustion process. Therefore, in order to ensure the normal operation of thermal power plants, strict safety measures and monitoring methods need to be taken. Summary of the invention

[0003] In view of the above-mentioned technical deficiencies, the purpose of the present invention is to provide an intelligent monitoring and early warning system for a fuel system.

[0004] In order to solve the above technical problems, the present invention adopts the following technical solution: The present invention provides an intelligent monitoring and early warning system for a fuel system, comprising:

[0005] The coal conveyor monitoring module is used to arrange various collection points on the coal conveyor in the thermal power plant, collect the temperature of the corresponding collection points on the coal conveyor in the thermal power plant, and judge whether the temperature on the coal conveyor in the thermal power plant is too high. If the temperature on the coal conveyor in the thermal power plant is too high, a signal is sent to the early warning terminal;

[0006] The environmental area monitoring module is used to arrange various collection time points in the thermal power plant according to the preset time intervals, and then collect the environmental information corresponding to each collection time point, wherein the environmental information includes the ambient temperature, ambient humidity, air oxygen concentration, combustible gas concentration, dust concentration and smoke concentration, analyze and obtain the corresponding environmental information evaluation coefficient in the thermal power plant, judge whether the environment in the thermal power plant is in a dangerous state, and if the environment in the thermal power plant is in a dangerous state, send a signal to the early warning terminal;

[0007] The fixed-point monitoring module is used to collect the operation status diagram corresponding to the coal conveyor in the thermal power plant through the camera at each collection time point, collect the coal flow rate and coal flow pressure corresponding to the coal drop pipe at each collection time point, analyze and obtain the blockage assessment coefficient corresponding to the coal drop pipe at each collection time point in the thermal power plant, and analyze and obtain the operation status assessment coefficient corresponding to the coal conveyor at each collection time point in the thermal power plant through the coal conveyor operation status diagram corresponding to each collection time point in the thermal power plant and the blockage assessment coefficient corresponding to the coal drop pipe, and judge whether the operation status of the coal conveyor corresponding to each collection time point in the thermal power plant is healthy. If the operation status of the coal conveyor corresponding to a certain collection time point in the thermal power plant is unhealthy, a signal is sent to the early warning terminal;

[0008] The personnel safety protection module is used to collect images of each staff member corresponding to each collection time point in the thermal power plant through a camera, and determine whether each staff member corresponding to each collection time point in the thermal power plant has dangerous behavior. If a staff member has dangerous behavior at a certain collection time point in the thermal power plant, a signal is sent to the early warning terminal;

[0009] The early warning terminal is used to issue early warning prompts when the temperature on the coal conveyor in the thermal power plant is too high, the environment in the thermal power plant is in a dangerous state, the operating state of the coal conveyor corresponding to a certain collection time point in the thermal power plant is unhealthy, or a staff member in the thermal power plant has dangerous behavior at a certain collection time point.

[0010] The database is used to store temperature thresholds, environmental information evaluation coefficient thresholds, operating status evaluation coefficient thresholds, safety protection equipment images and safety distances.

[0011] Preferably, the determination of whether the temperature in the thermal power plant is too high is specifically determined as follows: the temperatures of the corresponding collection points on the coal conveyor in the thermal power plant are compared with the temperature threshold stored in the database; if the temperature of a certain collection point corresponding to the coal conveyor in the thermal power plant is greater than or equal to the temperature threshold stored in the database, it is determined that the temperature on the coal conveyor in the thermal power plant is too high; if the temperature of a certain collection point corresponding to the coal conveyor in the thermal power plant is less than the temperature threshold stored in the database, it is determined that the temperature on the coal conveyor in the thermal power plant is not too high.

[0012] Preferably, the specific judging process of judging whether the environment in the thermal power plant is in a dangerous state is as follows:

[0013] According to the corresponding air oxygen concentration, combustible gas concentration, dust concentration and smoke concentration in the thermal power plant, the air environment assessment coefficient corresponding to each sampling time point in the thermal power plant is analyzed;

[0014] By calculating the formula The corresponding environmental information evaluation coefficient in the thermal power plant is calculated, where ζ is the corresponding environmental information evaluation coefficient in the thermal power plant, At i is the ambient temperature corresponding to the i-th collection time point in the thermal power plant, i is the number corresponding to each collection time point, i = 1, 2...n, Ah i is the ambient humidity corresponding to the i-th acquisition time point in the thermal power plant, At′ is the set ambient temperature reference value, Ah′ is the set ambient humidity reference value, ζ2 i is the air environment assessment coefficient corresponding to the i-th collection time point in the thermal power plant, ζ2′ is the set reference air environment assessment coefficient, σ1, σ2, σ2 are the weight factors corresponding to the ambient temperature, ambient humidity, and air environment assessment coefficient, respectively;

[0015] The corresponding environmental information assessment coefficient in the thermal power plant is compared with the environmental information assessment coefficient threshold stored in the database. If the corresponding environmental information assessment coefficient in the thermal power plant is greater than or equal to the environmental information assessment coefficient threshold stored in the database, it is determined that the environment in the thermal power plant is in a normal state. If the corresponding environmental information assessment coefficient in the thermal power plant is less than the environmental information assessment coefficient threshold stored in the database, it is determined that the environment in the thermal power plant is in a dangerous state.

[0016] Preferably, the analysis obtains the air environment assessment coefficient corresponding to each collection time point in the thermal power plant, and the specific analysis process is as follows:

[0017] By calculating the formula The air environment assessment coefficient corresponding to each sampling time point in the thermal power plant is calculated, where ζ2 i is the air environment assessment coefficient corresponding to the i-th collection time point in the thermal power plant, Ac i is the air oxygen concentration corresponding to the i-th sampling time point in the thermal power plant, Tc i is the combustible gas concentration corresponding to the i-th acquisition time point in the thermal power plant, Dc i is the dust concentration corresponding to the i-th collection time point in the thermal power plant, Sc i is the smoke concentration corresponding to the i-th collection time point in the thermal power plant, Ac′ is the set reference value of air oxygen concentration, Tc′ is the set reference value of combustible gas concentration, Dc′ is the set reference value of dust concentration, Sc′ is the set reference value of smoke concentration, ω1, ω2, ω3, and ω4 are the weight factors corresponding to the set air oxygen concentration, combustible gas concentration, dust concentration, and smoke concentration, respectively.

[0018] Preferably, the analysis obtains the blockage assessment coefficient corresponding to the coal drop pipe at each acquisition time point in the thermal power plant, and the specific analysis process is as follows:

[0019] By calculating the formula The blockage assessment coefficient corresponding to the coal drop pipe at each acquisition time point in the thermal power plant is calculated, where β i is the blockage assessment coefficient of the coal pipe corresponding to the i-th collection time point in the thermal power plant, i is the number corresponding to each collection time point, i = 1, 2...n, Cf i is the coal flow corresponding to the i-th collection time point in the thermal power plant, P i is the coal flow pressure corresponding to the i-th acquisition time point in the thermal power plant, Cf′ is the set coal flow reference value, P′ is the set coal flow pressure reference value, α1 and α2 are the weight factors corresponding to the set coal flow and coal flow pressure, respectively.

[0020] Preferably, the analysis obtains the operating status evaluation coefficient corresponding to the coal conveyor at each acquisition time point in the thermal power plant, and the specific judgment process is as follows:

[0021] Obtain the coal conveyor belt operation image corresponding to each acquisition time point in the thermal power plant from the coal conveyor operation status diagram corresponding to each acquisition time point in the thermal power plant, compare the coal conveyor belt operation images corresponding to each acquisition time point in the thermal power plant in the order of each acquisition time point, and obtain the overlap area of ​​the coal conveyor belt operation images corresponding to each acquisition time point in the thermal power plant; obtain the coal conveyor operation noise value corresponding to each acquisition time point from the sound sensor corresponding to the coal conveyor in the thermal power plant; obtain the electromagnetic pulse signal corresponding to the operation of the coal conveyor belt at each acquisition time point in the thermal power plant from the belt tear detection device corresponding to the coal conveyor in the thermal power plant, and then obtain the electromagnetic pulse signal amplitude corresponding to the operation of the coal conveyor belt at each acquisition time point in the thermal power plant through a waveform conversion circuit;

[0022] By calculating the formula The operating status evaluation coefficient of the coal conveyor corresponding to each acquisition time point in the thermal power plant is calculated, where δ i is the operating status evaluation coefficient of the coal conveyor corresponding to the i-th collection time point in the thermal power plant, i is the number corresponding to each collection time point, i = 1, 2...n, Sp i 、Sp i+1 are the overlap areas of the coal conveyor belt operation images corresponding to the i-th acquisition time point and the i+1-th acquisition time point in the thermal power plant, ΔSp is the set allowable deviation value of the overlap area of ​​the belt operation image, and No i is the noise value of the coal conveyor operation corresponding to the i-th sampling time point in the thermal power plant, No′ is the set allowable noise value of the coal conveyor operation, are the electromagnetic pulse signal amplitudes corresponding to the coal conveyor belt operation at the i-th acquisition time point, the i+1-th acquisition time point, and the i+2-th acquisition time point in the thermal power plant, respectively. i is the blockage assessment coefficient of the coal drop pipe at the i-th acquisition time point in the thermal power plant. ε1, ε2, and ε3 are the weight factors corresponding to the overlap area of ​​the belt running image, the coal conveyor running noise value, and the electromagnetic pulse signal amplitude, respectively.

[0023] Preferably, the determination of whether the operating status of the coal conveyor corresponding to each collection time point in the thermal power plant is healthy is specifically performed as follows: comparing the operating status evaluation coefficient corresponding to the coal conveyor at each collection time point in the thermal power plant with the operating status evaluation coefficient threshold stored in the database; if the operating status evaluation coefficient corresponding to the coal conveyor at a certain collection time point in the thermal power plant is less than the operating status evaluation coefficient threshold stored in the database, then it is determined that the operating status of the coal conveyor corresponding to the collection time point in the thermal power plant is healthy; if the operating status evaluation coefficient corresponding to a certain collection time point in the thermal power plant is greater than or equal to the operating status evaluation coefficient threshold stored in the database, then it is determined that the operating status of the coal conveyor corresponding to the collection time point in the thermal power plant is unhealthy.

[0024] Preferably, the specific judgment process of judging whether each staff member corresponding to each collection time point in the thermal power plant has dangerous behavior is as follows:

[0025] Extracting the images of the safety protection equipment of each worker corresponding to each acquisition time point in the thermal power plant from the images of each worker corresponding to each acquisition time point in the thermal power plant, and judging whether the safety protection status of each worker corresponding to each acquisition time point in the thermal power plant is insufficient;

[0026] Extract the distance between each staff member and the coal conveyor belt in the thermal power plant at each acquisition time point from the images of each staff member corresponding to each acquisition time point in the thermal power plant, obtain the belt distance corresponding to each staff member at each acquisition time point, compare the belt distance corresponding to each staff member at each acquisition time point with the safety distance stored in the database, if the belt distance corresponding to each staff member at each acquisition time point is greater than or equal to the safety distance stored in the database, then it is determined that the staff member at the acquisition time point in the thermal power plant is at a safe distance, if the belt distance corresponding to each staff member at each acquisition time point is less than the safety distance stored in the database, then it is determined that the staff member at the acquisition time point in the thermal power plant is at a dangerous distance;

[0027] When a worker corresponding to a certain collection time point in a thermal power plant is in an insufficient safety protection state or is at a dangerous distance, it is determined whether the workers corresponding to each collection time point in the thermal power plant have any dangerous behavior. In this way, it is determined whether the workers corresponding to each collection time point in the thermal power plant have any dangerous behavior.

[0028] Preferably, the determination of whether the safety protection status of each staff member corresponding to each collection time point is insufficient is specifically determined as follows: comparing the safety protection equipment image of each staff member corresponding to each collection time point in the thermal power plant with the safety protection equipment image stored in the database; if the safety protection equipment image of a staff member corresponding to a certain collection time point in the thermal power plant is inconsistent with the safety protection equipment image stored in the database, it is determined that the safety protection status of this staff member corresponding to the collection time point is insufficient, and in this way, it is determined whether the safety protection status of each staff member corresponding to each collection time point is insufficient.

[0029] The beneficial effects of the present invention are as follows: the present invention provides an intelligent monitoring and early warning system for the fuel system, which can realize instant, reliable and stable functions such as coal drop pipe blockage perception, coal feeder belt tear perception, and on-site ambient temperature perception through real-time monitoring and analysis of the coal feeder and the coal feeder area, thereby achieving uninterrupted coal feeder belt inspection throughout the day, and real-time monitoring of hidden dangers such as coal drop pipe blockage, coal feeder belt tearing, and coal feeder belt deviation, thereby comprehensively improving the safety, reliability and timeliness of the coal conveying system, not only reducing the workload of on-site inspectors, but also ensuring their life safety, improving the inherent safety level of the production site, and improving the intelligent detection level of the coal conveying system, while creating the underlying data conditions and application foundation for the more comprehensive intelligence of the overall coal conveying system of a thermal power plant. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0031] Figure 1 It is a schematic diagram of the system structure connection of the present invention. DETAILED DESCRIPTION

[0032] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0033] See also Figure 1 As shown, the present invention provides an intelligent monitoring and early warning system for a fuel system, including a coal conveyor monitoring module, an environmental area monitoring module, a fixed-point monitoring module, a personnel safety protection module, an early warning terminal and a database.

[0034] The coal conveyor monitoring module is respectively connected to the environmental area monitoring module, the database and the early warning terminal; the environmental area monitoring module is respectively connected to the coal conveyor monitoring module, the fixed-point monitoring module, the database and the early warning terminal; the fixed-point monitoring module is respectively connected to the environmental area monitoring module, the personnel safety protection module, the database and the early warning terminal; the personnel safety protection module is respectively connected to the fixed-point monitoring module, the database and the early warning terminal.

[0035] The coal conveyor monitoring module is used to arrange various collection points on the coal conveyor in the thermal power plant, collect the temperature of the corresponding collection points on the coal conveyor in the thermal power plant, and judge whether the temperature on the coal conveyor in the thermal power plant is too high. If the temperature on the coal conveyor in the thermal power plant is too high, a signal is sent to the early warning terminal;

[0036] It should be noted that the temperature of each collection point on the coal conveyor in the thermal power plant is collected by using the on-board infrared thermal imager carried by the inspection robot.

[0037] As an optional implementation method, the determination of whether the temperature in the thermal power plant is too high is specifically determined as follows: the temperatures of the corresponding collection points on the coal conveyor in the thermal power plant are compared with the temperature threshold stored in the database; if the temperature of a certain collection point on the coal conveyor in the thermal power plant is greater than or equal to the temperature threshold stored in the database, it is determined that the temperature on the coal conveyor in the thermal power plant is too high; if the temperature of a certain collection point on the coal conveyor in the thermal power plant is less than the temperature threshold stored in the database, it is determined that the temperature on the coal conveyor in the thermal power plant is not too high.

[0038] The environmental area monitoring module is used to arrange various collection time points in the thermal power plant according to the preset time intervals, and then collect the environmental information corresponding to each collection time point, wherein the environmental information includes the ambient temperature, ambient humidity, air oxygen concentration, combustible gas concentration, dust concentration and smoke concentration, analyze and obtain the corresponding environmental information evaluation coefficient in the thermal power plant, judge whether the environment in the thermal power plant is in a dangerous state, and if the environment in the thermal power plant is in a dangerous state, send a signal to the early warning terminal;

[0039] It should be noted that the environmental information corresponding to each collection time point in the thermal power plant is collected by the gas detector and the temperature and humidity sensor carried by the inspection robot in the thermal power plant.

[0040] It should also be noted that the combustible gas concentration includes but is not limited to hydrogen sulfide concentration and methane concentration.

[0041] As an optional implementation manner, the specific judgment process of judging whether the environment in the thermal power plant is in a dangerous state is as follows:

[0042] According to the corresponding air oxygen concentration, combustible gas concentration, dust concentration and smoke concentration in the thermal power plant, the air environment assessment coefficient corresponding to each sampling time point in the thermal power plant is analyzed;

[0043] By calculating the formula The corresponding environmental information evaluation coefficient in the thermal power plant is calculated, where ζ is the corresponding environmental information evaluation coefficient in the thermal power plant, At i is the ambient temperature corresponding to the i-th collection time point in the thermal power plant, i is the number corresponding to each collection time point, i = 1, 2...n, Ah i is the ambient humidity corresponding to the i-th acquisition time point in the thermal power plant, At′ is the set ambient temperature reference value, Ah′ is the set ambient humidity reference value, ζ2 i is the air environment assessment coefficient corresponding to the i-th collection time point in the thermal power plant, ζ2′ is the set reference air environment assessment coefficient, σ1, σ2, σ2 are the weight factors corresponding to the ambient temperature, ambient humidity, and air environment assessment coefficient, respectively;

[0044] The corresponding environmental information assessment coefficient in the thermal power plant is compared with the environmental information assessment coefficient threshold stored in the database. If the corresponding environmental information assessment coefficient in the thermal power plant is greater than or equal to the environmental information assessment coefficient threshold stored in the database, it is determined that the environment in the thermal power plant is in a normal state. If the corresponding environmental information assessment coefficient in the thermal power plant is less than the environmental information assessment coefficient threshold stored in the database, it is determined that the environment in the thermal power plant is in a dangerous state.

[0045] As an optional implementation method, the analysis obtains the air environment assessment coefficient corresponding to each collection time point in the thermal power plant, and the specific analysis process is as follows:

[0046] By calculating the formula The air environment assessment coefficient corresponding to each sampling time point in the thermal power plant is calculated, where ζ2 i is the air environment assessment coefficient corresponding to the i-th collection time point in the thermal power plant, Ac i is the air oxygen concentration corresponding to the i-th sampling time point in the thermal power plant, Tc i is the combustible gas concentration corresponding to the i-th acquisition time point in the thermal power plant, Dc i is the dust concentration corresponding to the i-th collection time point in the thermal power plant, Sc i is the smoke concentration corresponding to the i-th collection time point in the thermal power plant, Ac′ is the set reference value of air oxygen concentration, Tc′ is the set reference value of combustible gas concentration, Dc′ is the set reference value of dust concentration, Sc′ is the set reference value of smoke concentration, ω1, ω2, ω3, and ω4 are the weight factors corresponding to the set air oxygen concentration, combustible gas concentration, dust concentration, and smoke concentration, respectively.

[0047] The fixed-point monitoring module is used to collect the operation status diagram corresponding to the coal conveyor in the thermal power plant through the camera at each collection time point, collect the coal flow rate and coal flow pressure corresponding to the coal drop pipe at each collection time point, analyze and obtain the blockage assessment coefficient corresponding to the coal drop pipe at each collection time point in the thermal power plant, and analyze and obtain the operation status assessment coefficient corresponding to the coal conveyor at each collection time point in the thermal power plant through the coal conveyor operation status diagram corresponding to each collection time point in the thermal power plant and the blockage assessment coefficient corresponding to the coal drop pipe, and judge whether the operation status of the coal conveyor corresponding to each collection time point in the thermal power plant is healthy. If the operation status of the coal conveyor corresponding to a certain collection time point in the thermal power plant is unhealthy, a signal is sent to the early warning terminal;

[0048] It should be noted that the coal flow rate and coal flow pressure corresponding to the coal drop pipe at each acquisition time point are obtained through the flow sensor and pressure sensor corresponding to the coal drop pipe in the thermal power plant.

[0049] As an optional implementation method, the analysis obtains the blockage assessment coefficient corresponding to the coal drop pipe at each acquisition time point in the thermal power plant, and the specific analysis process is as follows:

[0050] By calculating the formula The blockage assessment coefficient corresponding to the coal drop pipe at each acquisition time point in the thermal power plant is calculated, where β iis the blockage assessment coefficient of the coal pipe corresponding to the i-th collection time point in the thermal power plant, i is the number corresponding to each collection time point, i = 1, 2...n, Cf i is the coal flow corresponding to the i-th collection time point in the thermal power plant, P i is the coal flow pressure corresponding to the i-th acquisition time point in the thermal power plant, Cf′ is the set coal flow reference value, P′ is the set coal flow pressure reference value, α1 and α2 are the weight factors corresponding to the set coal flow and coal flow pressure, respectively.

[0051] It should be noted that, when the coal flow rate is larger and the coal flow pressure is smaller, the blockage assessment coefficient is smaller.

[0052] As an optional implementation method, the analysis obtains the operating status evaluation coefficient corresponding to the coal conveyor at each acquisition time point in the thermal power plant, and the specific judgment process is as follows:

[0053] Obtain the coal conveyor belt operation image corresponding to each acquisition time point in the thermal power plant from the coal conveyor operation status diagram corresponding to each acquisition time point in the thermal power plant, compare the coal conveyor belt operation images corresponding to each acquisition time point in the thermal power plant in the order of each acquisition time point, and obtain the overlap area of ​​the coal conveyor belt operation images corresponding to each acquisition time point in the thermal power plant; obtain the coal conveyor operation noise value corresponding to each acquisition time point from the sound sensor corresponding to the coal conveyor in the thermal power plant; obtain the electromagnetic pulse signal corresponding to the operation of the coal conveyor belt at each acquisition time point in the thermal power plant from the belt tear detection device corresponding to the coal conveyor in the thermal power plant, and then obtain the electromagnetic pulse signal amplitude corresponding to the operation of the coal conveyor belt at each acquisition time point in the thermal power plant through a waveform conversion circuit;

[0054] By calculating the formula The operating status evaluation coefficient of the coal conveyor corresponding to each acquisition time point in the thermal power plant is calculated, where δ i is the operating status evaluation coefficient of the coal conveyor corresponding to the i-th collection time point in the thermal power plant, i is the number corresponding to each collection time point, i = 1, 2...n, Sp i 、Sp i+1 are the overlap areas of the coal conveyor belt operation images corresponding to the i-th acquisition time point and the i+1-th acquisition time point in the thermal power plant, ΔSp is the set allowable deviation value of the overlap area of ​​the belt operation image, and No i is the noise value of the coal conveyor operation corresponding to the i-th sampling time point in the thermal power plant, No′ is the set allowable noise value of the coal conveyor operation, are the electromagnetic pulse signal amplitudes corresponding to the coal conveyor belt operation at the i-th acquisition time point, the i+1-th acquisition time point, and the i+2-th acquisition time point in the thermal power plant, respectively. i is the blockage assessment coefficient of the coal drop pipe at the i-th acquisition time point in the thermal power plant. ε1, ε2, and ε3 are the weight factors corresponding to the overlap area of ​​the belt running image, the coal conveyor running noise value, and the electromagnetic pulse signal amplitude, respectively.

[0055] As an optional implementation method, the method of judging whether the operating status of the coal conveyor corresponding to each collection time point in the thermal power plant is healthy, specifically comprises the following judgment process: comparing the operating status evaluation coefficient corresponding to the coal conveyor at each collection time point in the thermal power plant with the operating status evaluation coefficient threshold stored in the database; if the operating status evaluation coefficient corresponding to the coal conveyor at a certain collection time point in the thermal power plant is less than the operating status evaluation coefficient threshold stored in the database, then it is judged that the operating status of the coal conveyor corresponding to the collection time point in the thermal power plant is healthy; if the operating status evaluation coefficient corresponding to the coal conveyor at a certain collection time point in the thermal power plant is greater than or equal to the operating status evaluation coefficient threshold stored in the database, then it is judged that the operating status of the coal conveyor corresponding to the collection time point in the thermal power plant is unhealthy.

[0056] The personnel safety protection module is used to collect images of each staff member corresponding to each collection time point in the thermal power plant through a camera, and determine whether each staff member corresponding to each collection time point in the thermal power plant has dangerous behavior. If a staff member has dangerous behavior at a certain collection time point in the thermal power plant, a signal is sent to the early warning terminal;

[0057] As an optional implementation method, the specific judgment process of judging whether each worker corresponding to each collection time point in the thermal power plant wears safety protection equipment is as follows:

[0058] The safety protection equipment images of each staff member corresponding to each acquisition time point in the thermal power plant are extracted from the images of each staff member corresponding to each acquisition time point in the thermal power plant, and the safety protection equipment images of each staff member corresponding to each acquisition time point in the thermal power plant are compared with the safety protection equipment images stored in the database. If the safety protection equipment image of a staff member corresponding to a certain acquisition time point in the thermal power plant is inconsistent with the safety protection equipment image stored in the database, it is determined that the staff member corresponding to the acquisition time point is not wearing safety protection equipment.

[0059] As an optional implementation method, the determination of whether each worker corresponding to each collection time point in the thermal power plant is too close to the coal conveyor belt is performed in the following specific determination process:

[0060] The distance between each staff member and the coal conveyor belt in the thermal power plant at each collection time point in the thermal power plant is extracted from the images of each staff member corresponding to each collection time point in the thermal power plant, and the belt distance corresponding to each staff member at each collection time point is obtained. The belt distance corresponding to each staff member at each collection time point is compared with the safety distance stored in the database. If the belt distance corresponding to each staff member at each collection time point is greater than or equal to the safety distance stored in the database, it is determined that the staff member is not too close to the belt at the collection time point in the thermal power plant. If the belt distance corresponding to each staff member at each collection time point is less than the safety distance stored in the database, it is determined that the staff member is too close to the belt at the collection time point in the thermal power plant.

[0061] The database is used to store temperature thresholds, environmental information evaluation coefficient thresholds, operating status evaluation coefficient thresholds, safety protection equipment images and safety distances.

[0062] The early warning terminal is used to issue early warning prompts when the temperature on the coal conveyor in the thermal power plant is too high, the environment in the thermal power plant is in a dangerous state, the operating state of the coal conveyor corresponding to a certain collection time point in the thermal power plant is unhealthy, or a staff member in the thermal power plant has dangerous behavior at a certain collection time point.

[0063] The embodiments of the present invention can realize functions such as instant, reliable and stable perception of coal drop pipe blockage, coal conveyor belt tearing, and on-site ambient temperature by real-time monitoring and analysis of the coal conveyor and the coal conveyor area, thereby achieving uninterrupted coal conveyor belt inspection throughout the day and real-time monitoring of hidden dangers such as coal drop pipe blockage, coal conveyor belt tearing, and coal conveyor belt deviation, thereby comprehensively improving the safety, reliability and timeliness of the coal conveying system, not only reducing the workload of on-site inspection personnel, but also ensuring their life safety, improving the inherent safety level of the production site, and improving the intelligent detection level of the coal conveying system. At the same time, it creates the underlying data conditions and application foundation for the more comprehensive intelligence of the overall coal conveying system of the thermal power plant.

[0064] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. Intelligent monitoring and early warning system for fuel system, characterized by: include: The coal conveyor monitoring module is used to arrange various collection points on the coal conveyor in the thermal power plant, collect the temperature of the corresponding collection points on the coal conveyor in the thermal power plant, and judge whether the temperature on the coal conveyor in the thermal power plant is too high. If the temperature on the coal conveyor in the thermal power plant is too high, a signal is sent to the early warning terminal; The environmental area monitoring module is used to arrange various collection time points in the thermal power plant according to the preset time intervals, and then collect the environmental information corresponding to each collection time point, wherein the environmental information includes the ambient temperature, ambient humidity, air oxygen concentration, combustible gas concentration, dust concentration and smoke concentration, analyze and obtain the corresponding environmental information evaluation coefficient in the thermal power plant, judge whether the environment in the thermal power plant is in a dangerous state, and if the environment in the thermal power plant is in a dangerous state, send a signal to the early warning terminal; The fixed-point monitoring module is used to collect the operation status diagram corresponding to the coal conveyor in the thermal power plant through the camera at each collection time point, collect the coal flow rate and coal flow pressure corresponding to the coal drop pipe at each collection time point, analyze and obtain the blockage assessment coefficient corresponding to the coal drop pipe at each collection time point in the thermal power plant, and analyze and obtain the operation status assessment coefficient corresponding to the coal conveyor at each collection time point in the thermal power plant through the coal conveyor operation status diagram corresponding to each collection time point in the thermal power plant and the blockage assessment coefficient corresponding to the coal drop pipe, and judge whether the operation status of the coal conveyor corresponding to each collection time point in the thermal power plant is healthy. If the operation status of the coal conveyor corresponding to a certain collection time point in the thermal power plant is unhealthy, a signal is sent to the early warning terminal; The analysis obtains the blockage assessment coefficient corresponding to the coal drop pipe at each acquisition time point in the thermal power plant. The specific analysis process is as follows: By calculating the formula The blockage assessment coefficient corresponding to the coal drop pipe at each acquisition time point in the thermal power plant is calculated, where β i is the blockage assessment coefficient of the coal pipe corresponding to the i-th collection time point in the thermal power plant, i is the number corresponding to each collection time point, i = 1, 2...n, Cf i is the coal flow corresponding to the i-th collection time point in the thermal power plant, P i is the coal flow pressure corresponding to the i-th acquisition time point in the thermal power plant, Cf′ is the set coal flow reference value, P′ is the set coal flow pressure reference value, α1 and α2 are the weight factors corresponding to the set coal flow and coal flow pressure respectively; The personnel safety protection module is used to collect images of each staff member corresponding to each collection time point in the thermal power plant through a camera, and determine whether each staff member corresponding to each collection time point in the thermal power plant has dangerous behavior. If a staff member has dangerous behavior at a certain collection time point in the thermal power plant, a signal is sent to the early warning terminal; The early warning terminal is used to issue early warning prompts when the temperature on the coal conveyor in the thermal power plant is too high, the environment in the thermal power plant is in a dangerous state, the operating state of the coal conveyor corresponding to a certain collection time point in the thermal power plant is unhealthy, or a staff member in the thermal power plant has dangerous behavior at a certain collection time point.

2. The intelligent monitoring and early warning system for the fuel system according to claim 1, characterized in that: The specific judgment process of judging whether the temperature in the thermal power plant is too high is as follows: comparing the temperatures of the corresponding collection points on the coal conveyor in the thermal power plant with the temperature threshold stored in the database; if the temperature of a certain collection point on the coal conveyor in the thermal power plant is greater than or equal to the temperature threshold stored in the database, it is judged that the temperature on the coal conveyor in the thermal power plant is too high; if the temperature of a certain collection point on the coal conveyor in the thermal power plant is less than the temperature threshold stored in the database, it is judged that the temperature on the coal conveyor in the thermal power plant is not too high.

3. The intelligent monitoring and early warning system for the fuel system according to claim 1, characterized in that: The specific process of judging whether the environment in the thermal power plant is in a dangerous state is as follows: According to the corresponding air oxygen concentration, combustible gas concentration, dust concentration and smoke concentration in the thermal power plant, the air environment assessment coefficient corresponding to each sampling time point in the thermal power plant is analyzed; By calculating the formula The corresponding environmental information evaluation coefficient in the thermal power plant is calculated, where ζ is the corresponding environmental information evaluation coefficient in the thermal power plant, At i is the ambient temperature corresponding to the i-th collection time point in the thermal power plant, i is the number corresponding to each collection time point, i = 1, 2...n, Ah i is the ambient humidity corresponding to the i-th acquisition time point in the thermal power plant, At′ is the set ambient temperature reference value, Ah′ is the set ambient humidity reference value, ζ2 i is the air environment assessment coefficient corresponding to the i-th collection time point in the thermal power plant, ζ2′ is the set reference air environment assessment coefficient, σ1, σ2, σ2 are the weight factors corresponding to the ambient temperature, ambient humidity, and air environment assessment coefficient, respectively; The corresponding environmental information assessment coefficient in the thermal power plant is compared with the environmental information assessment coefficient threshold stored in the database. If the corresponding environmental information assessment coefficient in the thermal power plant is greater than or equal to the environmental information assessment coefficient threshold stored in the database, it is determined that the environment in the thermal power plant is in a normal state. If the corresponding environmental information assessment coefficient in the thermal power plant is less than the environmental information assessment coefficient threshold stored in the database, it is determined that the environment in the thermal power plant is in a dangerous state.

4. The intelligent monitoring and early warning system for the fuel system as claimed in claim 3, characterized in that: The analysis obtains the air environment assessment coefficient corresponding to each collection time point in the thermal power plant. The specific analysis process is as follows: By calculating the formula The air environment assessment coefficient corresponding to each sampling time point in the thermal power plant is calculated, where ζ2 i is the air environment assessment coefficient corresponding to the i-th collection time point in the thermal power plant, Ac i is the air oxygen concentration corresponding to the i-th sampling time point in the thermal power plant, Tc i is the combustible gas concentration corresponding to the i-th acquisition time point in the thermal power plant, Dc i is the dust concentration corresponding to the i-th collection time point in the thermal power plant, Sc i is the smoke concentration corresponding to the i-th collection time point in the thermal power plant, Ac′ is the set reference value of air oxygen concentration, Tc′ is the set reference value of combustible gas concentration, Dc′ is the set reference value of dust concentration, Sc′ is the set reference value of smoke concentration, ω1, ω2, ω3, and ω4 are the weight factors corresponding to the set air oxygen concentration, combustible gas concentration, dust concentration, and smoke concentration, respectively.

5. The intelligent monitoring and early warning system for the fuel system according to claim 1, characterized in that: The analysis obtains the operating status evaluation coefficient corresponding to the coal conveyor at each acquisition time point in the thermal power plant. The specific judgment process is as follows: Obtain the coal conveyor belt operation image corresponding to each acquisition time point in the thermal power plant from the coal conveyor operation status diagram corresponding to each acquisition time point in the thermal power plant, compare the coal conveyor belt operation images corresponding to each acquisition time point in the thermal power plant in the order of each acquisition time point, and obtain the overlap area of ​​the coal conveyor belt operation images corresponding to each acquisition time point in the thermal power plant; obtain the coal conveyor operation noise value corresponding to each acquisition time point from the sound sensor corresponding to the coal conveyor in the thermal power plant; obtain the electromagnetic pulse signal corresponding to the operation of the coal conveyor belt at each acquisition time point in the thermal power plant from the belt tear detection device corresponding to the coal conveyor in the thermal power plant, and then obtain the electromagnetic pulse signal amplitude corresponding to the operation of the coal conveyor belt at each acquisition time point in the thermal power plant through a waveform conversion circuit; By calculating the formula The operating status evaluation coefficient of the coal conveyor corresponding to each acquisition time point in the thermal power plant is calculated, where δ i is the operating status evaluation coefficient of the coal conveyor corresponding to the i-th collection time point in the thermal power plant, i is the number corresponding to each collection time point, i = 1, 2...n, Sp i 、Sp i+1 are the overlap areas of the coal conveyor belt operation images corresponding to the i-th acquisition time point and the i+1-th acquisition time point in the thermal power plant, ΔSp is the set allowable deviation value of the overlap area of ​​the belt operation image, and No i is the noise value of the coal conveyor operation corresponding to the i-th sampling time point in the thermal power plant, No′ is the set allowable noise value of the coal conveyor operation, are the electromagnetic pulse signal amplitudes corresponding to the coal conveyor belt operation at the i-th acquisition time point, the i+1-th acquisition time point, and the i+2-th acquisition time point in the thermal power plant, respectively. i is the blockage assessment coefficient of the coal drop pipe at the i-th acquisition time point in the thermal power plant. ε1, ε2, and ε3 are the weight factors corresponding to the overlap area of ​​the belt running image, the coal conveyor running noise value, and the electromagnetic pulse signal amplitude, respectively.

6. The intelligent monitoring and early warning system for the fuel system according to claim 1, characterized in that: The method for judging whether the operating status of the coal conveyor corresponding to each collection time point in the thermal power plant is healthy is specifically judged as follows: comparing the operating status evaluation coefficient corresponding to the coal conveyor at each collection time point in the thermal power plant with the operating status evaluation coefficient threshold stored in the database; if the operating status evaluation coefficient corresponding to the coal conveyor at a certain collection time point in the thermal power plant is less than the operating status evaluation coefficient threshold stored in the database, then it is judged that the operating status of the coal conveyor corresponding to the collection time point in the thermal power plant is healthy; if the operating status evaluation coefficient corresponding to the coal conveyor at a certain collection time point in the thermal power plant is greater than or equal to the operating status evaluation coefficient threshold stored in the database, then it is judged that the operating status of the coal conveyor corresponding to the collection time point in the thermal power plant is unhealthy.

7. The intelligent monitoring and early warning system for the fuel system as claimed in claim 1, characterized in that: The specific judgment process of judging whether each staff member corresponding to each collection time point in the thermal power plant has dangerous behavior is as follows: Extracting the images of the safety protection equipment of each worker corresponding to each acquisition time point in the thermal power plant from the images of each worker corresponding to each acquisition time point in the thermal power plant, and judging whether the safety protection status of each worker corresponding to each acquisition time point in the thermal power plant is insufficient; Extract the distance between each staff member and the coal conveyor belt in the thermal power plant at each acquisition time point from the images of each staff member corresponding to each acquisition time point in the thermal power plant, obtain the belt distance corresponding to each staff member at each acquisition time point, compare the belt distance corresponding to each staff member at each acquisition time point with the safety distance stored in the database, if the belt distance corresponding to each staff member at each acquisition time point is greater than or equal to the safety distance stored in the database, then it is determined that the staff member at the acquisition time point in the thermal power plant is at a safe distance, if the belt distance corresponding to each staff member at each acquisition time point is less than the safety distance stored in the database, then it is determined that the staff member at the acquisition time point in the thermal power plant is at a dangerous distance; When a worker corresponding to a certain collection time point in a thermal power plant is in an insufficient safety protection state or is at a dangerous distance, it is determined whether the workers corresponding to each collection time point in the thermal power plant have any dangerous behavior. In this way, it is determined whether the workers corresponding to each collection time point in the thermal power plant have any dangerous behavior.

8. The intelligent monitoring and early warning system for the fuel system as claimed in claim 7, characterized in that: The specific judgment process of judging whether the safety protection status of each staff member corresponding to each collection time point is insufficient is as follows: comparing the safety protection equipment image of each staff member corresponding to each collection time point in the thermal power plant with the safety protection equipment image stored in the database; if the safety protection equipment image of a staff member corresponding to a certain collection time point in the thermal power plant is inconsistent with the safety protection equipment image stored in the database, it is judged that the safety protection status of this staff member corresponding to the collection time point is insufficient, and in this way, it is judged whether the safety protection status of each staff member corresponding to each collection time point is insufficient.

9. The intelligent monitoring and early warning system for the fuel system as claimed in claim 1, characterized in that: It also includes a database for storing temperature thresholds, environmental information assessment coefficient thresholds, operating status assessment coefficient thresholds, safety protection equipment images and safety distances.

Images