Fault warning system and method for bag dust collector

Abstract

The present invention discloses a fault warning system and method for a bag dust collector, which relates to the technical field of fault warning and solves the problem that the prior art promotes trouble-free operation by periodically checking the filter bags of the bag dust collector, which may result in the filter bags being discovered only after they fail, thereby increasing the maintenance cost of the bag dust collector and causing unnecessary waste of resources. The present invention collects environmental parameters in the filter bags in real time through environmental sensors; determines whether the filter bags of the dust collector can perform normal operations; if so, continues to use the bag dust collector; if not, issues a first warning signal; determines whether the filter bags need to be cleaned; if so, issues a second warning signal; if not, continues to determine; constructs a time prediction sequence based on the inspection results and the time for cleaning the filter bags; obtains the time for the next filter bag replacement based on the time prediction sequence; issues a fault warning and completes the filter bag replacement based on the time for the next filter bag replacement; the present invention effectively prevents equipment failures and reduces maintenance costs.

Description

Technical Field

[0001] The present invention belongs to the field of fault warning and relates to data analysis technology, and specifically provides a fault warning system and method for a bag dust collector. Background Art

[0002] By real-time monitoring of the operating status and key parameters of the bag dust collector, the system can immediately issue an early warning if any abnormal data appears, thereby effectively preventing safety accidents such as explosions and fires caused by excessive dust accumulation inside the equipment, excessive temperature or bag blockage; by building a fault early warning system, it can analyze based on historical data and predict potential problems in advance, allowing maintenance personnel to carry out inspections in advance, thereby significantly reducing safety hazards, thereby ensuring that the bag dust collector operates in the best condition and avoiding production line interruptions or efficiency reductions due to equipment failures; through timely maintenance and care, the service life of the bag dust collector can be extended and the replacement cost caused by equipment aging or damage can be reduced.

[0003] The existing technology promotes trouble-free operation by periodically inspecting the filter bags of the bag dust collector. However, since this method can only judge based on the working status of the bag dust collector, it may result in the bag dust collector being discovered only after it fails. In addition, the manpower and material resources consumed by periodic inspections are high, which increases the downtime and maintenance costs of the bag dust collector. Moreover, before the dust collector fails, its dust removal effect has been significantly reduced to an unusable state, which not only affects its normal function but also easily reduces its service life.

[0004] The present invention provides a bag filter fault warning system and method to solve the above technical problems. Summary of the Invention

[0005] The present invention aims to solve at least one of the technical problems existing in the prior art; to this end, the present invention proposes a fault warning system and method for a bag dust collector, which is used to solve the problem that the prior art promotes trouble-free operation by periodically inspecting the filter bags of the bag dust collector. However, since this method can only be judged based on the working status of the bag dust collector, it may result in the bag dust collector being discovered only after a fault occurs. In addition, the manpower and material resources consumed by the periodic inspection are high, which increases the downtime and maintenance cost of the bag dust collector. Moreover, before the dust collector fails, its dust removal effect has been significantly reduced to an unusable state, which not only affects its normal function but also easily reduces its service life.

[0006] To achieve the above-mentioned object, a first aspect of the present invention provides a bag filter fault warning system, comprising: a sensor monitoring module, a data analysis module, a warning response module, and a user interface module;

[0007] Sensor monitoring module: Obtain sensor installation diagrams from the database and install environmental sensors in the bag filter based on the sensor installation diagrams. The environmental sensors collect environmental parameters in the filter bags in real time, including temperature, humidity, pressure, and gas dust concentration.

[0008] Data analysis module: retrieves environmental parameters, debugs the bag filter before use, and determines whether the filter bags of the dust collector can work normally; if yes, the bag filter continues to be used; if not, an early warning signal is issued and the automatic maintenance mode of the filter bags is turned on, and several maintenance results are recorded in the database; determines whether the filter bags need to be cleaned; if yes, an early warning signal is issued and the time for cleaning the filter bags is recorded in the database; if not, the judgment continues;

[0009] Early warning response module: Constructs a time prediction sequence based on the maintenance results and the time for cleaning the filter bags; obtains the time for the next filter bag replacement based on the time prediction sequence; issues a fault warning based on the time for the next filter bag replacement and completes the filter bag replacement.

[0010] Preferably, the system further comprises: a user interface module: for providing users with real-time warning information; staff monitor the pressure drop in the filter bag according to the warning signal and operate the filter bag to enter the automatic maintenance mode.

[0011] The present invention can display the early warning information of the bag dust collector in real time through the user interface, so that the staff can quickly grasp the latest situation of the equipment. This real-time performance helps the staff to respond to the early warning signal in time to avoid further deterioration of the problem; when the early warning system detects an abnormal pressure drop in the filter bag or other conditions that require maintenance, the user interface can guide the staff to enter the automatic maintenance mode. In this mode, the equipment will automatically perform a series of inspection and repair operations, reducing the need for manual intervention and improving the accuracy and efficiency of maintenance.

[0012] Preferably, the determining whether the filter bag of the dust collector can work normally includes:

[0013] Obtain the historical pressure drop change value in the filter bag from the database and mark it as Bi;

[0014] The average value of the historical pressure drop change values ​​in the filter bag is calculated by the formula BP=Bi / i; wherein i is the number of historical pressure drop change values, i=1, 2, 3..., n; n is a positive integer;

[0015] The average value of the historical pressure drop change value is used as the change threshold to determine whether the real-time pressure drop in the filter bag is higher than the change threshold; if yes, the filter bag cannot work normally; if not, the filter bag can work normally.

[0016] The present invention calculates the average value of historical pressure drop changes and uses it as a transformation threshold, so as to timely discover the changing trend of filter bag performance. When the real-time detected pressure drop value exceeds this threshold, it indicates that there is a problem with the filter bag and needs to be dealt with in time. This method can achieve early warning of faults, avoid unplanned shutdowns caused by filter bag damage, and ensure the continuity and stability of production. It can not only effectively improve the operating efficiency and safety of the equipment, but also help enterprises save costs, improve environmental compliance, and make more informed decisions.

[0017] Preferably, the determining whether the filter bag needs to be cleaned includes:

[0018] Place gas concentration sensors at the inlet and outlet of the filter bag, mark the inlet concentration data as C1 and the outlet concentration data as C2;

[0019] The concentration ratio is calculated by the formula NZ = C1 / C2 × 100%, where C1 and C2 are both constants greater than 0;

[0020] The normal concentration ratio range is retrieved from the database to determine whether the concentration ratio falls within the normal concentration ratio range; if yes, the filter bag does not need to be cleaned; if not, the filter bag needs to be cleaned.

[0021] By measuring the gas concentration at the inlet and outlet, the present invention can accurately evaluate the filtration efficiency of the filter bag. If the concentration ratio exceeds the normal range, it means that the filtration effect of the filter bag has declined and needs to be cleaned or replaced. Once an abnormal concentration ratio is found, the system can immediately issue an alarm to remind the operator to take measures. This real-time monitoring capability helps to discover and solve problems in a timely manner, avoid production interruptions or environmental pollution caused by filter bag blockage, reduce unnecessary filter bag cleaning, and extend the service life of the filter bag.

[0022] Preferably, the time prediction sequence is constructed based on the inspection results and the time for cleaning the filter bags, including:

[0023] Retrieve the inspection results, determine the fault cause based on the inspection results, and mark it as Aj. Where j is the number of fault types, j = 1, 2, 3, 4, 5, 6, 7. Fault causes include: corrosive input gas, excessive filter bag cleaning, filter bag damage, high temperature inside the filter bag, high humidity inside the filter bag, filter media blockage, and dust cleaning system failure.

[0024] Obtain the historical filter bag cleaning time from the database, combine the historical filter bag cleaning time to count the number of filter bag cleaning times and mark it as t; set the filter bag cleaning number threshold and mark it as T;

[0025] The proportion of filter bag cleaning times is calculated using the formula LQ = t / T × 100%;

[0026] Obtain historical fault causes from the database, construct a histogram based on the current fault cause and historical fault causes, and count the proportion of each fault cause's occurrence. Build a time prediction sequence based on the proportion of fault causes' occurrences and the proportion of filter bag cleaning times.

[0027] It should be noted that the filter bag cleaning frequency threshold is set by the staff based on actual work experience.

[0028] The present invention can quickly and accurately identify the problem of the bag dust collector by retrieving the inspection results and automatically analyzing the cause of the fault. This automated identification process greatly reduces the time and error of manual judgment and improves the efficiency of fault diagnosis. By constructing a histogram to count the frequency of each fault cause, intuitive data support can be provided to equipment maintenance personnel, and these data provide a basis for formulating more effective maintenance plans. By constructing a time prediction sequence, historical data can be used to predict the cause and frequency of faults that may occur in the future.

[0029] Preferably, obtaining the time for next filter bag replacement according to the time prediction sequence includes:

[0030] Retrieve the time prediction model, input the time prediction sequence into the time prediction model, and obtain the time for next filter bag replacement; wherein, the time prediction model is constructed based on the artificial intelligence model.

[0031] Preferably, the time prediction model is constructed according to an artificial intelligence model, including:

[0032] Obtaining standard training data; wherein the standard training data includes standard input data consistent with the content attributes of the time prediction sequence and standard output data consistent with the content attributes of the time when the filter bag needs to be replaced;

[0033] The artificial intelligence model is trained using standard training data, and the trained artificial intelligence model is marked as a time prediction model; wherein the artificial intelligence model includes a convolutional neural network model or a long short-term memory neural network model.

[0034] The present invention can automatically predict the optimal replacement time of filter bags through a time prediction model, thereby reducing the subjectivity and errors of manual judgment; based on the prediction results, maintenance time and resources can be reasonably arranged, avoiding frequent inspections and unnecessary maintenance operations, thereby reducing maintenance costs; by replacing filter bags in time, it can be ensured that the bag dust collector is always in the best working condition, ensuring the continuity and stability of production.

[0035] Preferably, the method of providing a fault warning and completing the filter bag replacement according to the time of the next filter bag replacement includes:

[0036] Retrieve the next filter bag replacement time, set an inspection date before the next filter bag replacement time for manual inspection, and determine whether the filter bag has a fault during the inspection; if so, issue a fault warning and complete the filter bag replacement; if not, continue to determine.

[0037] It should be noted that the inspection date is set by the staff based on actual work experience.

[0038] The present invention achieves preventive monitoring of the filter bag status by setting the next filter bag replacement time in advance and arranging an inspection date before that time. This method helps to discover problems before the filter bag performance deteriorates significantly or fails, thereby avoiding production interruptions and environmental pollution caused by filter bag failure. At the same time, this method performs maintenance work without affecting normal production, helps to reduce downtime caused by equipment failure, and improves production efficiency and output.

[0039] To achieve the above objectives, the second aspect of the present invention provides a bag filter fault warning method:

[0040] S100: Obtain a sensor installation diagram from a database, and install an environmental sensor in the bag filter according to the sensor installation diagram; collect environmental parameters in the filter bag in real time through the environmental sensor; wherein the environmental parameters include: temperature, humidity, pressure, and gas dust concentration;

[0041] S200: Retrieve environmental parameters, debug the bag filter before use, and determine whether the filter bags of the dust collector can work normally; if yes, continue to use the bag filter; if no, issue a warning signal and start the automatic maintenance mode of the filter bags, and record several maintenance results in the database; determine whether the filter bags need to be cleaned; if yes, issue a second warning signal and record the time for cleaning the filter bags in the database; if no, continue to determine;

[0042] S300: Constructing a time prediction sequence based on the inspection results and the time for cleaning the filter bags; obtaining the time for the next filter bag replacement based on the time prediction sequence; issuing a fault warning based on the time for the next filter bag replacement and completing the filter bag replacement.

[0043] Compared with the prior art, the present invention has the following beneficial effects:

[0044] 1. By collecting key environmental parameters such as temperature, humidity, pressure and gas dust concentration in the filter bag in real time through environmental sensors, potential fault hazards can be discovered in time, which helps to avoid dust removal efficiency degradation or equipment damage caused by problems such as filter bag blockage, damage or overload operation; the data analysis module can perform intelligent analysis based on the real-time collected data to determine the working status of the dust collector filter bag. This automated and intelligent judgment mechanism reduces the need for manual intervention and improves the accuracy and timeliness of decision-making; when the system detects that the filter bag is not working properly or needs to be cleaned, it will automatically issue a warning signal and start the corresponding automatic maintenance mode, which not only reduces fault downtime, but also improves maintenance efficiency, ensures the continuous and stable operation of the dust collector, and further avoids the problem of reduced service life due to abnormal operation of the bag dust collector.

[0045] 2. The early warning response module constructs a time prediction sequence based on historical maintenance records and cleaning times, and can accurately predict the time for the next filter bag replacement. This predictive capability enables users to prepare in advance, arrange planned maintenance, and avoid production interruptions due to sudden failures; the system records each maintenance result and filter bag cleaning time in detail in the database, which provides valuable data support for subsequent analysis and optimization; at the same time, it also helps enterprises achieve full life cycle management of equipment and improve equipment efficiency and lifespan; through real-time monitoring, intelligent analysis and accurate prediction, users can minimize production losses and maintenance costs caused by equipment failure. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. 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 any creative work.

[0047] Figure 1 A schematic diagram showing the relationship between the modules included in the present invention;

[0048] Figure 2 Schematic diagram of the specific steps of data analysis of the present invention;

[0049] Figure 3 Schematic diagram of the specific steps of fault response of the present invention;

[0050] Figure 4 Schematic diagram of the fault warning process of the present invention. DETAILED DESCRIPTION

[0051] The technical solutions of the present invention will be clearly and completely described below in conjunction with the embodiments. 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 creative efforts are within the scope of protection of the present invention.

[0052] See also Figure 1 , a first aspect of the present invention provides a bag filter fault warning system, comprising: a sensor monitoring module, a data analysis module, a warning response module, and a user interface module;

[0053] Sensor monitoring module: Obtain sensor installation diagrams from the database and install environmental sensors in the bag filter based on the sensor installation diagrams. The environmental sensors collect environmental parameters in the filter bags in real time, including temperature, humidity, pressure, and gas dust concentration.

[0054] Data analysis module: retrieves environmental parameters, debugs the bag filter before use, and determines whether the filter bags of the dust collector can work normally; if yes, the bag filter continues to be used; if not, an early warning signal is issued and the automatic maintenance mode of the filter bags is turned on, and several maintenance results are recorded in the database; determines whether the filter bags need to be cleaned; if yes, an early warning signal is issued and the time for cleaning the filter bags is recorded in the database; if not, the judgment continues;

[0055] Early warning response module: Constructs a time prediction sequence based on the maintenance results and the time for cleaning the filter bags; obtains the time for the next filter bag replacement based on the time prediction sequence; issues a fault warning based on the time for the next filter bag replacement and completes the filter bag replacement.

[0056] See also Figure 2 The specific steps of data analysis are: obtain the sensor installation diagram from the database, install the environmental sensor in the bag filter according to the sensor installation diagram; use the environmental sensor to collect the environmental parameters in the filter bag in real time; the environmental parameters include: temperature, humidity, pressure and gas dust concentration; debug the bag filter before use, obtain the historical pressure drop change value in the filter bag from the database and mark it as Bi;

[0057] The average value of the historical pressure drop change values ​​in the filter bag is calculated by the formula BP=Bi / i; wherein i is the number of historical pressure drop change values, i=1, 2, 3..., n; n is a positive integer;

[0058] The average value of the historical pressure drop change value is used as the change threshold to determine whether the real-time pressure drop in the filter bag is higher than the change threshold; if yes, the filter bag cannot work normally, and an early warning signal is issued to start the automatic maintenance mode of the filter bag, and several maintenance results are recorded in the database; if no, the filter bag can work normally;

[0059] Place gas concentration sensors at the inlet and outlet of the filter bag, mark the inlet concentration data as C1 and the outlet concentration data as C2;

[0060] The concentration ratio is calculated by the formula NZ = C1 / C2 × 100%, where C1 and C2 are both constants greater than 0;

[0061] The normal concentration ratio range is retrieved from the database to determine whether the concentration ratio falls within the normal concentration ratio range; if yes, the filter bag does not need to be cleaned; if not, the filter bag needs to be cleaned.

[0062] For example, if a bag filter sensor needs to be fault-predicted, the sensor installation diagram is obtained from the database and the environmental sensor is installed in the bag filter based on the sensor installation diagram. The environmental sensor collects the environmental parameters in the filter bag in real time. Before use, the bag filter is debugged and five sets of historical pressure drop change values ​​in the filter bag are obtained from the database, namely 850Pa, 680Pa, 920Pa, 789Pa, and 876Pa.

[0063] The average value of the historical pressure drop change in the filter bag calculated by the formula BP=Bi / i is 823Pa; the average value of the historical pressure drop change is used as the conversion threshold, and the pressure drop values ​​of groups a and b are respectively 962Pa and 769Pa from the detected environmental parameters. Since the pressure drop value of group a is higher than the conversion threshold, the filter bag cannot work normally at this time, so an early warning signal is issued and the automatic repair mode of the filter bag is turned on; the pressure drop value of group b is lower than the conversion threshold, so the filter bag can work normally at this time;

[0064] Gas concentration sensors were placed at the inlet and outlet of the filter bag, and the inlet concentration data of two groups D1 and D2 at different times were measured and recorded as 455 mg / m 3 , 500mg / m 3 The two groups of outlet concentration data correspond to 15mg / m 3 , 40mg / m 3 ; Using the formula NZ=C1 / C2×100%, it is calculated that the concentration ratio of group D1 is 3.29%, and the concentration ratio of group D2 is 8%; the normal concentration ratio range is retrieved from the database, which is 1%-5%; if the concentration ratio of group D1 falls within the normal concentration ratio range, the filter bag of group D1 at the corresponding moment does not need to be cleaned; if the concentration ratio of group D2 exceeds the normal concentration ratio range, the filter bag of group D2 at the corresponding moment needs to be cleaned.

[0065] See also Figure 3, the specific steps of the fault response, retrieve the maintenance results, and determine the fault cause based on the maintenance results and mark it as Aj; where j is the number of fault types, j = 1, 2, 3, 4, 5, 6, 7; fault causes include: corrosive input gas, excessive filter bag cleaning times, filter bag damage, high temperature inside the filter bag, high humidity inside the filter bag, filter material blockage, and dust cleaning system failure;

[0066] Obtain the historical filter bag cleaning time from the database, combine the historical filter bag cleaning time to count the number of filter bag cleaning times and mark it as t; set the filter bag cleaning number threshold and mark it as T;

[0067] The proportion of filter bag cleaning times is calculated using the formula LQ = t / T × 100%;

[0068] Obtain historical fault causes from the database, construct a histogram based on the current fault cause and historical fault causes, and count the frequency ratio of each fault cause. Build a time prediction sequence based on the frequency ratio of the fault cause and the frequency ratio of the filter bag cleaning.

[0069] Retrieve the time prediction model, input the time prediction sequence into the time prediction model, and obtain the time for the next filter bag replacement; set an inspection date before the next filter bag replacement time to conduct a manual inspection to determine whether the filter bag has a fault during the inspection; if so, issue a fault warning and complete the filter bag replacement; if not, continue to determine.

[0070] For example, the inspection results of the bag sensor were retrieved. According to the inspection results, it was concluded that the fault causes of group A were high humidity in the filter bag, filter material blockage, and high temperature in the filter bag, which resulted in the filter bag needing to be replaced. The historical fault causes were obtained from the database. Among them, the filter bag was replaced 5 times in total. The filter bag was replaced once due to high humidity in the filter bag, accounting for 20% of the number of corresponding fault causes; the filter bag was replaced twice due to filter material blockage, accounting for 40% of the number of corresponding fault causes; the filter bag was replaced twice due to high temperature in the filter bag, accounting for 40% of the number of corresponding fault causes;

[0071] The filter bag cleaning frequency threshold is set to 4 times; therefore, the filter bag cleaning frequency of group A accounts for 25%;

[0072] A time prediction sequence is constructed based on the proportion of the number of failure causes and the proportion of filter bag cleaning times. The time prediction model is retrieved and the time prediction sequence is input into the time prediction model. It is found that the next time to replace the filter bag is 30 days later. A manual inspection is set 27 days before the next time to replace the filter bag. The inspection shows that the filter bag is faulty, a fault warning is issued, and the filter bag replacement is completed.

[0073] See also Figure 4The second embodiment of the present invention provides a bag filter fault warning method, comprising:

[0074] S100: Obtain a sensor installation diagram from a database, and install an environmental sensor in the bag filter according to the sensor installation diagram; collect environmental parameters in the filter bag in real time through the environmental sensor; wherein the environmental parameters include: temperature, humidity, pressure, and gas dust concentration;

[0075] S200: Retrieve environmental parameters, debug the bag filter before use, and determine whether the filter bags of the dust collector can work normally; if yes, continue to use the bag filter; if no, issue a warning signal and start the automatic maintenance mode of the filter bags, and record several maintenance results in the database; determine whether the filter bags need to be cleaned; if yes, issue a second warning signal and record the time for cleaning the filter bags in the database; if no, continue to determine;

[0076] S300: Constructing a time prediction sequence based on the inspection results and the time for cleaning the filter bags; obtaining the time for the next filter bag replacement based on the time prediction sequence; issuing a fault warning based on the time for the next filter bag replacement and completing the filter bag replacement.

[0077] Some of the data in the above formula are calculated by removing the dimensions and taking their numerical values. The formula is a formula that is closest to the actual situation obtained by software simulation of a large amount of collected data; the preset parameters and preset thresholds in the formula are set by technical personnel in this field according to actual conditions or obtained through simulation of a large amount of data.

[0078] The working principle of the present invention is as follows: the present invention obtains a sensor installation diagram from a database and installs an environmental sensor in the bag filter based on the sensor installation diagram; the environmental parameters in the filter bag are collected in real time by the environmental sensor; wherein the environmental parameters include: temperature, humidity, pressure and gas dust concentration;

[0079] Retrieve environmental parameters, debug the bag dust collector before use, and determine whether the filter bags of the dust collector can work normally; if yes, continue to use the bag dust collector; if not, issue a warning signal and start the automatic maintenance mode of the filter bags, and record several maintenance results in the database; determine whether the filter bags need to be cleaned; if yes, issue a second warning signal and record the time for cleaning the filter bags in the database; if not, continue to judge; construct a time prediction sequence based on the maintenance results and the time for cleaning the filter bags; obtain the time for the next filter bag replacement based on the time prediction sequence; issue a fault warning based on the time for the next filter bag replacement and complete the filter bag replacement.

[0080] The above embodiments are only used to illustrate the technical method of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A bag filter fault warning system, characterized in that: include: Sensor monitoring module, data analysis module, early warning response module, user interface module; Sensor monitoring module: obtains the sensor installation diagram from the database and installs the environmental sensor in the bag filter according to the sensor installation diagram; Environmental sensors collect environmental parameters in the filter bag in real time, including temperature, humidity, pressure, and gas dust concentration. Data analysis module: retrieves environmental parameters, debugs the bag filter before use, and determines whether the filter bags of the dust collector can work normally; if yes, the bag filter continues to be used; if not, an early warning signal is issued and the automatic maintenance mode of the filter bags is turned on, and several maintenance results are recorded in the database; determines whether the filter bags need to be cleaned; if yes, an early warning signal is issued and the time for cleaning the filter bags is recorded in the database; if not, the judgment continues; Early warning response module: Builds a time prediction sequence based on the inspection results and the time for cleaning the filter bags; obtains the next time to replace the filter bags based on the time prediction sequence; issues a fault warning based on the next time to replace the filter bags and completes the filter bag replacement; The time prediction sequence is constructed based on the inspection results and the time for cleaning the filter bags, including: Retrieve the maintenance results, determine the fault cause based on the results, and mark it as Aj. j is the number of fault types, j = 1, 2, 3, 4, 5, 6, 7. Fault causes include: corrosive input gas, excessive filter bag cleaning, filter bag damage, high temperature inside the filter bag, high humidity inside the filter bag, filter media blockage, and dust cleaning system failure. Obtain the historical filter bag cleaning time from the database, combine the historical filter bag cleaning time to count the number of filter bag cleaning times and mark it as t; set the filter bag cleaning number threshold and mark it as T; The proportion of filter bag cleaning times is calculated using the formula LQ=t / T×100%; Obtain historical fault causes from the database, construct a histogram based on the current fault cause and historical fault causes, and count the proportion of each fault cause's occurrence. Build a time prediction sequence based on the proportion of fault causes' occurrences and the proportion of filter bag cleaning times.

2. A bag filter fault warning system according to claim 1, characterized in that: The system also includes: a user interface module: used to provide users with real-time warning information; staff monitor the pressure drop in the filter bag according to the warning signal and operate the filter bag to enter the automatic maintenance mode.

3. The bag filter fault warning system according to claim 1, characterized in that: The determination of whether the filter bag of the dust collector can work normally includes: Obtain the historical pressure drop change value in the filter bag from the database and mark it as Bi; The average value of the historical pressure drop change value in the filter bag is calculated by the formula BP=Bi / i; where i is the number of historical pressure drop change values, i=1, 2, 3..., n; n is a positive integer; The average value of the historical pressure drop change value is used as the change threshold to determine whether the real-time pressure drop in the filter bag is higher than the change threshold; if yes, the filter bag cannot work normally; if not, the filter bag can work normally.

4. A bag filter fault warning system according to claim 1, characterized in that: The step of determining whether the filter bag needs to be cleaned includes: Place gas concentration sensors at the inlet and outlet of the filter bag, mark the inlet concentration data as C1 and the outlet concentration data as C2; The concentration ratio is calculated using the formula NZ=C1 / C2×100%, where C1 and C2 are both constants greater than 0. The normal concentration ratio range is retrieved from the database to determine whether the concentration ratio falls within the normal concentration ratio range; if yes, the filter bag does not need to be cleaned; if not, the filter bag needs to be cleaned.

5. The bag filter fault warning system according to claim 1, characterized in that: The method of obtaining the next filter bag replacement time according to the time prediction sequence includes: Retrieve the time prediction model, input the time prediction sequence into the time prediction model, and obtain the time for next filter bag replacement; wherein, the time prediction model is constructed based on the artificial intelligence model.

6. A bag filter fault warning system according to claim 5, characterized in that: The time prediction model is constructed based on an artificial intelligence model, including: Obtaining standard training data; wherein the standard training data includes standard input data consistent with the content attributes of the time prediction sequence and standard output data consistent with the content attributes of the time when the filter bag needs to be replaced; The artificial intelligence model is trained using standard training data, and the trained artificial intelligence model is marked as a time prediction model; wherein the artificial intelligence model includes a convolutional neural network model or a long short-term memory neural network model.

7. The bag filter fault warning system according to claim 1, characterized in that: The method of providing a fault warning and completing the filter bag replacement according to the next filter bag replacement time includes: Retrieve the next filter bag replacement time, set an inspection date before the next filter bag replacement time for manual inspection, and determine whether the filter bag has a fault during the inspection; if so, issue a fault warning and complete the filter bag replacement; if not, continue to determine.

8. A bag dust collector fault warning method, applied to a bag dust collector fault warning system according to any one of claims 1 to 7, characterized in that: include: S100: Obtain a sensor installation diagram from a database, and install an environmental sensor in the bag filter based on the sensor installation diagram; Environmental sensors collect environmental parameters in the filter bag in real time, including temperature, humidity, pressure, and gas dust concentration. S200: Retrieve environmental parameters, debug the bag filter before use, and determine whether the filter bags of the dust collector can work normally; if yes, continue to use the bag filter; if no, issue a warning signal and start the automatic maintenance mode of the filter bags, and record several maintenance results in the database; determine whether the filter bags need to be cleaned; if yes, issue a second warning signal and record the time for cleaning the filter bags in the database; if no, continue to determine; S300: Constructing a time prediction sequence based on the inspection results and the time for cleaning the filter bags; obtaining the time for the next filter bag replacement based on the time prediction sequence; issuing a fault warning based on the time for the next filter bag replacement and completing the filter bag replacement.

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