CN117605660A - Dynamic energy-saving control method and system for air compressor - Google Patents
Dynamic energy-saving control method and system for air compressor Download PDFInfo
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Classifications
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F04—POSITIVE - DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS FOR LIQUIDS OR ELASTIC FLUIDS
- F04B—POSITIVE-DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS
- F04B49/00—Control, e.g. of pump delivery, or pump pressure of, or safety measures for, machines, pumps, or pumping installations, not otherwise provided for, or of interest apart from, groups F04B1/00 - F04B47/00
- F04B49/06—Control using electricity
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F04—POSITIVE - DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS FOR LIQUIDS OR ELASTIC FLUIDS
- F04B—POSITIVE-DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS
- F04B49/00—Control, e.g. of pump delivery, or pump pressure of, or safety measures for, machines, pumps, or pumping installations, not otherwise provided for, or of interest apart from, groups F04B1/00 - F04B47/00
- F04B49/10—Other safety measures
Abstract
The invention discloses a dynamic energy-saving control method and a system of an air compressor, belonging to the field of intelligent control, wherein the method comprises the following steps: generating an air compressor simulation model; the air compressor simulation model is called to carry out load test, and a load monitoring data set and a load energy consumption data set are obtained; grading is carried out, and a plurality of load grades are obtained; respectively carrying out unloading test on the air compressor according to a plurality of load levels to obtain a plurality of unloading energy consumption, and establishing an unloading matching module based on the plurality of unloading energy consumption; acquiring a real-time load data set of a target air compressor to obtain first unloading energy consumption; when the first unloading energy consumption is larger than the preset unloading energy consumption, a first transition instruction is acquired, an unloading control stable curve is generated, and the unloading control stable curve is used for controlling the target air compressor. The method and the device solve the technical problems of low control precision and high operation energy consumption of the air compressor in the prior art, and achieve the technical effects of improving the control precision of the air compressor and dynamically reducing the operation energy consumption.
Description
Technical Field
The invention relates to the field of intelligent control, in particular to a dynamic energy-saving control method and system for an air compressor.
Background
The air compressor is widely applied to industrial production, improves the energy efficiency of the air compressor, reduces the operation energy consumption of the air compressor, is beneficial to saving electric power resources, is beneficial to reducing the production cost and improves the economic benefit. The existing air compressor control method often adopts a constant-rotation-speed running mode, cannot be adjusted according to different air consumption, so that the ineffective energy consumption is increased when the motor of the air compressor idles or the load is frequently changed, the air compressor is in a non-optimal working condition state for a long time, and the running energy consumption is large.
Disclosure of Invention
The application aims to solve the technical problems of low control precision and high operation energy consumption of the air compressor in the prior art by providing the dynamic energy-saving control method and system of the air compressor.
In view of the above problems, the present application provides a dynamic energy-saving control method and system for an air compressor.
In a first aspect of the present disclosure, a dynamic energy-saving control method for an air compressor is provided, where the method includes: performing finite element simulation on a target air compressor to generate an air compressor simulation model; the air compressor simulation model is called to carry out load test, and a load monitoring data set and a load energy consumption data set are obtained; grading is carried out according to the load monitoring data set and the load energy consumption data set, and a plurality of load grades are obtained; the method comprises the steps of calling an air compressor simulation model, respectively carrying out air compressor unloading tests according to a plurality of load levels to obtain a plurality of unloading energy consumption, and establishing an unloading matching module based on the unloading energy consumption, wherein the unloading energy consumption is electric energy consumption caused by the abrupt change process that a target air compressor is loaded from a corresponding load level to a shutdown state; acquiring a real-time load data set of a target air compressor, and inputting the real-time load data set into an unloading matching module to obtain first unloading energy consumption; when the first unloading energy consumption is larger than the preset unloading energy consumption, a first transition instruction is acquired, an unloading control stable curve is generated by utilizing an energy-saving optimizing function according to the first transition instruction, and the target air compressor is controlled by the unloading control stable curve.
In another aspect of the present disclosure, a dynamic energy-saving control system for an air compressor is provided, the system including: the finite element simulation unit is used for carrying out finite element simulation on the target air compressor and generating an air compressor simulation model; the load testing unit is used for calling the air compressor simulation model to carry out load test and obtaining a load monitoring data set and a load energy consumption data set; the grading unit is used for grading according to the load monitoring data set and the load energy consumption data set to obtain a plurality of load grades; the unloading test unit is used for calling the air compressor simulation model, respectively carrying out unloading test on the air compressor according to a plurality of load levels to obtain a plurality of unloading energy consumption, and establishing an unloading matching module based on the unloading energy consumption, wherein the unloading energy consumption is the electric energy consumption caused by the abrupt change process that the target air compressor is loaded from the corresponding load level to the shutdown state; the unloading energy consumption unit is used for acquiring a real-time load data set of the target air compressor, and inputting the real-time load data set into the unloading matching module to obtain first unloading energy consumption; and the air compressor control unit is used for acquiring a first transition instruction when the first unloading energy consumption is larger than the preset unloading energy consumption, generating an unloading control stable curve by using an energy-saving optimizing function according to the first transition instruction, and controlling the target air compressor by using the unloading control stable curve.
One or more technical solutions provided in the present application have at least the following technical effects or advantages:
because the air compressor simulation model is generated aiming at the target air compressor, the simulation test of the running state of the air compressor under different working conditions is convenient under the condition that the air compressor is not actually operated; the method comprises the steps of calling an air compressor simulation model to carry out load test, and obtaining a load monitoring data set and a load energy consumption data set so as to collect operation data of the air compressor under different load conditions; dividing the load state of the air compressor into a plurality of load levels according to the load monitoring data set and the load energy consumption data set, and providing basic information for carrying out unloading test of the air compressor; the air compressor unloading test is respectively carried out according to a plurality of load levels by calling an air compressor simulation model, so that a plurality of unloading energy consumption are obtained, and support is provided for building an unloading matching module; an unloading matching module is established based on unloading energy consumption, so that corresponding unloading energy consumption is obtained according to real-time load, and a basis is provided for dynamically adjusting the air compressor; acquiring a real-time load data set of the air compressor, inputting the real-time load data set into a matching module to obtain first unloading energy consumption, and acquiring a first transition instruction when the first unloading energy consumption is larger than preset unloading energy consumption to generate an unloading control stable curve so as to enable the air compressor to be stably adjusted to an optimal working condition; the target air compressor is controlled by the unloading control stable curve, so that the dynamic energy-saving technical scheme is realized, the technical problems of low air compressor control precision and high operation energy consumption in the prior art are solved, and the technical effects of improving the air compressor control precision and dynamically reducing the operation energy consumption are achieved.
The foregoing description is only an overview of the technical solutions of the present application, and may be implemented according to the content of the specification in order to make the technical means of the present application more clearly understood, and in order to make the above-mentioned and other objects, features and advantages of the present application more clearly understood, the following detailed description of the present application will be given.
Drawings
Fig. 1 is a schematic flow chart of a dynamic energy-saving control method of an air compressor according to an embodiment of the present application;
fig. 2 is a schematic flow chart of controlling a target air compressor by using an unloading secondary stability curve in a dynamic energy-saving control method of the air compressor according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of a dynamic energy-saving control system of an air compressor according to an embodiment of the present application.
Reference numerals illustrate: the device comprises a finite element simulation unit 11, a load test unit 12, a grading unit 13, an unloading test unit 14, an unloading energy consumption unit 15 and an air compressor control unit 16.
Detailed Description
The technical scheme provided by the application has the following overall thought:
the embodiment of the application provides a dynamic energy-saving control method and system for an air compressor. At present, in the operation process of an air compressor, when the air compressor is in idle running, starting and stopping are needed, and frequent starting and stopping can lead to service life attenuation of the air compressor, in order to improve the situation, starting and stopping mode energy consumption under different load conditions is analyzed, firstly, a simulation model is built for a target air compressor, and the model is used for testing and collecting the operation characteristics of the air compressor under different loads, so that the precondition for realizing dynamic energy-saving control is adopted. And then, dividing the running state of the air compressor into a plurality of load levels according to the collected load monitoring and energy consumption data, testing the unloading energy consumption condition of each load level, and establishing an unloading matching module based on the unloading energy consumption data of each load level. And then, monitoring the specific load of the target air compressor in real time, inputting monitoring data into an unloading matching module, matching according to the current load condition to obtain the actual unloading energy consumption, and generating a corresponding unloading control stable curve. And finally, taking the dynamically generated unloading control stable curve as a guide, and adjusting the operation parameters of the air compressor to ensure that the air compressor stably transits to the optimal working condition, thereby achieving the energy-saving control effects of saving energy and reducing cost.
Having described the basic principles of the present application, various non-limiting embodiments of the present application will now be described in detail with reference to the accompanying drawings.
Example 1
As shown in fig. 1, an embodiment of the present application provides a dynamic energy-saving control method for an air compressor, where the method includes:
performing finite element simulation on a target air compressor to generate an air compressor simulation model;
in the embodiment of the application, firstly, a three-dimensional design model of a target air compressor is obtained, wherein the three-dimensional design model refers to a three-dimensional digital model containing geometric structure parameters, fluid simulation parameters and material parameters of the target air compressor; then, the three-dimensional design model is imported into finite element analysis software, inlet and outlet boundary conditions of the air compressor are set, and the boundary conditions comprise parameters including but not limited to inlet total pressure, inlet total temperature, outlet static pressure and the like; then, grid distribution is performed on the imported three-dimensional design model, namely, discretization processing is performed on the three-dimensional digital model, and the three-dimensional digital model is divided into a plurality of small units. Setting solving control parameters, applying boundary conditions, and carrying out numerical simulation on a flow field by adopting a solver to obtain air flow state parameters including but not limited to air flow speed, pressure, temperature and other data; finally, analyzing and visualizing the flow field result by utilizing a post-processing technology to generate a simulation result comprising a speed vector, a streamline and a pressure cloud picture so as to observe flow field information, thereby obtaining an air compressor simulation model.
Invoking the air compressor simulation model to perform load test to obtain a load monitoring data set and a load energy consumption data set;
in the embodiment of the application, first, according to the actual use condition of the air compressor, a plurality of typical load working conditions are set, wherein the load working conditions comprise parameters such as inlet and outlet pressure, motor rotation speed and the like. And then, calling the established three-dimensional simulation model of the air compressor, applying different load working conditions one by one, and simulating the running process of the air compressor under each working condition. In the simulation process, multiple operation parameters such as flow, pressure, speed, temperature and the like of the air compressor under different load working conditions are recorded to form a load monitoring data set. Meanwhile, the input power of the air compressor under different load working conditions is counted, the product of the power and the time is calculated to be used as energy consumption by combining the operation time, and the energy consumption value under each load working condition is obtained to form a load energy consumption data set.
Load testing is carried out by calling the air compressor simulation model, so that a load monitoring data set and a load energy consumption data set of the air compressor under a plurality of load working conditions are obtained, and a data source is provided for subsequent load matching modeling.
Grading according to the load monitoring data set and the load energy consumption data set to obtain a plurality of load grades;
in the embodiment of the application, firstly, a load monitoring data set and a load energy consumption data set are loaded, and the data set is preprocessed, including outlier removal, normalization and the like. Then, setting parameters of a clustering algorithm, including the number k of clusters, namely the dividing number of load levels, a centroid initial value and the like. Then, a clustering algorithm, such as a K-means algorithm, is selected, and the load monitoring data set is classified by using the algorithm, so that the category of each load monitoring data is obtained, namely, the automatic classification of different load working conditions is completed. And meanwhile, carrying out corresponding classification on the load energy consumption data sets according to the clustering result of the load monitoring data sets, and determining the energy consumption data corresponding to each load level. And finally, merging the clustering result of the load monitoring data set and the corresponding load energy consumption data, namely obtaining a plurality of load levels aiming at the load of the air compressor, and a load interval and an energy consumption level of each level.
And dividing a plurality of load levels of the load of the air compressor through the load monitoring data set and the load energy consumption data set, and providing support for carrying out the unloading test in a grading manner.
The air compressor simulation model is called, air compressor unloading tests are respectively carried out according to the load levels, a plurality of unloading energy consumption is obtained, and an unloading matching module is built based on the unloading energy consumption, wherein the unloading energy consumption is electric energy consumption caused by the abrupt change process that the target air compressor is loaded from the corresponding load level to the shutdown state;
in the embodiment of the application, first, the determined working conditions of a plurality of load levels are applied to the air compressor simulation model, and the air compressor simulation model is operated to reach a steady state. Then, after the operation of the air compressor simulation model is stable, the operation of the air compressor simulation model is suddenly stopped, so that the air compressor simulation model is directly switched to a stop state from a corresponding load level, and the instantaneous power parameters of the air compressor in the process are recorded. And then, calculating the total amount of electric energy consumed by the air compressor in the transition process from the operation steady state to the complete stop state of the air compressor simulation model, and taking the total amount of electric energy as the unloading energy consumption under the load level. And repeating the process, and carrying out corresponding air compressor unloading tests on all load levels to obtain a plurality of unloading energy consumption.
Then, recording data in an unloading test of the air compressor, and constructing a training sample set; using a support vector machine, taking load data in a training sample set as input, unloading energy consumption as output, training an unloading matching model, and adopting cross verification to ensure the generalization performance of the model; and (3) adjusting the algorithm super-parameters, optimizing and unloading the matching model by adopting methods such as grid search, random search and the like, and improving the prediction precision. And then, establishing a prediction interface, and packaging the optimized unloading energy consumption model into a module to obtain an unloading matching module so as to receive the load data in real time and return to predicting the unloading energy consumption.
According to the unloading energy consumption data of the air compressor under various load conditions, an unloading energy consumption prediction model is trained and optimized, the establishment of an unloading matching module is realized, and support is provided for energy saving control.
Acquiring a real-time load data set of the target air compressor, and inputting the real-time load data set into the unloading matching module to obtain first unloading energy consumption;
in the embodiment of the application, a flow measuring instrument is arranged in an inlet pipeline and an outlet pipeline of the target air compressor and is connected with a sensor, so that inlet and outlet flow of the target air compressor is monitored in real time. And then, calculating the real-time load rate of the air compressor by the ratio of the flow, and determining a real-time load data set of the target air compressor by combining parameters such as the rotating speed, the pressure ratio and the like of the air compressor. And then, carrying out preprocessing such as smoothing filtering, format conversion and the like on the collected real-time load data set. And then, inputting the processed real-time load data set into an established unloading matching module according to a certain time interval and a data format. And the unloading matching module is used for providing support for unloading control according to the unloading energy consumption, namely the first unloading energy consumption, obtained by matching simulation under the real-time load by utilizing the input real-time load data set.
Firstly, presetting a maximum unloading energy consumption value allowed by an air compressor as preset unloading energy consumption. And then judging whether the first unloading energy consumption output by the unloading matching module is larger than the preset unloading energy consumption or not. When the first unloading energy consumption is greater than the preset unloading energy consumption, a first transition instruction is generated, an unloading control stable curve is generated by utilizing an energy-saving optimizing function according to the first transition instruction, and the unloading control stable curve is sent to a dynamic energy-saving control system for triggering the unloading control of the air compressor.
The expression of the energy-saving optimizing function is as follows:
；
wherein,first unloading energy consumption obtained by matching under real-time load data set of target air compressor>Optimizing the gradient in the descending direction of 0>Representing instantaneous energy consumption vector, reflecting energy consumption change trend of air compressor from current load to no load,/->And->Respectively representing the corresponding loss function values during the ith and the (i+1) th recursion optimization in the optimizing process,/and%>For the energy saving index based on the instantaneous energy consumption vector, such as the energy consumption reduction amount, the energy efficiency ratio lifting value and the like, n represents the number of recursion optimization.
The optimization objective of the energy-saving optimizing function is to enable the first unloading energy consumptionSuccessive approximation of 0 indicates that the unloading process is more energy efficient. And finding out the solution with the minimum loss function by recursively calculating the accumulated sum of the loss functions, thereby obtaining the dynamic energy-saving unloading control stable curve. Through the energy-saving optimizing function, the load state, the service life state of a unit component and the energy-saving requirement of the target air compressor can be fully considered, and the dynamic optimizing control of the unloading process is realized.
And after receiving the first transition instruction, the dynamic energy-saving control system extracts a real-time load data set of the current load state. And then, utilizing the real-time load data set as an initial value, and obtaining an unloading control stable curve according to the historical operation data of the target air compressor. And equally dividing the unloading control stable curve into a plurality of time periods, and planning the control quantity of the target air compressor to each part in each time period according to the curve, wherein the control quantity comprises the rotating speed, the air inlet power and the like. And then, outputting a control instruction to the target air compressor through the PLC, adjusting the opening of the valve, gradually unloading the target air compressor according to the instruction, and completely stopping the target air compressor after the load is reduced to the minimum, so as to complete the unloading control, realize the stable transition from the load state to the unloading state, and achieve the aim of energy conservation.
Further, as shown in fig. 2, the embodiment of the present application further includes:
when the first unloading energy consumption is smaller than or equal to the preset unloading energy consumption, acquiring a unit component life index of the target air compressor;
carrying out unloading risk identification according to the service life index of the unit component and the first unloading energy consumption, and obtaining a first abnormal probability, wherein the first abnormal probability is used for representing the instantaneous abnormal risk of each component based on the first unloading energy consumption;
and when the first abnormal probability meets the preset abnormal probability, generating a first early warning signal, generating an unloading secondary stable curve according to the first early warning signal, and controlling the target air compressor by the unloading secondary stable curve.
In one possible embodiment, sensors are provided on each component of the same type of air compressor, such as an air filter, an air intake pipe, a compressor, a motor, etc., and each component operating parameter is collected in real time, and the collected operating data includes, but is not limited to, pressure, temperature, vibration, rotation speed, current, etc., and reflects the loss condition of the component. Then, data cleaning and calibration are carried out on the collected operation parameters, a relation model between the operation parameters and the service life of the unit components is established, for example, the increase of the pressure drop of the filter indicates the service time of the filter; an increase in motor current represents an increase in losses. When the first unloading energy consumption is less than or equal to the preset unloading energy consumption, the operation parameters acquired for the unit components of the target air compressor are brought into the correlation model, the loss degree of each unit component is evaluated, and the unit component service life index of the target air compressor is generated.
The crew life index and the first unloading energy consumption are then input into a pre-set unloading risk assessment model, which model principle is that the worse the crew condition, the greater the risk of experiencing an energy consumption impact. And integrating the life index of the unit components and the unloading energy consumption through an unloading risk assessment model, judging the abnormal probability of each unit component under the influence of given energy consumption, and obtaining a first abnormal probability which represents the unloading risk of each component based on the first unloading energy consumption.
And then, when the obtained first abnormal probability is higher than the preset abnormal probability, indicating that a certain risk exists in the unloading process of the target air compressor, generating a first abnormal early warning signal at the moment, and sending the first abnormal early warning signal to the dynamic energy-saving control system for reminding the possible unloading risk. After the dynamic energy-saving control system receives the first abnormal early warning signal, according to possible unloading risks, an unloading secondary stable curve is generated, wherein the stable curve is gentle and gentle compared with a normal unloading curve, and damage to a unit component caused by too fast unloading is prevented, and in a preferred embodiment:
acquiring an abnormal probability difference between the first abnormal probability and a preset abnormal probability; based on the energy-saving optimizing function, the step length of gradient descent of the unloading control stable curve is obtained, the step length of gradient descent of the unloading secondary stable curve is adjusted according to abnormal probability difference, wherein the step length of gradient descent of the unloading secondary stable curve is smaller than or equal to the step length of gradient descent of the unloading control stable curve, then a control instruction is sent to the target air compressor, so that the target air compressor performs relatively gentle unloading according to the unloading secondary stable curve, mechanical stress and energy consumption impact are reduced to the maximum extent, faults are prevented, and when the pressure is reduced to the minimum, the target air compressor is completely stopped, the assessment of the sudden unloading risk of the air compressor and corresponding protection control are realized, and the safety and the intelligence of the air compressor control are improved.
Further, the embodiment of the application further includes:
the air compressor simulation model is called, air compressor loading tests are respectively carried out according to the load levels, so that multiple loading energy consumption is obtained, and a loading matching module is built based on the multiple loading energy consumption, wherein the loading energy consumption is electric energy consumption caused by the abrupt change process that the target air compressor is loaded from a stop state to a corresponding load level;
acquiring a target loading data set of the target air compressor, and inputting the target loading data set into the loading matching module to obtain first loading energy consumption;
and when the first loading energy consumption is larger than the preset loading energy consumption, acquiring a second transition instruction, generating a loading control stable curve according to the second transition instruction, and controlling the target air compressor by using the loading control stable curve.
In a preferred embodiment, first, according to an established air compressor simulation model, a plurality of load simulation tests are performed on the air compressor simulation model based on a plurality of load classes. And loading the air compressor simulation model in a corresponding load level under the stop state of the air compressor, and then directly enabling the air compressor to enter a starting-up mode until the air compressor simulation model stably operates. In the loading test process, parameters such as motor input power, stable duration and the like of the air compressor are recorded, and the total energy consumption from no load to loaded is obtained. And repeating the process to obtain loading energy consumption data of loading working conditions corresponding to each load level, and obtaining a plurality of loading energy consumption. Then, recording data in the loading test of the air compressor, and constructing a training sample set; the neural network is adopted, loading data in a training sample set is taken as input, loading energy consumption is taken as output, and a loading energy consumption prediction model is trained; and the super parameters of the algorithm are adjusted, and the methods such as cross verification and the like are used to improve the model prediction precision. And establishing a prediction interface, and packaging the optimized loading energy consumption prediction model into a module to obtain a loading matching module so as to receive loading data in real time and return predicted loading energy consumption.
And then, acquiring loading data of the target air compressor in real time through a sensor arranged on the target air compressor to obtain a target loading data set. And then, converting the target loading data set into an input format of the loading matching module, and carrying out data normalization processing. And inputting the processed target loading data set into a loading matching module. And the loading matching module obtains a predicted energy consumption value under the loading condition, namely the first loading energy consumption, through forward calculation of the module according to the input data.
And then presetting a maximum loading energy consumption threshold allowed by the target air compressor, namely presetting loading energy consumption. And comparing the first loading energy consumption obtained by the loading matching module through prediction with the preset loading energy consumption, and sending a second transition instruction to the dynamic energy-saving control system when the first loading energy consumption is larger than the preset loading energy consumption. And after receiving the second transition instruction, the dynamic energy-saving control system generates an optimal loading curve, namely a loading control stable curve, according to the current loading state so as to enable the target air compressor to realize loading under the minimum energy consumption. Then, the loading control stable curve is converted into control quantity of each control element of the target air compressor, and the control output is carried out through a PLC (programmable logic controller) and the like, so that the target air compressor is loaded according to an optimal loading track, and energy consumption impact caused by rapid loading is avoided.
Further, the embodiment of the application further includes:
if the loading and unloading energy-saving control module receives a first loading instruction or a first unloading instruction, acquiring the loading and unloading frequency of the target air compressor;
judging whether the loading and unloading frequency is larger than or equal to a preset frequency, and acquiring a loading control stable curve corresponding to the first loading instruction or an unloading control stable curve corresponding to the first unloading instruction when the loading and unloading frequency is smaller than the preset frequency.
In one possible implementation manner, a loading and unloading frequency counter is set in the loading and unloading energy-saving control module of the target air compressor. When the loading and unloading energy-saving control module receives a first loading instruction or a first unloading instruction of the target air compressor in real time, triggering the loading and unloading frequency counter to count, and accumulating the loading instruction frequency and the unloading instruction frequency. At the same time, a counting period, such as 1 hour or 1 work shift, etc., is set. And when the counting time period is over, obtaining the total loading and unloading times in the time period, and calculating the ratio of the total loading and unloading times to the counting time period to obtain the loading and unloading frequency.
And then presetting a maximum allowable loading and unloading frequency value of the target air compressor according to experience, and taking the maximum allowable loading and unloading frequency value as a preset frequency. Comparing the obtained loading and unloading frequency with a preset frequency, and judging that the loading and unloading frequency of the target air compressor is normal when the loading and unloading frequency is smaller than the preset frequency. At this time, the loading control stable curve corresponding to the first loading instruction or the first unloading instruction is called and is used as the control quantity output of the target air compressor to implement the loading and unloading process. By limiting and controlling the loading and unloading frequency of the target air compressor, risks under abnormal loading and unloading conditions are prevented, and safe and reliable operation of the air compressor is ensured.
Further, the embodiment of the application further includes:
when the loading and unloading frequency is greater than or equal to the preset frequency, generating air pressure fault reminding information, and sending a maintenance instruction to an air pressure control module of the target air compressor according to the air pressure fault reminding information;
and carrying out abnormal positioning on the air pressure sensing data in the air pressure control module according to the maintenance instruction, overhauling according to an abnormal positioning result, and uploading an overhauling result to the loading and unloading energy-saving control module after overhauling is finished.
In a possible implementation manner, the obtained loading and unloading frequency is compared with a preset frequency, when the loading and unloading frequency is greater than or equal to the preset frequency, the air pressure of the target air compressor is judged to have faults, and corresponding air pressure fault reminding information such as 'air channel blockage' and the like is generated at the moment. Then, analyzing the air pressure fault reminding information, making a maintenance scheme for the corresponding fault information in the air pressure fault reminding information, and sending the maintenance scheme to an air pressure control module integrated with the target air compressor in a maintenance instruction mode.
After receiving the maintenance instruction, the air pressure control module carries out self diagnosis on the air pressure sensor and detects real-time data of the sensor; if the sensing data is abnormal, judging that the sensor is faulty, and replacing and maintaining the sensor; if the sensor works normally and the fluctuation of the detected pressure data is too large, the pipeline is judged to be blocked, the pipeline is checked, the blocking position is positioned, and the dredging is performed. After the maintenance work is completed, uploading the overhaul result to the loading and unloading energy-saving control module. Wherein the service report contains the failure point and the processing result, such as "replace intake air pressure sensor", etc.
Further, the embodiment of the application further includes:
after acquiring the service life index of the unit component of the target air compressor, generating an instantaneous energy consumption vector according to the service life index of the unit component of the target air compressor;
and constructing an energy-saving optimizing function by taking the real-time load data set as a starting point and the instantaneous energy consumption vector as a step length, carrying out gradient descent optimizing on the energy-saving optimizing function, obtaining a recursive coordinate set, and drawing the unloading control stable curve according to the recursive coordinate set.
In a preferred embodiment, after the current unit component life index of the target air compressor is acquired, a mathematical model is built according to each unit component life index to calculate the theoretical energy consumption level of the current target air compressor, namely the theoretical total energy consumption of the target air compressor in the process of running to complete stop under the current unit component state. And then, on the basis of obtaining the energy consumption level of the target air compressor at the current moment, predicting the theoretical energy consumption level of the air compressor at a plurality of subsequent sampling moments (for example, 10 sampling moments), and forming a theoretical energy consumption change trend vector from the current state of the air compressor to the complete stop state, wherein the theoretical energy consumption change trend vector reflects the influence of the state of a unit component in the current target air compressor on energy consumption and is an instantaneous energy consumption vector.
Then, an energy-saving optimizing function with the aim of minimizing the unloading total energy consumption is established, wherein the optimizing function takes a real-time load data set of the target air compressor at the current moment as a starting point and takes an instantaneous energy consumption vector as a step length. And then, carrying out iterative optimization on the optimizing function by utilizing a gradient descent algorithm, gradually approaching the global minimum value to obtain a series of recursion calculated intermediate load coordinate points, and forming a recursion coordinate set. And sequentially connecting the intermediate load coordinate points obtained by the recursive calculation to form an unloading control stable curve in the unloading control process, and guiding the unloading process of the target air compressor by taking the stable curve as a control curve to realize accurate control and energy-saving optimization.
In summary, the dynamic energy-saving control method for the air compressor provided by the embodiment of the application has the following technical effects:
finite element simulation is carried out on the target air compressor, and an air compressor simulation model is generated, so that the simulation of the running state of the target air compressor under different working conditions is facilitated under the condition that the air compressor is not actually operated; and (3) calling an air compressor simulation model to perform load test, obtaining a load monitoring data set and a load energy consumption data set, and providing data support for modeling. And grading is carried out according to the load monitoring data set and the load energy consumption data set, a plurality of load grades are obtained, and the load conditions are graded, so that the unloading matching modules aiming at different loads are conveniently established. And calling an air compressor simulation model, respectively carrying out air compressor unloading tests according to a plurality of load levels to obtain a plurality of unloading energy consumption, and establishing an unloading matching module based on the unloading energy consumption, wherein the unloading energy consumption is electric energy consumption caused by the abrupt change process of loading the target air compressor from the corresponding load level to the shutdown state, and is used for matching the real-time load condition to realize optimal unloading control. And acquiring a real-time load data set of the target air compressor, and inputting the real-time load data set into an unloading matching module to obtain first unloading energy consumption, thereby providing a basis for subsequent unloading control. When the first unloading energy consumption is larger than the preset unloading energy consumption, a first transition instruction is acquired, an unloading control stable curve is generated according to the first transition instruction, the target air compressor is controlled by the unloading control stable curve, and dynamic energy-saving control of the air compressor is achieved.
Example two
Based on the same inventive concept as the dynamic energy-saving control method of an air compressor in the foregoing embodiments, as shown in fig. 3, an embodiment of the present application provides a dynamic energy-saving control system of an air compressor, where the system includes:
the finite element simulation unit 11 is used for performing finite element simulation on the target air compressor to generate an air compressor simulation model;
the load testing unit 12 is used for calling the air compressor simulation model to perform load testing to obtain a load monitoring data set and a load energy consumption data set;
a grading unit 13, configured to grade according to the load monitoring data set and the load energy consumption data set, and obtain a plurality of load grades;
the unloading test unit 14 is configured to invoke the air compressor simulation model, perform unloading tests on the air compressors according to the multiple load levels, obtain multiple unloading energy consumption, and establish an unloading matching module based on the multiple unloading energy consumption, where the unloading energy consumption is electric energy consumption caused by a sudden change process that the target air compressor is loaded from the corresponding load level to a shutdown state;
the unloading energy consumption unit 15 is configured to obtain a real-time load data set of the target air compressor, and input the real-time load data set into the unloading matching module to obtain a first unloading energy consumption;
the air compressor control unit 16 is configured to obtain a first transition instruction when the first unloading energy consumption is greater than a preset unloading energy consumption, generate an unloading control stable curve according to the first transition instruction by using an energy-saving optimizing function, and control the target air compressor with the unloading control stable curve, where an expression of the energy-saving optimizing function is as follows:
；
wherein,representing the first unloading energy consumption obtained by matching under the real-time load data set of the target air compressor, and enabling +.>Optimizing the gradient in the descending direction of 0>Representing instantaneous energy consumption vector, ">Loss data for the ith recursion when gradient falls,>loss data for the (i+1) th recursion at gradient descent, +.>And n is the number of recursions for the energy saving index corresponding to the instantaneous energy consumption vector.
Further, the air compressor control unit 16 includes the following execution steps:
acquiring a unit component life index of the target air compressor, and generating an instantaneous energy consumption vector according to the unit component life index of the target air compressor;
and constructing an energy-saving optimizing function by taking the real-time load data set as a starting point and the instantaneous energy consumption vector as a step length, carrying out gradient descent optimizing on the energy-saving optimizing function, obtaining a recursive coordinate set, and drawing the unloading control stable curve according to the recursive coordinate set.
Further, the air compressor control unit 16 further includes the following execution steps:
when the first unloading energy consumption is smaller than or equal to the preset unloading energy consumption, acquiring a unit component life index of the target air compressor;
carrying out unloading risk identification according to the service life index of the unit component and the first unloading energy consumption, and obtaining a first abnormal probability, wherein the first abnormal probability is used for representing the instantaneous abnormal risk of each component based on the first unloading energy consumption;
and when the first abnormal probability meets the preset abnormal probability, generating a first early warning signal, generating an unloading secondary stable curve according to the first early warning signal, and controlling the target air compressor by the unloading secondary stable curve.
Further, the air compressor control unit 16 further includes the following execution steps:
acquiring an abnormal probability difference between the first abnormal probability and the preset abnormal probability;
and based on the energy-saving optimizing function, acquiring the step length of the unloading control stable curve for gradient descent, and adjusting the step length of the unloading secondary stable curve for gradient descent according to the abnormal probability difference, wherein the step length of the unloading secondary stable curve for gradient descent is smaller than or equal to the step length of the unloading control stable curve for gradient descent.
Further, the embodiment of the application further comprises a loading test unit, wherein the loading test unit comprises the following execution steps:
the air compressor simulation model is called, air compressor loading tests are respectively carried out according to the load levels, so that multiple loading energy consumption is obtained, and a loading matching module is built based on the multiple loading energy consumption, wherein the loading energy consumption is electric energy consumption caused by the abrupt change process that the target air compressor is loaded from a stop state to a corresponding load level;
acquiring a target loading data set of the target air compressor, and inputting the target loading data set into the loading matching module to obtain first loading energy consumption;
and when the first loading energy consumption is larger than the preset loading energy consumption, acquiring a second transition instruction, generating a loading control stable curve according to the second transition instruction, and controlling the target air compressor by using the loading control stable curve.
Further, the embodiment of the application further includes an instruction processing unit, which includes the following execution steps:
if the loading and unloading energy-saving control module receives a first loading instruction or a first unloading instruction, acquiring the loading and unloading frequency of the target air compressor;
judging whether the loading and unloading frequency is larger than or equal to a preset frequency, and acquiring a loading control stable curve corresponding to the first loading instruction or an unloading control stable curve corresponding to the first unloading instruction when the loading and unloading frequency is smaller than the preset frequency.
Further, the instruction processing unit further includes the following execution steps:
when the loading and unloading frequency is greater than or equal to the preset frequency, generating air pressure fault reminding information, and sending a maintenance instruction to an air pressure control module of the target air compressor according to the air pressure fault reminding information;
and carrying out abnormal positioning on the air pressure sensing data in the air pressure control module according to the maintenance instruction, overhauling according to an abnormal positioning result, and uploading an overhauling result to the loading and unloading energy-saving control module after overhauling is finished.
Any of the steps of the methods described above may be stored as computer instructions or programs in a non-limiting computer memory and may be called by a non-limiting computer processor to identify any of the methods to implement embodiments of the present application, without unnecessary limitations.
Further, the first or second element may not only represent a sequential relationship, but may also represent a particular concept, and/or may be selected individually or in whole among a plurality of elements. It will be apparent to those skilled in the art that various modifications and variations can be made in the present application without departing from the scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the present application and the equivalents thereof, the present application is intended to cover such modifications and variations.
Claims (8)
1. The dynamic energy-saving control method of the air compressor is characterized by comprising the following steps of:
performing finite element simulation on a target air compressor to generate an air compressor simulation model;
invoking the air compressor simulation model to perform load test to obtain a load monitoring data set and a load energy consumption data set;
grading according to the load monitoring data set and the load energy consumption data set to obtain a plurality of load grades;
the air compressor simulation model is called, air compressor unloading tests are respectively carried out according to the load levels, a plurality of unloading energy consumption is obtained, and an unloading matching module is built based on the unloading energy consumption, wherein the unloading energy consumption is electric energy consumption caused by the abrupt change process that the target air compressor is loaded from the corresponding load level to the shutdown state;
acquiring a real-time load data set of the target air compressor, and inputting the real-time load data set into the unloading matching module to obtain first unloading energy consumption;
when the first unloading energy consumption is larger than the preset unloading energy consumption, a first transition instruction is acquired, an unloading control stable curve is generated by using an energy-saving optimizing function according to the first transition instruction, and the target air compressor is controlled by the unloading control stable curve, wherein the expression of the energy-saving optimizing function is as follows:
；
wherein,representing the real-time load data set of the target air compressor obtained by matchingFirst unloading energy consumption, let ∈ ->Optimizing the gradient in the descending direction of 0>Representing instantaneous energy consumption vector, ">Loss data for the ith recursion when gradient falls,>loss data for the (i+1) th recursion at gradient descent, +.>And n is the number of recursions for the energy saving index corresponding to the instantaneous energy consumption vector.
2. The method of claim 1, wherein generating an offload control plateau curve from the first transition instruction, the method further comprises:
acquiring a unit component life index of the target air compressor, and generating an instantaneous energy consumption vector according to the unit component life index of the target air compressor;
and constructing an energy-saving optimizing function by taking the real-time load data set as a starting point and the instantaneous energy consumption vector as a step length, carrying out gradient descent optimizing on the energy-saving optimizing function, obtaining a recursive coordinate set, and drawing the unloading control stable curve according to the recursive coordinate set.
3. The method of claim 2, wherein the method further comprises:
when the first unloading energy consumption is smaller than or equal to the preset unloading energy consumption, acquiring a unit component life index of the target air compressor;
carrying out unloading risk identification according to the service life index of the unit component and the first unloading energy consumption, and obtaining a first abnormal probability, wherein the first abnormal probability is used for representing the instantaneous abnormal risk of each component based on the first unloading energy consumption;
and when the first abnormal probability meets the preset abnormal probability, generating a first early warning signal, generating an unloading secondary stable curve according to the first early warning signal, and controlling the target air compressor by the unloading secondary stable curve.
4. A method as claimed in claim 3, wherein the method further comprises:
acquiring an abnormal probability difference between the first abnormal probability and the preset abnormal probability;
and based on the energy-saving optimizing function, acquiring the step length of the unloading control stable curve for gradient descent, and adjusting the step length of the unloading secondary stable curve for gradient descent according to the abnormal probability difference, wherein the step length of the unloading secondary stable curve for gradient descent is smaller than or equal to the step length of the unloading control stable curve for gradient descent.
5. The method of claim 1, wherein the method further comprises:
the air compressor simulation model is called, air compressor loading tests are respectively carried out according to the load levels, so that multiple loading energy consumption is obtained, and a loading matching module is built based on the multiple loading energy consumption, wherein the loading energy consumption is electric energy consumption caused by the abrupt change process that the target air compressor is loaded from a stop state to a corresponding load level;
acquiring a target loading data set of the target air compressor, and inputting the target loading data set into the loading matching module to obtain first loading energy consumption;
and when the first loading energy consumption is larger than the preset loading energy consumption, acquiring a second transition instruction, generating a loading control stable curve according to the second transition instruction, and controlling the target air compressor by using the loading control stable curve.
6. The method of claim 5, wherein the method further comprises:
if the loading and unloading energy-saving control module receives a first loading instruction or a first unloading instruction, acquiring the loading and unloading frequency of the target air compressor;
judging whether the loading and unloading frequency is larger than or equal to a preset frequency, and acquiring a loading control stable curve corresponding to the first loading instruction or an unloading control stable curve corresponding to the first unloading instruction when the loading and unloading frequency is smaller than the preset frequency.
7. The method of claim 6, wherein when the loading and unloading frequency is greater than or equal to the preset frequency, generating air pressure fault reminding information, and sending a maintenance instruction to an air pressure control module of the target air compressor according to the air pressure fault reminding information;
and carrying out abnormal positioning on the air pressure sensing data in the air pressure control module according to the maintenance instruction, overhauling according to an abnormal positioning result, and uploading an overhauling result to the loading and unloading energy-saving control module after overhauling is finished.
8. A dynamic energy-saving control system for an air compressor, for implementing the dynamic energy-saving control method for an air compressor according to any one of claims 1 to 7, the system comprising:
the finite element simulation unit is used for carrying out finite element simulation on the target air compressor and generating an air compressor simulation model;
the load test unit is used for calling the air compressor simulation model to carry out load test and acquiring a load monitoring data set and a load energy consumption data set;
the grading unit is used for grading according to the load monitoring data set and the load energy consumption data set to obtain a plurality of load grades;
the unloading test unit is used for calling the air compressor simulation model, respectively carrying out unloading test on the air compressors according to the load levels to obtain a plurality of unloading energy consumption, and establishing an unloading matching module based on the unloading energy consumption, wherein the unloading energy consumption is the electric energy consumption caused by the abrupt change process of loading the target air compressor from the corresponding load level to the shutdown state;
the unloading energy consumption unit is used for acquiring a real-time load data set of the target air compressor, and inputting the real-time load data set into the unloading matching module to obtain first unloading energy consumption;
the air compressor control unit is used for acquiring a first transition instruction when the first unloading energy consumption is larger than a preset unloading energy consumption, generating an unloading control stable curve by using an energy-saving optimizing function according to the first transition instruction, and controlling the target air compressor by using the unloading control stable curve, wherein the expression of the energy-saving optimizing function is as follows:
；
wherein,representing the first unloading energy consumption obtained by matching under the real-time load data set of the target air compressor, and enabling +.>Optimizing the gradient in the descending direction of 0>Representing instantaneous energy consumption vector, ">Loss data for the ith recursion when gradient falls,>loss for the (i+1) th recursion at gradient descentData,/->And n is the number of recursions for the energy saving index corresponding to the instantaneous energy consumption vector.
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