Industrial smoke monitoring method and system with filter bag life prediction

Abstract

The present invention provides an industrial smoke monitoring method and system with the ability to predict the life of filter bags. The method sets sensors at the air inlet and air outlet of a bag dust collector, and the sensors are used to collect the smoke temperature, smoke humidity, smoke concentration, air intake volume at the air inlet, and smoke concentration at the air outlet in real time; based on the collected data, the real-time filtration efficiency and resistance of the filter bag are calculated, and a mathematical model between the filter bag resistance and the filter bag life is established; according to the mathematical model, the life of the filter bag is predicted by monitoring the resistance change of the filter bag, and the replacement time of the filter bag is determined; the method can accurately calculate the real-time filtration efficiency and resistance of the filter bag, and achieve accurate prediction of the filter bag life.

Description

Technical Field

[0001] The invention belongs to the technical field of industrial smoke monitoring, and in particular relates to an industrial smoke monitoring method and system capable of predicting the life of a filter bag. Background Art

[0002] Dust emissions are unavoidable in industrial production, and their effective treatment is crucial for environmental protection and worker health. As core equipment for industrial dust treatment, the performance of bag filters directly impacts dust removal efficiency and operating costs. Filter bags, critical components of bag filters, have a lifespan that directly determines the dust collector's maintenance cycle and overall operating efficiency. However, traditional filter bag replacement strategies often rely on empirical judgment or scheduled replacement. This approach can lead to premature bag replacement, resulting in wasteful resources, and untimely replacement can compromise dust removal effectiveness and even cause equipment failure.

[0003] Most existing technologies are still at the stage of manual operation and human judgment, lacking intelligent and automated solutions. They cannot dynamically adjust the filter bag maintenance strategy based on real-time data. As production conditions change, the load and wear of the filter bags will also change. Traditional methods cannot respond to these changes in a timely manner, causing maintenance strategies to lag behind actual needs.

[0004] Therefore, there is an urgent need for a monitoring method that can predict the life of filter bags in industrial smoke monitoring. Summary of the Invention

[0005] The present invention provides a monitoring system based on sensors and mathematical models, which can realize industrial smoke monitoring and simultaneously achieve the purpose of predicting the life of filter bags.

[0006] The technical solutions of the present invention are as follows:

[0007] An industrial smoke monitoring method for predicting filter bag life comprises the following steps:

[0008] In step S1, sensors are installed at the air inlet and outlet of the bag filter, and the sensors are used to collect the smoke temperature, smoke humidity, smoke concentration, air volume at the air inlet and smoke concentration at the air outlet in real time.

[0009] Step S2: Based on the collected data, the real-time filtration efficiency and resistance of the filter bag are calculated, and a mathematical model between the filter bag resistance and the filter bag life is established.

[0010] The calculation formula for the filtration efficiency of the filter bag is: Among them, η is the filtration efficiency of the filter bag, C in is the inlet flue gas concentration, C out is the exhaust gas concentration.

[0011] Assuming the time of filter bag replacement is the initial time 0, R0 is the initial resistance of the filter bag, then the resistance R(t) of the filter bag at time t is expressed by the nonlinear equation:

[0012]

[0013] Where M is the dust accumulation capacity of the filter bag, M max is the maximum dust accumulation threshold, M=∫Q in C in (1-η)dt;Q in Indicates the air intake volume, C in represents the inlet smoke concentration, η represents the filtration efficiency, t is the time variable; β is the current average wind speed v avg , Flue gas temperature at the air inlet T in 、Humidity H in Related variables, Among them, a and b are constants greater than 0, which are related to the material of the filter bag and are obtained by fitting historical data.

[0014] The current average wind speed v avg The calculation method is: Among them, A tot is the effective filtration area of ​​the filter bag;

[0015] For cylindrical filter bags, the effective filtration area A tot =πDL, D is the diameter of the filter bag, L is the length of the filter bag;

[0016] For flat filter bags, the effective filtration area A tot =2WL, ​​W is the width of the filter bag.

[0017] Step S3: Based on the mathematical model, the life of the filter bag is predicted by monitoring the resistance change of the filter bag, and the replacement time of the filter bag is determined.

[0018] Set the resistance threshold when the filter bag fails to be R max , the R max It is obtained by measuring the resistance of the historical filter bag in the failure state. Suppose the resistance of n filter bags of the same material in the failure state are R1, R2, ... R n ,but 1.1≤k≤1.3.

[0019] The dust accumulation amount of the filter bag and the resistance R(t) of the filter bag at time t are monitored in real time.

[0020] If M≥M max When the filter bag is cleaned manually, it is necessary to clean the filter bag manually.

[0021] If M <M max And R(t) <Rmax When the resistance threshold of the filter bag failure is R max Substitute into the nonlinear equation, so that The solution t′ of the equation is obtained, and the predicted remaining life of the filter bag Δt=t ′ -t.

[0022] If M <M max And R(t)≥R max When the filter bag is dirty, it is necessary to replace the filter bag in time.

[0023] Based on the same inventive concept, the present invention also provides an industrial smoke monitoring system with a function of predicting filter bag life, which is used to execute the industrial smoke monitoring method of the present invention. The system includes: a data acquisition module, a model building module and a life prediction module connected in sequence.

[0024] The data acquisition module is based on sensors set at the air inlet and air outlet of the bag dust collector to collect the flue gas temperature, flue gas humidity, flue gas concentration, air intake volume and flue gas concentration at the air inlet in real time.

[0025] The model building module calculates the real-time filtration efficiency and resistance of the filter bag based on the collected data, and establishes a mathematical model between the filter bag resistance and the filter bag life.

[0026] The life prediction module predicts the life of the filter bag based on the mathematical model by monitoring the resistance change of the filter bag and determines the replacement time of the filter bag.

[0027] Compared with the prior art, the present invention has the following beneficial effects:

[0028] The present invention monitors various parameters of the air inlet and outlet in real time, and in combination with the established mathematical model, can accurately calculate the real-time filtration efficiency and resistance of the filter bag, thereby realizing accurate prediction of the life of the filter bag; this prediction method is more scientific than the traditional replacement method based on experience or fixed period; the present invention not only predicts the life of the filter bag, but also provides a strategy to guide cleaning and replacement based on the real-time monitoring results of the dust accumulation and resistance of the filter bag; when the dust accumulation of the filter bag reaches the set threshold, manual cleaning is performed; when it is predicted that the remaining life of the filter bag is insufficient, replacement is arranged in time. These measures can maximize the service life of the filter bag, improve the dust removal efficiency, and reduce the additional cost caused by frequent replacement of filter bags. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 This is a flow chart of the industrial smoke monitoring method capable of predicting filter bag life according to the present invention;

[0030] Figure 2 This is a schematic diagram of the industrial smoke monitoring system capable of predicting filter bag life according to the present invention. DETAILED DESCRIPTION

[0031] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention are described clearly and completely below. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts are within the scope of protection of the present invention.

[0032] Example 1

[0033] like Figure 1 FIG. 1 is a flow chart of an industrial smoke monitoring method for predicting filter bag life, wherein the method comprises the following steps:

[0034] An industrial smoke monitoring method for predicting filter bag life comprises the following steps:

[0035] In step S1, sensors are installed at the air inlet and outlet of the bag filter, and the sensors are used to collect the smoke temperature, smoke humidity, smoke concentration, air volume at the air inlet and smoke concentration at the air outlet in real time.

[0036] In order to accurately predict the life of the filter bags, it is first necessary to install sensors at key locations of the bag dust collector to collect key parameters reflecting the working status of the filter bags in real time. Specifically, the sensors should be installed at the air inlet and outlet; the flue gas temperature reflects the thermal state of the incoming flue gas and has a direct impact on the thermal stability of the filter bag material; the flue gas humidity: too high humidity can easily cause condensation on the filter bags, accelerating corrosion and clogging of the filter bags; the difference between the inlet concentration and the outlet concentration reflects the filtration efficiency of the filter bags and is an important indicator for evaluating the performance of the filter bags; the air intake volume directly affects the dust accumulation speed and resistance changes of the filter bags.

[0037] Step S2: Based on the collected data, the real-time filtration efficiency and resistance of the filter bag are calculated, and a mathematical model between the filter bag resistance and the filter bag life is established.

[0038] The calculation formula for the filtration efficiency of the filter bag is: Among them, η is the filtration efficiency of the filter bag, C in is the inlet flue gas concentration, C out is the exhaust gas concentration.

[0039] Assuming the time of filter bag replacement is the initial time 0, R0 is the initial resistance of the filter bag, then the resistance R(t) of the filter bag at time t is expressed by the nonlinear equation:

[0040]

[0041] Where M is the dust accumulation capacity of the filter bag, M max is the maximum dust accumulation threshold, M=∫Q in Cin (1-η)dt;Q in Indicates the air intake volume, C in represents the inlet smoke concentration, η represents the filtration efficiency, t is the time variable; β is the current average wind speed v avg , Flue gas temperature at the air inlet T in 、Humidity H in Related variables, Among them, a and b are constants greater than 0, which are related to the material of the filter bag and are obtained by fitting historical data.

[0042] The current average wind speed v avg The calculation method is: Among them, A tot is the effective filtration area of ​​the filter bag;

[0043] For cylindrical filter bags, the effective filtration area A tot =πDL, D is the diameter of the filter bag, L is the length of the filter bag;

[0044] For flat filter bags, the effective filtration area A tot =2WL, ​​W is the width of the filter bag.

[0045] Step S3: Based on the mathematical model, the life of the filter bag is predicted by monitoring the resistance change of the filter bag, and the replacement time of the filter bag is determined.

[0046] Set the resistance threshold when the filter bag fails to be R max , the R max It is obtained by measuring the resistance of the historical filter bag in the failure state. Suppose the resistance of n filter bags of the same material in the failure state are R1, R2, ... R n ,but 1.1≤k≤1.3.

[0047] The dust accumulation amount of the filter bag and the resistance R(t) of the filter bag at time t are monitored in real time.

[0048] If M≥M max When the filter bag is cleaned manually, it is necessary to clean the filter bag manually.

[0049] If M <M max And R(t) <R max When the resistance threshold of the filter bag failure is R max Substitute into the nonlinear equation, so that The positive solution t′ of the equation is obtained, and the predicted remaining life of the filter bag Δt=t ′ -t; t′ is obtained by solving the nonlinear equation R max The corresponding time point.

[0050] If M <Mmax And R(t)≥R max When the filter bag is dirty, it is necessary to replace the filter bag in time.

[0051] Example 2

[0052] like Figure 2 As shown, a schematic diagram of an industrial smoke monitoring system with the function of predicting filter bag life is shown, which is used to execute the industrial smoke monitoring method of Example 1. The system includes: a data acquisition module, a model building module and a life prediction module connected in sequence.

[0053] The data acquisition module is based on sensors set at the air inlet and air outlet of the bag dust collector to collect the flue gas temperature, flue gas humidity, flue gas concentration, air intake volume and flue gas concentration at the air inlet in real time.

[0054] The model building module calculates the real-time filtration efficiency and resistance of the filter bag based on the collected data, and establishes a mathematical model between the filter bag resistance and the filter bag life.

[0055] The life prediction module predicts the life of the filter bag based on the mathematical model by monitoring the resistance change of the filter bag and determines the replacement time of the filter bag.

[0056] It should be noted that those skilled in the art will appreciate that various modifications and equivalent substitutions may be made to the present invention without departing from the scope of the present invention. Furthermore, various modifications may be made to the present invention for specific circumstances or materials without departing from the scope of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed, but rather includes all embodiments falling within the scope of the claims of the present invention.

Claims

1. An industrial smoke monitoring method with the ability to predict filter bag life, characterized in that: The method comprises the following steps: Step S1, installing sensors at the air inlet and air outlet of the bag filter, wherein the sensors are used to collect the flue gas temperature, flue gas humidity, flue gas concentration, air volume at the air inlet, and flue gas concentration at the air outlet in real time; Step S2, based on the collected data, calculate the real-time filtration efficiency and resistance of the filter bag, and establish a mathematical model between the filter bag resistance and the filter bag life; Step S3, predicting the life of the filter bag by monitoring the resistance change of the filter bag according to the mathematical model and determining the replacement time of the filter bag; The calculation formula for the filtration efficiency of the filter bag is: Among them, η is the filtration efficiency of the filter bag, C in is the inlet flue gas concentration, C out is the exhaust gas concentration; Assuming the time of filter bag replacement is the initial time 0, R0 is the initial resistance of the filter bag, then the resistance R(t) of the filter bag at time t is expressed by the nonlinear equation: Where M is the dust accumulation capacity of the filter bag, M max is the maximum dust accumulation threshold, M=∫Q in C in (1-η)dt;Q in Indicates the air intake volume, C in represents the inlet smoke concentration, η represents the filtration efficiency, t is the time variable; β is the current average wind speed v avg , Flue gas temperature at the air inlet T in 、Humidity H in Related variables, Among them, a and b are constants greater than 0, which are related to the material of the filter bag and are obtained by fitting historical data; Set the resistance threshold when the filter bag fails to be R max , the R max It is obtained by measuring the resistance of the historical filter bag in the failure state. Assuming that the resistance of n filter bags of the same material in the failure state are R1, R2, ... R respectively, then 1.1≤k≤1.3; The dust accumulation amount of the filter bag and the resistance R(t) of the filter bag at time t are monitored in real time; If M≥M max When the filter bag is cleaned manually, If M <M max And R(t) <R max When the resistance threshold of the filter bag failure is R max Substitute into the nonlinear equation, so that The solution t′ of the equation is obtained, and the predicted remaining life of the filter bag is Δt=t′-t; If M <M max And R(t)≥R max When the filter bag is dirty, it is necessary to replace the filter bag in time.

2. The industrial smoke monitoring method with the function of predicting filter bag life according to claim 1, characterized in that: The current average wind speed v avg The calculation method is: Among them, A tot is the effective filtration area of ​​the filter bag; For cylindrical filter bags, the effective filtration area A tot =πDL, D is the diameter of the filter bag, L is the length of the filter bag; For flat filter bags, the effective filtration area A tot =2WL, ​​W is the width of the filter bag.

3. An industrial smoke monitoring system capable of predicting filter bag life, used to implement the industrial smoke monitoring method according to any one of claims 1 to 2, characterized in that: The system includes: a data acquisition module, a model building module and a life prediction module connected in sequence; The data acquisition module is based on sensors set at the air inlet and air outlet of the bag filter to collect the smoke temperature, smoke humidity, smoke concentration, air volume at the air inlet and smoke concentration at the air outlet in real time; The model building module calculates the real-time filtration efficiency and resistance of the filter bag based on the collected data, and establishes a mathematical model between the filter bag resistance and the filter bag life; The life prediction module predicts the life of the filter bag based on the mathematical model by monitoring the resistance change of the filter bag and determines the replacement time of the filter bag.

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