A fault early warning method and device for a desulfurization device

Abstract

A method and apparatus for fault early warning of desulfurization equipment, relating to the field of fault detection technology, are disclosed. The method involves: acquiring target operating parameters corresponding to the desulfurization equipment; determining the operating state of the desulfurization equipment based on the target operating parameters; identifying the equipment to be analyzed; determining the target analysis method based on the equipment to be analyzed and the operating state; acquiring first monitoring data; comparing the first monitoring data with preset monitoring data; determining that the equipment to be analyzed is in a fault state when the first monitoring data is inconsistent with the preset monitoring data; generating early warning information based on the fault state; and displaying the early warning information to the user so that the user can handle the equipment to be analyzed according to the early warning information. Implementing the technical solution provided in this application solves the problems of inaccurate fault location determination and low troubleshooting efficiency in existing methods based on exhaust gas detection results.

Description

Technical Field

[0001] This application relates to the field of fault detection technology, specifically to a fault early warning method and device for desulfurization equipment. Background Technology

[0002] Industrial production processes generate waste gases containing sulfur pollutants. Using desulfurization equipment can significantly reduce the amount of sulfur pollutants in these waste gases, ensuring that emissions comply with environmental regulations and thus reducing air pollution.

[0003] Currently, to ensure the stable operation of desulfurization equipment, fault detection is necessary. Existing fault detection methods primarily rely on detecting the exhaust gas after desulfurization treatment. Specifically, this involves re-testing the desulfurized exhaust gas, comparing the results with preset thresholds, and determining whether the desulfurization equipment is malfunctioning. However, this method based on exhaust gas detection results cannot accurately pinpoint the exact location of the fault, requiring a thorough inspection of each part of the equipment. Therefore, this fault monitoring method is inefficient.

[0004] Therefore, there is an urgent need for a method and device for early warning of desulfurization equipment failures that can solve the above-mentioned technical problems. Summary of the Invention

[0005] This application provides a method and device for early warning of faults in desulfurization equipment. This method effectively solves the problems of inaccurate fault location judgment and low troubleshooting efficiency based on exhaust gas detection results in existing methods.

[0006] Firstly, this application provides a method for early warning of faults in desulfurization equipment, applied in a monitoring platform. The method includes: acquiring target operating parameters corresponding to the desulfurization equipment; determining the operating state of the desulfurization equipment based on the target operating parameters, the operating state including working state and non-working state; identifying the equipment to be analyzed, determining a target analysis method based on the equipment to be analyzed and the operating state, and acquiring first monitoring data, wherein the equipment to be analyzed is any one of the desulfurization equipment, including spray gun equipment, flue equipment, desulfurizing agent storage equipment, and oxidation fan equipment, and the first monitoring data is obtained by monitoring the equipment to be analyzed using the target analysis method; comparing the first monitoring data with preset monitoring data; when the first monitoring data is inconsistent with the preset monitoring data, determining that the equipment to be analyzed is in a fault state, generating early warning information based on the fault state, and displaying the early warning information to the user so that the user can handle the equipment to be analyzed according to the early warning information.

[0007] By adopting the above technical solution, target operating parameters corresponding to the desulfurization equipment are obtained. These target operating parameters reflect the operating status of the desulfurization equipment. Analyzing these parameters allows for accurate determination of the current operating status of the desulfurization equipment, identification of the equipment to be analyzed, and determination of the target analysis method based on the equipment to be analyzed and its operating status. This enables precise monitoring and analysis of each specific piece of equipment within the desulfurization system. The specific location of the fault can be quickly pinpointed based on the equipment to be analyzed, without needing to inspect the entire desulfurization system piece by piece. The acquired initial monitoring data is then compared with preset monitoring data to determine whether the equipment to be analyzed is in a normal state. This real-time data comparison method can promptly detect anomalies in the equipment to be analyzed, allowing for rapid intervention. When the initial monitoring data is inconsistent with the preset monitoring data, it can be determined that the equipment to be analyzed is in a fault state, and an early warning message can be generated based on the fault state. Direct monitoring of each piece of equipment to be analyzed within the desulfurization system, with precise fault location down to the specific equipment, significantly improves the efficiency and accuracy of fault monitoring, thus solving the problem of low efficiency in traditional methods based on exhaust gas detection results.

[0008] Optionally, the operating status of the desulfurization equipment is determined based on the target operating parameters, specifically including: acquiring a first concentration value and a target flue gas flow rate, where the first concentration value is the sulfur dioxide concentration value obtained at the inlet of the desulfurization equipment; acquiring a second concentration value, where the second concentration value is the sulfur dioxide concentration value obtained at the outlet of the desulfurization equipment; and outputting the first concentration value, the second concentration value, and the target flue gas flow rate as target operating parameters; determining whether the first concentration value and the second concentration value are the same, and whether the target flue gas flow rate is within a preset flue gas range; when the first concentration value and the second concentration value are the same, and the target flue gas flow rate is not within the preset flue gas range, determining that the desulfurization equipment is in a non-working state; when the first concentration value and the second concentration value are different, and the target flue gas flow rate is within the preset flue gas range, determining that the desulfurization equipment is in a working state.

[0009] By adopting the above technical solution, the sulfur dioxide concentration values ​​at the inlet and outlet of the desulfurization equipment and the target flue gas flow rate are obtained. By comparing the first concentration value and the second concentration value, the removal effect of the desulfurization equipment on sulfur dioxide can be intuitively understood. At the same time, considering whether the target flue gas flow rate is within the preset flue gas range, the accuracy of the judgment is further ensured. When the first concentration value and the second concentration value are the same, and the target flue gas flow rate is not within the preset flue gas range, it can be quickly determined that the desulfurization equipment is in a non-working state. When the first concentration value and the second concentration value are different, and the target flue gas flow rate is within the preset flue gas range, it can be determined that the desulfurization equipment is in a working state. By accurately judging the operating status of the desulfurization equipment, the efficiency of fault detection is improved.

[0010] Optionally, the device to be analyzed is determined, and a target analysis method is determined based on the device and its operating status. First monitoring data is then acquired, specifically including: after determining that the desulfurization equipment is in a non-working state, a first detection method is determined based on the non-working state and the device to be analyzed, and the first detection method is output as the target analysis method; the device to be analyzed is tested using the first detection method to obtain second monitoring data, and the second monitoring data is output as the first monitoring data; when the device to be analyzed is a spray gun, the second monitoring data includes part dimensions and corrosion values; when the device to be analyzed is an oxidation blower, the second monitoring data includes insulation resistance, winding resistance, and target current; when the device to be analyzed is a desulfurizing agent storage device, the second monitoring data includes first humidity; when the device to be analyzed is a flue gas ash accumulation value.

[0011] By adopting the above technical solution, after determining that the desulfurization equipment is in a non-working state, a dedicated detection method is designed for different equipment to be analyzed and corresponding monitoring data is output. This enables accurate location and efficient troubleshooting of desulfurization equipment faults. By distinguishing different equipment to be analyzed, such as spray guns, oxidation fans, desulfurizing agent storage equipment, and flue equipment, key parameters are collected in a targeted manner, which can quickly pinpoint the faulty equipment. This avoids the blindness of traditional whole-system troubleshooting and realizes the upgrade of desulfurization equipment operation and maintenance from passive response to proactive prevention.

[0012] Optionally, the device to be analyzed is determined, and a target analysis method is determined based on the device and its operating status. First monitoring data is then acquired, specifically including: after confirming the desulfurization equipment is in operation, a second detection method is determined based on the operating status and the device to be analyzed, and the second detection method is output as the target analysis method; the device to be analyzed is tested using the second detection method to obtain third monitoring data, which is output as the first monitoring data; when the device to be analyzed is a spray gun, the third monitoring data includes spray pressure, paint flow rate, audio information, and spray area distribution density; when the device to be analyzed is an oxidation fan, the third monitoring data includes vibration, fan temperature, audio information, and exhaust pressure; when the device to be analyzed is a desulfurizing agent storage device, the third monitoring data includes second humidity; when the device to be analyzed is a flue gas device, the third monitoring data includes flue gas temperature and flue gas pressure.

[0013] By adopting the above technical solution, after determining that the desulfurization equipment is in working condition, a second detection method is designed for different equipment to be analyzed and corresponding third monitoring data is output. Different equipment to be analyzed corresponds to different monitoring parameters. The monitoring parameters are used to determine whether the equipment to be analyzed is in a fault state, thus realizing comprehensive, real-time and accurate monitoring of the operating status of the desulfurization equipment.

[0014] Optionally, when the first monitoring data is inconsistent with the preset monitoring data, the device to be analyzed is determined to be in a fault state. This includes: determining the preset monitoring data based on the device to be analyzed; determining whether the first monitoring data is consistent with the preset monitoring data; when the first monitoring data is inconsistent with the preset monitoring data, obtaining the fourth monitoring data, which is the monitoring data in the first monitoring data that is inconsistent with the preset monitoring data; obtaining the first value and the second value from the fourth monitoring data, which are the values ​​corresponding to any two monitoring data in the fourth monitoring data; calculating the first value and the second value to obtain a fault score; and determining the fault state based on the fault score.

[0015] By adopting the above technical solution, the corresponding preset monitoring data is determined according to the equipment to be analyzed. The actual collected first monitoring data is compared with the preset monitoring data to quickly identify abnormal parameters. When the first monitoring data is inconsistent with the preset monitoring data, the inconsistent fourth monitoring data is extracted. Two parameters are randomly selected from the fourth monitoring data. By calculating the fault score, the abnormal parameters are converted into quantifiable fault scores. The fault status is determined according to the fault score. Safety maintenance is carried out in advance according to the fault score to avoid unplanned downtime caused by fault escalation.

[0016] Optionally, the fault status includes low fault level, medium fault level, and high fault level. The fault status is determined based on the fault score, specifically including: determining whether the fault score is less than a preset fault score; when the fault score is less than the preset fault score, the equipment under analysis is determined to be at a low fault level, and a first handling measure is output based on the low fault level; when the fault score is equal to the preset fault score, the equipment under analysis is determined to be at a medium fault level, and a second handling measure is output based on the medium fault level; when the fault score is greater than the preset fault score, the equipment under analysis is determined to be at a high fault level, and a third handling measure is output based on the high fault level.

[0017] By adopting the above technical solution, the fault score is compared with the preset fault score. When the fault score is less than the preset fault score, the equipment under analysis is determined to be at a low fault level, and the first treatment measure is taken according to the low fault level. When the fault score is equal to the preset fault score, the equipment under analysis is determined to be at a medium fault level, and the second treatment measure is taken according to the medium fault level. When the fault score is greater than the preset fault score, the equipment under analysis is determined to be at a high fault level, and the third treatment measure is taken according to the high fault level. By matching the optimal treatment measure through the score threshold, over-maintenance or delays are avoided, and early monitoring of low fault levels and intervention of medium fault levels are achieved to realize early control of faults.

[0018] Optionally, an early warning message is generated based on the fault status and displayed to the user so that the user can handle the equipment to be analyzed according to the early warning message. Specifically, this includes: obtaining the target time point and target location, where the target time point is the time point after the equipment to be analyzed is determined to be in a fault state, and the target location is the position of the equipment to be analyzed in the desulfurization equipment; generating an early warning message based on the fault status and target time point, and sending the early warning message and target location to the user so that the user can go to the target location to handle the fault of the equipment to be analyzed.

[0019] By adopting the above technical solution, after the fault status is confirmed, the current time point is automatically recorded as the target time point. After obtaining the target location corresponding to the equipment to be analyzed, an early warning message is generated based on the fault level and the target time point. The early warning message and the target location are then sent to the user so that the user can go to the target location to repair the equipment to be analyzed, eliminating the need for manual location search. The automatic push of the fault location significantly improves maintenance efficiency.

[0020] In a second aspect, this application provides a fault early warning device for desulfurization equipment. The device is a monitoring platform, which includes an acquisition unit, a processing unit, and a confirmation unit. The acquisition unit acquires the target operating parameters corresponding to the desulfurization equipment. The processing unit determines the operating state of the desulfurization equipment based on the target operating parameters, including a working state and a non-working state. It identifies the equipment to be analyzed, determines the target analysis method based on the equipment to be analyzed and the operating state, and acquires first monitoring data. The equipment to be analyzed can be any one of the desulfurization equipment, including spray gun equipment, flue equipment, desulfurizing agent storage equipment, and oxidation fan equipment. The first monitoring data is obtained by monitoring the equipment to be analyzed using the target analysis method. The first monitoring data is compared with preset monitoring data. The confirmation unit determines that the equipment to be analyzed is in a fault state when the first monitoring data is inconsistent with the preset monitoring data, generates an early warning message based on the fault state, and displays the early warning message to the user so that the user can handle the equipment to be analyzed according to the early warning message.

[0021] Optionally, the acquisition unit is used to acquire a first concentration value and a target flue gas flow rate, wherein the first concentration value is the sulfur dioxide concentration value obtained at the inlet of the desulfurization equipment; acquire a second concentration value, wherein the second concentration value is the sulfur dioxide concentration value obtained at the outlet of the desulfurization equipment; and output the first concentration value, the second concentration value, and the target flue gas flow rate as target operating parameters; the processing unit is used to determine whether the first concentration value and the second concentration value are the same, and whether the target flue gas flow rate is within a preset flue gas range; the confirmation unit is used to determine that the desulfurization equipment is in a non-working state when the first concentration value and the second concentration value are the same, and the target flue gas flow rate is not within the preset flue gas range; and to determine that the desulfurization equipment is in a working state when the first concentration value and the second concentration value are different, and the target flue gas flow rate is within the preset flue gas range.

[0022] Optionally, the confirmation unit determines a first detection method based on the non-working state and the equipment to be analyzed after confirming that the desulfurization equipment is in a non-working state, and outputs the first detection method as the target analysis method; the processing unit uses the first detection method to detect the equipment to be analyzed, obtains second monitoring data, and outputs the second monitoring data as the first monitoring data; when the equipment to be analyzed is a spray gun, the second monitoring data includes part dimensions and corrosion values; when the equipment to be analyzed is an oxidation blower, the second monitoring data includes insulation resistance, winding resistance, and target current; when the equipment to be analyzed is a desulfurizing agent storage device, the second monitoring data includes first humidity; when the equipment to be analyzed is a flue gas device, the second monitoring data includes flue gas ash accumulation values.

[0023] Optionally, the confirmation unit determines a second detection method based on the working state and the equipment to be analyzed after confirming that the desulfurization equipment is in operation, and outputs the second detection method as the target analysis method. The processing unit uses the second detection method to detect the equipment to be analyzed, obtains third monitoring data, and outputs the third monitoring data as the first monitoring data. When the equipment to be analyzed is a spray gun, the third monitoring data includes spray pressure, paint flow rate, audio information, and spray area distribution density. When the equipment to be analyzed is an oxidation fan, the third monitoring data includes vibration, fan temperature, audio information, and exhaust pressure. When the equipment to be analyzed is a desulfurizing agent storage device, the third monitoring data includes second humidity. When the equipment to be analyzed is a flue gas device, the third monitoring data includes flue gas temperature and flue gas pressure.

[0024] Optionally, the processing unit is used to determine preset monitoring data based on the device to be analyzed; determine whether the first monitoring data is consistent with the preset monitoring data; the acquisition unit is used to acquire fourth monitoring data when the first monitoring data is inconsistent with the preset monitoring data, the fourth monitoring data being the monitoring data in the first monitoring data that is inconsistent with the preset monitoring data; acquire a first value and a second value from the fourth monitoring data, the first value and the second value being the values ​​corresponding to any two monitoring data in the fourth monitoring data; the processing unit is used to calculate the first value and the second value to obtain a fault score; and determine the fault status based on the fault score.

[0025] Optionally, the processing unit is used to determine whether the fault score is less than the preset fault score; the confirmation unit is used to determine that the device to be analyzed is in a low fault level when the fault score is less than the preset fault score, and output a first processing measure according to the low fault level; when the fault score is equal to the preset fault score, determine that the device to be analyzed is in a medium fault level, and output a second processing measure according to the medium fault level; when the fault score is greater than the preset fault score, determine that the device to be analyzed is in a high fault level, and output a third processing measure according to the high fault level.

[0026] Optionally, the acquisition unit is used to acquire the target time point and the target location. The target time point is the time point after it is determined that the equipment to be analyzed is in a fault state, and the target location is the location of the equipment to be analyzed in the desulfurization equipment. The processing unit is used to generate early warning information based on the fault state and the target time point, and send the early warning information and the target location to the user so that the user can go to the target location to handle the fault of the equipment to be analyzed.

[0027] In a third aspect, this application provides an electronic device including a processor, a memory, a user interface, and a network interface. The memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory, causing the electronic device to perform any of the methods described above in this application.

[0028] In a fourth aspect, this application provides a computer-readable storage medium storing instructions that, when executed, perform any of the methods described above in this application.

[0029] In summary, one or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0030] 1. Obtain the target operating parameters corresponding to the desulfurization equipment. These parameters reflect the operating status of the desulfurization equipment. Analyzing these parameters allows for accurate determination of the current operating status of the desulfurization equipment, identification of the equipment to be analyzed, and determination of the target analysis method based on the equipment and its operating status. This enables precise monitoring and analysis of each specific piece of equipment within the desulfurization system. The system can quickly pinpoint the location of a fault based on the analyzed equipment without needing to inspect the entire desulfurization system piece by piece. The acquired initial monitoring data is then compared with preset monitoring data to determine if the analyzed equipment is in a normal state. This real-time data comparison method can promptly detect anomalies in the analyzed equipment, allowing for rapid intervention. When the initial monitoring data differs from the preset monitoring data, it can determine that the analyzed equipment is in a fault state and generate an early warning message based on the fault status. Direct monitoring of each analyzed piece of equipment within the desulfurization system, with precise fault location down to the analyzed equipment, significantly improves the efficiency and accuracy of fault monitoring, thus solving the inefficiency problem of traditional methods based on exhaust gas detection results.

[0031] 2. Obtain the sulfur dioxide concentration values ​​at the inlet and outlet of the desulfurization equipment, as well as the target flue gas flow rate. Then compare the first concentration value with the second concentration value to intuitively understand the desulfurization equipment's removal effect on sulfur dioxide. At the same time, consider whether the target flue gas flow rate is within the preset flue gas range to further ensure the accuracy of the judgment. When the first concentration value is the same as the second concentration value and the target flue gas flow rate is not within the preset flue gas range, it can be quickly determined that the desulfurization equipment is in a non-working state. When the first concentration value is different from the second concentration value and the target flue gas flow rate is within the preset flue gas range, it can be determined that the desulfurization equipment is in a working state. By accurately judging the operating status of the desulfurization equipment, the efficiency of fault detection can be improved. Attached Figure Description

[0032] Figure 1 This is a flowchart illustrating a method for early warning of faults in desulfurization equipment provided in an embodiment of this application;

[0033] Figure 2 This is a schematic diagram of a fault early warning device for desulfurization equipment provided in an embodiment of this application;

[0034] Figure 3 This is a schematic diagram of the structure of an electronic device disclosed in an embodiment of this application.

[0035] Explanation of reference numerals in the attached drawings: 201, acquisition unit; 202, processing unit; 203, confirmation unit; 300, electronic device; 301, processor; 302, memory; 303, user interface; 304, network interface; 305, communication bus. Detailed Implementation

[0036] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0037] In the description of the embodiments of this application, the words "for example" or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design that is described as "for example" or "for instance" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design options. Rather, the use of the words "for example" or "for instance" is intended to present the relevant concepts in a specific manner.

[0038] In the description of the embodiments of this application, the term "multiple" means two or more. For example, multiple systems means two or more systems, and multiple screen terminals means two or more screen terminals. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the indicated technical features. Thus, a feature defined with "first" or "second" may explicitly or implicitly include one or more of that feature. The terms "comprising," "including," "having," and variations thereof all mean "including but not limited to," unless otherwise specifically emphasized.

[0039] Industrial production processes generate waste gases containing sulfur pollutants. Using desulfurization equipment can significantly reduce the amount of sulfur pollutants in these waste gases, ensuring that emissions comply with environmental regulations and thus reducing air pollution.

[0040] Currently, to ensure the stable operation of desulfurization equipment, fault detection is necessary. Existing fault detection methods primarily rely on detecting the exhaust gas after desulfurization treatment. Specifically, this involves re-testing the desulfurized exhaust gas, comparing the results with preset thresholds, and determining whether the desulfurization equipment is malfunctioning. However, this method based on exhaust gas detection results cannot accurately pinpoint the exact location of the fault, requiring a thorough inspection of each part of the equipment. Therefore, this fault monitoring method is inefficient.

[0041] Therefore, how to solve the problem of inaccurate fault location determination and low troubleshooting efficiency based on existing exhaust gas detection results? This application provides a fault early warning method for desulfurization equipment, applied in a monitoring platform. The monitoring platform of this application can be a platform providing fault detection services for desulfurization equipment to industrial production enterprises. Figure 1This is a flowchart illustrating a fault early warning method for desulfurization equipment provided in an embodiment of this application. (Refer to...) Figure 1 The method includes the following steps S101-S105.

[0042] S101: Obtain the target operating parameters corresponding to the desulfurization equipment.

[0043] In S101 above, in industrial production applications, sulfur dioxide in exhaust gas needs to be treated to prevent the emission of untreated exhaust gas. Currently, desulfurization equipment is used to treat sulfur dioxide in exhaust gas. This embodiment mainly aims to solve the problem that current fault detection of desulfurization equipment can only be based on exhaust gas detection methods, but this method cannot specifically locate the fault, resulting in low fault diagnosis efficiency.

[0044] In addition, when troubleshooting desulfurization equipment, it is necessary to first determine which components make up the desulfurization equipment.

[0045] Desulfurization equipment can be understood as a desulfurization system, which consists of multiple devices that work together to remove sulfur dioxide. The desulfurization equipment includes a screw feeder, absorption tower, spray guns, flue gas ducts, desulfurizing agent storage equipment, and oxidation fans. The screw feeder is mainly used to transport the desulfurizing agent from the storage equipment to the absorption tower, ensuring that the desulfurizing agent enters the absorption tower at a stable rate, providing raw materials for subsequent chemical reactions. The desulfurizing agent storage equipment stores the chemical reagents required for desulfurization, such as limestone powder. These reagents are key raw materials in the desulfurization process and are used to react chemically with sulfur dioxide in the flue gas. The absorption tower is the core equipment of the desulfurization system. After the flue gas enters the absorption tower, it comes into full contact with the slurry containing desulfurizing agent sprayed from the spray guns. Inside the absorption tower, the desulfurizing agent (such as limestone slurry) reacts chemically with the sulfur dioxide in the flue gas to produce compounds such as calcium sulfite or calcium sulfate. The spray gun equipment is typically installed inside the absorption tower to evenly spray the desulfurizing agent slurry into the flue gas. Through the spray gun, the desulfurizing agent can fully contact the sulfur dioxide in the flue gas, improving reaction efficiency. The flue gas duct system transports the flue gas from the boiler to the absorption tower and then conveys the desulfurized flue gas to the chimney for emission. The oxidation blower provides oxygen to the desulfurization process, promoting the oxidation reaction of sulfur dioxide. Oxygen is introduced into the absorption tower so that, under the combined action of oxygen and the desulfurizing agent, the sulfur dioxide in the waste gas is converted into sulfuric acid and water, thus achieving the purpose of desulfurization. After determining the multiple devices included in the desulfurization equipment, sensors can be installed at the flue gas inlet and outlet of the desulfurization equipment. The sensors are sulfur dioxide meters, which monitor the concentration of sulfur dioxide in the flue gas. Flow meters are also installed in the flue gas duct equipment to measure the flue gas flow rate in real time. The obtained sulfur dioxide concentration and flue gas flow rate are then combined to obtain the target operating parameters. These target operating parameters are transmitted to the monitoring platform via network protocols (Modbus, 4G network) so that the monitoring platform can receive the current target operating parameters of the desulfurization equipment.

[0046] S102: Determine the operating status of the desulfurization equipment according to the target operating parameters. The operating status includes the working status and the non-working status.

[0047] In S102 above, after obtaining the target operating parameters corresponding to the desulfurization equipment, the operating state of the desulfurization equipment is determined according to the target operating parameters. Specifically, this includes: obtaining a first concentration value and a target flue gas flow rate, where the first concentration value is the sulfur dioxide concentration value obtained at the inlet of the desulfurization equipment; obtaining a second concentration value, where the second concentration value is the sulfur dioxide concentration value obtained at the outlet of the desulfurization equipment; and outputting the first concentration value, the second concentration value, and the target flue gas flow rate as target operating parameters; determining whether the first concentration value and the second concentration value are the same, and whether the target flue gas flow rate is within a preset flue gas range; when the first concentration value and the second concentration value are the same, and the target flue gas flow rate is not within the preset flue gas range, determining that the desulfurization equipment is in a non-working state; and when the first concentration value and the second concentration value are different, and the target flue gas flow rate is within the preset flue gas range, determining that the desulfurization equipment is in a working state.

[0048] Specifically, a sulfur dioxide concentration sensor (such as an electrochemical sensor or an infrared absorption sensor) is installed at the inlet of the desulfurization equipment. The sensor collects the sulfur dioxide concentration in the inlet flue gas in real time, in mg / Nm³ or ppm. The data is transmitted to the monitoring platform via analog signal (4-20mA) or digital signal (Modbus RTU). A flow meter (such as a Pitot tube flow meter or a thermal mass flow meter) is installed in the flue. The flow meter measures the flue gas flow rate in real time, in Nm³ / h or m³ / s. This data is transmitted synchronously to the monitoring platform along with the sulfur dioxide concentration data. A sulfur dioxide concentration sensor identical to the one at the inlet is installed at the outlet of the desulfurization equipment; the outlet refers to the area where the desulfurized exhaust gas is emitted. The sensor collects the sulfur dioxide concentration in the outlet flue gas in real time. The outlet sulfur dioxide concentration data is transmitted synchronously to the monitoring platform along with the inlet data. For example, at the inlet of a power plant's desulfurization system, a sulfur dioxide concentration sensor collects a first concentration value of 450 mg / Nm³ in real time, while a flue gas flow meter measures a target flue gas flow rate of 120,000 Nm³ / h. At the outlet, a sulfur dioxide concentration sensor collects a second concentration value of 50 mg / Nm³ in real time. Comparing the first and second concentration values, the absolute difference between them can be calculated. If the absolute difference is less than a preset concentration threshold, the first and second concentration values ​​are considered the same; if the absolute difference is greater than or equal to the preset threshold, they are considered different. The target flue gas flow rate is then compared to a preset flue gas flow range, which can be understood as the flow rate of flue gas in the flue during desulfurization. When the first and second concentration values ​​are different, and the target flue gas flow rate is within the preset flow range, the desulfurization equipment is determined to be in operation. In this case, "operational state" refers to the state in which the desulfurization equipment removes sulfur dioxide from the exhaust gas. When the first concentration value is the same as the second concentration value, and the target flue gas flow rate is not within the preset flue gas flow rate range, the desulfurization equipment is determined to be in a non-operating state. A non-operating state can also be understood as the desulfurization equipment not yet starting desulfurization work. At this time, the sulfur dioxide concentration at the inlet and outlet is close to the original flue gas concentration, and the flue gas flow rate in the flue is too low, indicating that the desulfurization equipment is not running. By comparing real-time data, the operating status of the desulfurization equipment can be identified in advance. Then, different fault analysis methods can be selected according to different operating states, allowing for timely detection of faulty desulfurization equipment.

[0049] For example, if the first concentration of sulfur dioxide at the inlet is 450 mg / Nm³ and the second concentration at the outlet is 445 mg / Nm³, the absolute difference between the first and second concentrations is calculated. If the absolute difference is less than a preset concentration threshold, the first and second concentrations are considered to be the same. Then, if the target flue gas flow rate is set to 1000 Nm³ / h (with a preset flow rate range of 500,000-100,000 Nm³ / h), and the target flue gas flow rate is not within the preset flow rate range, the desulfurization efficiency of the desulfurization equipment is almost zero. Therefore, it can be determined that the desulfurization equipment is in a non-operating state.

[0050] In addition to identifying the operating status of the desulfurization equipment through target operating parameters, the start / stop buttons and indicator lights of each component of the desulfurization equipment can also be used for identification. If the button is in the stop position and the indicator light is off, it means that the desulfurization equipment is not running, i.e., in a non-working state; when the button is in the start position and the indicator light is on, it means that the desulfurization equipment is in a working state. The specific method chosen to determine the operating status of the desulfurization equipment can be selected based on the actual situation, and no further restrictions are imposed here.

[0051] S103: Identify the device to be analyzed, determine the target analysis method based on the device and its operating status, and obtain the first monitoring data.

[0052] In step S103 above, since the desulfurization equipment consists of multiple devices, including a screw feeder, an absorption tower, a spray gun, a flue gas duct, a desulfurizing agent storage device, and an oxidation fan, any one of these devices can be selected as the device to be analyzed. This device can be any one of the screw feeder, absorption tower, spray gun, flue gas duct, desulfurizing agent storage device, or oxidation fan. Alternatively, the device to be analyzed can be determined according to the treatment sequence of the waste gas by each device. Based on the operating status and the device to be analyzed, a suitable target analysis method is selected, and then the target analysis method is used to monitor the device to be analyzed, obtaining the first monitoring data.

[0053] In addition, the equipment to be analyzed is identified, and the target analysis method is determined based on the equipment and its operating status. First monitoring data is then acquired, specifically including: after determining that the desulfurization equipment is in a non-working state, a first detection method is determined based on the non-working state and the equipment to be analyzed, and the first detection method is output as the target analysis method; the equipment to be analyzed is tested using the first detection method to obtain second monitoring data, and the second monitoring data is output as the first monitoring data; when the equipment to be analyzed is a spray gun, the second monitoring data includes part dimensions and corrosion values; when the equipment to be analyzed is an oxidation fan, the second monitoring data includes insulation resistance, winding resistance, and target current; when the equipment to be analyzed is a desulfurizing agent storage device, the second monitoring data includes first humidity; when the equipment to be analyzed is a flue gas ash accumulation value.

[0054] Specifically, when the desulfurization equipment is determined to be in a non-operating state based on the aforementioned steps, the equipment to be analyzed can be selected from multiple devices according to priority. In this case, priority can be ranked according to the frequency of each device's malfunction; the lower the malfunction frequency, the higher the priority, and vice versa. For example, if the spray gun malfunctions every 5 days and the oxidation blower malfunctions every 10 days, the spray gun malfunction has a higher priority than the oxidation blower, and the spray gun malfunction can be checked first. Therefore, the equipment to be analyzed in this case is the spray gun malfunction. Based on the type of equipment to be analyzed and its non-operating state, the corresponding detection method is matched from the predefined monitoring methods. For spray gun equipment, a laser rangefinder can be used to detect part dimensions, and an ultrasonic thickness gauge can be used to detect corrosion values. For oxidation blower equipment, an insulation resistance tester can be used to detect insulation resistance, a multimeter can be used to detect winding resistance, and a current clamp meter can be used to detect target current. For desulfurizer storage equipment, a humidity sensor is used to detect humidity inside the tank. For flue equipment, lidar or image recognition is used to detect flue gas ash accumulation values. For screw feeder equipment, a vibration sensor can be used to detect the first vibration data, a temperature sensor can be used to detect the first temperature data, a displacement sensor can be used to detect component displacement data, and an insulation sensor can be used to detect motor winding data. For absorption tower equipment, an ultrasonic thickness gauge is used to obtain the absorption tower wall thickness, and infrared thermal imaging is used to obtain data such as weld cracks or tower body cracks.

[0055] When the device to be analyzed is a spray gun, the first detection method is used to detect it. This first detection method refers to either a laser rangefinder or an ultrasonic thickness gauge. The laser rangefinder measures the diameter of the spray gun nozzle (part size) in mm, and the ultrasonic thickness gauge measures the spray gun wall thickness (corrosion value) in mm. Besides using a laser rangefinder or ultrasonic thickness gauge, images of the spray gun can also be acquired and processed using a camera. Image processing algorithms are used to analyze the acquired spray gun images and extract the contours of each part. Common algorithms include edge detection algorithms (such as the Canny edge detection algorithm) and contour extraction algorithms. These algorithms can accurately identify the boundaries of the parts and thus calculate their dimensions. Then, an image segmentation algorithm is used to separate the corroded areas on the spray gun surface from the normal areas. Feature extraction is performed on the segmented images, such as color, texture, and shape. Finally, classification algorithms (such as support vector machines and neural networks) are used to classify the extracted features to accurately identify the corroded areas. After accurately identifying the corrosion area, the number of pixels occupied by the corrosion area in the image can be calculated. Combined with the camera's calibration parameters, this pixel count is converted into an area in the real world, thus obtaining the corrosion value. After obtaining the part size and corrosion value, these represent the second monitoring data. This second monitoring data is then integrated into the first monitoring data for output. For example, if the part size is 12.5mm (nozzle diameter) and the corrosion value is 3.8mm, then when analyzing an oxidation blower, an insulation resistance tester is used to measure the insulation resistance of the motor windings (in MΩ), a multimeter is used to measure the winding resistance (in Ω), and a current clamp meter is used to measure the operating current (in A). The second monitoring data includes insulation resistance, winding resistance, and operating current. This second monitoring data is then integrated into the first monitoring data for output. For example, if the insulation resistance is 0.5 MΩ, the winding resistance is 15Ω, and the operating current is 25A, then the second monitoring data is used to output the first monitoring data. When the equipment to be analyzed is a desulfurizing agent storage device, a humidity sensor can be used to measure the humidity inside the tank (first humidity), in %RH. The second monitoring data refers to the first humidity, which is then output as the first monitoring data. For example, 85%RH. When the equipment to be analyzed is a flue gas system, a lidar sensor can be installed on the inner wall of the flue. The lidar sensor scans the inner wall of the flue and calculates the ash accumulation thickness (flue gas ash accumulation value), in mm. The second monitoring value refers to the flue gas ash accumulation value, which is then output as the first monitoring data. When the equipment to be analyzed is a screw feeder, vibration sensors, temperature sensors, displacement sensors, and insulation resistance sensors are used to acquire the second monitoring data for each component of the screw feeder. The second monitoring data includes first vibration data, first temperature, first displacement, and first resistance.When the equipment to be analyzed is an absorption tower, an ultrasonic thickness gauge is used to obtain the wall thickness of the absorption tower, and infrared thermal imaging is used to detect leaks such as weld cracks or tower body cracks. The second monitoring data includes the absorption tower wall thickness and leakage status. The detection method is determined based on the non-operating state and the equipment to be analyzed, and the detection method is used to monitor the equipment to be analyzed, thus achieving precise location of desulfurization equipment faults.

[0056] In one possible implementation, the device to be analyzed is identified, a target analysis method is determined based on the device and its operating status, and first monitoring data is obtained. Specifically, this includes: after determining that the desulfurization equipment is in operation, a second detection method is determined based on the operating status and the device to be analyzed, and the second detection method is output as the target analysis method; the device to be analyzed is tested using the second detection method to obtain third monitoring data, and the third monitoring data is output as the first monitoring data; when the device to be analyzed is a spray gun, the third monitoring data includes spray pressure, paint flow rate, audio information, and spray area distribution density; when the device to be analyzed is an oxidation fan, the third monitoring data includes vibration, fan temperature, audio information, and exhaust pressure; when the device to be analyzed is a desulfurizing agent storage device, the third monitoring data includes second humidity; when the device to be analyzed is a flue gas device, the third monitoring data includes flue gas temperature and flue gas pressure.

[0057] Specifically, the desulfurization equipment is determined to be in working condition through preliminary steps, and the equipment to be analyzed is selected from multiple devices based on priority. Then, a second analysis method is determined based on the equipment to be analyzed and its working condition, and this second analysis method is used to monitor the equipment to be analyzed, obtaining third monitoring data. For the spray gun equipment, a pressure sensor can be used to detect the spraying pressure, a flow meter to detect the paint flow rate, an audio sensor to detect the spraying audio, and image recognition to detect the distribution density of the sprayed area. The distribution density is obtained as follows: First, a suitable high-speed camera is selected based on the spraying speed and particle motion characteristics. The faster the spraying speed, the higher the required camera frame rate. Then, a suitable frame rate is set based on the spraying speed and particle motion characteristics. A suitable shooting duration is set based on the duration of the spraying process. After the spray gun equipment starts working, the spraying process can be filmed from different angles, such as directly in front of, to the side, and above the spray gun, to obtain particle distribution information in different directions. The captured images are preprocessed, and then a threshold segmentation method is used to separate the particles from the background. A suitable threshold is selected for segmentation based on the grayscale difference between the particles and the background. Edge detection algorithms (such as the Sobel operator and Canny operator) are used to extract the edge information of particles, further refining their contours. For identified particles, their size is measured. The distribution of particles within the spraying area is statistically analyzed. Indicators such as particle number density (number of particles per unit area) and spatial distribution uniformity can be calculated. Visual charts such as particle size distribution histograms and particle distribution heatmaps are generated to intuitively display the analysis results; in this case, the analysis results refer to the distribution density within the spraying area. For the oxidation blower equipment, vibration sensors detect vibration values, temperature sensors detect blower temperature, audio sensors detect operating audio, and pressure sensors detect exhaust pressure. For desulfurizing agent storage equipment, a humidity sensor is used to detect the second humidity; for flue gas equipment, a temperature sensor is used to detect the flue gas temperature, and a pressure sensor is used to detect the flue gas pressure; for absorption tower equipment, a sulfur dioxide analyzer is used to detect the sulfur dioxide content, a level gauge is used to monitor the slurry circulation pump, a differential pressure sensor is used to acquire the differential pressure, and a temperature sensor is used to acquire the second temperature; for screw feeder equipment, a current sensor is used to acquire the motor current, a vibration sensor is used to acquire the second vibration data, a speed sensor is used to acquire the drive shaft speed, a flow meter is used to acquire the discharge port speed, and a temperature sensor is used to acquire the third temperature of the motor, bearings, and reducer.

[0058] Furthermore, when the equipment to be analyzed is a spray gun, a pressure sensor measures the spraying pressure, a flow meter measures the paint flow rate, an audio sensor collects audio signals during the spraying process, a camera captures the sprayed area, and an image recognition algorithm calculates the distribution density, such as the number of spray points per unit area. The third monitoring data includes the spraying pressure value, paint flow rate, audio information, and the distribution density of the sprayed area. This third monitoring data is then integrated into the first monitoring data. When the equipment to be analyzed is an oxidation blower, a vibration sensor measures the blower vibration value, a temperature sensor measures the blower temperature, an audio sensor collects the operating audio, and a pressure sensor measures the exhaust pressure. The third monitoring data includes the vibration value, blower temperature, audio information, and exhaust pressure value. This third monitoring data is then integrated into the first monitoring data. When the equipment to be analyzed is a desulfurizing agent storage device, a humidity sensor measures the humidity inside the tank (second humidity). The third monitoring data includes the second humidity, which is output as the first monitoring data. When the equipment to be analyzed is a flue gas device, a temperature sensor measures the flue gas temperature, and a pressure sensor measures the flue gas pressure. The third monitoring data includes both the flue gas temperature and flue gas pressure values. This third monitoring data is then integrated into the first monitoring data. When the equipment to be analyzed is an absorption tower, a sulfur dioxide analyzer detects sulfur dioxide to obtain its concentration. A densitometer is used to detect the solid content of the slurry circulation pump. A differential pressure sensor obtains the differential pressure value, and a temperature sensor obtains the second temperature. The third monitoring data includes sulfur dioxide concentration, solid content, differential pressure value, and second temperature. The third monitoring data is integrated into the first monitoring data. When the equipment to be analyzed is a screw feeder, a current sensor obtains the motor current, a vibration sensor obtains the second vibration data, a speed sensor obtains the drive shaft speed, a flow meter obtains the discharge port speed, and a temperature sensor obtains the third temperature of the motor, bearings, and reducer. The third monitoring data includes the second vibration data, speed, discharge flow rate, and third temperature. The third monitoring data is integrated into the first monitoring data.

[0059] S104: Compare the first monitoring data with the preset monitoring data.

[0060] In step S104 above, the corresponding sensor data is retrieved based on the target analysis method and the device to be analyzed, and the acquired sensor data is then used as the first monitoring data. After acquiring the first monitoring data corresponding to the device to be analyzed, preset monitoring data is selected based on the device to be analyzed and its operating status. Different preset monitoring data correspond to different operating states of the device to be analyzed. The preset monitoring data is set according to the equipment parameter manual and historical data provided by the manufacturer. Historical data of the device to be analyzed over a period of time is acquired, and a dynamic threshold is generated by referring to the equipment parameter manual. The first monitoring data is then compared with the preset monitoring data, and a multi-parameter joint judgment is made to determine whether the device to be analyzed is in a fault state.

[0061] S105: When the first monitoring data is inconsistent with the preset monitoring data, it is determined that the device to be analyzed is in a fault state. An early warning message is generated based on the fault state and displayed to the user so that the user can handle the device to be analyzed according to the early warning message.

[0062] In S105 above, when the first monitoring data is inconsistent with the preset monitoring data, it is determined that the device to be analyzed is in a fault state. Specifically, this includes: determining the preset monitoring data based on the device to be analyzed; determining whether the first monitoring data is consistent with the preset monitoring data; when the first monitoring data is inconsistent with the preset monitoring data, obtaining the fourth monitoring data, which is the monitoring data in the first monitoring data that is inconsistent with the preset monitoring data; obtaining the first value and the second value from the fourth monitoring data, which are the values ​​corresponding to any two monitoring data in the fourth monitoring data; calculating the first value and the second value to obtain a fault score; and determining the fault state based on the fault score.

[0063] Specifically, based on the operating status of the desulfurization equipment, preset monitoring data corresponding to the equipment to be analyzed are determined. Different preset monitoring data correspond to different operating statuses. When the operating status is working, the preset monitoring data are the parameter thresholds that the equipment should meet under normal working conditions. When the operating status is not working, the preset monitoring data are the parameter thresholds corresponding to the equipment in the non-working state. If it is determined that the desulfurization equipment is in working condition, the preset monitoring data corresponding to the equipment to be analyzed is obtained based on the working status. It is then determined whether the first monitoring data is consistent with the preset monitoring data. For each parameter in the first monitoring data, it is checked whether it falls within the range of the preset monitoring data. For example, when the equipment to be analyzed is a spray gun, the desulfurization equipment is in working condition, and the preset monitoring data includes preset spraying pressure, preset paint flow rate, preset audio information, and preset distribution density. The first monitoring data is obtained, which includes spraying pressure, paint flow rate, audio information, and spray area distribution density. Each parameter in the first monitoring data is compared sequentially with the preset monitoring data to determine whether each parameter in the first monitoring data falls within the range of the preset monitoring data. When one parameter in the first monitoring data is outside the range of the preset monitoring data, the first monitoring data is determined to be inconsistent with the preset monitoring data, and the device under analysis is identified as being in a fault state. Although both cases of one parameter being outside the preset monitoring data range and cases of multiple parameters being outside the preset monitoring data range indicate a fault state, the severity of the fault differs. Quantifying the severity of the fault is crucial to understanding the fault level of the device under analysis. The first monitoring data is compared with the preset monitoring data. During the comparison, a fourth monitoring data point is obtained where the first monitoring data is not included in the preset monitoring data. This fourth monitoring data point represents the monitoring data where the first monitoring data is inconsistent with the preset monitoring data.For example, if the device to be analyzed is a spray gun, the first monitoring data includes spray pressure, paint flow rate, audio information, and distribution density. The spray pressure is 0.5 MPa, the paint flow rate is 12 L / min, the audio information is 85 dB, and the distribution density is 85 points / m². Since the desulfurization equipment is in operation, the preset monitoring data for the spray gun includes preset spray pressure, preset paint flow rate, preset audio information, and preset distribution density. The preset spray pressure is set to 0.45 ± 0.05 MPa, the preset paint flow rate is set to 10 ± 1 L / min, the preset audio information is set to 80 ± 5 dB, and the preset distribution density is set to 100 ± 5 points / m². Comparing the first monitoring data with the preset monitoring data, the spray pressure and audio information in the first monitoring data are consistent with the preset spray pressure and audio information in the preset monitoring data. However, the paint flow rate and distribution density in the first monitoring data are inconsistent with the preset monitoring data. Therefore, the paint flow rate and distribution density in the first monitoring data are used as the fourth monitoring data. The fourth monitoring data is the set of parameters in the first monitoring data that are inconsistent with the preset monitoring data. From the fourth set of monitoring data, several parameters are randomly selected as the first and second values. Multiple parameters included in the first monitoring data for the device under analysis can be predetermined. Each parameter is assigned a weight based on its influence on the device, with a total weight of 1. The first and second values ​​are then weighted and summed to obtain a fault score, which represents the severity of the fault in the device under analysis. The fault status is determined based on the fault score.

[0064] For example, the first monitoring data includes spray pressure, paint flow rate, audio information, and distribution density. Since normal spraying is closely related to spray pressure and distribution density, the weights of spray pressure and distribution density are set to 0.3 each. Because the impact of paint flow rate is greater than that of audio information, the weight of paint flow rate is set to 0.2, and the weight of audio information is set to 0.1, for a total weight of 1. Since the fourth monitoring data includes paint flow rate and distribution density, the first value corresponding to paint flow rate and the second value corresponding to distribution density are obtained. The first value is then calculated with the weight corresponding to paint flow rate to obtain the first score. The second value is then calculated with the weight corresponding to distribution density to obtain the second score. Finally, the first and second scores are added together and divided by the target number to obtain the fault score. The target number refers to the total number of parameters in the fourth monitoring data. Different devices require different monitoring data. Weights can be assigned to each monitoring data point based on the actual situation of the device to be analyzed, so as to evaluate the level of fault status of the device.

[0065] Furthermore, fault states are categorized into low, medium, and high fault levels. The fault state is determined based on a fault score, specifically including: determining if the fault score is less than a preset fault score; if the fault score is less than the preset fault score, the equipment under analysis is determined to be at a low fault level, and a first handling measure is output based on the low fault level; if the fault score is equal to the preset fault score, the equipment under analysis is determined to be at a medium fault level, and a second handling measure is output based on the medium fault level; if the fault score is greater than the preset fault score, the equipment under analysis is determined to be at a high fault level, and a third handling measure is output based on the high fault level. Specifically, after obtaining the fault score corresponding to the equipment under analysis, the fault score is compared with the preset fault score. The preset fault score is the threshold for classifying the fault level of the equipment under analysis and can be set using historical data. If the fault score is less than the preset fault score, the equipment under analysis is determined to be at a low fault level, and a first handling measure is output based on the low fault level. The first handling measure is a maintenance suggestion for low fault levels, typically involving observation or simple maintenance. For example, if the equipment under analysis is a spray gun, the first handling measure would be: the equipment is operating normally, but the paint flow rate is slightly high, requiring regular monitoring of the paint flow rate. The monitoring platform displays the first handling measure, which can be pushed to the user via SMS. Here, the user refers to the staff performing routine maintenance on the desulfurization equipment. When the fault score equals the preset fault score, the equipment under analysis is determined to be at a medium fault level. Based on this level, a second handling measure is output, which is a maintenance suggestion for medium fault levels, typically involving planned maintenance or component replacement. For example, if the equipment under analysis is a spray gun, the second handling measure would be: the equipment has a moderate fault, with abnormal paint flow and spray area distribution density, suggesting planned maintenance; or shut down the machine to check if the spray gun nozzles are clogged, and clean or replace the nozzles. The second handling measure is displayed on the monitoring platform and pushed to the user via SMS / email. When the fault score equals the preset fault score, the equipment under analysis is determined to be at a high fault level. Based on this level, a third handling measure is output, which is a maintenance suggestion for high fault levels, typically involving emergency shutdown or component replacement. For example, if the equipment under analysis is a spray gun, the third handling measure would be: the equipment has a serious fault, with severely abnormal paint flow and spray area distribution density, suggesting immediate shutdown for repair. The monitoring platform displays the third handling measure, pushes it to the user via SMS / email, and triggers an alarm.

[0066] The fault level of the equipment to be analyzed is determined based on the fault score. Corresponding handling measures are then determined based on the fault level. The target time point corresponding to the fault state of the equipment to be analyzed is obtained. An early warning message is generated based on the target time point and the fault level, and this message is sent to the user so that the user can handle the equipment to be analyzed according to the warning message. Specifically, this includes: obtaining the target time point and target location; the target time point is the time point after the equipment to be analyzed is determined to be in a fault state, and the target location is the location of the equipment to be analyzed within the desulfurization equipment; generating an early warning message based on the fault state and the target time point, and sending the warning message and target location to the user so that the user can go to the target location to handle the fault of the equipment to be analyzed. Specifically, the time point after the equipment to be analyzed is determined to be in a fault state is detected, i.e., the target time point. If the fault score of the equipment to be analyzed is not 0, it is assumed that the equipment to be analyzed is in a fault state, and the current time is immediately recorded as the target time point. The specific location of each device within the desulfurization equipment is obtained in advance, and each device is sequentially bound to its corresponding location. Alternatively, a spatial layout diagram of the desulfurization equipment can be constructed, and the location of each device can be marked on the spatial layout diagram. After confirming that the equipment to be analyzed is in a fault state, the target location corresponding to the equipment is obtained. The target location refers to the spatial coordinates of the equipment. A fault score is determined for the equipment, and the fault level is determined according to the score. The corresponding handling measures are obtained, and the target time, fault level, handling measures, and the name of the equipment are integrated to obtain an early warning message. For example, if the equipment to be analyzed is an oxidation blower, and it corresponds to a high fault level, the early warning message would be: "The oxidation blower detected a fault at 14:30:20 on 2025-04-11. The fault level is high. Please immediately shut down the desulfurization equipment and proceed with the handling!" The early warning message and the target location (the spatial coordinates of the equipment) are then sent to the user via a push notification from the monitoring platform. The appropriate push method can be selected based on the fault level of the equipment. For high fault levels, telephone or voice broadcasting is preferred; for medium fault levels, SMS is preferred; and for low fault levels, email or an app is preferred. When pushing out information, a link to a floor plan showing the equipment location can be attached for easy user navigation. After receiving the warning message, users can view the target location information and proceed to the site accordingly. Based on the fault level of the equipment to be analyzed in the warning message, appropriate handling measures are taken. This closed-loop process—obtaining the target time and location, generating warning messages based on the fault status and target time, and then pushing the warning messages and target location to the user—achieves rapid early warning and accurate location of desulfurization equipment faults, reduces manual intervention, and shortens fault handling time based on tiered warnings.

[0067] In one possible implementation, when the first monitoring data matches the preset monitoring data, the equipment under analysis is determined to be in normal condition, indicating that no abnormalities have been found in the equipment under analysis. Then, following the fault monitoring method described above for the equipment under analysis, other equipment in the desulfurization system is monitored sequentially to promptly identify faulty equipment and generate corresponding early warning information, facilitating user repair of faulty equipment.

[0068] In one possible implementation, multiple devices to be analyzed can be selected from the desulfurization equipment. Based on the operating status of the desulfurization equipment, an appropriate detection method is selected to monitor each device, obtaining multiple monitoring data points. These data points are then input into a preset fault model for analysis to determine whether any fault exists in the analyzed devices. The preset fault model is a pre-trained fault model constructed by training on historical monitoring data from the desulfurization equipment. Subsequently, the monitoring data corresponding to each of the analyzed devices is input into the preset fault model for processing, sequentially outputting the operating status (fault status or normal status) of each analyzed device. Appropriate handling measures are then selected based on the operating status of each analyzed device, allowing the user to promptly address any faults in the analyzed devices. This application also provides a fault early warning device for desulfurization equipment. Figure 2 This is a schematic diagram of a fault early warning device for desulfurization equipment provided in an embodiment of this application. (Refer to...) Figure 2 The device is a monitoring platform, which includes an acquisition unit 201, a processing unit 202, and a confirmation unit 203.

[0069] Acquisition unit 201 acquires the target operating parameters corresponding to the desulfurization equipment.

[0070] Processing unit 202 determines the operating status of the desulfurization equipment based on the target operating parameters. The operating status includes working status and non-working status. It determines the equipment to be analyzed, determines the target analysis method based on the equipment to be analyzed and the operating status, and obtains the first monitoring data. The equipment to be analyzed is any one of the desulfurization equipment, including spray gun equipment, flue equipment, desulfurizing agent storage equipment, and oxidation fan equipment. The first monitoring data is obtained by monitoring the equipment to be analyzed using the target analysis method. The first monitoring data is compared with the preset monitoring data.

[0071] The confirmation unit 203 determines that the device to be analyzed is in a fault state when the first monitoring data is inconsistent with the preset monitoring data. It generates an early warning message based on the fault state and displays the early warning message to the user so that the user can handle the device to be analyzed according to the early warning message.

[0072] In one possible implementation, the acquisition unit 201 is used to acquire a first concentration value and a target flue gas flow rate, wherein the first concentration value is the sulfur dioxide concentration value obtained at the inlet of the desulfurization equipment; acquire a second concentration value, wherein the second concentration value is the sulfur dioxide concentration value obtained at the outlet of the desulfurization equipment; and output the first concentration value, the second concentration value, and the target flue gas flow rate as target operating parameters; the processing unit 202 is used to determine whether the first concentration value and the second concentration value are the same, and whether the target flue gas flow rate is within a preset flue gas range; the confirmation unit 203 is used to determine that the desulfurization equipment is in a non-working state when the first concentration value and the second concentration value are the same, and the target flue gas flow rate is not within the preset flue gas range; and to determine that the desulfurization equipment is in a working state when the first concentration value and the second concentration value are different, and the target flue gas flow rate is within the preset flue gas range.

[0073] In one possible implementation, the confirmation unit 203, after determining that the desulfurization equipment is in a non-working state, determines a first detection method based on the non-working state and the equipment to be analyzed, and outputs the first detection method as the target analysis method; the processing unit 202 is used to detect the equipment to be analyzed using the first detection method to obtain second monitoring data, and outputs the second monitoring data as the first monitoring data; when the equipment to be analyzed is a spray gun, the second monitoring data includes part dimensions and corrosion values; when the equipment to be analyzed is an oxidation blower, the second monitoring data includes insulation resistance, winding resistance, and target current; when the equipment to be analyzed is a desulfurizing agent storage device, the second monitoring data includes first humidity; when the equipment to be analyzed is a flue gas device, the second monitoring data includes flue gas ash accumulation values.

[0074] In one possible implementation, the confirmation unit 203, after determining that the desulfurization equipment is in operation, determines a second detection method based on the operating status and the equipment to be analyzed, and outputs the second detection method as the target analysis method; the processing unit 202, uses the second detection method to detect the equipment to be analyzed, obtains third monitoring data, and outputs the third monitoring data as the first monitoring data; when the equipment to be analyzed is a spray gun, the third monitoring data includes spray pressure value, paint flow rate, audio information, and spray area distribution density; when the equipment to be analyzed is an oxidation fan, the third monitoring data includes vibration value, fan temperature, audio information, and exhaust pressure value; when the equipment to be analyzed is a desulfurizing agent storage device, the third monitoring data includes second humidity; when the equipment to be analyzed is a flue gas device, the third monitoring data includes flue gas temperature and flue gas pressure values.

[0075] In one possible implementation, the processing unit 202 is used to determine preset monitoring data based on the device to be analyzed; determine whether the first monitoring data is consistent with the preset monitoring data; the acquisition unit 201 is used to acquire fourth monitoring data when the first monitoring data is inconsistent with the preset monitoring data, the fourth monitoring data being the monitoring data in the first monitoring data that is inconsistent with the preset monitoring data; acquire a first value and a second value from the fourth monitoring data, the first value and the second value being the values ​​corresponding to any two monitoring data in the fourth monitoring data; the processing unit 202 is used to calculate the first value and the second value to obtain a fault score; and determine the fault status based on the fault score.

[0076] In one possible implementation, the processing unit 202 is used to determine whether the fault score is less than a preset fault score; the confirmation unit 203 is used to determine that the device to be analyzed is at a low fault level when the fault score is less than the preset fault score, and output a first processing measure according to the low fault level; when the fault score is equal to the preset fault score, determine that the device to be analyzed is at a medium fault level, and output a second processing measure according to the medium fault level; when the fault score is greater than the preset fault score, determine that the device to be analyzed is at a high fault level, and output a third processing measure according to the high fault level.

[0077] In one possible implementation, the acquisition unit 201 is used to acquire the target time point and the target location. The target time point is the time point after it is determined that the equipment to be analyzed is in a fault state, and the target location is the location of the equipment to be analyzed in the desulfurization equipment. The processing unit 202 is used to generate early warning information based on the fault state and the target time point, and send the early warning information and the target location to the user so that the user can go to the target location to handle the fault of the equipment to be analyzed.

[0078] It should be noted that the above embodiments of the apparatus are only illustrated by the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the apparatus and method embodiments provided in the above embodiments belong to the same concept, and the specific implementation process can be found in the method embodiments, which will not be repeated here.

[0079] This application also discloses an electronic device. (See reference...) Figure 3 , Figure 3 This application provides a schematic diagram of the structure of an electronic device. The electronic device 300 may include: at least one processor 301, at least one network interface 304, a user interface 303, a memory 302, and at least one communication bus 305.

[0080] The communication bus 305 is used to enable communication between these components.

[0081] The user interface 303 may include a display screen and a camera. Optionally, the user interface 303 may also include a standard wired interface and a wireless interface.

[0082] The network interface 304 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface).

[0083] The processor 301 may include one or more processing cores. The processor 301 connects to various parts of the server using various interfaces and lines, and performs various server functions and processes data by running or executing instructions, programs, code sets, or instruction sets stored in memory 302, and by calling data stored in memory 302. Optionally, the processor 301 may be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). The processor 301 may integrate one or a combination of several of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), and modem. The CPU primarily handles the operating system, user interface, and application requests; the GPU is responsible for rendering and drawing the content required for display; and the modem handles wireless communication. It is understood that the modem may also not be integrated into the processor 301 and may be implemented as a separate chip.

[0084] The memory 302 may include random access memory (RAM) or read-only memory. Optionally, the memory 302 may include a non-transitory computer-readable storage medium. The memory 302 may be used to store instructions, programs, code, code sets, or instruction sets. The memory 302 may include a program storage area and a data storage area. The program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch functionality, sound playback functionality, image playback functionality, etc.), instructions for implementing the various method embodiments described above, etc. The data storage area may store data involved in the various method embodiments described above. Optionally, the memory 302 may also be at least one storage device located remotely from the aforementioned processor 301.

[0085] like Figure 3 As shown, the memory 302, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface module, and an application program for fault warning of desulfurization equipment.

[0086] exist Figure 3 In the electronic device 300 shown, the user interface 303 is mainly used to provide an input interface for the user and to obtain the user input data; while the processor 301 can be used to call the application program for fault warning of desulfurization equipment stored in the memory 302. When executed by one or more processors, the electronic device performs one or more of the methods described in the above embodiments.

[0087] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0088] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0089] In the several embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some service interfaces; indirect couplings or communication connections between devices or units may be electrical or other forms.

[0090] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0091] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0092] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as USB flash drives, portable hard drives, magnetic disks, or optical disks.

[0093] The above description is merely an exemplary embodiment of this disclosure and should not be construed as limiting the scope of this disclosure. Any equivalent changes and modifications made in accordance with the teachings of this disclosure shall still fall within the scope of this disclosure. Those skilled in the art will readily conceive of other embodiments of this disclosure upon considering the specification and the disclosure of practical truths. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not described in this disclosure.

Claims

1. A method for early warning of faults in desulfurization equipment, characterized in that, When applied to a monitoring platform, the method includes: Obtain the target operating parameters corresponding to the desulfurization equipment; The desulfurization equipment's operating state is determined based on the target operating parameters. The operating state includes a working state and a non-working state. Specifically, determining the operating state based on the target operating parameters includes: acquiring a first concentration value and a target flue gas flow rate, where the first concentration value is the sulfur dioxide concentration obtained at the inlet of the desulfurization equipment; acquiring a second concentration value, where the second concentration value is the sulfur dioxide concentration obtained at the outlet of the desulfurization equipment; outputting the first concentration value, the second concentration value, and the target flue gas flow rate as the target operating parameters; determining whether the first concentration value and the second concentration value are the same, and whether the target flue gas flow rate is within a preset flue gas range; when the first concentration value and the second concentration value are the same, and the target flue gas flow rate is not within the preset flue gas range, determining that the desulfurization equipment is in the non-working state. When the first concentration value is different from the second concentration value, and the target flue gas flow rate is within the preset flue gas range, the desulfurization equipment is determined to be in the working state. The process involves identifying the device to be analyzed, determining a target analysis method based on the device and its operating status, and acquiring first monitoring data. The device to be analyzed is any one of the desulfurization devices, including a spray gun, a flue, a desulfurizing agent storage device, and an oxidation fan. The first monitoring data is obtained by monitoring the device using the target analysis method. Specifically, determining the target analysis method and acquiring the first monitoring data includes: after determining that the desulfurization device is in a non-working state, determining a first detection method based on the non-working state and the device to be analyzed, and then... The first detection method is used as the target analysis method for output; the device to be analyzed is detected using the first detection method to obtain second monitoring data, and the second monitoring data is output as the first monitoring data; when the device to be analyzed is the spray gun device, the second monitoring data includes part dimensions and corrosion values; when the device to be analyzed is the oxidation fan device, the second monitoring data includes insulation resistance, winding resistance, and target current; when the device to be analyzed is the desulfurizing agent storage device, the second monitoring data includes first humidity; when the device to be analyzed is the flue gas device, the second monitoring data includes flue gas ash accumulation values; Compare the first monitoring data with the preset monitoring data; When the first monitoring data is inconsistent with the preset monitoring data, it is determined that the device to be analyzed is in a fault state. An early warning message is generated based on the fault state and displayed to the user so that the user can handle the device to be analyzed according to the early warning message.

2. The method according to claim 1, characterized in that, The process of determining the device to be analyzed, determining the target analysis method based on the device to be analyzed and the operating status, and acquiring the first monitoring data specifically includes: After determining that the desulfurization equipment is in the working state, a second detection method is determined based on the working state and the equipment to be analyzed, and the second detection method is output as the target analysis method. The device to be analyzed is detected using the second detection method to obtain third monitoring data, and the third monitoring data is output as the first monitoring data. When the device to be analyzed is the spray gun, the third monitoring data includes spray pressure value, paint flow rate, audio information, and spray area distribution density; When the device to be analyzed is the oxidation blower, the third monitoring data includes vibration values, blower temperature, audio information, and exhaust pressure values. When the device to be analyzed is the desulfurizing agent storage device, the third monitoring data includes the second humidity; When the device to be analyzed is the flue equipment, the third monitoring data includes flue gas temperature and flue gas pressure values.

3. The method according to claim 2, characterized in that, The step of determining that the device to be analyzed is in a fault state when the first monitoring data is inconsistent with the preset monitoring data specifically includes: The preset monitoring data is determined based on the device to be analyzed; Determine whether the first monitoring data is consistent with the preset monitoring data; When the first monitoring data is inconsistent with the preset monitoring data, a fourth monitoring data is obtained, wherein the fourth monitoring data is the monitoring data in the first monitoring data that is inconsistent with the preset monitoring data; A first value and a second value are obtained from the fourth monitoring data, wherein the first value and the second value are values ​​corresponding to any two monitoring data in the fourth monitoring data; The fault score is obtained by calculating the first value and the second value; The fault status is determined based on the fault score.

4. The method according to claim 3, characterized in that, The fault status includes low fault level, medium fault level, and high fault level. Determining the fault status based on the fault score specifically includes: Determine whether the fault score is less than a preset fault score; When the fault score is less than the preset fault score, the device to be analyzed is determined to be in the low fault level, and a first processing measure is output according to the low fault level. When the fault score is equal to the preset fault score, the device to be analyzed is determined to be at the medium fault level, and a second processing measure is output according to the medium fault level. When the fault score is greater than the preset fault score, the device to be analyzed is determined to be in the high fault level, and a third processing measure is output according to the high fault level.

5. The method according to claim 4, characterized in that, The step of generating an early warning message based on the fault status and displaying the early warning message to the user so that the user can process the device to be analyzed based on the early warning message specifically includes: Obtain the target time point and the target location, wherein the target time point is the time point after the equipment to be analyzed is determined to be in the fault state, and the target location is the position of the equipment to be analyzed in the desulfurization equipment; The warning message is generated based on the fault status and the target time point, and the warning message and the target location are sent to the user so that the user can go to the target location to handle the fault of the device to be analyzed.

6. A fault early warning device for desulfurization equipment, characterized in that, The device is a monitoring platform, which includes an acquisition unit (201), a processing unit (202), and a confirmation unit (203). The acquisition unit (201) acquires the target operating parameters corresponding to the desulfurization equipment; The processing unit (202) determines the operating state of the desulfurization equipment according to the target operating parameters. The operating state includes a working state and a non-working state. Specifically, determining the operating state of the desulfurization equipment according to the target operating parameters includes: acquiring a first concentration value and a target flue gas flow rate, where the first concentration value is the sulfur dioxide concentration value obtained at the inlet of the desulfurization equipment; acquiring a second concentration value, where the second concentration value is the sulfur dioxide concentration value obtained at the outlet of the desulfurization equipment; outputting the first concentration value, the second concentration value, and the target flue gas flow rate as the target operating parameters; determining whether the first concentration value and the second concentration value are the same, and whether the target flue gas flow rate is within a preset flue gas range; when the first concentration value and the second concentration value are the same, and the target flue gas flow rate is not within the preset flue gas range, determining that the desulfurization equipment is in the non-working state; when the first concentration value and the second concentration value are different, and the target flue gas flow rate is within the preset flue gas range, determining that the desulfurization equipment is in the working state. The process involves identifying the device to be analyzed, determining a target analysis method based on the device and its operating status, and acquiring first monitoring data. The device to be analyzed is any one of the desulfurization devices, including a spray gun, a flue, a desulfurizing agent storage device, and an oxidation fan. The first monitoring data is obtained by monitoring the device using the target analysis method. Specifically, determining the target analysis method and acquiring the first monitoring data involves: after determining that the desulfurization device is in a non-working state, determining a first detection method based on the non-working state and the device to be analyzed, and using the first detection method as the target analysis method. The analysis method outputs the data; the device to be analyzed is tested using the first detection method to obtain second monitoring data, which is then output as the first monitoring data; when the device to be analyzed is the spray gun device, the second monitoring data includes part dimensions and corrosion values; when the device to be analyzed is the oxidation fan device, the second monitoring data includes insulation resistance, winding resistance, and target current; when the device to be analyzed is the desulfurizing agent storage device, the second monitoring data includes first humidity; when the device to be analyzed is the flue gas device, the second monitoring data includes flue gas ash accumulation values; the first monitoring data is compared with preset monitoring data; When the first monitoring data is inconsistent with the preset monitoring data, the confirmation unit (203) determines that the device to be analyzed is in a fault state, generates an early warning message based on the fault state, and displays the early warning message to the user so that the user can process the device to be analyzed according to the early warning message.

7. An electronic device, characterized in that, The device includes a processor (301), a memory (302), a user interface (303), and a network interface (304). The memory (302) is used to store instructions. The user interface (303) and the network interface (304) are used to communicate with other devices. The processor (301) is used to execute the instructions stored in the memory (302) to cause the electronic device (300) to perform the method as described in any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions that, when executed, perform the method as described in any one of claims 1-5.

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