Analysis method and device for monitoring terminal data

Abstract

The invention relates to the technical field of data analysis, in particular to a monitoring terminal data analysis method and device, and the method comprises the steps: building a database of glass inclination types and corresponding faults based on historical data; when the glass in the image data is judged to be inclined and the smudginess type of the surface of the glass is no smudginess, comparing the four groups of data with corresponding threshold values set by each group of data through the data analysis module, and respectively outputting first probabilities of four groups of faults based on the range of the exceeded threshold values; when the glass in the image data is judged to be inclined and the smudginess type of the surface of the glass is smudginess; and comparing the two groups of data with a corresponding threshold value set by each group of data through the data analysis module, and respectively outputting second probabilities of the two groups of faults based on the range of the exceeded threshold values. According to the method, relatively comprehensive fault prediction can be given, and a worker can select a subsequent troubleshooting plan according to the probability value.

Description

Technical Field

[0001] The present invention relates to the technical field of data analysis, and in particular to a method and device for analyzing monitoring terminal data. Background Art

[0002] Glass cleaning machines are used to clean glass efficiently and accurately. Glass cleaning machines are usually composed of a transmission unit, a scrubbing unit, a clean water flushing unit, an electronic control unit, etc. The relevant status data of these units during operation are usually monitored through a monitoring terminal, and then the monitoring terminal analyzes the data to determine whether the relevant units have failed. The current judgment method is usually to set a threshold and then detect multiple data in real time. When a certain data exceeds the corresponding threshold, it is determined that the part has failed. The current monitoring data usually only includes wind pressure, water temperature, water pressure, and motor speed. The monitoring data is not comprehensive enough. When it is found that the glass is tilted during the cleaning process, a relatively comprehensive fault prediction cannot be given. Summary of the invention

[0003] In view of this, the purpose of the present invention is to propose a method and device for analyzing monitoring terminal data to solve the problem that the current monitoring data is not comprehensive enough and when it is detected that the glass is tilted during the cleaning process, a relatively comprehensive fault prediction cannot be given.

[0004] Based on the above purpose, the present invention provides a method for analyzing monitoring terminal data, which is used for analyzing working data of a glass cleaning machine. The method is executed by a monitoring terminal device, and the monitoring terminal device includes: a first camera module, a second camera module, an image processing module, a water pressure detection module, a brush height detection module, a pressure roller height detection module and a data analysis module. The method includes: Based on historical data, a database of glass tilt types and corresponding faults is established; Acquiring image data of the glass after cleaning through the first camera module; Based on the image data, the image processing module determines the tilt type of the glass and the dirt type on the glass surface in the image data. When it is determined that the glass in the image data is tilted and the dirt type on the glass surface is not dirty: Acquiring the rotation data of the conveying roller in the glass washing machine through the second camera module and the image processing module; Acquire first pressure data on both sides of the water pipe of the flushing unit in the glass washing machine through the water pressure inspection module; Detecting first height data of both sides of the brush in the glass cleaning machine by the brush height detection module; Detecting the height data of both sides of the pressure roller in the glass washing machine by the pressure roller height detection module; The data analysis module compares the four groups of data with the corresponding thresholds set for each group of data, and outputs the first probabilities of the four groups of faults respectively based on the range of the exceeded thresholds; When it is determined that the glass is tilted in the image data and the dirt type on the glass surface is dirty; Acquire second pressure data on both sides of the water pipe of the flushing unit in the glass washing machine through the water pressure inspection module; Detecting second height data of both sides of the brush in the glass cleaning machine by the brush height detection module; The data analysis module compares the two groups of data with the corresponding thresholds set for each group of data, and outputs the second probabilities of the two groups of faults based on the range of the exceeded thresholds.

[0005] Optionally, when the first probabilities are the same, the tilt angle of the glass in the image data is obtained, and the third probabilities of the four groups of faults are output respectively based on the number of times the glass appears at the tilt angle corresponding to the four groups of faults in the historical fault records.

[0006] Optionally, when the second probabilities are the same, the tilt angle of the glass in the image data is obtained, and the fourth probabilities of the two groups of faults are output respectively based on the number of times the glass appears at the tilt angle corresponding to the two groups of faults in the historical fault records.

[0007] Optionally, when the third probabilities are the same, obtain the position information of the conveying roller corresponding to the third probability, obtain the position information of the water pipe corresponding to the third probability, obtain the position information of the brush corresponding to the third probability, and obtain the position information of the pressing roller corresponding to the third probability; Based on the above four groups of position information, the adjacent relationship of the conveying rollers, water pipes, brushes and pressure rollers corresponding to the third probability is obtained. When at least two groups of conveying rollers, water pipes, brushes and pressure rollers corresponding to the third probability are in an adjacent state, the third probabilities corresponding to the adjacent states are added together as the fifth probability output.

[0008] Optionally, the second camera module includes multiple groups of cameras, which are used to shoot one end of the conveyor roller. One end of the conveyor roller is wrapped with a sticker, and the sticker has two groups of different colors evenly distributed in a ring shape. The rotation state of the conveyor roller is judged by the color changes in pictures taken at predetermined time intervals.

[0009] Optionally, the water pressure detection module includes pressure sensors arranged on both sides of the top of the water pipe. When the nozzle on one side of the bottom of the water pipe is blocked and the nozzle on the other side is not blocked, the reaction force on the water pipe on the side not blocked by the nozzle is greater than the reaction force on the water pipe on the side blocked by the nozzle, so that the value of the pressure sensor on the water pipe on the side not blocked by the nozzle is greater than the value of the pressure sensor on the water pipe on the side blocked by the nozzle.

[0010] Optionally, the brush height detection module and the pressure roller height detection module both detect whether the heights of the two ends of the brush and the pressure roller are consistent through distance sensors, thereby determining whether the brush and the pressure roller are tilted.

[0011] Based on the same invention, the present invention also provides a device for analyzing the monitoring terminal data, the method is executed by the monitoring terminal transfer device, the monitoring terminal device comprises: a first camera module, a second camera module, an image processing module, a water pressure detection module, a brush height detection module, a pressure roller height detection module and a data analysis module, wherein: The first camera module is used to obtain image data of the glass after cleaning; The image processing module is used to process the acquired image data accordingly and output the processed data; The second camera module is used to obtain image data of a conveyor roller in a glass cleaning machine; The water pressure inspection module is used to obtain first pressure data on both sides of the water pipe of the flushing unit in the glass washing machine; The brush height detection module is used to detect first height data of both sides of the brush in the glass cleaning machine; The pressure roller height detection module is used to detect the height data of both sides of the pressure roller in the glass washing machine; The data analysis module is used to analyze the acquired data and output the failure probability value of the corresponding unit according to the analysis result.

[0012] During operation, the image data of the glass after cleaning is obtained through the first camera module; based on the image data, the image processing module is used to determine the tilt type of the glass in the image data and the type of dirt on the glass surface. When it is determined that the glass is tilted in the image data and the type of dirt on the glass surface is not dirty, it means that the brush and the flushing unit can clean the glass. There are many possible reasons for the tilt of the glass. At this time, the rotation data of the conveyor roller in the glass cleaning machine is obtained through the second camera module and the image processing module; the first pressure data on both sides of the water pipe of the flushing unit in the glass cleaning machine is obtained through the water pressure inspection module; the first height data on both sides of the brush in the glass cleaning machine is detected through the brush height detection module; the height data on both sides of the pressure roller in the glass cleaning machine is detected through the roller height detection module; the above four groups of data are compared with the corresponding threshold value set for each group of data through the data analysis module, and the first probability of four groups of faults is output respectively based on the range of the exceeded threshold value. The larger the range of the exceeded threshold value, the higher the probability of the fault of the unit. At this time, the output corresponding to the unit is larger, and the staff can select the subsequent troubleshooting plan according to the high or low first probability value.

[0013] When it is determined that the glass is tilted in the image data and the type of dirt on the glass surface is dirty, it means that the brush and the flushing unit cannot clean the glass. This means that the glass may be tilted because the brush is tilted or the water pressure on one side of the water pipe in the flushing unit is high and the water pressure on the other side is low. Therefore, the faults of these two units can be checked first. The second pressure data on both sides of the water pipe of the flushing unit in the glass washing machine is obtained through the water pressure inspection module; the second height data on both sides of the brush in the glass washing machine is detected through the brush height detection module; the above two groups of data are compared with the corresponding thresholds set for each group of data through the data analysis module, and the second probabilities of the two groups of faults are output based on the range of the exceeded thresholds. The staff can choose the subsequent troubleshooting plan according to the second probability value.

[0014] From the above, it can be seen that when the present invention detects that the glass is tilted, data detection can be performed on multiple groups of units that cause the tilt, and the data is more comprehensive. Then, the corresponding fault probability is analyzed, and the fault prediction is expressed by probability. A relatively comprehensive fault prediction can be given, and the staff can choose the subsequent troubleshooting plan according to the probability value. At the same time, some data in this method do not need to be detected in real time, which reduces energy consumption and data processing. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only for the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0016] Figure 1 is a cross-sectional view of a sticker according to an embodiment of the present invention; Figure 2 It is a schematic structural diagram of a water pipe according to an embodiment of the present invention.

[0017] 1. Sticker; 2. Water pipe; 3. Pressure sensor. DETAILED DESCRIPTION

[0018] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with specific embodiments.

[0019] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention should be understood by people with ordinary skills in the field to which the present invention belongs. The "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0020] like Figure 1 As shown, a monitoring terminal data analysis method is used for analyzing working data of a glass cleaning machine. The method is executed by a monitoring terminal device, and the monitoring terminal device includes: a first camera module, a second camera module, an image processing module, a water pressure detection module, a brush height detection module, a pressure roller height detection module and a data analysis module. The method includes: Based on historical data, a database of glass tilt types and corresponding faults is established; Acquiring image data of the glass after cleaning by the first camera module; Based on the image data, the image processing module determines the tilt type of the glass and the dirt type on the glass surface in the image data. When it is determined that the glass in the image data is tilted and the dirt type on the glass surface is not dirty: Acquiring the rotation data of the conveying roller in the glass washing machine through the second camera module and the image processing module; Acquire first pressure data on both sides of the water pipe of the flushing unit in the glass washing machine through the water pressure inspection module; Detecting first height data of both sides of the brush in the glass cleaning machine by the brush height detection module; Detecting the height data of both sides of the pressure roller in the glass washing machine by the pressure roller height detection module; The data analysis module compares the four groups of data with the corresponding thresholds set for each group of data, and outputs the first probabilities of the four groups of faults respectively based on the range of the exceeded thresholds; When it is determined that the glass is tilted in the image data and the dirt type on the glass surface is dirty; Acquire second pressure data on both sides of the water pipe of the flushing unit in the glass washing machine through the water pressure inspection module; Detecting second height data of both sides of the brush in the glass cleaning machine by the brush height detection module; The data analysis module compares the two groups of data with the corresponding thresholds set for each group of data, and outputs the second probabilities of the two groups of faults based on the range of the exceeded thresholds.

[0021] This method is mainly aimed at predicting faults when the glass is tilted after cleaning. In this method, only the first camera module and the image processing module need to work at the beginning, and other modules can be temporarily idle or work in stages. The database contains historical detection data, fault conditions corresponding to the historical data, and glass tilt types corresponding to the fault conditions. The type of glass tilt can be divided according to the angle of tilt. For example, in the historical data, when the brush is tilted, what type of glass tilt is generally caused? During operation, the image data of the glass after cleaning is obtained through the first camera module; based on the image data, the image processing module determines the type of glass tilt and the type of dirt on the glass surface in the image data. When it is determined that the glass is tilted in the image data and the type of dirt on the glass surface is not dirty, it means that the brush and the flushing unit are able to tilt the glass. The glass is clean. There are many possible reasons for the tilt of the glass. At this time, the rotation data of the conveyor roller in the glass cleaning machine is obtained through the second camera module and the image processing module; the first pressure data on both sides of the water pipe of the flushing unit in the glass cleaning machine is obtained through the water pressure inspection module; the first height data on both sides of the brush in the glass cleaning machine is detected by the brush height detection module; the height data on both sides of the pressure roller in the glass cleaning machine is detected by the pressure roller height detection module; the above four groups of data are compared with the corresponding thresholds set for each group of data through the data analysis module, and the first probabilities of four groups of faults are output respectively based on the range of the exceeded threshold. The larger the range of the exceeded threshold, the higher the probability of failure of the unit, and the larger the first probability value corresponding to the unit output at this time, and the staff can choose the subsequent troubleshooting plan according to the first probability value.

[0022] When it is determined that the glass is tilted in the image data and the type of dirt on the glass surface is dirty, it means that the brush and the flushing unit cannot clean the glass. This means that the glass may be tilted because the brush is tilted or the water pressure on one side of the water pipe in the flushing unit is high and the water pressure on the other side is low. Therefore, the faults of these two units can be checked first. The second pressure data on both sides of the water pipe of the flushing unit in the glass washing machine is obtained through the water pressure inspection module; the second height data on both sides of the brush in the glass washing machine is detected through the brush height detection module; the above two groups of data are compared with the corresponding thresholds set for each group of data through the data analysis module, and the second probabilities of the two groups of faults are output based on the range of the exceeded thresholds. The staff can choose the subsequent troubleshooting plan according to the second probability value.

[0023] From the above, it can be seen that when the present invention detects that the glass is tilted, data detection can be performed on multiple groups of units that cause the tilt, and the data is more comprehensive. Then, the corresponding fault probability is analyzed, and the fault prediction is expressed by probability. A relatively comprehensive fault prediction can be given, and the staff can choose the subsequent troubleshooting plan according to the probability value. At the same time, some data in this method do not need to be detected in real time, which reduces energy consumption and data processing.

[0024] In some embodiments, when the first probabilities are the same or differ very slightly, for example, less than 2%, the tilt angle of the glass in the image data is obtained, and the third probabilities of the four groups of faults are output respectively based on the number of times the glass appears at the tilt angle corresponding to the four groups of faults in the historical fault records.

[0025] When the first probabilities are the same or differ very slightly, for example, less than 2%, it means that failures of several units may cause the glass to tilt. At this time, in order to better provide guidance for the staff, the third probabilities of the four groups of failures are output respectively based on the number of times the glass appears at this tilt angle at the four groups of failures in the historical fault records. That is, although the first probabilities are the same, under the same probability, the higher the number of times the four groups of failures appear at this tilt angle, the greater the third probability output at this time. For example, at a tilt of 20 degrees, the number of times caused by the conveyor roller is the largest, and the probability of conveyor roller failure output at this time is the largest, which can better provide guidance for the staff.

[0026] In some embodiments, when the second probabilities are the same, the tilt angle of the glass in the image data is obtained, and the fourth probabilities of the two groups of faults are output respectively based on the number of times the glass appears at the tilt angle corresponding to the two groups of faults in the historical fault records.

[0027] The principle of this design is the same as that of the previous embodiment. The probability is further calculated by the number of failures, which can provide better guidance to the staff.

[0028] In some embodiments, when the third probabilities are the same or have a very small difference, for example, less than 2%, it means that the statistics of the historical times cannot provide guidance to the staff, and at this time, the position information of the conveying roller corresponding to the third probability is obtained, the position information of the water pipe corresponding to the third probability is obtained, the position information of the brush corresponding to the third probability is obtained, and the position information of the pressure roller corresponding to the third probability is obtained; Based on the above four groups of position information, the adjacent relationship of the conveying rollers, water pipes, brushes and pressure rollers corresponding to the third probability is obtained. When at least two groups of conveying rollers, water pipes, brushes and pressure rollers corresponding to the third probability are in an adjacent state, the third probabilities corresponding to the adjacent states are added together as the fifth probability output.

[0029] When the third probability also fails to provide guidance to the staff, in order to further provide guidance to the staff, the above four groups of position information are obtained, and the adjacent relationship of the conveying rollers, water pipes, brushes and pressure rollers corresponding to the third probability is obtained. When at least two groups of conveying rollers, water pipes, brushes and pressure rollers corresponding to the third probability are in an adjacent state, the third probabilities corresponding to the adjacent states are added together as the fifth probability output. When at least two groups of faulty conveying rollers, water pipes, brushes and pressure rollers are in an adjacent state, it means that the glass will be affected by multiple faults when passing through the adjacent place. Therefore, the probability that the adjacent place is a fault point is greatly increased. Therefore, adding the third probabilities corresponding to the adjacent states as the fifth probability output can further provide guidance to the staff.

[0030] In some embodiments, the top view projection of the glass cleaning machine is set in a natural coordinate system, and the coordinate positions of all conveying rollers, water pipes, brushes and pressure rollers in the coordinate system are obtained. When the third probability K1 is the same or the difference is very small, for example, less than 2%, the coordinate position information A of the conveying roller corresponding to the third probability K1 is obtained, the coordinate position information B of the water pipe corresponding to the third probability K1 is obtained, the coordinate position information C of the brush corresponding to the third probability K1 is obtained, the coordinate position information D of the pressure roller corresponding to the third probability K1 is obtained, and the size L of the cleaned glass along the travel direction of the glass cleaning machine is obtained, and the sixth probability K2 is calculated by the following formula: |XY| <L,K2=2*K1; Here, X represents A or B or C or D, and Y represents A or B or C or D different from X.

[0031] In this embodiment, the above inequality is used to determine whether the distance between the fault points is less than the dimension L in the direction of glass travel. When it is judged to be less than, it means that the glass will be affected by the two faults at the same time when passing through the two fault points. Therefore, the probability of the glass tilting here is greater than the probability of the location of a single fault point. Therefore, the sixth probability K2 is output as twice K1. Such distinction can further provide guidance to the staff on the fault location.

[0032] like Figure 1As shown, in some embodiments, the second camera module includes multiple cameras, and the cameras are used to shoot one end of the conveyor roller. One end of the conveyor roller is wrapped with a sticker, and the sticker is evenly distributed in two groups of different colors in a ring shape. The rotation state of the conveyor roller is judged by the color change in the pictures taken at predetermined time intervals. The color change is completed by the image processing module. In this embodiment, when the color in the pictures taken at predetermined time intervals does not change, or the rotation state of the conveyor roller can be judged according to the degree of change. If there is basically no change, it means that the conveyor roller has a transmission failure and cannot be normally rotated to convey the glass.

[0033] like Figure 2 As shown, in some embodiments, the water pressure detection module includes pressure sensors arranged on both sides of the top of the water pipe. When the nozzle on one side of the bottom of the water pipe is blocked and the nozzle on the other side is not blocked, the reaction force on the water pipe on the side not blocked by the nozzle is greater than the reaction force on the water pipe on the side blocked by the nozzle, so that the value of the pressure sensor on the water pipe on the side not blocked by the nozzle is greater than the value of the pressure sensor on the water pipe on the side blocked by the nozzle. The blockage degree of one side of the water pipe is determined by detecting the pressure difference on both sides of the water pipe. The greater the pressure difference, the more serious the blockage of one side of the water pipe.

[0034] In some embodiments, the brush height detection module and the roller height detection module both use distance sensors to detect whether the heights of the brush and the roller are consistent, thereby determining whether the brush and the roller are tilted. The tilt of the brush is determined by detecting the height difference between the brush and the roller. The greater the height difference, the greater the tilt of the brush.

[0035] In order to further implement the present invention, the present invention also provides a device for analyzing the monitoring terminal data, the method is executed by the monitoring terminal transfer device, the monitoring terminal device comprises: a first camera module, a second camera module, an image processing module, a water pressure detection module, a brush height detection module and a pressure roller height detection module and a data analysis module, wherein: The first camera module is used to obtain image data of the glass after cleaning; The image processing module is used to process the acquired image data accordingly and output the processed data; The second camera module is used to obtain image data of a conveyor roller in a glass cleaning machine; The water pressure inspection module is used to obtain first pressure data on both sides of the water pipe of the flushing unit in the glass washing machine; The brush height detection module is used to detect first height data of both sides of the brush in the glass cleaning machine; The pressure roller height detection module is used to detect the height data of both sides of the pressure roller in the glass washing machine; The data analysis module is used to analyze the acquired data and output the failure probability value of the corresponding unit according to the analysis result.

[0036] When the device detects that the glass is tilted, it can perform data detection on multiple groups of units that cause the tilt, so that the data is more comprehensive, and then analyze the corresponding fault probability. By expressing the fault prediction through probability, a relatively comprehensive fault prediction can be given. The staff can choose the subsequent troubleshooting plan according to the probability value. At the same time, some data in this method do not need to be detected in real time, which reduces energy consumption and data processing volume.

[0037] It should be understood by those skilled in the art that the discussion of any of the above embodiments is merely illustrative and is not intended to imply that the scope of the present invention (including the claims) is limited to these examples. Under the concept of the present invention, the technical features in the above embodiments or different embodiments may be combined, the steps may be implemented in any order, and there are many other variations of the above aspects of the present invention, which are not provided in detail for the sake of simplicity.

[0038] The present invention is intended to cover all such substitutions, modifications and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for analyzing monitoring terminal data, used for analyzing working data of a glass washing machine, characterized in that: The method is performed by a monitoring terminal device, which includes: a first camera module, a second camera module, an image processing module, a water pressure detection module, a brush height detection module, a pressure roller height detection module and a data analysis module. The method includes: Based on historical data, a database of glass tilt types and corresponding faults is established; Acquiring image data of the glass after cleaning through the first camera module; Based on the image data, the image processing module determines the tilt type of the glass and the dirt type on the glass surface in the image data. When it is determined that the glass in the image data is tilted and the dirt type on the glass surface is not dirty: Acquiring the rotation data of the conveying roller in the glass washing machine through the second camera module and the image processing module; Acquire first pressure data on both sides of the water pipe of the flushing unit in the glass washing machine through the water pressure inspection module; Detecting first height data of both sides of the brush in the glass cleaning machine by the brush height detection module; Detecting the height data of both sides of the pressure roller in the glass washing machine by the pressure roller height detection module; The data analysis module compares the four groups of data with the corresponding thresholds set for each group of data, and outputs the first probabilities of the four groups of faults respectively based on the range of the exceeded thresholds; When it is determined that the glass is tilted in the image data and the dirt type on the glass surface is dirty; Acquire second pressure data on both sides of the water pipe of the flushing unit in the glass washing machine through the water pressure inspection module; Detecting second height data of both sides of the brush in the glass cleaning machine by the brush height detection module; The data analysis module compares the two groups of data with the corresponding thresholds set for each group of data, and outputs the second probabilities of the two groups of faults based on the range of the exceeded thresholds.

2. The method for analyzing monitoring terminal data according to claim 1, characterized in that: When the first probabilities are the same, the tilt angle of the glass in the image data is obtained, and the third probabilities of the four groups of faults are output respectively based on the number of times the glass appears at the tilt angle corresponding to the four groups of faults in the historical fault records.

3. The method for analyzing monitoring terminal data according to claim 1, characterized in that: When the second probabilities are the same, the tilt angle of the glass in the image data is obtained, and the fourth probabilities of the two groups of faults are outputted respectively based on the number of times the glass appears at the tilt angle corresponding to the two groups of faults in the historical fault records.

4. The method for analyzing monitoring terminal data according to claim 2, characterized in that: When the third probabilities are the same, obtain the position information of the conveying roller corresponding to the third probability, obtain the position information of the water pipe corresponding to the third probability, obtain the position information of the brush corresponding to the third probability, and obtain the position information of the pressing roller corresponding to the third probability; Based on the above four groups of position information, the adjacent relationship of the conveying rollers, water pipes, brushes and pressure rollers corresponding to the third probability is obtained. When at least two groups of conveying rollers, water pipes, brushes and pressure rollers corresponding to the third probability are in an adjacent state, the third probabilities corresponding to the adjacent states are added together as the fifth probability output.

5. The method for analyzing monitoring terminal data according to claim 1, characterized in that: The second camera module includes multiple groups of cameras, which are used to shoot one end of the conveyor roller. One end of the conveyor roller is wrapped with a sticker, and the sticker has two groups of different colors evenly distributed in a ring shape. The rotation state of the conveyor roller is judged by the color changes in the pictures taken at predetermined time intervals.

6. The method for analyzing monitoring terminal data according to claim 1, characterized in that: The water pressure detection module includes pressure sensors arranged on both sides of the top of the water pipe. When the nozzle on one side of the bottom of the water pipe is blocked and the nozzle on the other side is not blocked, the reaction force received by the water pipe on the side not blocked by the nozzle is greater than the reaction force received by the water pipe on the side blocked by the nozzle, so that the value of the pressure sensor on the water pipe on the side not blocked by the nozzle is greater than the value of the pressure sensor on the water pipe on the side blocked by the nozzle.

7. The method for analyzing monitoring terminal data according to claim 1, characterized in that: The brush height detection module and the pressure roller height detection module both detect whether the heights of the two ends of the brush and the pressure roller are consistent through distance sensors, thereby determining whether the brush and the pressure roller are tilted.

8. A device for executing the method for analyzing monitoring terminal data according to claim 1, characterized in that: The method is performed by a monitoring terminal device, which includes: a first camera module, a second camera module, an image processing module, a water pressure detection module, a brush height detection module, a pressure roller height detection module and a data analysis module, wherein: The first camera module is used to obtain image data of the glass after cleaning; The image processing module is used to process the acquired image data accordingly and output the processed data; The second camera module is used to obtain image data of a conveyor roller in a glass cleaning machine; The water pressure inspection module is used to obtain first pressure data on both sides of the water pipe of the flushing unit in the glass washing machine; The brush height detection module is used to detect first height data of both sides of the brush in the glass cleaning machine; The pressure roller height detection module is used to detect the height data of both sides of the pressure roller in the glass washing machine; The data analysis module is used to analyze the acquired data and output the failure probability value of the corresponding unit according to the analysis result.

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