Remote operation and maintenance system of gas pressurization station for double-chamber kiln

Abstract

The invention discloses a gas pressurization station remote operation and maintenance system for a double-chamber kiln, which relates to the technical field of double-chamber kiln operation and maintenance and comprises a rotating speed interval acquisition module, a track deviation range acquisition module, a fan blade fault signal generation module and a shutdown control module. The real-time deviation value and the rotating speed of the fan blades of the fan are obtained in real time, the fan blade fault signals are generated through comparative analysis, meanwhile, the early warning mechanism is triggered, when it is detected that the track deviation exceeds the normal range, the fan blade fault signals are generated, the system automatically triggers the early warning mechanism, operation and maintenance personnel are reminded to handle in time in the modes of sound-light alarm, short message notification and the like, and the operation and maintenance efficiency is improved. When the track deviation is detected to exceed a normal range, the system automatically triggers an early warning mechanism, so that operation and maintenance personnel can quickly respond to fan blade faults and can be timely notified to take corresponding measures, potential faults are effectively avoided, the reliability and stability of the system are improved, and the operation and maintenance efficiency is improved.

Description

Technical Field

[0001] The invention relates to the technical field of double-chamber kiln operation and maintenance, and in particular to a remote operation and maintenance system of a gas pressure station for a double-chamber kiln. Background Art

[0002] The double-chamber kiln is an important industrial kiln equipment, which is widely used in metallurgy, building materials and other industries. The gas booster station is the key link to provide a stable gas supply for the double-chamber kiln. As an important energy medium, gas plays a vital role in the production process of the double-chamber kiln. Rational use of gas resources, improving energy efficiency and reducing production costs are important goals pursued by enterprises. The effective operation of the gas booster station can ensure the stability of the gas pressure during the transportation process, improve the combustion efficiency of the gas, and thus achieve efficient use of energy. With the continuous development of automation and intelligent technology, the demand for remote operation and maintenance in industrial production is increasing.

[0003] Patent publication number CN116659646A discloses a machine vision-based wind turbine blade vibration detection method and device, which relates to the field of blade vibration detection. The method comprises: collecting wind turbine blade vibration images, and converting the wind turbine blade vibration images into digital image information; preprocessing and preliminarily denoising the digital image information, and performing deep denoising on the preliminarily denoised digital image information based on a deep learning recognition model trained with historical wind turbine blade images; amplifying the digital image information based on an adaptive video amplification method, and extracting the displacement time-history response of the wind turbine blade vibration from the amplified video through a sub-pixel template matching algorithm; normalizing the displacement time-history response to obtain the actual displacement time-history response, and performing fast Fourier transform on the actual displacement time-history response to obtain the vibration frequency of the wind turbine blade. The method has the advantages of high reliability, strong anti-interference ability, simple installation, low cost, targeted feature extraction, and high recognition accuracy.

[0004] Fan blades are the most important parts of a fan. If hidden dangers are not monitored and handled in time, the performance and safety of the fan will be affected. Therefore, it is very important to monitor the status of the fan blades and diagnose faults.

[0005] However, when monitoring the operating status of the fan, especially the operating trajectory of the fan blades, it is difficult to intuitively and accurately understand the actual operating trajectory of the fan blades, it is impossible to analyze the position changes of the fan blades passing through a fixed area, and it is impossible to promptly discover minor abnormalities in the operation of the fan blades, resulting in the inability to promptly discover fan failures or abnormalities; based on this, a remote operation and maintenance system for the gas booster station for double-chamber kilns is proposed. Summary of the invention

[0006] The purpose of the present invention is to provide a remote operation and maintenance system for a gas booster station for a double-chamber kiln, which solves the technical problems of being unable to intuitively and accurately understand the actual operating trajectory of the fan blades and being unable to promptly discover minor anomalies in the operation of the fan blades.

[0007] The purpose of the present invention can be achieved by the following technical solutions:

[0008] The remote operation and maintenance system of the gas booster station for double-chamber kilns includes:

[0009] The speed range acquisition module acquires multiple speed ranges of the fan by dividing them into equal intervals according to the preset upper and lower limits of the fan speed;

[0010] The trajectory deviation range acquisition module analyzes the operation images of the fan blades in each speed range to obtain the trajectory deviation range corresponding to each speed range;

[0011] The fan blade fault signal generation module obtains the deviation value of the fan blade and the current real-time speed of the fan in real time, obtains the comparison deviation range from the corresponding trajectory deviation range in each speed interval, compares and analyzes the real-time deviation value of the fan blade with the comparison deviation range, and determines and generates a fan blade fault signal based on the analysis result;

[0012] The shutdown control module compares the difference between the real-time deviation value of the fan blade and the trajectory deviation upper limit value of the comparison deviation range. When the difference is greater than the preset threshold value Y3, a shutdown signal is generated to shut down the fan.

[0013] As a further solution of the present invention: the specific method of obtaining multiple speed ranges of the fan is:

[0014] The fan speed upper limit value ZA and lower limit value ZB are preset, and the upper limit value and the lower limit value are divided into equal intervals according to a uniform preset interval ZC to obtain multiple speed intervals.

[0015] As a further solution of the present invention: the specific method of obtaining the trajectory deviation range corresponding to each speed interval is:

[0016] A1: Randomly select one of the fan speed ranges as the target speed range;

[0017] Through the camera device installed inside the fan, the running image of the fan blade is obtained at every time interval T, and the position trajectory of the fan blade in the preset area of ​​the image is obtained repeatedly, and then the analysis images of multiple fan blades are obtained. Here, the time interval T is 3 seconds;

[0018] A2: Select one of the multiple analysis images as the target image, set a two-dimensional coordinate system and multiple calibration lines in the target image, obtain the coordinates of the intersections between the wind blade trajectory and each calibration line and the coordinates of the center point of the target image, calculate and analyze the distances between each intersection and the center point of the target image, and obtain the maximum offset value and the minimum offset value of the target image;

[0019] A3: Repeat A2 to analyze multiple analysis images to obtain the maximum offset value PAa and the minimum offset value PBa corresponding to each analysis image, calculate the discrete value U of the maximum offset value PAa, analyze the discrete value U to obtain the upper limit of the trajectory deviation in the target speed range, and use the minimum value of the minimum offset value as the lower limit of the trajectory deviation in the target speed range to generate the trajectory deviation range corresponding to the target speed range, where a refers to different analysis images, a=1, 2, ..., e, e refers to the number of analysis images, e≥1;

[0020] A4: Repeat steps A1-A3 to obtain the trajectory deviation range corresponding to the fan blades in each speed range.

[0021] As a further solution of the present invention: the specific method of analyzing the discrete value U to obtain the upper limit value of the trajectory deviation in the target speed range is:

[0022] When the discrete value U is less than the preset value Y1, the mean PAp of PAc is used as the upper limit EA1 of the trajectory deviation in the target speed range. When U is greater than or equal to the preset value Y1, the values ​​that deviate greatly from the mean PAp are deleted in order from small to large according to the numerical values ​​corresponding to PAc, and the number b of deleted values ​​is recorded. At the same time, the discrete degree value is recalculated at each deletion until the discrete value satisfies the preset value Y1. When the number b of deletions is greater than the preset value Y2, the average of the maximum and minimum values ​​in PAc is used as the upper limit EA1 of the trajectory deviation in the target speed range. When the number b of deletions is less than or equal to the preset value Y2, the mean PAp of PAc is used as the upper limit EA1 of the trajectory deviation in the target speed range.

[0023] As a further solution of the present invention: the specific method of obtaining the maximum offset value and the minimum offset value of the target image is:

[0024] Set multiple calibration lines from top to bottom in the target image, obtain the intersection coordinates Bi (BXi, BYi) between the wind blade trajectory in the target image and each calibration line, and obtain the center point coordinates Z (ZX, ZY) of the target image at the same time, and calculate the distance formula: Calculate the distances Li between each intersection point Bi in the target image and the center point Z, take the maximum value of the distances Li as the maximum offset value of the target image, and take the minimum value of the distances Li as the minimum offset value of the target image, where i refers to different calibration lines, i is a positive integer, and i≥1.

[0025] As a further solution of the present invention: the specific method of determining and generating a fan blade fault signal is:

[0026] The real-time speed of the fan and the comparison deviation range relative to the real-time speed are obtained. When the speed does not fall within the comparison deviation range, a fan blade fault signal is generated. When the real-time speed falls within the comparison deviation range, no processing is performed.

[0027] As a further solution of the present invention: the specific method of obtaining the position trajectory of the fan blades in the preset area of ​​the image is:

[0028] The rectangular area in the running image is intercepted to obtain the position trajectory of the fan blades in the preset area of ​​the image.

[0029] As a further solution of the present invention: it also includes a shutdown control module;

[0030] The shutdown control module obtains the difference between the real-time deviation value of the fan blade and the upper limit value of the trajectory deviation in the comparison deviation range. When the difference is greater than the preset threshold value Y3, a shutdown signal is generated to shut down the fan. Otherwise, no processing is performed.

[0031] Beneficial effects of the present invention:

[0032] (1) The present invention obtains the real-time deviation value of the fan blade and the fan speed in real time, compares and analyzes and generates a fan blade fault signal, and triggers an early warning mechanism at the same time. When it is detected that the trajectory deviation exceeds the normal range, a fan blade fault signal is generated, and the system automatically triggers the early warning mechanism, which will immediately sound an alarm, and remind the operation and maintenance personnel to deal with it in time through sound and light alarms, text message notifications, etc. When it is detected that the trajectory deviation exceeds the normal range, the system automatically triggers the early warning mechanism, which enables the operation and maintenance personnel to respond quickly to the fan blade fault and promptly notify the operation and maintenance personnel to take corresponding measures, effectively avoiding the occurrence of potential faults, improving the reliability and stability of the system, and improving the operation and maintenance efficiency;

[0033] (2) The present invention generates a shutdown signal to shut down the fan when the difference between the real-time deviation value of the fan blades and the upper limit value of the trajectory deviation in the comparison deviation range is greater than a preset threshold value. This makes it impossible to continue to operate the fan when the blade position deviation is serious, resulting in damage to the fan. This avoids unnecessary damage to the fan by the fan blades, further ensures the normal operation of the fan, and reduces maintenance costs and downtime. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The present invention will be further described below in conjunction with the accompanying drawings.

[0035] Figure 1 It is a schematic diagram of the system framework structure of the present invention;

[0036] Figure 2 It is a structural schematic diagram of the fan blade operation image of the present invention;

[0037] Figure 3 It is a schematic diagram of the structure of the fan blades of the present invention within the preset area of ​​the image. DETAILED DESCRIPTION

[0038] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0039] Embodiment 1

[0040] See also Figure 1-Figure 3 As shown, the present invention is a remote operation and maintenance system for a gas pressure station for a double-chamber kiln, comprising:

[0041] The speed range acquisition module obtains multiple speed ranges of the fan according to the preset upper and lower limits of the fan speed. The specific method is as follows:

[0042] The upper limit value ZA and the lower limit value ZB of the fan speed are preset, and multiple speed intervals of the fan are obtained according to the upper limit value ZA and the lower limit value ZB. The division method can be equal interval division or unequal interval division. Here, the equal interval division method is adopted to obtain multiple speed intervals, and the upper limit value ZA and the lower limit value ZB are divided according to the unified preset interval ZC, so as to obtain multiple speed intervals of the fan [ZB, ZB+ZC], (ZB+ZC, ZB+2ZC], ..., (ZA-ZC, ZA], wherein ZA>ZB, and the specific value of ZC is formulated by relevant personnel according to actual needs and application scenarios;

[0043] By presetting the upper and lower limits of the fan speed, multiple speed intervals are obtained by equally spaced division, making the analysis of the fan under different speed states more detailed and accurate, solving the problem that the existing remote operation and maintenance system may not be detailed enough for the fan speed analysis and cannot perform targeted monitoring and maintenance for different speed intervals. It can more accurately understand the operating status of the fan at different speeds, provide a clearer reference range for the subsequent trajectory deviation analysis, and improve the pertinence and effectiveness of operation and maintenance;

[0044] The trajectory deviation range acquisition module is used to analyze the running images of the fan blades in each speed range, and obtain the trajectory deviation ranges corresponding to the fan blades in each speed range according to the analysis results. The specific method is as follows:

[0045] A1: Randomly select one of the fan speed ranges as the target speed range;

[0046] By installing a camera inside the fan, it is ensured that the image of the fan blade passing through a fixed position can be clearly captured. Specifically, the camera is installed inside the fan close to the running track of the fan blade and can clearly observe the fan blade passing through the fixed area. The specific location should be considered to avoid interference from other components inside the fan. At the same time, it is ensured that the running image of the fan blade can be stably obtained. It can be installed on the fan casing and aimed at the running area of ​​the fan blade through a specific window or opening, or a small, fixed camera is used, which is directly installed on the supporting structure inside the fan to obtain the best shooting angle. The above belongs to existing and mature technologies and therefore no further description is made here;

[0047] The running image of the fan blade when it passes through the fixed area position is obtained, and the outline of the fan blade is further extracted from the intercepted rectangular area by using image processing technology, and the obtained running image is preliminarily preprocessed, including image denoising, contrast enhancement and other operations. At the same time, common image processing algorithms and threshold segmentation methods can be used to detect the edge of the fan blade in the image. These algorithms determine the position of the edge by calculating the gradient of the image, thereby extracting the outline of the fan blade. The above are existing and mature technologies, so no further description is made here;

[0048] Make the fan speed within the target speed range, and use the camera to obtain the running image of the fan blades at a time interval T, and obtain the position trajectory of the fan blades in the preset area of ​​the image. After obtaining multiple times in succession, obtain multiple analysis images of the fan blades. The specific value of the time interval T is determined by relevant personnel according to actual needs. Here, T is 3 seconds;

[0049] The method of obtaining the position trajectory of the fan blades in the preset area of ​​the image is as follows: a rectangular area is preset in the image, the rectangular area in the running image is intercepted, and then the position trajectory of the fan blades in the preset area of ​​the image is obtained;

[0050] A2: Select one of the multiple analysis images as the target image;

[0051] A two-dimensional coordinate system is set in the target image, that is, a two-dimensional coordinate system is set in the rectangular area of ​​the running image, and multiple calibration lines are set in the target image from top to bottom, and the coordinates of the intersections between the wind blade trajectory in the target image and each calibration line are obtained, and marked as Bi (BXi, BYi), where i refers to different calibration lines, i is a positive integer, i≥1;

[0052] Get the center point coordinates of the target image, that is, the center point coordinates of the rectangular area, and mark it as Z (ZX, ZY);

[0053] The distance calculation formula is: Calculate the distance Li between each intersection point Bi in the target image and the center point Z;

[0054] Get the maximum value L among Li max and the minimum value L min , and the maximum value L max As the maximum offset value PA1 of the target image, the minimum value L min As the minimum offset value PB1 of the target image;

[0055] A3: Repeat A2 to analyze multiple analysis images, and obtain the maximum offset value PAa and the minimum offset value PBa corresponding to each analysis image, where a refers to different analysis images, a=1, 2, ..., e, e refers to the number of analysis images, e≥1;

[0056] By formula The discrete value U of the maximum offset value PAa is calculated, wherein PAc refers to any value in PAa, PAp is the mean value of PAc, a≥c≥1, when the discrete value U is less than the preset value Y1, the mean value PAp is used as the upper limit value EA1 of the trajectory deviation in the target speed range, when U is greater than or equal to the preset value Y1, the values ​​with larger deviations from the mean value PAp are deleted in ascending order according to the values ​​corresponding to PAc, and the number b of deleted values ​​is recorded, and the discrete degree value is recalculated each time the discrete value is deleted until the discrete value satisfies the preset value Y1, when the number b of deletions is greater than the preset value Y2, the average of the maximum and minimum values ​​in PAc is used as the upper limit value EA1 of the trajectory deviation in the target speed range, that is, through EA1=(PA max +P min ) / 2, calculate the upper limit value EA1 of the trajectory deviation in the target speed range, where PA max is the maximum value in PAc, PA minis the minimum value in PAc. When the number of deletions b is less than or equal to the preset value Y2, the mean value PAp of PAc is used as the upper limit value EA1 of the trajectory deviation in the target speed range. The specific values ​​of Y1 and Y2 are set by relevant personnel according to specific application scenarios and requirements.

[0057] At the same time, the minimum value among the minimum offset values ​​PAa corresponding to each analysis image is used as the trajectory deviation lower limit value EB1 of the target speed range;

[0058] According to the trajectory deviation upper limit EA1 and the trajectory deviation lower limit EB1 of the target speed interval, a trajectory deviation range [EB1, EA1] corresponding to the target speed interval is generated;

[0059] A4: Repeat steps A1-A3 to obtain the corresponding upper deviation limit EAr and trajectory deviation lower limit EBr of the fan blades in each speed range, and then obtain the corresponding trajectory deviation range [EBr,EAr] of the fan blades in each speed range, where r refers to different speed ranges, r is a positive integer, r≥1;

[0060] The fan blade fault signal generation module obtains the real-time deviation value of the fan blade and the real-time speed of the fan in real time, obtains the comparison deviation range from the trajectory deviation range corresponding to each speed interval according to the real-time speed of the fan, compares and analyzes the real-time deviation value of the fan blade with the comparison deviation range, and determines and generates the fan blade fault signal according to the analysis result. The specific method is as follows:

[0061] The real-time speed of the fan and the comparison deviation range relative to the real-time speed are obtained. When the real-time speed is within the comparison deviation range, no processing is performed. When the speed is not within the comparison deviation range, a fan blade fault signal is generated.

[0062] By installing a camera inside the fan and using image processing technology to obtain the contour and position trajectory of the fan blades, the deviation range of the fan blades' running trajectories in each speed range can be accurately analyzed, solving the problem that the existing system cannot accurately grasp the deviation of the fan blades' running trajectories. It can timely detect abnormal deviations in the operation of the fan blades, and warn of potential faults in advance, providing more accurate fault diagnosis basis for operation and maintenance personnel, and reducing the risk of fan failures caused by abnormal fan blade trajectories.

[0063] The real-time deviation value of the fan blade and the fan speed are obtained in real time, and a fan blade fault signal is generated through comparative analysis. At the same time, the early warning mechanism is triggered. When it is detected that the trajectory deviation exceeds the normal range, a fan blade fault signal is generated, and the system automatically triggers the early warning mechanism, and an alarm is immediately sounded. The operation and maintenance personnel are reminded to deal with it in time through sound and light alarms, text message notifications, etc. When it is detected that the trajectory deviation exceeds the normal range, the system automatically triggers the early warning mechanism, which enables the operation and maintenance personnel to respond quickly to the fan blade failure and promptly notify the operation and maintenance personnel to take corresponding measures, effectively avoiding the occurrence of potential failures, improving the reliability and stability of the system, and improving the operation and maintenance efficiency.

[0064] Embodiment 2

[0065] As the second embodiment of the present invention, when the present application is implemented, compared with the first embodiment, the difference between the technical solution of the present embodiment and the first embodiment is only that in the present embodiment, the shutdown control module;

[0066] The shutdown control module obtains the difference between the real-time deviation value of the fan blade and the upper limit value of the trajectory deviation of the comparison deviation range. When the difference is greater than the preset threshold value Y3, a shutdown signal is generated to shut down the fan. Otherwise, no processing is performed.

[0067] When the difference between the real-time deviation value of the fan blade and the upper limit value of the trajectory deviation of the comparison deviation range is large, it means that the position deviation of the fan blade is serious, which affects the normal operation of the fan. Continuing to operate the fan blade will cause damage to the fan. Therefore, a shutdown signal is generated to shut down the fan to avoid unnecessary damage to the fan by the fan blade, thereby further ensuring the normal operation of the fan.

[0068] When the difference between the real-time deviation value of the fan blades and the upper limit value of the trajectory deviation in the comparison deviation range is greater than the preset threshold, a shutdown signal is generated to shut down the fan, so that when the blade position deviation is serious, the fan cannot continue to operate, causing damage to the fan, thereby avoiding unnecessary damage to the fan by the fan blades, further ensuring the normal operation of the fan, and reducing maintenance costs and downtime.

[0069] Embodiment 3

[0070] As the third embodiment of the present invention, when the present application is specifically implemented, compared with the first and second embodiments, the technical solution of this embodiment is to combine the solutions of the first and second embodiments mentioned above for implementation.

[0071] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters and thresholds in the formula are set by technicians in this field according to actual conditions.

[0072] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. The remote operation and maintenance system of the gas pressure station for double-chamber kiln is characterized by: include: The speed range acquisition module acquires multiple speed ranges of the fan by dividing them into equal intervals according to the preset upper and lower limits of the fan speed; The trajectory deviation range acquisition module analyzes the operation images of the fan blades in each speed range to obtain the trajectory deviation range corresponding to each speed range; The fan blade fault signal generation module obtains the deviation value of the fan blade and the current real-time speed of the fan in real time, obtains the comparison deviation range from the corresponding trajectory deviation range in each speed interval, compares and analyzes the real-time deviation value of the fan blade with the comparison deviation range, and determines and generates a fan blade fault signal based on the analysis result; The shutdown control module compares the difference between the real-time deviation value of the fan blade and the trajectory deviation upper limit value of the comparison deviation range. When the difference is greater than the preset threshold value Y3, a shutdown signal is generated to shut down the fan.

2. The remote operation and maintenance system for the gas pressure station for double-chamber kiln according to claim 1 is characterized in that: The specific method of obtaining multiple speed ranges of the fan is: The fan speed upper limit value ZA and lower limit value ZB are preset, and the upper limit value and the lower limit value are divided into equal intervals according to a uniform preset interval ZC to obtain multiple speed intervals.

3. The remote operation and maintenance system for the gas pressure station for the double-chamber kiln according to claim 2 is characterized in that: The specific method for obtaining the trajectory deviation range corresponding to each speed range is: A1: Randomly select one of the fan speed ranges as the target speed range; Through the camera device installed inside the fan, the running image of the fan blade is obtained at every time interval T, and the position trajectory of the fan blade in the preset area of ​​the image is obtained repeatedly, and then the analysis images of multiple fan blades are obtained. Here, the time interval T is 3 seconds; A2: Select one of the multiple analysis images as the target image, set a two-dimensional coordinate system and multiple calibration lines in the target image, obtain the coordinates of the intersections between the wind blade trajectory and each calibration line and the coordinates of the center point of the target image, calculate and analyze the distances between each intersection and the center point of the target image, and obtain the maximum offset value and the minimum offset value of the target image; A3: Repeat A2 to analyze multiple analysis images to obtain the maximum offset value PAa and the minimum offset value PBa corresponding to each analysis image, calculate the discrete value U of the maximum offset value PAa, analyze the discrete value U to obtain the upper limit of the trajectory deviation in the target speed range, and use the minimum value of the minimum offset value as the lower limit of the trajectory deviation in the target speed range to generate the trajectory deviation range corresponding to the target speed range, where a refers to different analysis images, a=1, 2, ..., e, e refers to the number of analysis images, e≥1; A4: Repeat steps A1-A3 to obtain the trajectory deviation range corresponding to the fan blades in each speed range.

4. The remote operation and maintenance system for the gas pressure station for double-chamber kiln according to claim 1 is characterized in that: The specific method of analyzing the discrete value U to obtain the upper limit of the trajectory deviation in the target speed range is: When the discrete value U is less than the preset value Y1, the mean PAp of PAc is used as the upper limit EA1 of the trajectory deviation in the target speed range. When U is greater than or equal to the preset value Y1, the values ​​that deviate greatly from the mean PAp are deleted in order from small to large according to the numerical values ​​corresponding to PAc, and the number b of deleted values ​​is recorded. At the same time, the discrete degree value is recalculated at each deletion until the discrete value satisfies the preset value Y1. When the number b of deletions is greater than the preset value Y2, the average of the maximum and minimum values ​​in PAc is used as the upper limit EA1 of the trajectory deviation in the target speed range. When the number b of deletions is less than or equal to the preset value Y2, the mean PAp of PAc is used as the upper limit EA1 of the trajectory deviation in the target speed range.

5. The remote operation and maintenance system for the gas pressure station for double-chamber kiln according to claim 4 is characterized in that: The specific method of obtaining the maximum offset value and the minimum offset value of the target image is: Set multiple calibration lines from top to bottom in the target image, obtain the intersection coordinates Bi (BX i, BYi) between the wind blade trajectory in the target image and each calibration line, and obtain the center point coordinates Z (ZX, ZY) of the target image at the same time, and calculate the distance formula: Calculate the distance Li between each intersection point Bi in the target image and the center point Z, take the maximum value of the distance Li as the maximum offset value of the target image, and take the minimum value of the distance Li as the minimum offset value of the target image, where i refers to different calibration lines, i is a positive integer, and i≥1.

6. The remote operation and maintenance system for the gas pressure station for double-chamber kiln according to claim 5 is characterized in that: The specific method for determining and generating a fan blade fault signal is as follows: The real-time speed of the fan and the comparison deviation range relative to the real-time speed are obtained. When the speed does not fall within the comparison deviation range, a fan blade fault signal is generated. When the real-time speed falls within the comparison deviation range, no processing is performed.

7. The remote operation and maintenance system for the gas pressure station for double-chamber kiln according to claim 6 is characterized in that: The specific method of obtaining the position trajectory of the fan blades in the preset area of ​​the image is: The rectangular area in the running image is intercepted to obtain the position trajectory of the fan blades in the preset area of ​​the image.

8. The remote operation and maintenance system for the gas pressure station for double-chamber kiln according to claim 7 is characterized in that: Also includes a shutdown control module; The shutdown control module obtains the difference between the real-time deviation value of the fan blade and the upper limit value of the trajectory deviation in the comparison deviation range. When the difference is greater than the preset threshold value Y3, a shutdown signal is generated to shut down the fan. Otherwise, no processing is performed.

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