A screw vacuum pump fault monitoring system and method based on data analysis

Abstract

The present invention discloses a screw vacuum pump fault monitoring system and method based on data analysis, which belongs to the field of intelligent monitoring technology. The system includes a device control module, a data acquisition module, a local database, a model analysis module, an intelligent calculation module, an early warning module and an interactive module; the device control module is used to control the start or shut down of the screw vacuum pump; the data acquisition module is used to collect state data during the operation of the screw vacuum pump; the local database is used to store historical data; the model analysis module is used to establish a variable analysis model to analyze the influence of different input powers, gas internal and external pressure differences and internal temperatures of the screw vacuum pump on the vibration amplitude; the intelligent calculation module is used to calculate the influence value of the wear of the screw vacuum pump on the vibration amplitude and calculate the total wear of the screw vacuum pump; the early warning module is used to determine whether an alarm is needed; the interactive module is used to provide an interactive display platform for fault alarm.

Description

Technical Field

[0001] The present invention relates to the field of intelligent monitoring technology, and in particular to a screw vacuum pump fault monitoring system and method based on data analysis. Background Art

[0002] A screw vacuum pump is a mechanical device that uses a pair of meshing screws to rotate in a pump body to generate a vacuum. The working principle of a screw vacuum pump can be divided into three processes: suction, compression, and exhaust. As the rotor rotates, each pair of meshing teeth completes the same working cycle in succession. During the suction process, the volume between the teeth expands to form a vacuum, and gas flows in. During the compression process, the volume between the teeth decreases, causing the pressure to rise, thereby achieving gas compression. During the exhaust process, after the volume between the teeth is connected to the exhaust port, the gas is gradually discharged through the exhaust port. With the rapid development of industrialization, screw vacuum pumps have been widely used in microelectronics, pharmaceuticals and other fields.

[0003] During the operation of the screw vacuum pump, the rotor, bearings and other components are often overloaded and worn, so personnel are required to perform regular maintenance and inspections to prevent certain faults from occurring. For some potential complex faults, simple safety inspections are often difficult to capture, and it is impossible to comprehensively evaluate the degree of faults in the screw vacuum pump. The existing technology extracts and analyzes the features of the vacuum pump operating status data to determine the fault, but does not effectively screen the analysis data, and does not consider the impact of other conditions and factors on the judgment of screw vacuum pump faults, which can easily cause system misjudgment. Summary of the invention

[0004] The object of the present invention is to provide a screw vacuum pump fault monitoring system and method based on data analysis to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: a screw vacuum pump fault monitoring method based on data analysis, the method comprising the following steps:

[0006] S10, starting the screw vacuum pump, and collecting status data of the screw vacuum pump during operation; the status data includes input power, gas pressure difference, internal temperature and vibration amplitude of the screw vacuum pump;

[0007] S20, storing the collected status data as historical data in a local database, dividing the historical data into safety historical data and risk historical data, and continuously updating the local database; wherein, based on the safety historical data stored in the local database, establishing a variable analysis model to analyze the influence of different input powers, gas internal and external pressure differences, and internal temperatures of the screw vacuum pump on the vibration amplitude;

[0008] S30, calculating the influence value of the wear of the screw vacuum pump on the vibration amplitude according to the collected state data and the established variable analysis model, and calculating the total wear degree of the screw vacuum pump according to the vibration amplitude influence value and the historical data stored in the local database;

[0009] S40. Obtain the total wear data of the screw vacuum pump when it fails, determine the fault alarm threshold of the screw vacuum pump based on the total wear data obtained, and judge whether an alarm is needed based on the total wear and fault alarm threshold of the screw vacuum pump under the current operating state; if an alarm is needed, send an alarm signal to the management personnel; wherein, repeat steps S10-S40 until the screw vacuum pump is shut down.

[0010] A screw vacuum pump fault monitoring system based on data analysis, the system includes an equipment control module, a data acquisition module, a local database, a model analysis module, an intelligent calculation module, an early warning module and an interaction module;

[0011] The device control module is used to control the start or shut down of the screw vacuum pump; when the screw vacuum pump is started, a signal is sent to the data acquisition module to start data acquisition; when the screw vacuum pump is shut down, a signal is sent to the data acquisition module to stop data acquisition;

[0012] The data acquisition module is used to collect status data of the screw vacuum pump during operation; the status data includes input power, gas pressure difference, internal temperature and vibration amplitude of the screw vacuum pump; and the collected status data is sent to the local database, intelligent computing module and interactive module;

[0013] The local database is used to store the collected status data as historical data in the local database, divide the historical data into safety historical data and risk historical data, and continuously update the local database;

[0014] The model analysis module is used to establish a variable analysis model based on the safety history data stored in the local database to analyze the influence of different input powers, internal and external pressure differences of the gas and internal temperatures of the screw vacuum pump on the vibration amplitude;

[0015] The intelligent calculation module is used to calculate the influence value of the wear of the screw vacuum pump on the vibration amplitude according to the collected state data and the variable analysis model established in the model analysis module, and calculate the total wear degree of the screw vacuum pump according to the vibration amplitude influence value and the historical data stored in the local database; send the calculated total wear degree to the early warning module; send the calculated vibration amplitude influence value and total wear degree to the interactive module;

[0016] The early warning module is used to obtain the total wear data of the screw vacuum pump when it fails, determine the fault alarm threshold of the screw vacuum pump based on the total wear data obtained, and judge whether an alarm is needed based on the total wear and fault alarm threshold of the screw vacuum pump in the current operating state; if an alarm is needed, send an alarm signal to the interactive module;

[0017] The interactive module is used to provide an interactive display platform, perform fault alarms, and display the collected status data of the screw vacuum pump during operation, the calculated impact value of the screw vacuum pump wear on the vibration amplitude, and the total wear of the screw vacuum pump on the interactive display platform, so that management personnel can view it conveniently.

[0018] Compared with the prior art, the beneficial effects achieved by the present invention are: by updating the local database and performing fault monitoring based on the latest status data of the screw vacuum pump, the true status of the screw vacuum pump can be better reflected, thereby improving the accuracy of fault judgment of the screw vacuum pump; by establishing a variable analysis model, considering the influence of other conditions and factors on the vibration amplitude, and calculating the total wear of the screw vacuum pump, it is determined whether the screw vacuum pump is faulty, thereby helping managers to further effectively evaluate the degree of faults and reducing the risk of faults. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a schematic diagram of the steps of a screw vacuum pump fault monitoring method based on data analysis of the present invention;

[0020] Figure 2 It is a structural schematic diagram of a screw vacuum pump fault monitoring system based on data analysis of the present invention. DETAILED DESCRIPTION

[0021] 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.

[0022] See also Figure 1-2 , the present invention provides a technical solution:

[0023] See also Figure 1In the first embodiment of the present invention, a screw vacuum pump fault monitoring method based on data analysis is provided. In the method, a dry screw vacuum pump is used to provide a vacuum environment for the production process of photovoltaic modules, and the fault of the dry screw vacuum pump is monitored according to influencing factors such as vibration amplitude. Since some potential faults of the dry screw vacuum pump are often difficult to troubleshoot during operation, the method monitors the vibration amplitude of the dry screw vacuum pump to narrow the scope of troubleshooting for managers, thereby realizing intelligent monitoring of dry screw vacuum pump faults. The method includes the following steps:

[0024] S10, starting the screw vacuum pump, and collecting status data of the screw vacuum pump during operation; the status data includes input power, gas pressure difference, internal temperature and vibration amplitude of the screw vacuum pump.

[0025] Furthermore, the screw vacuum pump is installed with a power meter, a pressure sensor, a temperature sensor and a vibration sensor; the power meter is used to determine the input power of the screw vacuum pump by collecting the current and voltage at the input end of the screw vacuum pump; the pressure sensor is used to collect the gas pressure at the inlet and outlet of the screw vacuum pump, and the gas pressure difference at the inlet and outlet is used as the gas pressure difference of the screw vacuum pump; the temperature sensor is used to collect the internal temperature of the screw vacuum pump; the vibration sensor is used to collect the vibration amplitude of the screw vacuum pump; the vibration amplitude represents the maximum distance that the screw vacuum pump leaves the equilibrium position.

[0026] In this implementation, the power meter is installed at the current and voltage input ends of the screw vacuum pump; the pressure sensor is installed at the inlet and outlet of the screw vacuum pump gas; the temperature sensor is installed inside the screw vacuum pump; since the vibration of the screw vacuum pump mainly comes from the movement of the bearing, the vibration sensor is installed close to the bearing of the screw vacuum pump. Therefore, this implementation is to monitor the bearing failure of the screw vacuum pump.

[0027] It should be noted that this method can also perform fault diagnosis on the components of each module of the screw vacuum pump; when performing fault diagnosis on the components, the data collected by the power meter, pressure sensor, temperature sensor and vibration sensor are the status data of the corresponding components; for example, when the fault diagnosed component is the rotor, the input power at the rotor is obtained according to the current, voltage and rotor work power ratio at the input end of the screw vacuum pump; and the temperature sensor and vibration sensor are installed near the rotor; among them, since the gas pressure difference of the rotor cannot be measured, only the influence of input power and internal temperature is considered.

[0028] S20. Store the collected status data as historical data in a local database, divide the historical data into safety historical data and risk historical data, and continuously update the local database; wherein, based on the safety historical data stored in the local database, establish a variable analysis model to analyze the effects of different input powers of the screw vacuum pump, the pressure difference between the inside and outside of the gas, and the internal temperature on the vibration amplitude.

[0029] Furthermore, the screw vacuum pump is periodically maintained, the number of maintenance times is recorded, and the timestamp t1 at the end of each maintenance of the screw vacuum pump and the timestamp t2 at the beginning of the next maintenance are recorded; the division time T of the safety history data and the risk history data is determined; t1 is used as the initial time, and the status data of the screw vacuum pump operation time less than T in the time period from t1 to t2 is used as the safety history data, and the status data of the screw vacuum pump operation time greater than T in the time period from t1 to t2 is used as the risk history data; wherein, the method for continuously updating the local database is: when the screw vacuum pump starts maintenance, the status data of the screw vacuum pump in the previous maintenance cycle is continued to be stored in the local database as historical data, and the status data in other maintenance cycles is uploaded to the cloud database as historical data and then deleted; wherein, the division time size of T is 48 hours, and the periodic maintenance time of the screw vacuum pump is 3 months.

[0030] It should be noted that the safety history data represents status data collected when the screw vacuum pump is less worn during a maintenance cycle; the risk history data represents status data collected when the screw vacuum pump is more worn during a maintenance cycle; during a maintenance cycle, the screw vacuum pump has different operating time periods, and these different operating time periods are accumulated to obtain the operating time of the screw vacuum pump, and the operating time of the screw vacuum pump is compared with the divided time T, and the safety history data and the risk history data are divided, so as to screen the analysis data of the subsequent variable analysis model, which can better reflect the influence of power, gas pressure difference and temperature influencing conditions on the vibration amplitude, thereby improving the accuracy of data analysis.

[0031] Furthermore, based on the safety history data stored in the local database, the method steps for establishing the variable analysis model are as follows:

[0032] S201. Analyze the safety history data and determine the input power of the screw vacuum pump at different timestamps t0. Gas pressure difference Internal temperature and vibration amplitude

[0033] Among them, t0 represents the timestamp corresponding to the security history data stored in the local database;

[0034] S202. Establish a variable analysis model, take the input power P, gas pressure difference Y and internal temperature W of the screw vacuum pump as independent variables, take the vibration amplitude F of the screw vacuum pump as the dependent variable, analyze the influence of different input power, gas internal and external pressure difference and internal temperature of the screw vacuum pump on the vibration amplitude, according to the calculation formula:

[0035]

[0036] Among them, a1, a2, b1, b2, c1, c2 and d are all constants; and Substitute them into the above calculation formula respectively, and solve a1, a2, b1, b2, c1, c2 and d according to the least squares method to minimize the mean square error between the predicted value and the actual value.

[0037] It should be noted that the time step of the timestamp is the time it takes for the vibration amplitude of the screw vacuum pump to change from the maximum distance from the equilibrium position on one side to the maximum distance from the equilibrium position on the other side. and There are corresponding values ​​at different timestamps; a1 and a2 represent the influence of different input powers of the screw vacuum pump on the vibration amplitude; b1 and b2 represent the influence of different internal and external pressure differences of the screw vacuum pump on the vibration amplitude; c1 and c2 represent the influence of different internal temperatures of the screw vacuum pump on the vibration amplitude; d represents the error term; By establishing a variable analysis model, As the training parameters of P; As the training parameters of Y; As the training parameter of W; As the training parameters of F; substitute them into the above calculation formula respectively to determine the predicted values ​​F corresponding to different values ​​of a1, a2, b1, b2, c1, c2 and d yu According to the least squares method, the predicted value F yu With the actual value F t The mean square error value is calculated, and a1, a2, b1, b2, c1, c2 and d corresponding to the minimum mean square error value between the predicted value and the actual value are used as constants in the variable analysis model; according to the established variable analysis model, the influence of subsequent screw vacuum pump wear on the vibration amplitude is calculated, and the influence of power, gas pressure difference and temperature conditions on the vibration amplitude is considered, which helps managers to further effectively evaluate the degree of fault.

[0038] In this embodiment, the input power P, gas pressure difference Y and internal temperature W of the screw vacuum pump correspond to the state data analyzed during the bearing fault monitoring, and the influence value I of the bearing wear on the vibration amplitude in the screw vacuum pump at different time stamps t is calculated.t , and calculate the total wear of the screw vacuum pump bearing at different time stamps t

[0039] S30. Calculate the influence of the wear of the screw vacuum pump on the vibration amplitude according to the collected state data and the established variable analysis model, and calculate the total wear degree of the screw vacuum pump according to the vibration amplitude influence value and the historical data stored in the local database.

[0040] Specifically, the method steps are:

[0041] S301, analyzing the collected status data to determine the input power P of the screw vacuum pump at different time stamps t t , gas pressure difference Y t 、Internal temperature W t and vibration amplitude F t , according to P t , Y t , W t 、F t The variable analysis model established is used to calculate the influence value I of the screw vacuum pump wear on the vibration amplitude at different time stamps t. t :

[0042]

[0043] S302, analyzing the historical data stored in the local database, and finding the timestamp t corresponding to the shortest time since the last maintenance of the screw vacuum pump x As the initial time, according to I t , calculate the total wear of the screw vacuum pump at different time stamps t

[0044]

[0045] Among them, I i represents the influence of screw vacuum pump wear on vibration amplitude at time i; t represents different timestamps; X t represents the maintenance times of the screw vacuum pump at different timestamps t; α represents the influence weight of the maintenance times of the screw vacuum pump on the total wear degree.

[0046] It should be noted that by calculating the impact of screw vacuum pump wear on vibration amplitude and the total wear of the screw vacuum pump, managers can more intuitively understand the current failure level of the screw vacuum pump, thereby reducing the risk of failure.

[0047] S40. Obtain the total wear data of the screw vacuum pump when it fails, determine the fault alarm threshold of the screw vacuum pump based on the total wear data obtained, and judge whether an alarm is needed based on the total wear and fault alarm threshold of the screw vacuum pump under the current operating state; if an alarm is needed, send an alarm signal to the management personnel; wherein, repeat steps S10-S40 until the screw vacuum pump is shut down.

[0048] Further, the method for determining whether an alarm is required in step S40 is: obtaining total wear data when the screw vacuum pump fails, analyzing the obtained total wear data, determining different total wear degrees corresponding to the screw vacuum pump failure, and obtaining a set H, wherein: represents the different total wear degrees corresponding to the total wear degree data analyzed; m represents the number of total wear degree data analyzed; according to the set H, the fault alarm threshold K of the screw vacuum pump is determined by the least squares method max ; Determine the total wear degree I of the screw vacuum pump under the current operating state z , will I z With K max To compare; when I z ≤K max When the screw vacuum pump is safe, no alarm is required; when I z >K max When the screw vacuum pump is at risk of failure, an alarm needs to be issued to send an alarm signal to the management personnel.

[0049] It should be noted that the screw vacuum pump failure includes but is not limited to bearing damage, bearing bending deformation, and increased vibration amplitude of the screw vacuum pump. Since the increase in vibration amplitude will lead to increased wear and damage to the internal components of the screw vacuum pump, the larger the vibration amplitude, the more serious the screw vacuum pump failure. Troubleshooting through the vibration amplitude of the screw vacuum pump can help managers reduce their workload.

[0050] In this implementation, based on the set H, the least squares method is used to determine the fault alarm threshold K of the screw vacuum pump bearing. max The method is: calculate the square difference PF, so that K max Requirements: in, Indicates the jth total wear degree corresponding to the total wear degree data analyzed; j = 1, 2, ..., m; Determine the total wear degree I of the screw vacuum pump bearing in the current operating state z , will I z With K max To compare; when I z ≤K max When the screw vacuum pump bearing is safe; when IZ >K max When the screw vacuum pump bearing is at risk of failure, an alarm signal is sent to the management personnel.

[0051] Furthermore, the method for confirming the division time T of the safety history data and the risk history data is: based on the historical safety data stored in the local database and the cloud database, the total wear calculated under different division time lengths T is analyzed, and according to the accuracy of the screw vacuum pump fault judgment, the value of T is adjusted to maximize the accuracy of the screw vacuum pump fault judgment.

[0052] It should be noted that when the value of the division time T is small, the amount of historical safety data analyzed by the variable analysis model will decrease, resulting in incomplete analysis data and reduced model accuracy; when the value of the division time T is large, the wear of the screw vacuum pump continues to increase, which may easily lead to the accuracy of the analyzed historical safety data itself being insufficient and the accuracy of the model being reduced; therefore, when the value of T is within a moderate range, the accuracy of the variable analysis model reaches the highest level, and the value of T is continuously adjusted based on the historical safety data stored in the local database and the cloud database to determine the final value.

[0053] In this implementation, by continuously adjusting the value of T and selecting 2000 total wear data of screw vacuum pump bearing failures as a verification set, the accuracy of the variable analysis model is verified. It is found that when the division time of T is 48 hours, the accuracy of the variable analysis model reaches the highest.

[0054] Furthermore, an interactive display platform is provided to perform fault alarms, and the collected status data of the screw vacuum pump during operation, the calculated impact value of the screw vacuum pump wear on the vibration amplitude and the total wear of the screw vacuum pump are displayed on the interactive display platform to facilitate viewing by management personnel.

[0055] See also Figure 2 , in this implementation 2: a screw vacuum pump fault monitoring system based on data analysis is provided, the system includes an equipment control module, a data acquisition module, a local database, a model analysis module, an intelligent calculation module, an early warning module and an interactive module;

[0056] The device control module is used to control the start or shut down of the screw vacuum pump; when the screw vacuum pump is started, a signal is sent to the data acquisition module to start data acquisition; when the screw vacuum pump is shut down, a signal is sent to the data acquisition module to stop data acquisition;

[0057] The data acquisition module is used to collect status data of the screw vacuum pump during operation; the status data includes input power, gas pressure difference, internal temperature and vibration amplitude of the screw vacuum pump; and the collected status data is sent to the local database, intelligent computing module and interactive module;

[0058] The local database is used to store the collected status data as historical data in the local database, divide the historical data into safety historical data and risk historical data, and continuously update the local database;

[0059] The model analysis module is used to establish a variable analysis model based on the safety history data stored in the local database to analyze the influence of different input powers, internal and external pressure differences of the gas and internal temperatures of the screw vacuum pump on the vibration amplitude;

[0060] The intelligent calculation module is used to calculate the influence value of the wear of the screw vacuum pump on the vibration amplitude according to the collected state data and the variable analysis model established in the model analysis module, and calculate the total wear degree of the screw vacuum pump according to the vibration amplitude influence value and the historical data stored in the local database; send the calculated total wear degree to the early warning module; send the calculated vibration amplitude influence value and total wear degree to the interactive module;

[0061] The early warning module is used to obtain the total wear data of the screw vacuum pump when it fails, determine the fault alarm threshold of the screw vacuum pump based on the total wear data obtained, and judge whether an alarm is needed based on the total wear and fault alarm threshold of the screw vacuum pump in the current operating state; if an alarm is needed, send an alarm signal to the interactive module;

[0062] The interactive module is used to provide an interactive display platform, perform fault alarms, and display the collected status data of the screw vacuum pump during operation, the calculated impact value of the screw vacuum pump wear on the vibration amplitude, and the total wear of the screw vacuum pump on the interactive display platform, so that management personnel can view it conveniently.

[0063] In this embodiment:

[0064] When the screw vacuum pump starts to work, the equipment control module controls the screw vacuum pump to start, sends a signal to the data acquisition module, and starts data acquisition; the data acquisition module collects the status data of the screw vacuum pump during operation, and sends the collected status data to the local database, the intelligent calculation module and the interaction module; the local database stores the collected status data as historical data in the local database, and continuously updates the local database; the model analysis module establishes a variable analysis model based on the safety history data stored in the local database, and analyzes the influence of different input powers, gas internal and external pressure differences and internal temperatures of the screw vacuum pump on the vibration amplitude; the intelligent calculation module calculates the influence of the wear of the screw vacuum pump on the vibration amplitude, Calculate the total wear of the screw vacuum pump; send the calculated total wear to the early warning module; send the calculated vibration amplitude impact value and total wear to the interactive module; the early warning module determines whether an alarm is required based on the total wear of the screw vacuum pump and the fault alarm threshold under the current operating state; if an alarm is required, send an alarm signal to the interactive module; the interactive module is used to provide an interactive display platform, perform fault alarms, and display the collected status data of the screw vacuum pump during operation, the calculated impact value of the screw vacuum pump wear on the vibration amplitude, and the total wear of the screw vacuum pump on the interactive display platform; when the screw vacuum pump stops operating, the equipment control module sends a signal to the data acquisition module to stop data acquisition.

[0065] Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A screw vacuum pump fault monitoring method based on data analysis, characterized in that: The method comprises the following steps: S10, starting the screw vacuum pump, and collecting status data of the screw vacuum pump during operation; the status data includes input power, gas pressure difference, internal temperature and vibration amplitude of the screw vacuum pump; S20, storing the collected status data as historical data in a local database, dividing the historical data into safety historical data and risk historical data, and continuously updating the local database; wherein, based on the safety historical data stored in the local database, establishing a variable analysis model to analyze the influence of different input powers, gas internal and external pressure differences, and internal temperatures of the screw vacuum pump on the vibration amplitude; S30, calculating the influence value of the wear of the screw vacuum pump on the vibration amplitude according to the collected state data and the established variable analysis model, and calculating the total wear degree of the screw vacuum pump according to the vibration amplitude influence value and the historical data stored in the local database; S40. Obtain the total wear data of the screw vacuum pump when it fails, determine the fault alarm threshold of the screw vacuum pump based on the total wear data obtained, and judge whether an alarm is needed based on the total wear and fault alarm threshold of the screw vacuum pump under the current operating state; if an alarm is needed, send an alarm signal to the management personnel; wherein, repeat steps S10-S40 until the screw vacuum pump is shut down.

2. A screw vacuum pump fault monitoring method based on data analysis according to claim 1, characterized in that: The screw vacuum pump is installed with a power meter, a pressure sensor, a temperature sensor and a vibration sensor; the power meter is used to determine the input power of the screw vacuum pump by collecting the current and voltage at the input end of the screw vacuum pump; the pressure sensor is used to collect the gas pressure at the inlet and outlet of the screw vacuum pump, and the gas pressure difference at the inlet and outlet is used as the gas pressure difference of the screw vacuum pump; the temperature sensor is used to collect the internal temperature of the screw vacuum pump; the vibration sensor is used to collect the vibration amplitude of the screw vacuum pump; the vibration amplitude represents the maximum distance that the screw vacuum pump leaves the equilibrium position.

3. The method for monitoring screw vacuum pump failure based on data analysis according to claim 1, characterized in that: Perform periodic maintenance on the screw vacuum pump, record the number of maintenances, and record the timestamp t1 when each maintenance of the screw vacuum pump ends and the timestamp t2 when the next maintenance starts; Determine the division time T of safety history data and risk history data; take t1 as the initial time, and take the status data of the screw vacuum pump operation time less than T in the time period from t1 to t2 as safety history data, and take the status data of the screw vacuum pump operation time greater than T in the time period from t1 to t2 as risk history data; wherein, the method for continuously updating the local database is: when the screw vacuum pump starts maintenance, the status data of the screw vacuum pump in the previous maintenance cycle will continue to be stored in the local database as historical data, and the status data in other maintenance cycles will be uploaded to the cloud database as historical data and then deleted.

4. A screw vacuum pump fault monitoring method based on data analysis according to claim 3, characterized in that: Based on the safety history data stored in the local database, the method steps for establishing the variable analysis model are as follows: S201. Analyze the safety history data and determine the input power of the screw vacuum pump at different timestamps t0. Gas pressure difference Internal temperature and vibration amplitude Among them, t0 represents the timestamp corresponding to the security history data stored in the local database; S202. Establish a variable analysis model, take the input power P, gas pressure difference Y and internal temperature W of the screw vacuum pump as independent variables, take the vibration amplitude F of the screw vacuum pump as the dependent variable, analyze the influence of different input power, gas internal and external pressure difference and internal temperature of the screw vacuum pump on the vibration amplitude, according to the calculation formula: Among them, a1, a2, b1, b2, c1, c2 and d are all constants; and Substitute them into the calculation formula respectively, and solve a1, a2, b1, b2, c1, c2 and d according to the least squares method to minimize the mean square error between the predicted value and the actual value.

5. A screw vacuum pump fault monitoring method based on data analysis according to claim 4, characterized in that: The method steps of step S30 are: S301, analyzing the collected status data to determine the input power P of the screw vacuum pump at different time stamps t t , gas pressure difference Y t 、Internal temperature W t and vibration amplitude F t , according to P t , Y t , W t 、F t The variable analysis model established is used to calculate the influence value I of the screw vacuum pump wear on the vibration amplitude at different time stamps t. t : S302, analyzing the historical data stored in the local database, and finding the timestamp t corresponding to the shortest time since the last maintenance of the screw vacuum pump x As the initial time, according to I t , calculate the total wear of the screw vacuum pump at different time stamps t Among them, I i represents the influence of screw vacuum pump wear on vibration amplitude at time i; t represents different timestamps; X t represents the maintenance times of the screw vacuum pump at different timestamps t; α represents the influence weight of the maintenance times of the screw vacuum pump on the total wear degree.

6. A screw vacuum pump fault monitoring method based on data analysis according to claim 5, characterized in that: The method for determining whether an alarm is required in step S40 is: obtaining total wear data when the screw vacuum pump fails, analyzing the obtained total wear data, determining different total wear degrees corresponding to the screw vacuum pump failure, and obtaining a set H, wherein: represents the different total wear degrees corresponding to the total wear degree data analyzed; m represents the number of total wear degree data analyzed; according to the set H, the fault alarm threshold K of the screw vacuum pump is determined by the least squares method max ; Determine the total wear degree I of the screw vacuum pump under the current operating state z , will I z With K max To compare; when I z ≤K max When the screw vacuum pump is safe, no alarm is required; when I z >K max When the screw vacuum pump is at risk of failure, an alarm needs to be issued to send an alarm signal to the management personnel.

7. A screw vacuum pump fault monitoring method based on data analysis according to claim 6, characterized in that: The method for confirming the division time T of safety history data and risk history data is: based on the historical safety data stored in the local database and the cloud database, the total wear calculated under different division time lengths T is analyzed, and according to the accuracy of the screw vacuum pump fault judgment, the value of T is adjusted to maximize the accuracy of the screw vacuum pump fault judgment.

8. A screw vacuum pump fault monitoring method based on data analysis according to claim 6, characterized in that: An interactive display platform is provided for fault alarm, and the collected status data of the screw vacuum pump during operation, the calculated impact value of the screw vacuum pump wear on the vibration amplitude and the total wear degree of the screw vacuum pump are displayed on the interactive display platform for easy viewing by management personnel.

9. A screw vacuum pump fault monitoring system based on data analysis, characterized in that: The system includes an equipment control module, a data acquisition module, a local database, a model analysis module, an intelligent calculation module, an early warning module and an interaction module; The device control module is used to control the start or shut down of the screw vacuum pump; when the screw vacuum pump is started, a signal is sent to the data acquisition module to start data acquisition; when the screw vacuum pump is shut down, a signal is sent to the data acquisition module to stop data acquisition; The data acquisition module is used to collect status data of the screw vacuum pump during operation; the status data includes input power, gas pressure difference, internal temperature and vibration amplitude of the screw vacuum pump; and the collected status data is sent to the local database, intelligent computing module and interactive module; The local database is used to store the collected status data as historical data in the local database, divide the historical data into safety historical data and risk historical data, and continuously update the local database; The model analysis module is used to establish a variable analysis model based on the safety history data stored in the local database to analyze the influence of different input powers, internal and external pressure differences of the gas and internal temperatures of the screw vacuum pump on the vibration amplitude; The intelligent calculation module is used to calculate the influence value of the wear of the screw vacuum pump on the vibration amplitude according to the collected state data and the variable analysis model established in the model analysis module, and calculate the total wear degree of the screw vacuum pump according to the vibration amplitude influence value and the historical data stored in the local database; send the calculated total wear degree to the early warning module; send the calculated vibration amplitude influence value and total wear degree to the interactive module; The early warning module is used to obtain the total wear data of the screw vacuum pump when it fails, determine the fault alarm threshold of the screw vacuum pump based on the total wear data obtained, and judge whether an alarm is needed based on the total wear and fault alarm threshold of the screw vacuum pump in the current operating state; if an alarm is needed, send an alarm signal to the interactive module; The interactive module is used to provide an interactive display platform, perform fault alarms, and display the collected status data of the screw vacuum pump during operation, the calculated impact value of the screw vacuum pump wear on the vibration amplitude, and the total wear of the screw vacuum pump on the interactive display platform, so that management personnel can view it conveniently.

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