Life prediction method and system based on power analysis of dry vacuum pump set

Abstract

The invention provides a life prediction method and system based on dry vacuum pump set power analysis, and relates to the technical field of power analysis, and the method comprises the steps: obtaining a dry vacuum pump set which comprises a first vacuum pump and a second vacuum pump; respectively acquiring a first pump power signal set and a second pump power signal set; collecting a first motor power signal and a second motor power signal; predicting by 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 obtain first transmission abnormal power and second transmission abnormal power; and performing identification by using the power coupling model, and outputting a first life prediction result. The method solves the technical problems that a traditional method cannot effectively predict a potential fault or a life end point, and the accuracy and reliability of system life prediction are low due to the fact that the abnormal condition of power transmission between the motor and the pump is not accurately identified.

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 state leads to difficulties in life prediction using existing technologies. 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 in system life prediction. Summary of the invention

[0003] The present application provides a life prediction method and system based on power analysis of a dry vacuum pump group, aiming to solve the technical problems that the life prediction method of a traditional 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.

[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 working 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, and obtaining a first transmission abnormal power and a second transmission abnormal power of power transmission between the motor and the pump; using a power coupling model to identify the first transmission abnormal power and the second transmission abnormal power, and outputting 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 is used for the above method, and the system includes: a vacuum pump acquisition module, the vacuum pump acquisition module is used to acquire a dry vacuum pump group, 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 work in combination; a pump power signal acquisition module, the pump power signal acquisition module is used to respectively acquire 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; a motor power signal acquisition module, the motor power signal acquisition module is used to acquire a first motor power signal of a first motor, and a second motor power signal of a 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 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 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: By collecting the power signals of the first vacuum pump and the second vacuum pump, as well as the power signals of the motor connected thereto, the power of the entire system is fully collected and analyzed; the power signals of different pumps and motors are combined into the first group and the second group of signals, and the abnormal power of power transmission between the motor and the pump is recognized in advance by predicting these two groups of signals; the power coupling model is introduced for analysis, and the model can more accurately identify the first abnormal power transmission and the second abnormal power transmission, thereby improving the accuracy of fault diagnosis; through the above steps, the method finally outputs the prediction result of the system life, provides timely early warning information for maintenance personnel, helps to take preventive maintenance measures, prolong the equipment life, and improve the reliability and stability of the system. In summary, the life prediction method based on the power analysis of the dry vacuum pump group effectively improves the accuracy and reliability of the system life prediction through comprehensive power collection and precise analysis.

[0008] 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

[0009] 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; Figure 2 A schematic diagram of the structure of a life prediction system based on power analysis of a dry vacuum pump group is provided for an embodiment of the present application.

[0010] 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

[0011] The embodiment of the present application provides 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.

[0012] After introducing the basic principles of the present application, various non-limiting implementation methods of the present application will be specifically described below in conjunction with the drawings in the specification.

[0013] Embodiment 1 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: Obtain a dry vacuum pump group, wherein the dry vacuum pump group comprises a first vacuum pump and a second vacuum pump, wherein the first vacuum pump and the second vacuum pump operate in combination; The first vacuum pump is a Roots vacuum pump, which is a screw or gear type vacuum pump used for high vacuum or large flow applications. It consists of two intermeshing spiral blades or gears, and generates vacuum by rotation; the second vacuum pump is a dry pump, which refers to a vacuum pump that does not use liquid sealing fluid, and uses mechanical, sliding or rotary technology to remove gas, and is suitable for applications that require a dry and clean environment. The first vacuum pump and the second vacuum pump are combined together through mechanical connections, pipeline connections, etc., to work together and maintain the required vacuum level in the entire system.

[0014] 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; Select a power collection device suitable for the vacuum pump, which can measure and record the power output of the vacuum pump. Install the power collection device in the power circuit of the first vacuum pump and the second vacuum pump respectively. First, start the first vacuum pump to put it in working state. Through the power collection device, collect the power signal of the first vacuum pump in real time, including parameters such as current, voltage and power factor. The power signal is a signal reflecting the power consumption of the equipment when working. Record it continuously to obtain the power signal set of the first vacuum pump. Then start the second vacuum pump and collect the power signal set of the second pump in the same way.

[0015] 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 motor is an electric motor used to drive the vacuum pump to operate. It connects the first motor and the first vacuum pump to ensure that mechanical and electrical connections are 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 to run 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.

[0016] 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.

[0017] 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, so as to obtain a first abnormal transmission power and a second abnormal transmission power of power transmission between the motor and the pump; 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.

[0018] 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 are predicted based on the first transfer loss power, and a first transfer abnormal power is output, and the second group of signals are predicted based on the second transfer loss power, and a second transfer abnormal power is output, the abnormal power represents an abnormal power change in the system, and here, it reflects the abnormal power transmission between the motor and the vacuum pump.

[0019] The predicted abnormal power can be used to correlate the power transfer process between the motor and the vacuum pump. The abnormal power may indicate an abnormal working state between the motor and the pump. For example, a degradation in the performance of the vacuum pump may result in an abnormal increase in the motor power. Based on the correlation between the increase in motor power and the decrease in vacuum pump power, it can be inferred that the abnormal power may result in a decrease in the life of the motor because it reflects the existence of certain abnormalities or faults in the system.

[0020] Further, obtaining a first abnormal power and a second abnormal power of power transmission between the motor and the pump includes: Acquire a connection structure between the first vacuum pump and the first motor, wherein the connection structure includes a structure composed of 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 composed of 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 abnormal power; The second group of signals is predicted based on the second transmission loss power, and a second transmission abnormality power is output.

[0021] Determine the connection points between the first vacuum pump and the first motor, including the rotor of the vacuum pump and the output shaft of the motor, where the rotor refers to the rotating part in the first vacuum pump used to generate vacuum, which can be a spiral blade or other structure; the output shaft refers to the shaft in the first motor, which transmits power to the connected device, i.e., the first vacuum pump, through the operation of the motor. Determine how the connection structure connects the rotor of the first vacuum pump to the output shaft of the first motor, including threaded connection, keyway connection, etc., and record these detailed information for subsequent analysis.

[0022] In the same way, the component structure between the second vacuum pump and the second motor is obtained.

[0023] Transfer loss power refers to the power loss caused by the connection structure and mechanical transmission during the energy transfer process 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, which can be determined by experimental measurement 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.

[0024] 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.

[0025] In the same way, the second transmission loss power of the second vacuum pump and the second motor is calculated. 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 that the power of the first vacuum pump during operation is greater than the 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 that the power of the first motor during operation is greater than the preset load power. Based on the abnormal pump power signal and the abnormal motor power signal, a synchronization abnormality signal is obtained, and 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, and the first transmission abnormal power is output according to the synchronization difference of the synchronization abnormality signal.

[0026] The second transmission abnormal power is obtained in the same way.

[0027] Further, predicting the first group of signals based on the first transmission loss power and outputting a first transmission abnormal power includes: Identify the 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; Identify the 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; Based on the abnormal pump power signal and the abnormal motor power signal, obtaining a synchronous abnormal signal; Performing a prediction based on the first transmission loss power, obtaining a predicted synchronization difference between the abnormal pump power signal and the abnormal motor power signal; A first transmission abnormality power is output according to the synchronization difference degree of the synchronization abnormality signal.

[0028] The power level of the first vacuum pump is obtained according to equipment specifications, manufacturer data or historical performance data, and then the preset load power of the first vacuum pump when the system is operating normally is determined. During the operation of the first vacuum pump, the first pump power signal and the preset load power are compared 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.

[0029] The first motor power signal is identified in the same way to obtain an abnormal motor power signal.

[0030] The abnormal pump power signal and the abnormal motor power signal are aligned on the time axis to ensure that the correlation between the two can accurately reflect the impact of pump power changes on motor power. By aligning the time axis, the abnormal pump power signal and the abnormal motor power signal are synchronously processed to generate a synchronous abnormal signal, which reflects the synchronous change of motor power when the pump power increases, and it captures the correlation and synchronization between the two.

[0031] The first transfer loss power calculated previously is used to calculate the loss of the abnormal motor power signal to obtain a predicted abnormal pump power signal. The predicted 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 to obtain the predicted synchronization difference, which is the difference obtained under ideal conditions according to the first transfer loss power calculation.

[0032] For the abnormal synchronization 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 situations.

[0033] 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, and 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.

[0034] 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.

[0035] A power coupling model is trained, and the model can learn the characteristics and abnormal patterns of the system according to the sample data of the first abnormal power transferred and the second abnormal power transferred. When training the model, the first abnormal power transferred and the second abnormal power transferred 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, wherein 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.

[0036] The predicted first abnormal power and second abnormal power are input into the trained power coupling model. The model is based on the abnormal pattern in the learned historical samples. By comparing the input abnormal power with the normal power range learned by the model, it is identified whether the input abnormal power exceeds the normal range. According to the recognition result of the model, the first life decay degree and the second life decay degree are output. The first life decay degree and the second life decay degree are coupled based on the coupling coordination degree, and the first life prediction result is output.

[0037] The above methods can help detect system problems early, take maintenance measures in advance, and extend the service life of the equipment.

[0038] Furthermore, using the power coupling model to identify the first abnormal transmission power and the second abnormal transmission power also includes: Training a power coupling model, wherein the power coupling model includes a first abnormal power transmission sample, a second abnormal power transmission sample, identification information identifying a life attenuation degree, and training acquisition of 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 life decay degree and a second life decay degree; The first life decay degree and the second life decay degree are coupled with the coupling coordination degree, and a first life prediction result is output.

[0039] The first transmission abnormal power samples and the second transmission abnormal power samples are collected. These samples contain abnormal power conditions recorded in actual operation, and at the same time, the identification information of the life attenuation degree is identified, including the equipment operation time, use conditions, etc. The coupling coordination degree is introduced into the model as a parameter to represent the coupling relationship between the first vacuum pump and the second vacuum pump.

[0040] Determine the structure of the power coupling model, such as a neural network structure. Use the prepared training data to train the model through an iterative optimization algorithm, such as gradient descent. During the training process, the model will try to adjust the parameters to best fit the relationship between abnormal power samples and life decay. After training, use the validation set to evaluate the performance of the model. Adjust and optimize the model based on the validation results, including adjusting the model structure, hyperparameter tuning, etc., to ensure that the model can accurately predict life decay.

[0041] The obtained 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. Through this model, the life attenuation degree can be predicted based on the recorded abnormal power conditions, thereby realizing the prediction of system life.

[0042] The first abnormal power of transmission and the second abnormal power of transmission are used as the input of the model. These two inputs reflect the abnormal power situation between the pump and the motor in the system. Using the trained power coupling model, the input abnormal power data is substituted into the model. The model calculates the first life attenuation degree and the second life attenuation degree according to the input abnormal power data and the weight and coordination parameters learned in the training stage. These attenuation degrees represent the relative attenuation degree of the system life.

[0043] The first life decay degree and the second life decay degree are coupled and calculated using the coupling coordination degree formula to obtain the coupled life decay degree, which is used as the first life prediction result. This result reflects the life state of the entire system and takes into account the coordination relationship between the first vacuum pump and the second vacuum pump. Through the coupling coordination degree, the life state of the system can be estimated more accurately, making the prediction result more consistent with the actual operation.

[0044] Furthermore, 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 abnormal power is and the second transfer abnormal power proportion.

[0045] is the coupling coordination degree, indicating 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 transmission abnormal power and the second transmission abnormal power, respectively, and they represent the contribution ratio of each abnormal power in the total coordination degree.

[0046] In summary, this expression describes the calculation of the coupling coordination between the two transmitted abnormal powers, taking into account their coupling degree and their respective proportions. This expression can evaluate the degree of coordination between the two abnormal powers while taking multiple factors into consideration, thereby making a more accurate life prediction.

[0047] Furthermore, the method comprises: Based on the synchronous abnormal signal of the abnormal pump power signal and the abnormal motor power signal, an asynchronous abnormal signal is obtained; Acquire a first pump abnormality index based on the first vacuum pump and a first motor abnormality index of the first motor according to the asynchronous abnormality signal; 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.

[0048] On the basis of 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.

[0049] The asynchronous abnormal signal is deeply analyzed, including signal processing and pattern recognition, to determine the type and characteristics of the abnormality, and the asynchronous abnormal signal is associated 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 association results, the abnormal indicators related to the first vacuum pump and the abnormal indicators related to the first motor are extracted. These abnormal indicators include the specific mode, frequency, amplitude, etc. of the abnormality, which are used to describe the characteristics of the abnormality. The extracted abnormal indicators are used as output to represent the abnormal conditions of the first vacuum pump and the first motor respectively.

[0050] The second pump abnormality index and the second motor abnormality index are obtained in the same way.

[0051] The first pump abnormality indicator and the first motor abnormality indicator are integrated together to form a first group of abnormality indicators, and the second pump abnormality indicator and the second motor abnormality indicator are integrated together to form a second group of abnormality indicators. Using these two groups of abnormality indicators, a life prediction model is trained. This model can be a machine learning model or a neural network model. During the training, known life decay data can be used to adjust the model parameters, and the coupling coordination degree between the first vacuum pump and the second vacuum pump is used for training, so that it can accurately predict the life of the component.

[0052] The first pump abnormality index and the first motor abnormality index are input into the trained model to obtain the third life decay degree, and the second pump abnormality index and the second motor abnormality index are input into the trained model to obtain the fourth life decay degree. The third life decay degree and the fourth life decay degree are coupled with the coupling coordination degree to obtain the second life prediction result, which is an estimated value of the life, reflecting the health status of the component and the possible life decay trend.

[0053] Compare the first life prediction result and the second life prediction result to check the consistency and difference between them, including comparing the estimated value of life, life decay trend, etc. Based on the comparison result, use the second life prediction result to adjust the first life prediction result, including increasing or decreasing the estimated value of life, adjusting the decay trend, etc. Output the adjusted first life prediction result, which can more accurately reflect the life status of the components in the system, while taking into account the information of the second life prediction. This adjustment can be based on the comprehensive consideration of multiple life prediction results to improve the overall prediction accuracy and credibility.

[0054] Furthermore, the method further comprises: Detecting 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 according to the real-time transfer loss power; The first life prediction result is adjusted according to the third life prediction result.

[0055] 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.

[0056] The real-time transmission loss power and the first transmission loss power are obtained, and the power difference between them is calculated by difference calculation. A preset power difference threshold is set, and the threshold is set according to system requirements, performance standards or experience values. The selection of the preset power difference threshold represents the tolerance for abnormal conditions. It is determined whether the power difference between the real-time transmission loss power and the first transmission loss power is greater than the preset power difference threshold. If it is greater than the threshold, it means that the transmission loss in the system has changed significantly, and there may be an abnormal situation. According to the real-time transmission loss power, a third life prediction result is obtained, which is obtained by using a method similar to the previous life prediction to more accurately reflect the current health status of the system.

[0057] 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 the adjusted first life prediction result is output. 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.

[0058] In summary, the life prediction method and system based on power analysis of a dry vacuum pump group provided in the embodiments of the present application have the following technical effects: 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 thereto, comprehensive collection and analysis of the power of the entire system is achieved; 2. Combine the power signals of different pumps and motors into the first group and the second group of signals, and realize the early identification of abnormal power transmission between the motor and the pump by predicting these two groups of signals; 3. The power coupling model is introduced for analysis, which can more accurately identify the first transmission abnormal power and the second transmission abnormal power, thereby improving the accuracy of fault diagnosis; 4. Through the above steps, the method finally outputs the prediction results of the system life, provides timely early warning information for maintenance personnel, helps to take preventive maintenance measures, prolong the life of equipment, and improve the reliability and stability of the system.

[0059] 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 collection and precise analysis.

[0060] Embodiment 2 Based on the same inventive concept as the life prediction method based on power analysis of the dry vacuum pump group in the aforementioned embodiment, Figure 2 As shown, the present application provides a life prediction system based on power analysis of a dry vacuum pump group, the system comprising: A vacuum pump acquisition module 10, wherein the 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, wherein the first vacuum pump and the second vacuum pump operate in combination; A pump power signal acquisition module 20, the pump power signal acquisition module 20 is used to respectively acquire 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; a motor power signal acquisition module 30, the motor power signal acquisition module 30 is used 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; The abnormal power transmission acquisition module 40 is used 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 abnormal power transmission and a second abnormal power transmission of power between the motor and the pump; 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.

[0061] Furthermore, the abnormal transmission power acquisition module 40 further includes the following operation steps: Acquire a connection structure between the first vacuum pump and the first motor, wherein the connection structure includes a structure composed of 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 composed of 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 abnormal power; The second group of signals is predicted based on the second transmission loss power, and a second transmission abnormality power is output.

[0062] Furthermore, the system further comprises a first abnormal power transmission output module to perform the following operation steps: Identify the 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; Identify the 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; Based on the abnormal pump power signal and the abnormal motor power signal, obtaining a synchronous abnormal signal; Performing a prediction based on the first transmission loss power, obtaining a predicted synchronization difference between the abnormal pump power signal and the abnormal motor power signal; A first transmission abnormality power is output according to the synchronization difference degree of the synchronization abnormality signal.

[0063] Furthermore, the system further includes a first adjustment module to perform the following operation steps: Based on the synchronous abnormal signal of the abnormal pump power signal and the abnormal motor power signal, an asynchronous abnormal signal is obtained; Acquire a first pump abnormality index based on the first vacuum pump and a first motor abnormality index of the first motor according to the asynchronous abnormality signal; 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.

[0064] Furthermore, the system further includes a second adjustment module to perform the following operation steps: Detecting 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 according to the real-time transfer loss power; The first life prediction result is adjusted according to the third life prediction result.

[0065] Furthermore, the system further includes an abnormal power identification module to perform the following operation steps: Training a power coupling model, wherein the power coupling model includes a first abnormal power transmission sample, a second abnormal power transmission sample, identification information identifying a life attenuation degree, and training acquisition of 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 life decay degree and a second life decay degree; The first life decay degree and the second life decay degree are coupled with the coupling coordination degree, and a first life prediction result is output.

[0066] Furthermore, 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 abnormal power is and the second transfer abnormal power proportion.

[0067] Through the aforementioned detailed description of the life prediction method based on power analysis of a dry vacuum pump group in this 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.

[0068] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those 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 will not be limited to the embodiments shown herein, but will 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 a dry vacuum pump group, characterized in that: The method comprises: Obtain a dry vacuum pump group, wherein the dry vacuum pump group comprises a first vacuum pump and a second vacuum pump, wherein the first vacuum pump and the second vacuum pump operate in combination; 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; 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, so as 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, characterized in that Acquiring a first abnormal transmission power and a second abnormal transmission power of power transmission between a motor and a pump, the method comprising: Acquire a connection structure between the first vacuum pump and the first motor, wherein the connection structure includes a structure composed of 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 composed of 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 abnormal 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, characterized in that The first group of signals is predicted based on the first transmission loss power, and a first transmission abnormal power is output, the method comprising: Identify the 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; Identify the 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; Based on the abnormal pump power signal and the abnormal motor power signal, obtaining a synchronous abnormal signal; Performing a prediction based on the first transmission loss power, obtaining a predicted synchronization difference between the abnormal pump power signal and the abnormal motor power signal; A first transmission abnormality power is output according to the synchronization difference degree of the synchronization abnormality signal.

4. The method according to claim 3, characterized in that The method comprises: Based on the synchronous abnormal signal of the abnormal pump power signal and the abnormal motor power signal, an asynchronous abnormal signal is obtained; Acquire a first pump abnormality index based on the first vacuum pump and a first motor abnormality index of the first motor according to the asynchronous abnormality signal; 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, characterized in that The method further comprises: Detecting 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 according to 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, characterized in that Using a power coupling model, identifying the first abnormal transfer power and the second abnormal transfer power, the method further includes: Training a power coupling model, wherein the power coupling model includes a first abnormal power transmission sample, a second abnormal power transmission sample, identification information identifying a life attenuation degree, and training acquisition of 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 life decay degree and a second life decay degree; The first life decay degree and the second life decay degree are coupled with the coupling coordination degree, and a first life prediction result is output.

7. The method according to claim 3, characterized in that 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 abnormal power is 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, the pump power signal acquisition module is used to respectively acquire 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; a motor power signal acquisition module, the motor power signal acquisition module being used 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 is used 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 the 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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