High static pressure axial flow fan and intelligent monitoring system

Abstract

The present application belongs to the field of industrial fan, and relates to abnormality monitoring technology, which is used to solve the problem that the existing high static pressure axial flow fan and intelligent monitoring system cannot make decision analysis on abnormal treatment measures of the fan according to abnormal monitoring data, and specifically is a high static pressure axial flow fan and intelligent monitoring system, which comprises an intelligent monitoring platform, wherein the intelligent monitoring platform is communicatively connected with an operation monitoring module, a maintenance analysis module, an abnormality analysis module and a storage module; the operation monitoring module is used for monitoring and analyzing the operation state of the high static pressure axial flow fan; the high static pressure axial flow fan is marked as a monitoring object, a monitoring period is generated, and the monitoring period is divided into a plurality of monitoring time periods; the present application can monitor and analyze the operation state of the high static pressure axial flow fan, monitor the operation abnormality degree of the fan in the monitoring time period through the operation coefficient, mark the monitoring time period, and provide data support for maintenance necessity analysis and abnormality analysis.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of industrial fans, and relates to abnormality monitoring technology, in particular to a high-static-pressure axial flow fan and an intelligent monitoring system. BACKGROUND

[0002] An industrial fan refers to a fan specially used for ventilation and fire-fighting high-temperature smoke exhaust in places such as tunnels, underground garages, high-grade civil buildings, metallurgy and mines, and mainly comprises a impeller, a casing, an inlet flow collector, a guide vane, a motor and the like, and a key component of a refrigeration high-efficiency cooling fan is a cooling coil combined with a designed advanced fin shape and a heat exchange pipe.

[0003] The existing high-static-pressure axial flow fan and intelligent monitoring system cannot monitor the running state of the fan, and cannot make decision analysis on abnormal treatment measures of the fan according to abnormal monitoring data, so that the fan cannot be scientifically and reasonably overhauled and maintained.

[0004] In view of the above technical problems, the application provides a solution. SUMMARY

[0005] The application aims to provide a high-static-pressure axial flow fan and an intelligent monitoring system, and aims to solve the problem that the existing high-static-pressure axial flow fan and intelligent monitoring system cannot make decision analysis on abnormal treatment measures of the fan according to abnormal monitoring data.

[0006] The application needs to solve the technical problem of how to provide a high-static-pressure axial flow fan and an intelligent monitoring system that can make decision analysis on abnormal treatment measures of the fan according to abnormal monitoring data.

[0007] The application can be achieved by the following technical scheme.

[0008] The intelligent monitoring system of the high-static-pressure axial flow fan comprises an intelligent monitoring platform, and the intelligent monitoring platform is communicatively connected with a running monitoring module, a maintenance analysis module, an abnormality analysis module and a storage module.

[0009] The running monitoring module is used for monitoring and analyzing the running state of the high-static-pressure axial flow fan: the high-static-pressure axial flow fan is marked as a monitoring object, a monitoring period is generated, the monitoring period is divided into a plurality of monitoring time periods, static pressure data JY, air volume data FL and rotating speed data ZS of the monitoring object in the monitoring time period are obtained, the running coefficient YX of the monitoring object in the monitoring time period is obtained by numerical calculation on the static pressure data JY, the air volume data FL and the rotating speed data ZS, and the monitoring time period is marked as a normal time period, an abnormal time period or a pending time period through the running coefficient YX.

[0010] The maintenance analysis module is used for monitoring and analyzing the maintenance necessity of the high-static-pressure axial flow fan: after the monitoring period ends, the pending data DD, the continuous data LX and the normal data ZC of the monitoring period are obtained; the maintenance coefficient WH of the monitoring period is obtained by numerical calculation on the pending data DD, the continuous data LX and the normal data ZC; whether the monitoring object has the maintenance necessity in the monitoring period is determined by the maintenance coefficient WH.

[0011] The abnormality analysis module is used for analyzing the influencing factors of the operation abnormality of the high-static-pressure axial flow fan.

[0012] As a preferred embodiment of the present application, the obtaining process of the static pressure data JY includes: obtaining the outflow static pressure value of the monitoring object, calling the static pressure range of the monitoring object, marking the average value of the maximum value and the minimum value of the static pressure range as the static pressure standard value, marking the absolute value of the difference between the outflow static pressure value and the static pressure standard value as the static pressure value, and marking the maximum value of the static pressure value in the monitoring period as the static pressure data JY; the obtaining process of the air volume data FL includes: obtaining the outflow volume of the monitoring object in the monitoring period, calling the air volume range, marking the average value of the maximum value and the minimum value of the air volume range as the air volume standard value, and marking the absolute value of the difference between the outflow volume and the air volume standard value as the air volume data FL; the obtaining process of the rotating speed data ZS includes: obtaining the impeller rotating speed value of the monitoring object, calling the rotating speed range, marking the average value of the maximum value and the minimum value of the rotating speed range as the rotating speed standard value, marking the absolute value of the difference between the rotating speed value and the rotating speed standard value as the rotating speed deviation value, and marking the maximum value of the rotating speed deviation value in the monitoring period as the rotating speed data ZS.

[0013] As a preferred embodiment of the present application, the specific process of marking the monitoring period as the normal period, the abnormal period or the pending period includes: obtaining the operation threshold YXmax and YXmin by the storage module, comparing the operation coefficient YX of the monitoring object in the monitoring period with the operation threshold YXmax and YXmin: if YX≤YXmin, it is determined that the operation state of the monitoring object in the monitoring period meets the requirements, and the corresponding monitoring period is marked as the normal period; if YXmin<YX<YXmax, the corresponding monitoring period is marked as the pending period; if YX≥YXmax, it is determined that the operation state of the monitoring object in the monitoring period does not meet the requirements, the corresponding monitoring period is marked as the abnormal period, a shutdown maintenance signal is generated and an abnormality analysis signal is sent to the intelligent monitoring platform, and the intelligent monitoring platform sends the abnormality analysis signal to the abnormality analysis module after receiving the abnormality analysis signal.

[0014] As a preferred embodiment of the present application, the pending data DD is the number of pending periods in the monitoring period, the normal data ZC is the number of normal periods in the monitoring period, and the acquisition process of the continuous data LX includes: if the monitoring period is continuously marked as a pending period, the number of continuous pending periods is marked as a pending value, and the maximum value of the pending value in the monitoring period is marked as the continuous data LX.

[0015] As a preferred embodiment of the present application, the specific process of determining whether the monitoring object has maintenance necessity in the monitoring period includes: obtaining the maintenance threshold WHmax through the storage module, comparing the maintenance coefficient WH of the monitoring period with the maintenance threshold WHmax, if the maintenance coefficient WH is less than the maintenance threshold WHmax, it is determined that the monitoring object does not have maintenance necessity in the monitoring period, if the maintenance coefficient WH is greater than or equal to the maintenance threshold WHmax, it is determined that the monitoring object has maintenance necessity in the monitoring period, a device maintenance signal is generated and sent to the intelligent monitoring platform, and the intelligent monitoring platform sends the device maintenance signal to the mobile terminal of the management personnel after receiving the device maintenance signal.

[0016] As a preferred embodiment of the present application, the specific process of the abnormal analysis module analyzing the influencing factors of the operation abnormality of the high static pressure axial flow fan includes: obtaining the voltage value of the monitoring object power supply line in the abnormal period, comparing the voltage value with the voltage range, if the voltage value is within the voltage range, a mechanical repair signal is generated and sent to the intelligent monitoring platform, and the intelligent monitoring platform sends the mechanical repair signal to the mobile terminal of the management personnel after receiving the mechanical repair signal, if the voltage value is outside the voltage range, a circuit repair signal is generated and sent to the intelligent monitoring platform, and the intelligent monitoring platform sends the circuit repair signal to the mobile terminal of the management personnel after receiving the circuit repair signal.

[0017] As a preferred embodiment of the present application, the working method of the high static pressure axial flow fan and the intelligent monitoring system includes the following steps:

[0018] Step one: monitoring and analyzing the running state of the high static pressure axial flow fan: marking the high static pressure axial flow fan as a monitoring object, generating a monitoring period, dividing the monitoring period into a plurality of monitoring periods, obtaining the static pressure data JY, the air volume data FL and the rotating speed data ZS of the monitoring object in the monitoring period and performing numerical calculation to obtain the running coefficient YX;

[0019] Step two: marking the monitoring period as a normal period, an abnormal period or a pending period through the running coefficient YX;

[0020] Step three: monitoring and analyzing the necessity of maintenance of the high static pressure axial flow fan: after the end of the monitoring period, the pending data DD and continuous data LX and normal data ZC of the monitoring period are obtained and numerical calculation is carried out to obtain the maintenance coefficient WH, and whether the monitoring equipment has the necessity of maintenance in the monitoring period is judged through the maintenance coefficient WH;

[0021] Step four: analyzing the influencing factors of the running abnormity of the high static pressure axial flow fan: the voltage value of the power supply line of the monitoring object in the abnormal period is obtained, the voltage value is compared with the voltage range, the mechanical maintenance signal or the circuit maintenance signal is generated through the comparison result and is sent to the intelligent monitoring platform.

[0022] The present application has the following advantages:

[0023] 1. The running state of the high static pressure axial flow fan can be monitored and analyzed through the running monitoring module, the fan running parameters in each monitoring period are collected and analyzed in a time period monitoring manner to obtain the running coefficient, the running abnormity degree of the fan in the monitoring period is monitored through the running coefficient, and the monitoring period is marked to provide data support for maintenance necessity analysis and abnormality analysis;

[0024] 2. The maintenance necessity of the high static pressure axial flow fan can be monitored and analyzed through the maintenance analysis module, the maintenance coefficient is obtained by counting and analyzing the monitoring period marking state in the monitoring period, and the maintenance necessity of the high static pressure axial flow fan is fed back according to the maintenance coefficient, so that a dynamic maintenance scheme for the high static pressure axial flow fan is formulated;

[0025] 3. The influencing factors of the running abnormity of the high static pressure axial flow fan can be analyzed through the abnormality analysis module, the power supply of the high static pressure axial flow fan is analyzed when the high static pressure axial flow fan appears running abnormity, so that the influencing factors of the running abnormity of the high static pressure axial flow fan are marked as circuit abnormity or mechanical abnormity, and the maintenance efficiency of the high static pressure axial flow fan is improved. BRIEF DESCRIPTION OF DRAWINGS

[0026] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0027] Figure 1 The system block diagram of the first embodiment of the present application is shown in the figure.

[0028] Figure 2 The method flow chart of the second embodiment of the present application is shown in the figure. DETAILED DESCRIPTION

[0029] The technical solutions of the present application will be described clearly and completely in combination with the embodiments below. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0030] Embodiment one

[0031] As shown in Figure 1 The intelligent monitoring system of the high static pressure axial flow fan comprises an intelligent monitoring platform, and the intelligent monitoring platform is communicatively connected with an operation monitoring module, a maintenance analysis module, an abnormality analysis module and a storage module.

[0032] The operation monitoring module is used for monitoring and analyzing the operation state of the high-static-pressure axial flow fan: marking the high-static-pressure axial flow fan as a monitoring object, generating a monitoring period, dividing the monitoring period into a plurality of monitoring time periods, obtaining static pressure data JY, air volume data FL and rotating speed data ZS of the monitoring object in the monitoring time period, the obtaining process of the static pressure data JY including: obtaining an outlet static pressure value of the monitoring object, calling a static pressure range of the monitoring object, marking an average value of a maximum value and a minimum value of the static pressure range as a static pressure standard value, marking an absolute value of a difference between the outlet static pressure value and the static pressure standard value as a static pressure value, and marking a maximum value of the static pressure value in the monitoring time period as the static pressure data JY; the obtaining process of the air volume data FL including: obtaining an outlet air volume of the monitoring object in the monitoring time period, calling an air volume range, marking an average value of a maximum value and a minimum value of the air volume range as an air volume standard value, and marking an absolute value of a difference between the outlet air volume and the air volume standard value as the air volume data FL; the obtaining process of the rotating speed data ZS including: obtaining an impeller rotating speed value of the monitoring object, calling a rotating speed range, marking an average value of a maximum value and a minimum value of the rotating speed range as a rotating speed standard value, marking an absolute value of a difference between the rotating speed value and the rotating speed standard value as a rotating speed deviation value, and marking a maximum value of the rotating speed deviation value in the monitoring time period as the rotating speed data ZS; obtaining an operation coefficient YX of the monitoring object in the monitoring time period through a formula YX = α1*JY + α2*FL + α3*ZS, wherein α1, α2 and α3 are proportional coefficients, and α1>α2>α3>1; obtaining operation threshold values YXmax and YXmin through the storage module, and comparing the operation coefficient YX of the monitoring object in the monitoring time period with the operation threshold values YXmax and YXmin: if YX≤YXmin, it is determined that the operation state of the monitoring object in the monitoring time period meets the requirements, the corresponding monitoring time period is marked as a normal time period; if YXmin

[0033] The maintenance analysis module is used for monitoring and analyzing the maintenance necessity of the high static pressure axial flow fan: after the end of the monitoring period, the pending data DD and the continuous data LX and the normal data ZC of the monitoring period are obtained, the pending data DD is the number value of the pending period in the monitoring period, the normal data ZC is the number value of the normal period in the monitoring period, and the continuous data LX is obtained by the following process: if the monitoring period is continuously marked as a pending period, the number value of the continuous pending period is marked as a pending value, and the maximum value of the pending value in the monitoring period is marked as the continuous data LX; the maintenance coefficient WH of the monitoring period is obtained by the formula WH=(β1*LX+β2*DD) / (β3*ZC), wherein β1, β2 and β3 are proportional coefficients, and β1>β2>β3>1; the maintenance threshold WHmax is obtained by the storage module, and the maintenance coefficient WH of the monitoring period is compared with the maintenance threshold WHmax: if the maintenance coefficient WH is less than the maintenance threshold WHmax, it is determined that the monitoring object does not have maintenance necessity in the monitoring period; if the maintenance coefficient WH is greater than or equal to the maintenance threshold WHmax, it is determined that the monitoring object has maintenance necessity in the monitoring period, a device maintenance signal is generated and sent to the intelligent monitoring platform, and the device maintenance signal is sent to the mobile terminal of the management personnel after being received by the intelligent monitoring platform; the maintenance necessity of the high static pressure axial flow fan is monitored and analyzed, the maintenance coefficient is obtained by counting and analyzing the monitoring period in the monitoring period, and the maintenance necessity of the high static pressure axial flow fan is fed back according to the maintenance coefficient, so as to formulate a dynamic maintenance scheme for the high static pressure axial flow fan.

[0034] The abnormality analysis module is used for analyzing the influencing factors of the running abnormality of the high static pressure axial flow fan: the voltage value of the monitoring object power supply line in the abnormal period is obtained, and the voltage value is compared with the voltage range: if the voltage value is within the voltage range, a mechanical maintenance signal is generated and sent to the intelligent monitoring platform, and the mechanical maintenance signal is sent to the mobile terminal of the management personnel after being received by the intelligent monitoring platform; if the voltage value is outside the voltage range, a circuit maintenance signal is generated and sent to the intelligent monitoring platform, and the circuit maintenance signal is sent to the mobile terminal of the management personnel after being received by the intelligent monitoring platform; the influencing factors of the running abnormality of the high static pressure axial flow fan are analyzed, the power supply of the high static pressure axial flow fan is analyzed when the high static pressure axial flow fan appears running abnormality, so as to mark the influencing factors of the running abnormality of the high static pressure axial flow fan as circuit abnormality or mechanical abnormality, and improve the maintenance efficiency of the high static pressure axial flow fan.

[0035] Embodiment two

[0036] As shown in Figure 2 The intelligent monitoring method of the high static pressure axial flow fan comprises the following steps:

[0037] Step one: monitoring and analyzing the running state of high static pressure axial flow fan: marking the high static pressure axial flow fan as the monitoring object, generating the monitoring period, dividing the monitoring period into several monitoring time periods, obtaining the static pressure data JY, air volume data FL and rotating speed data ZS of the monitoring object in the monitoring time period and performing numerical calculation to obtain the running coefficient YX;

[0038] Step two: marking the monitoring time period as normal time period, abnormal time period or pending time period through the running coefficient YX;

[0039] Step three: monitoring and analyzing the maintenance necessity of the high static pressure axial flow fan: after the end of the monitoring period, obtaining the pending data DD, continuous data LX and normal data ZC of the monitoring period and performing numerical calculation to obtain the maintenance coefficient WH, and determining whether the monitoring equipment has maintenance necessity in the monitoring period through the maintenance coefficient WH;

[0040] Step four: analyzing the influencing factors of the running abnormality of the high static pressure axial flow fan: obtaining the voltage value of the power supply line of the monitoring object in the abnormal time period, comparing the voltage value with the voltage range, generating the mechanical maintenance signal or circuit maintenance signal through the comparison result and sending to the intelligent monitoring platform.

[0041] In one specific embodiment, a high static pressure axial flow fan with the above intelligent monitoring system is further included;

[0042] The intelligent monitoring system of the high static pressure axial flow fan, when working, marks the high static pressure axial flow fan as the monitoring object, generates the monitoring period, divides the monitoring period into several monitoring time periods, obtains the static pressure data JY, air volume data FL and rotating speed data ZS of the monitoring object in the monitoring time period and performs numerical calculation to obtain the running coefficient YX; marks the monitoring time period as normal time period, abnormal time period or pending time period through the running coefficient YX; after the end of the monitoring period, obtains the pending data DD, continuous data LX and normal data ZC of the monitoring period and performs numerical calculation to obtain the maintenance coefficient WH, and determines whether the monitoring equipment has maintenance necessity in the monitoring period through the maintenance coefficient WH; obtains the voltage value of the power supply line of the monitoring object in the abnormal time period, compares the voltage value with the voltage range, generates the mechanical maintenance signal or circuit maintenance signal through the comparison result and sends to the intelligent monitoring platform.

[0043] The above content is only an example and description of the structure of the application, and those skilled in the art can make various modifications or supplements or use similar ways to replace the described specific embodiments, as long as they do not deviate from the structure of the application or exceed the scope defined by the present claims, which shall belong to the protection scope of the application.

[0044] The above formulas are obtained by collecting a large amount of data for software simulation and selecting one formula close to the true value, and the coefficients in the formula are set by a person skilled in the art according to the actual situation; for example: formula YX = a1*JY + a2*FL + a3*ZS; a plurality of sample data are collected by a person skilled in the art, and a corresponding running coefficient is set for each sample data; the set running coefficient and the collected sample data are substituted into the formula, any three formulas constitute a ternary linear equation group, the calculated coefficients are screened and the mean value is taken, and the values of a1, a2 and a3 are 4.45, 2.68 and 2.35 respectively;

[0045] The size of the coefficient is a specific value obtained by quantifying each parameter, which is convenient for subsequent comparison. The size of the coefficient depends on the number of sample data and the preliminary setting of the corresponding running coefficient by a person skilled in the art for each sample data. As long as it does not affect the proportional relationship between the parameter and the quantized value, the value of the running coefficient is proportional to the static pressure data.

[0046] In the description of the present specification, the description of the terms "one embodiment", "example", "specific example" and the like means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In the present specification, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0047] The preferred embodiments of the application disclosed above are only used to help explain the application. The preferred embodiments do not describe all the details and limit the application to the specific embodiments. Obviously, many modifications and changes can be made according to the content of the present specification. The present specification selects and describes these embodiments in order to better explain the principles and practical applications of the application, so that those skilled in the art can well understand and utilize the application. The application is limited by the claims and their entire scope and equivalents.

Claims

1. Intelligent monitoring system for high static pressure axial flow fans, characterized by: It includes an intelligent monitoring platform, which is communicatively connected to an operation monitoring module, a maintenance analysis module, an abnormality analysis module and a storage module; The operation monitoring module is used to monitor and analyze the operating status of the high static pressure axial flow fan: the high static pressure axial flow fan is marked as a monitoring object, a monitoring cycle is generated, the monitoring cycle is divided into a number of monitoring time periods, and the static pressure data JY, air volume data FL, and speed data ZS of the monitoring object during the monitoring time period are obtained; the operation coefficient YX of the monitoring object during the monitoring time period is obtained by numerically calculating the static pressure data JY, air volume data FL, and speed data ZS; The monitoring period is marked as a normal period, an abnormal period or a pending period through the operation coefficient YX; The maintenance analysis module is used to monitor and analyze the maintenance necessity of the high static pressure axial flow fan: after the monitoring period ends, the pending data DD, the continuous data LX, and the normal data ZC of the monitoring period are obtained; the maintenance coefficient WH of the monitoring period is obtained by numerically calculating the pending data DD, the continuous data LX, and the normal data ZC; The maintenance coefficient WH is used to determine whether the monitored object needs maintenance during the monitoring period; The pending data DD is the quantity value of the pending period within the monitoring period, the normal data ZC is the quantity value of the normal period within the monitoring period, and the acquisition process of the continuous data LX includes: if the monitoring periods are marked as pending periods continuously, then the quantity values ​​of the consecutive pending periods are marked as pending values, and the maximum value of the pending values ​​within the monitoring period is marked as the continuous data LX; The abnormality analysis module is used to analyze factors affecting the abnormal operation of the high static pressure axial flow fan.

2. The intelligent monitoring system for high static pressure axial flow fans according to claim 1, characterized in that: The process of obtaining static pressure data JY includes: obtaining the outlet static pressure value of the monitored object, retrieving the static pressure range of the monitored object, marking the average of the maximum and minimum values ​​of the static pressure range as the static pressure standard value, marking the absolute value of the difference between the outlet static pressure value and the static pressure standard value as the static pressure value, and marking the maximum value of the static pressure value within the monitoring period as the static pressure data JY.

3. The intelligent monitoring system for high static pressure axial flow fans according to claim 1, characterized in that: The process of obtaining the air volume data FL includes: obtaining the air volume of the monitored object during the monitoring period, retrieving the air volume range, marking the average of the maximum and minimum values ​​of the air volume range as the air volume standard value, and marking the absolute value of the difference between the air volume and the air volume standard value as the air volume data FL.

4. The intelligent monitoring system for high static pressure axial flow fans according to claim 1, characterized in that: The process of obtaining the speed data ZS includes: obtaining the impeller speed value of the monitored object, calling the speed range, marking the average of the maximum and minimum values ​​of the speed range as the speed standard value, marking the absolute value of the difference between the speed value and the speed standard value as the speed deviation value, and marking the maximum value of the speed deviation value within the monitoring period as the speed data ZS.

5. The intelligent monitoring system for high static pressure axial flow fans according to claim 1, characterized in that: The specific process of marking the monitoring period as a normal period, an abnormal period or a pending period includes: obtaining the operating thresholds YXmax and YXmin through the storage module, and comparing the operating coefficient YX of the monitored object during the monitoring period with the operating thresholds YXmax and YXmin: if YX≤YXmin, it is determined that the operating status of the monitored object during the monitoring period meets the requirements, and the corresponding monitoring period is marked as a normal period; if YXmin<YX<YXmax, the corresponding monitoring period is marked as a pending period; if YX≥YXmax, it is determined that the operating status of the monitored object during the monitoring period does not meet the requirements, and the corresponding monitoring period is marked as an abnormal period, a shutdown maintenance signal is generated, and the abnormal analysis signal is sent to the intelligent monitoring platform. After receiving the abnormal analysis signal, the intelligent monitoring platform sends the abnormal analysis signal to the abnormal analysis module.

6. The intelligent monitoring system for high static pressure axial flow fans according to claim 1, characterized in that: The specific process of determining whether maintenance is necessary for the monitored object within the monitoring period includes: obtaining the maintenance threshold WHmax through the storage module, and comparing the maintenance coefficient WH of the monitoring period with the maintenance threshold WHmax: if the maintenance coefficient WH is less than the maintenance threshold WHmax, it is determined that the monitored object does not need maintenance within the monitoring period; if the maintenance coefficient WH is greater than or equal to the maintenance threshold WHmax, it is determined that maintenance is necessary for the monitored object within the monitoring period, generating a device maintenance signal and sending the device maintenance signal to the intelligent monitoring platform. After receiving the device maintenance signal, the intelligent monitoring platform sends the device maintenance signal to the mobile phone terminal of the manager.

7. The intelligent monitoring system for high static pressure axial flow fans according to claim 6, characterized in that: The specific process of the abnormal analysis module analyzing the factors affecting the abnormal operation of the high static pressure axial flow fan includes: obtaining the voltage value of the power supply line of the monitored object during the abnormal period, and comparing the voltage value with the voltage range: if the voltage value is within the voltage range, a mechanical maintenance signal is generated and sent to the intelligent monitoring platform, and the intelligent monitoring platform sends the mechanical maintenance signal to the mobile phone terminal of the manager after receiving the mechanical maintenance signal; if the voltage value is outside the voltage range, a circuit maintenance signal is generated and sent to the intelligent monitoring platform, and the intelligent monitoring platform sends the circuit maintenance signal to the mobile phone terminal of the manager after receiving the circuit maintenance signal.

8. The intelligent monitoring system for a high static pressure axial flow fan according to any one of claims 1 to 7, characterized in that: The working method of the intelligent monitoring system of the high static pressure axial flow fan includes the following steps: Step 1: Monitor and analyze the operating status of the high-static-pressure axial-flow fan: Mark the high-static-pressure axial-flow fan as a monitoring object, generate a monitoring cycle, divide the monitoring cycle into several monitoring time periods, obtain the static pressure data JY, air volume data FL, and speed data ZS of the monitoring object during the monitoring period, and perform numerical calculations to obtain the operating coefficient YX; Step 2: Mark the monitoring period as normal period, abnormal period or pending period through the operation coefficient YX; Step 3: Monitor and analyze the maintenance necessity of the high static pressure axial flow fan: After the monitoring period ends, obtain the pending data DD, continuous data LX, and normal data ZC of the monitoring period and perform numerical calculations to obtain the maintenance coefficient WH. The maintenance coefficient WH is used to determine whether the monitoring equipment needs maintenance during the monitoring period. Step 4: Analyze the factors affecting the abnormal operation of the high static pressure axial flow fan: obtain the voltage value of the power supply line of the monitored object during the abnormal period, compare the voltage value with the voltage range, generate a mechanical maintenance signal or a circuit maintenance signal based on the comparison result and send it to the intelligent monitoring platform.

9. High static pressure axial flow fan, characterized in that: The high static pressure axial flow fan includes the intelligent monitoring system according to any one of claims 1 to 7.

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