Method and system for life prediction based on power analysis of dry vacuum pump set

Abstract

The application provides a life prediction method and system based on power analysis of a dry vacuum pump set, relates to the technical field of power analysis, and comprises the following steps: obtaining a dry vacuum pump set, which comprises a first vacuum pump and a second vacuum pump; obtaining a first pump power signal set and a second pump power signal set respectively; collecting a first motor power signal and a second motor power signal; taking the first pump power signal set and the first motor power signal as a first group of signals and taking the second pump power signal set and the second motor power signal as a second group of signals to perform prediction and obtain a first abnormal power transmission and a second abnormal power transmission; and identifying by using a power coupling model and outputting a first life prediction result. The application solves the technical problem that the traditional method cannot effectively predict potential faults or life ends and cannot accurately identify abnormal power transmission between the motor and the pump, thereby reducing the accuracy and reliability of system life prediction.

Description

Technical Field

[0001] The present invention relates to the technical field of power analysis, and in particular to a life prediction method and system based on power analysis of a dry vacuum pump group. Background Art

[0002] A vacuum pump group usually consists of multiple vacuum pumps and related motors. The complexity of its working conditions makes it difficult for existing technologies to predict its life. On the one hand, traditional life prediction methods cannot accurately take into account the mutual influence between the various components in the system, especially the identification of abnormal conditions in power transmission between the motor and the pump is not accurate enough, making it impossible to detect potential faults in advance, resulting in difficulty in accurately predicting the life of the vacuum pump group; on the other hand, traditional life prediction methods are limited by the accurate capture of actual working conditions and cannot effectively predict potential faults or the end of life, resulting in low accuracy and reliability of system life prediction. Summary of the Invention

[0003] This application provides a life prediction method and system based on power analysis of dry vacuum pump groups, aiming to solve the technical problems that the life prediction method of traditional vacuum pump groups is limited by the accurate capture of actual working conditions, cannot effectively predict potential failures or life end, and is not accurate enough in identifying abnormal conditions of power transmission between the motor and the pump, making it impossible to detect potential failures in advance, resulting in low accuracy and reliability of system life prediction.

[0004] In view of the above problems, the present application provides a life prediction method and system based on power analysis of a dry vacuum pump group.

[0005] The first aspect disclosed in the present application provides a life prediction method based on power analysis of a dry vacuum pump group, the method comprising: obtaining a dry vacuum pump group, the dry vacuum pump group comprising a first vacuum pump and a second vacuum pump, the first vacuum pump and the second vacuum pump operating in combination; obtaining a first pump power signal set and a second pump power signal set of the first vacuum pump and the second vacuum pump respectively through a power acquisition device; collecting a first motor power signal of a first motor and a second motor power signal of a second motor, wherein the first motor is connected to the first vacuum pump and the second motor is connected to the second vacuum pump; using the first pump power signal set and the first motor power signal as a first group of signals, and using the second pump power signal set and the second motor power signal as a second group of signals for prediction, to obtain a first abnormal transmission power and a second abnormal transmission power of power transmission between the motor and the pump; using a power coupling model to identify the first abnormal transmission power and the second abnormal transmission power, and output a first life prediction result.

[0006] Another aspect disclosed in the present application provides a life prediction system based on power analysis of a dry vacuum pump group, the system being used for the above method, and comprising: a vacuum pump acquisition module, the vacuum pump acquisition module being used to acquire a dry vacuum pump group, the dry vacuum pump group comprising a first vacuum pump and a second vacuum pump, the first vacuum pump and the second vacuum pump operating in combination; a pump power signal acquisition module, the pump power signal acquisition module being used to acquire a first pump power signal set and a second pump power signal set of the first vacuum pump and the second vacuum pump respectively through a power acquisition device; a motor power signal acquisition module, the motor power signal acquisition module being used to acquire a first motor power signal of the first motor, and a second motor power signal of the second motor. a second motor power signal of a machine, wherein the first motor is connected to the first vacuum pump, and the second motor is connected to the second vacuum pump; a transmission abnormal power acquisition module, the transmission abnormal power acquisition module is used to use the first pump power signal set and the first motor power signal as a first group of signals, and the second pump power signal set and the second motor power signal as a second group of signals for prediction, to obtain a first transmission abnormal power and a second transmission abnormal power of power transmission between the motor and the pump; a life prediction result acquisition module, the life prediction result acquisition module is used to use a power coupling model to identify the first transmission abnormal power and the second transmission abnormal power, and output a first life prediction result.

[0007] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0008] By collecting the power signals of the first and second vacuum pumps, as well as the power signals of the motors connected to them, comprehensive collection and analysis of the power of the entire system is achieved. The power signals of different pumps and motors are combined into a first and second group of signals. By predicting these two groups of signals, early identification of abnormal power transmission between the motor and the pump is achieved. A power coupling model is introduced for analysis, which can more accurately identify the first and second abnormal power transmissions, thereby improving the accuracy of fault diagnosis. Through the above steps, the method ultimately outputs a prediction result for the system life, providing maintenance personnel with timely early warning information, helping to take preventive maintenance measures, extend equipment life, and improve system reliability and stability. In summary, this life prediction method based on dry vacuum pump group power analysis effectively improves the accuracy and reliability of system life prediction through comprehensive power collection and precise analysis.

[0009] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1 A flow chart of a life prediction method based on power analysis of a dry vacuum pump group is provided for the embodiment of the present application;

[0011] Figure 2 A schematic diagram of the life prediction system structure based on power analysis of a dry vacuum pump group is provided for the embodiment of the present application.

[0012] Explanation of reference numerals: vacuum pump acquisition module 10 , pump power signal acquisition module 20 , motor power signal acquisition module 30 , abnormal power transmission acquisition module 40 , life prediction result acquisition module 50 . DETAILED DESCRIPTION

[0013] The embodiments of the present application provide a life prediction method based on power analysis of a dry vacuum pump group, thereby solving the technical problem that the traditional life prediction method of a vacuum pump group is limited by the accurate capture of the actual working state, cannot effectively predict potential failures or the end of life, and is not accurate enough in identifying abnormal conditions of power transmission between the motor and the pump, making it impossible to detect potential failures in advance, resulting in low accuracy and reliability of system life prediction.

[0014] After introducing the basic principles of the present application, various non-limiting implementation methods of the present application will be specifically introduced in conjunction with the drawings in the specification.

[0015] Example 1

[0016] like Figure 1 As shown, the embodiment of the present application provides a life prediction method based on power analysis of a dry vacuum pump group, the method comprising:

[0017] Obtain a dry vacuum pump assembly, the dry vacuum pump assembly comprising a first vacuum pump and a second vacuum pump, wherein the first vacuum pump and the second vacuum pump operate in combination;

[0018] The first vacuum pump is a Roots vacuum pump, a screw or gear-type vacuum pump used for high vacuum or high-flow applications. It consists of two intermeshing spiral blades or gears that rotate to generate vacuum. The second vacuum pump is a dry pump, which does not use liquid packing fluids but instead uses mechanical, sliding, or rotary techniques to remove gases. It is suitable for applications requiring a dry and clean environment. The first and second vacuum pumps are connected through mechanical and piping connections to work together to maintain the required vacuum level throughout the system.

[0019] respectively acquiring a first pump power signal set and a second pump power signal set of the first vacuum pump and the second vacuum pump through a power acquisition device;

[0020] Select a power collection device suitable for vacuum pumps that can measure and record the power output of the vacuum pumps. Install the power collection device in the power circuits of the first and second vacuum pumps. First, start the first vacuum pump and put it into operation. The power collection device collects the first vacuum pump's power signal in real time, including parameters such as current, voltage, and power factor. The power signal reflects the power consumption of the device during operation. This signal is continuously recorded to obtain the first vacuum pump's power signal set. Then, start the second vacuum pump and use the same method to collect the second pump's power signal set.

[0021] collecting a first motor power signal of a first motor and a second motor power signal of a second motor, wherein the first motor is connected to the first vacuum pump and the second motor is connected to the second vacuum pump;

[0022] The motor is an electric motor used to drive the vacuum pump. It connects the first motor and the first vacuum pump to ensure that a mechanical and electrical connection is established between the first motor and the first vacuum pump so that the motor can effectively drive the vacuum pump. The first motor is started and runs together with the first vacuum pump. The power signal of the first motor is collected in real time through the power collection device, including parameters such as current, voltage, and power factor, and the power signal set of the first motor is recorded for subsequent analysis and prediction.

[0023] Similarly, the second motor and the second vacuum pump are connected, and the second motor is started to run together with the second vacuum pump. The power signal of the second motor is collected in real time through the power collection device, and the power signal set of the second motor is recorded.

[0024] The first pump power signal set and the first motor power signal are used as a first group of signals, and the second pump power signal set and the second motor power signal are used as a second group of signals for prediction, to obtain a first abnormal transmission power and a second abnormal transmission power of power transmission between the motor and the pump;

[0025] The first pump power signal set and the first motor power signal are combined into a data set as a first group of signals; the second pump power signal set and the second motor power signal are combined into a data set as a second group of signals.

[0026] According to the connection structure between the first vacuum pump and the first motor, and the connection structure between the second vacuum pump and the second motor, a first transfer loss power and a second transfer loss power are generated. The first group of signals is predicted based on the first transfer loss power, and a first transfer abnormal power is output. The second group of signals is predicted based on the second transfer loss power, and a second transfer abnormal power is output. The abnormal power represents the power change in an abnormal state in the system. Here, it reflects the abnormal power transmission between the motor and the vacuum pump.

[0027] The predicted abnormal power can be used to correlate the power transfer process between the motor and the vacuum pump. Abnormal power may indicate an abnormal working state between the motor and the pump. For example, a decline in vacuum pump performance may cause an abnormal increase in motor power. Based on the correlation between the increase in motor power and the decrease in vacuum pump power, it can be inferred that abnormal power may lead to a decrease in motor life because it reflects the existence of certain abnormalities or faults in the system.

[0028] Furthermore, obtaining a first abnormal power and a second abnormal power of power transmission between the motor and the pump includes:

[0029] Acquire a connection structure between the first vacuum pump and the first motor, wherein the connection structure includes a structure between a rotor of the first vacuum pump and an output shaft of the first motor;

[0030] Acquire a connection structure between the second vacuum pump and the second motor, wherein the connection structure includes a structure between a rotor of the second vacuum pump and an output shaft of the second motor;

[0031] generating a first transmission loss power and a second transmission loss power according to a connection structure between the first vacuum pump and the first motor, and a connection structure between the second vacuum pump and the second motor;

[0032] predicting the first group of signals based on the first transmission loss power and outputting a first transmission abnormality power;

[0033] The second group of signals is predicted based on the second transmission loss power, and a second transmission abnormality power is output.

[0034] Identify the connection points between the first vacuum pump and the first motor, including the vacuum pump's rotor and the motor's output shaft. The rotor refers to the rotating component in the first vacuum pump that generates vacuum and can be a spiral blade or other structure. The output shaft refers to the shaft in the first motor that transmits power to the connected device, namely the first vacuum pump, through the motor's operation. Determine how the connection structure connects the first vacuum pump's rotor to the first motor's output shaft, including threaded connections, keyed connections, and other methods. Record these details for subsequent analysis.

[0035] In the same way, the structure between the second vacuum pump and the second motor is obtained.

[0036] Transfer loss power refers to the power loss caused by the connection structure and mechanical transmission during the energy transfer between the motor and the vacuum pump in the mechanical transmission. The efficiency of the mechanical transmission is obtained, that is, the efficiency of transferring the power output of the motor to the vacuum pump. This can be determined through experimental measurements or performance data provided by the manufacturer. The transfer loss power is calculated using the basic power transfer formula, which is: ,in, is the transfer loss power, is the torque, is the angular velocity, For transmission efficiency.

[0037] At the same time, based on the friction coefficient between the surfaces and the friction force of the moving parts, the friction loss in the connection structure and other additional losses that may be introduced by the connection structure, such as energy loss caused by vibration, are estimated, and the friction loss and the additional loss are added to the transmission loss power to generate the first transmission loss power.

[0038] In the same way, the second transmission loss power of the second vacuum pump and the second motor is calculated.

[0039] The first pump power signal in the first group of signals is identified to obtain an abnormal pump power signal, wherein the abnormal pump power signal is an abnormal power signal indicating that the power of the first vacuum pump during operation is greater than a preset load power. The first motor power signal in the first group of signals is identified to obtain an abnormal motor power signal, wherein the abnormal motor power signal is an abnormal power signal indicating that the power of the first motor during operation is greater than a preset load power. A synchronization abnormality signal is obtained based on the abnormal pump power signal and the abnormal motor power signal. A prediction is made based on the first transmission loss power to obtain a predicted synchronization difference between the abnormal pump power signal and the abnormal motor power signal. A first transmission abnormality power is output based on the synchronization difference of the synchronization abnormality signal.

[0040] The second transmission abnormal power is obtained in the same way.

[0041] Furthermore, predicting the first group of signals based on the first transmission loss power and outputting a first transmission abnormality power includes:

[0042] Identifying a first pump power signal in the first group of signals to obtain an abnormal pump power signal, wherein the abnormal pump power signal is an abnormal power signal in which the power of the first vacuum pump during operation is greater than a preset load power;

[0043] Identifying a first motor power signal in the first group of signals to obtain an abnormal motor power signal, wherein the abnormal motor power signal is an abnormal power signal in which the power of the first motor during operation is greater than a preset load power;

[0044] obtaining a synchronous abnormality signal based on the abnormal pump power signal and the abnormal motor power signal;

[0045] Performing a prediction based on the first transmission loss power to obtain a predicted synchronization difference between the abnormal pump power signal and the abnormal motor power signal;

[0046] A first transmission abnormality power is output according to the synchronization difference degree of the synchronization abnormality signal.

[0047] The power level of the first vacuum pump is obtained based on equipment specifications, manufacturer data, or historical performance data, thereby determining a preset load power for the first vacuum pump during normal system operation. During operation of the first vacuum pump, the first pump power signal is compared with the preset load power in real time. When the first pump power signal exceeds the preset load power, it is marked as abnormal. Once the first pump power signal is identified as abnormal, it is extracted to form an abnormal pump power signal.

[0048] The first motor power signal is identified in the same way to obtain an abnormal motor power signal.

[0049] The abnormal pump power signal and abnormal motor power signal are aligned on the time axis to ensure that the correlation between them accurately reflects the impact of pump power changes on motor power. By aligning the time axis, the abnormal pump power signal and abnormal motor power signal are processed synchronously to generate a synchronous abnormality signal. This signal reflects the synchronous change in motor power when the pump power increases, capturing the correlation and synchronization between the two.

[0050] Using the previously calculated first transfer loss power, the abnormal motor power signal is subjected to loss calculation to obtain a predicted abnormal pump power signal. The predicted abnormal pump power signal is compared with the abnormal motor power signal to calculate a synchronization difference between them. For example, by calculating their difference, a predicted synchronization difference is obtained. This predicted synchronization difference is the ideal synchronization difference obtained based on the first transfer loss power calculation.

[0051] For the synchronization abnormality signal, the abnormal pump power signal and the abnormal motor power signal are compared to calculate the synchronization difference between them. For example, by calculating their difference, the synchronization difference is obtained. This synchronization difference is the difference caused by power loss in actual circumstances.

[0052] According to the actual application scenario and specific needs, a preset threshold value of the synchronization difference is generated. For example, within ±2% of the predicted synchronization difference is an acceptable range. The synchronization difference is compared with the predicted synchronization difference. When the preset threshold value is not met, it indicates that there is a first transmission abnormality, that is, the synchronization between the motor output and the power obtained by the pump is not as expected, and the abnormal power is output as the first transmission abnormal power.

[0053] The first abnormal transmission power and the second abnormal transmission power are identified by using a power coupling model, and a first life prediction result is output.

[0054] A power coupling model is trained, which can learn the characteristics and abnormal patterns of the system based on sample data of the first abnormal power and the second abnormal power. When training the model, the first abnormal power and the second abnormal power are used as input parameters, and identification information of the life attenuation degree and information about the coupling coordination degree between the first vacuum pump and the second vacuum pump are identified. Among them, the life attenuation degree is used to measure the degree of reduction in the life of the system over time, which is related to the increase in abnormal power here, indicating that the system may be approaching the end of its life.

[0055] The predicted first and second abnormal transmission powers are input into a trained power coupling model. Based on the abnormal patterns in the learned historical samples, the model compares the input abnormal power with the normal power range learned by the model to identify whether the input abnormal power exceeds the normal range. Based on the model's identification results, a first life decay degree and a second life decay degree are output. The first and second life decay degrees are coupled based on the coupling coordination degree to output a first life prediction result.

[0056] The above methods can help detect system problems early, take maintenance measures in advance, and extend the service life of the equipment.

[0057] Furthermore, using a power coupling model to identify the first abnormal transmission power and the second abnormal transmission power further includes:

[0058] Training a power coupling model, the power coupling model including a first abnormal power transmission sample, a second abnormal power transmission sample, identification information identifying a life attenuation degree, and a coupling coordination degree between the first vacuum pump and the second vacuum pump;

[0059] Inputting the first abnormal transmission power and the second abnormal transmission power into the power coupling model to obtain a first lifetime decay degree and a second lifetime decay degree;

[0060] The first lifetime decay degree and the second lifetime decay degree are coupled using the coupling coordination degree, and a first lifetime prediction result is output.

[0061] First and second abnormal power transmission samples are collected. These samples contain abnormal power conditions recorded during actual operation, as well as information indicating lifespan degradation, including equipment operating time and usage conditions. The coupling coordination factor is introduced into the model as a parameter that represents the coupling relationship between the first and second vacuum pumps.

[0062] Determine the structure of the power coupling model, such as a neural network. Using the prepared training data, train the model using an iterative optimization algorithm, such as gradient descent. During training, the model adjusts parameters to best fit the relationship between abnormal power samples and lifetime decay. After training, use a validation set to evaluate model performance. Based on the validation results, adjust and optimize the model, including adjusting the model structure and tuning hyperparameters, to ensure that the model accurately predicts lifetime decay.

[0063] The resulting power coupling model is a mathematical model that can be constructed based on a neural network to describe the relationship between abnormal power and life attenuation. It also takes into account the coupling relationship between the first vacuum pump and the second vacuum pump. This model can be used to predict the life attenuation based on the recorded abnormal power conditions, thereby enabling the prediction of system life.

[0064] The first and second abnormal power transfers are used as inputs to the model. These two inputs reflect the abnormal power conditions between the pump and motor in the system. Using the trained power coupling model, the input abnormal power data is substituted into the model. Based on the input abnormal power data and the weights and coordination parameters learned during the training phase, the model calculates the first and second life decay degrees. These decay degrees represent the relative degree of system life decay.

[0065] The first and second life decay degrees are coupled and calculated using the coupling coordination formula. The resulting coupled life decay degree is used as the first life prediction result. This result reflects the life status of the entire system, taking into account the coordination relationship between the first and second vacuum pumps. The coupling coordination degree allows for a more accurate estimation of the system's life status, ensuring that the prediction results are more consistent with actual operating conditions.

[0066] Furthermore, the coupling coordination expression in the power coupling model is as follows:

[0067] ;

[0068] in, Abnormal power for the first transmission and the second transfer abnormal power The coupling coordination degree is , Abnormal power for the first transmission and the second transfer abnormal power The coupling degree, , , The first abnormal power is and the second transfer abnormal power proportion.

[0069] is the coupling coordination degree, which indicates the first abnormal power transmission and the second transfer abnormal power The coordination degree between them is a quantity with a value between 0 and 1, which is used to measure the degree of coupling between two abnormal power transmissions; is the coupling degree, indicating the first abnormal power transmission and the second transfer abnormal power The coupling degree is calculated as , that is, the coupling degree is determined according to the ratio of the product and sum of the two abnormal powers, and this value reflects the mutual relationship between the abnormal powers; and are the proportions of the first and second transmission abnormal powers, respectively, and they represent the contribution ratio of their respective abnormal powers to the total coordination degree.

[0070] In summary, this expression describes the calculation of the coupling coordination between two transmitted abnormal powers, taking into account the coupling degree and their respective proportions. This expression can evaluate the degree of coordination between two abnormal powers while taking multiple factors into consideration, thereby making a more accurate life prediction.

[0071] Furthermore, the method comprises:

[0072] obtaining an asynchronous abnormal signal based on the synchronous abnormal signal of the abnormal pump power signal and the abnormal motor power signal;

[0073] acquiring, according to the asynchronous abnormality signal, a first pump abnormality indicator based on the first vacuum pump and a first motor abnormality indicator of the first motor;

[0074] Acquire a second pump abnormality indicator and a second motor abnormality indicator;

[0075] Obtaining a second life prediction result by using the first pump abnormality indicator and the first motor abnormality indicator, and the second pump abnormality indicator and the second motor abnormality indicator;

[0076] The first life prediction result is adjusted according to the second life prediction result.

[0077] Based on the synchronous abnormal signal, the asynchronous part is detected, which means that the pump power has changed, but the motor power has not changed accordingly, or vice versa, an asynchronous abnormal signal is obtained. The asynchronous abnormal signal indicates that the abnormal changes between the pump and the motor are no longer synchronized, which indicates that there may be some problems, such as damage to specific parts of the pump or motor or other abnormal conditions in the system.

[0078] The asynchronous abnormal signal is analyzed in depth, including signal processing and pattern recognition, to determine the type and characteristics of the abnormality. The asynchronous abnormal signal is then correlated with the first vacuum pump and the first motor to determine which parts of the abnormal signal are related to the first vacuum pump and which are related to the first motor. Based on the correlation results, abnormality indicators related to the first vacuum pump and the first motor are extracted. These abnormality indicators include the specific pattern, frequency, amplitude, and other characteristics of the abnormality, which are used to describe the abnormality. The extracted abnormality indicators are output as output, representing the abnormal conditions of the first vacuum pump and the first motor, respectively.

[0079] The second pump abnormality index and the second motor abnormality index are obtained in the same way.

[0080] The first pump anomaly indicator and the first motor anomaly indicator are combined to form a first set of anomaly indicators. The second pump anomaly indicator and the second motor anomaly indicator are combined to form a second set of anomaly indicators. Using these two sets of anomaly indicators, a life prediction model is trained. This model can be a machine learning model or a neural network model. During training, known life decay data can be used to adjust model parameters. The coupling coordination between the first vacuum pump and the second vacuum pump can also be used for training, enabling accurate prediction of component life.

[0081] The first pump anomaly indicator and the first motor anomaly indicator are input into the trained model to obtain a third life decay degree. The second pump anomaly indicator and the second motor anomaly indicator are input into the trained model to obtain a fourth life decay degree. The third and fourth life decay degrees are coupled using the coupling coordination degree to obtain a second life prediction result. This result is an estimated lifespan that reflects the component's health status and possible life decay trends.

[0082] The first and second life prediction results are compared to examine their consistency and discrepancies, including comparing life estimates and life decay trends. Based on the comparison results, the second life prediction result is used to adjust the first life prediction result, including increasing or decreasing the life estimate and adjusting the decay trend. The adjusted first life prediction result is output. This adjusted result more accurately reflects the life status of the components in the system, taking into account the information from the second life prediction. This adjustment can be based on a comprehensive consideration of multiple life prediction results to improve the overall prediction accuracy and reliability.

[0083] Furthermore, the method further comprises:

[0084] detecting a real-time transmission loss power of a connection structure between the first vacuum pump and the first motor;

[0085] determining whether a power difference between the real-time transfer loss power and the first transfer loss power is greater than a preset power difference, and if so, obtaining a third life prediction result based on the real-time transfer loss power;

[0086] The first life prediction result is adjusted according to the third life prediction result.

[0087] A power acquisition device is used to acquire power signals of the first vacuum pump and the first motor in real time. Based on the first vacuum pump power signal and the first motor power signal acquired in real time, the real-time transfer loss power is obtained by calculating the difference between the real-time motor power and the real-time pump power. The obtained real-time transfer loss power reflects the actual situation of transfer loss in the system.

[0088] The real-time transfer loss power and the first transfer loss power are obtained, and the power difference between them is calculated through difference calculation. A preset power difference threshold is set, which is determined based on system requirements, performance standards, or empirical values. The selection of the preset power difference threshold represents the tolerance for abnormal conditions. A determination is made as to whether the power difference between the real-time transfer loss power and the first transfer loss power is greater than the preset power difference threshold. If so, it indicates that the transfer loss in the system has significantly changed, possibly indicating an abnormal condition. Based on the real-time transfer loss power, a third life prediction result is obtained. This result is obtained using a method similar to the previous life prediction method to more accurately reflect the current health of the system.

[0089] The third life prediction result is used to adjust the first life prediction result, including increasing or decreasing the life estimate, adjusting the attenuation trend, etc., and outputting the adjusted first life prediction result. By adjusting the first life prediction result to better reflect the health status and life prediction of the system, such adjustment helps to improve the accuracy of life prediction and the effectiveness of system maintenance.

[0090] In summary, the life prediction method and system based on power analysis of a dry vacuum pump group provided by the embodiments of the present application have the following technical effects:

[0091] 1. By collecting the power signals of the first vacuum pump and the second vacuum pump, as well as the power signals of the motors connected to them, comprehensive collection and analysis of the power of the entire system is achieved;

[0092] 2. Combine the power signals of different pumps and motors into a first group and a second group of signals. By predicting these two groups of signals, it is possible to identify abnormal power transmission between the motor and the pump in advance;

[0093] 3. Introducing a power coupling model for analysis, this model can more accurately identify the first and second abnormal power transmissions, thereby improving the accuracy of fault diagnosis;

[0094] 4. Through the above steps, the method finally outputs the prediction results of the system life, providing timely early warning information for maintenance personnel, helping to take preventive maintenance measures, extend equipment life, and improve system reliability and stability.

[0095] In summary, the life prediction method based on power analysis of dry vacuum pump groups effectively improves the accuracy and reliability of system life prediction through comprehensive power acquisition and precise analysis.

[0096] Example 2

[0097] Based on the same inventive concept as the life prediction method based on power analysis of dry vacuum pump group in the above embodiment, Figure 2As shown, the present application provides a life prediction system based on power analysis of a dry vacuum pump group, the system comprising:

[0098] A vacuum pump acquisition module 10 is used to acquire a dry vacuum pump group, wherein the dry vacuum pump group includes a first vacuum pump and a second vacuum pump, and the first vacuum pump and the second vacuum pump operate in combination;

[0099] a pump power signal acquisition module 20, configured to acquire a first pump power signal set and a second pump power signal set of the first vacuum pump and the second vacuum pump respectively through a power acquisition device;

[0100] a motor power signal acquisition module 30, configured to acquire a first motor power signal of a first motor and a second motor power signal of a second motor, wherein the first motor is connected to the first vacuum pump and the second motor is connected to the second vacuum pump;

[0101] The abnormal power transmission acquisition module 40 is configured to predict the first pump power signal set and the first motor power signal as a first signal group, and the second pump power signal set and the second motor power signal as a second signal group, to obtain a first abnormal power transmission and a second abnormal power transmission between the motor and the pump;

[0102] The life prediction result acquisition module 50 is used to identify the first abnormal transmission power and the second abnormal transmission power by using a power coupling model, and output a first life prediction result.

[0103] Furthermore, the abnormal power transmission acquisition module 40 further includes the following operation steps:

[0104] Acquire a connection structure between the first vacuum pump and the first motor, wherein the connection structure includes a structure between a rotor of the first vacuum pump and an output shaft of the first motor;

[0105] Acquire a connection structure between the second vacuum pump and the second motor, wherein the connection structure includes a structure between a rotor of the second vacuum pump and an output shaft of the second motor;

[0106] generating a first transmission loss power and a second transmission loss power according to a connection structure between the first vacuum pump and the first motor, and a connection structure between the second vacuum pump and the second motor;

[0107] predicting the first group of signals based on the first transmission loss power and outputting a first transmission abnormality power;

[0108] The second group of signals is predicted based on the second transmission loss power, and a second transmission abnormality power is output.

[0109] Furthermore, the system further includes a first abnormal power transmission output module to perform the following operation steps:

[0110] Identifying a first pump power signal in the first group of signals to obtain an abnormal pump power signal, wherein the abnormal pump power signal is an abnormal power signal in which the power of the first vacuum pump during operation is greater than a preset load power;

[0111] Identifying a first motor power signal in the first group of signals to obtain an abnormal motor power signal, wherein the abnormal motor power signal is an abnormal power signal in which the power of the first motor during operation is greater than a preset load power;

[0112] obtaining a synchronous abnormality signal based on the abnormal pump power signal and the abnormal motor power signal;

[0113] Performing a prediction based on the first transmission loss power to obtain a predicted synchronization difference between the abnormal pump power signal and the abnormal motor power signal;

[0114] A first transmission abnormality power is output according to the synchronization difference degree of the synchronization abnormality signal.

[0115] Furthermore, the system further includes a first adjustment module to perform the following operation steps:

[0116] obtaining an asynchronous abnormal signal based on the synchronous abnormal signal of the abnormal pump power signal and the abnormal motor power signal;

[0117] acquiring, according to the asynchronous abnormality signal, a first pump abnormality indicator based on the first vacuum pump and a first motor abnormality indicator of the first motor;

[0118] Acquire a second pump abnormality indicator and a second motor abnormality indicator;

[0119] Obtaining a second life prediction result by using the first pump abnormality indicator and the first motor abnormality indicator, and the second pump abnormality indicator and the second motor abnormality indicator;

[0120] The first life prediction result is adjusted according to the second life prediction result.

[0121] Furthermore, the system further includes a second adjustment module to perform the following operation steps:

[0122] detecting a real-time transmission loss power of a connection structure between the first vacuum pump and the first motor;

[0123] determining whether a power difference between the real-time transfer loss power and the first transfer loss power is greater than a preset power difference, and if so, obtaining a third life prediction result based on the real-time transfer loss power;

[0124] The first life prediction result is adjusted according to the third life prediction result.

[0125] Furthermore, the system further includes an abnormal power identification module to perform the following operation steps:

[0126] Training a power coupling model, the power coupling model including a first abnormal power transmission sample, a second abnormal power transmission sample, identification information identifying a life attenuation degree, and a coupling coordination degree between the first vacuum pump and the second vacuum pump;

[0127] Inputting the first abnormal transmission power and the second abnormal transmission power into the power coupling model to obtain a first lifetime decay degree and a second lifetime decay degree;

[0128] The first lifetime decay degree and the second lifetime decay degree are coupled using the coupling coordination degree, and a first lifetime prediction result is output.

[0129] Furthermore, the coupling coordination expression in the power coupling model is as follows:

[0130] ;

[0131] in, Abnormal power for the first transmission and the second transfer abnormal power The coupling coordination degree is , Abnormal power for the first transmission and the second transfer abnormal power The coupling degree, , , The first abnormal power is and the second transfer abnormal power proportion.

[0132] Through the detailed description of the life prediction method based on power analysis of a dry vacuum pump group in the foregoing specification, those skilled in the art can clearly understand the life prediction system based on power analysis of a dry vacuum pump group in this embodiment. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the description of the method part.

[0133] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present application. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application is not limited to the embodiments shown herein, but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A life prediction method based on power analysis of dry vacuum pump groups, characterized in that: The method comprises: Obtain a dry vacuum pump assembly, the dry vacuum pump assembly comprising a first vacuum pump and a second vacuum pump, wherein the first vacuum pump and the second vacuum pump operate in combination; respectively acquiring a first pump power signal set and a second pump power signal set of the first vacuum pump and the second vacuum pump through a power acquisition device; collecting a first motor power signal of a first motor and a second motor power signal of a second motor, wherein the first motor is connected to the first vacuum pump and the second motor is connected to the second vacuum pump; The first pump power signal set and the first motor power signal are used as a first group of signals, and the second pump power signal set and the second motor power signal are used as a second group of signals for prediction, to obtain a first abnormal transmission power and a second abnormal transmission power of power transmission between the motor and the pump; The first abnormal transmission power and the second abnormal transmission power are identified by using a power coupling model, and a first life prediction result is output.

2. The method according to claim 1, wherein Acquiring a first abnormal transmission power and a second abnormal transmission power of power transmission between the motor and the pump, the method comprising: Acquire a connection structure between the first vacuum pump and the first motor, wherein the connection structure includes a structure between a rotor of the first vacuum pump and an output shaft of the first motor; Acquire a connection structure between the second vacuum pump and the second motor, wherein the connection structure includes a structure between a rotor of the second vacuum pump and an output shaft of the second motor; generating a first transmission loss power and a second transmission loss power according to a connection structure between the first vacuum pump and the first motor, and a connection structure between the second vacuum pump and the second motor; predicting the first group of signals based on the first transmission loss power and outputting a first transmission abnormality power; The second group of signals is predicted based on the second transmission loss power, and a second transmission abnormality power is output.

3. The method according to claim 2, wherein Predicting the first group of signals based on the first transmission loss power and outputting a first transmission abnormality power, the method comprising: Identifying a first pump power signal in the first group of signals to obtain an abnormal pump power signal, wherein the abnormal pump power signal is an abnormal power signal in which the power of the first vacuum pump during operation is greater than a preset load power; Identifying a first motor power signal in the first group of signals to obtain an abnormal motor power signal, wherein the abnormal motor power signal is an abnormal power signal in which the power of the first motor during operation is greater than a preset load power; obtaining a synchronous abnormality signal based on the abnormal pump power signal and the abnormal motor power signal; Predicting based on the first transmission loss power to obtain a predicted abnormal pump power signal, obtaining a predicted synchronization difference between the predicted abnormal pump power signal and the abnormal motor power signal, and obtaining a synchronization difference between the abnormal pump power signal and the abnormal motor power signal; A first transmission abnormality power is outputted according to the synchronization difference degree and the predicted synchronization difference degree of the synchronization abnormality signal.

4. The method according to claim 3, wherein The method comprises: obtaining an asynchronous abnormal signal based on the synchronous abnormal signal of the abnormal pump power signal and the abnormal motor power signal; acquiring, according to the asynchronous abnormality signal, a first pump abnormality indicator based on the first vacuum pump and a first motor abnormality indicator of the first motor; Acquire a second pump abnormality indicator and a second motor abnormality indicator; Obtaining a second life prediction result by using the first pump abnormality indicator and the first motor abnormality indicator, and the second pump abnormality indicator and the second motor abnormality indicator; The first life prediction result is adjusted according to the second life prediction result.

5. The method according to claim 3, wherein The method further comprises: detecting a real-time transmission loss power of a connection structure between the first vacuum pump and the first motor; determining whether a power difference between the real-time transfer loss power and the first transfer loss power is greater than a preset power difference, and if so, obtaining a third life prediction result based on the real-time transfer loss power; The first life prediction result is adjusted according to the third life prediction result.

6. The method according to claim 1, wherein Using a power coupling model, identifying the first abnormal transmission power and the second abnormal transmission power, the method further includes: Training a power coupling model, the power coupling model including a first abnormal power transmission sample, a second abnormal power transmission sample, identification information identifying a life attenuation degree, and information on a coupling coordination degree between the first vacuum pump and the second vacuum pump; Inputting the first abnormal transmission power and the second abnormal transmission power into the power coupling model to obtain a first lifetime decay degree and a second lifetime decay degree; The first lifetime decay degree and the second lifetime decay degree are coupled using the coupling coordination degree, and a first lifetime prediction result is output.

7. The method according to claim 3, wherein The coupling coordination expression in the power coupling model is as follows: ； in, Abnormal power for the first transmission and the second transfer abnormal power The coupling coordination degree is , Abnormal power for the first transmission and the second transfer abnormal power The coupling degree, , , The first transmission abnormal power and the second transfer abnormal power proportion.

8. The life prediction system based on power analysis of dry vacuum pump group is characterized by: The method for predicting the life of a dry vacuum pump group based on power analysis according to any one of claims 1 to 7 comprises: A vacuum pump acquisition module, wherein the vacuum pump acquisition module is used to acquire a dry vacuum pump group, wherein the dry vacuum pump group includes a first vacuum pump and a second vacuum pump, wherein the first vacuum pump and the second vacuum pump operate in combination; a pump power signal acquisition module, configured to acquire a first pump power signal set and a second pump power signal set of the first vacuum pump and the second vacuum pump, respectively, through a power acquisition device; a motor power signal acquisition module, the motor power signal acquisition module being configured to acquire a first motor power signal of a first motor and a second motor power signal of a second motor, wherein the first motor is connected to the first vacuum pump, and the second motor is connected to the second vacuum pump; a transmission abnormal power acquisition module, the transmission abnormal power acquisition module being configured to predict the first pump power signal set and the first motor power signal as a first group of signals, and the second pump power signal set and the second motor power signal as a second group of signals, to acquire a first transmission abnormal power and a second transmission abnormal power of power transmission between the motor and the pump; The life prediction result acquisition module is used to use a power coupling model to identify the first abnormal transmission power and the second abnormal transmission power, and output a first life prediction result.

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