Air compressor operating environment adaptive adjustment system

Abstract

The present application provides an air compressor operating environment adaptive adjustment system, which relates to the field of air compressor adjustment technology. The system includes: a first dynamic detection module, which is used to obtain first target operating characteristic information; an initial discrimination result acquisition module, which is used to obtain initial discrimination results; a second dynamic monitoring module, which is used to obtain second target operating characteristic information; a weighted analysis module, which is used to obtain a target operating index; an instruction issuing module, which is used to issue an adaptive adjustment instruction; and an adaptive adjustment module, which is used to adaptively adjust the operating environment of the target air compressor according to a predetermined adjustment strategy. Through this application, the technical problem that it is difficult for traditional air compressors to automatically adjust their operating states according to changes in the operating environment, resulting in high energy consumption and unstable performance, can be solved, and adaptive adjustment of the operating environment of the air compressor can be achieved, ensuring that the air compressor can operate stably in different environments, reducing energy consumption and extending the service life.

Description

Technical Field

[0001] The present application relates to the technical field of air compressor regulation, and in particular to an air compressor operating environment adaptive regulation system. Background Art

[0002] With the rapid development of industrial production and the continuous improvement of process technology, the stability and efficiency of the operating environment of air compressors, as important power equipment, have a vital impact on the continuity of the production process and product quality. However, with the continuous expansion of production scale and the increasing complexity of process flow, the monitoring and management of the operating environment of air compressors face unprecedented challenges. When dealing with a changing operating environment, traditional air compressors are unable to adjust their operating status in real time according to changes in environmental parameters. Traditional air compressors often face problems such as high energy consumption and unstable performance, which not only increases the operating costs of enterprises, but may also affect production efficiency and product quality. Summary of the invention

[0003] The purpose of this application is to provide an air compressor operating environment adaptive adjustment system to solve the technical problem of being unable to provide high-reliability data transmission due to the complexity and variability of the communication environment and equipment topology.

[0004] In view of the above problems, the present application provides an air compressor operating environment adaptive adjustment system.

[0005] The present application provides an air compressor operating environment adaptive adjustment system, the system comprising: a first dynamic detection module, used to dynamically detect the air compressor through a multi-probe device to obtain first target operating characteristic information; an initial discrimination result acquisition module, used to input the first target operating characteristic information into an adjustment discriminator to obtain an initial discrimination result, wherein the adjustment discriminator is an intelligent model trained based on the support vector machine principle; a second dynamic monitoring module, used to dynamically monitor the operating state of the air compressor when the initial discrimination result meets the predetermined adjustment constraint to obtain second target operating characteristic information; a weighted analysis module, used to perform weighted analysis on the second target operating characteristic information after normalization to obtain a target operating index; an instruction issuing module, used to issue an adaptive adjustment instruction when the target operating index does not meet the operating index limit; an adaptive adjustment module, used to read a predetermined adjustment strategy based on the adaptive adjustment instruction, and adaptively adjust the operating environment of the air compressor according to the predetermined adjustment strategy.

[0006] The technical solution provided in this application has at least the following technical effects or advantages:

[0007] The above-mentioned air compressor operating environment adaptive adjustment system detects the operating state of the air compressor in real time and dynamically through a multi-probe device, and collects data to obtain the first target operating characteristic information. Subsequently, the collected data is input into the adjustment discriminator for intelligent analysis, and an initial discrimination result is generated, which can determine whether the air compressor needs to be adjusted in some form. If the initial discrimination result shows that the air compressor needs to be adjusted, that is, it meets the predetermined adjustment constraints, the operating state of the air compressor is more deeply dynamically monitored to obtain more refined operating data, that is, the second target operating characteristic information. After that, the second target operating characteristic information is normalized to have a unified metric. Then, by the weighted analysis method, the importance of each parameter is comprehensively considered to calculate a target operating index that can comprehensively reflect the operating status of the air compressor. If the calculated target operating index does not meet the operating index limit, an adaptive adjustment instruction will be issued immediately. Then, according to this instruction, a pre-set adjustment strategy is read, and the operating environment of the air compressor is adaptively adjusted accordingly according to this strategy to ensure that the air compressor can operate in the best state. Through multiple steps such as multi-probe real-time monitoring, intelligent identification, dynamic monitoring, weighted analysis and adaptive adjustment, precise control of the air compressor operating environment can be achieved, ensuring that the air compressor can operate stably in various environments, reduce energy consumption and increase service life.

[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 according to the contents of the specification, and 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 specifically cited below. It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easy to understand through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] In order to more clearly illustrate the technical solutions in the present application or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0010] Figure 1 This is a schematic diagram of the structure of the air compressor operating environment adaptive adjustment system of this application.

[0011] Figure 2 This is a schematic diagram of the process of obtaining the first target operating characteristic information of the air compressor operating environment adaptive adjustment system of the present application.

[0012] Description of reference numerals:

[0013] A first dynamic detection module 1, an initial discrimination result acquisition module 2, a second dynamic monitoring module 3, a weighted analysis module 4, an instruction issuing module 5, and an adaptive adjustment module 6. DETAILED DESCRIPTION

[0014] The present application solves the technical problem that it is difficult for traditional air compressors to automatically adjust their operating states according to changes in the operating environment, resulting in high energy consumption and unstable performance, by providing an air compressor operating environment adaptive adjustment system. This realizes adaptive adjustment of the air compressor operating environment, ensures that the air compressor can operate stably in different environments, reduces energy consumption, and extends its service life.

[0015] Below, the technical solutions in the present application will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments of the present application. It should be understood that the present application is not limited to the example embodiments described herein. Based on the embodiments of the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application. It should also be noted that, for the convenience of description, only the parts related to the present application are shown in the accompanying drawings, rather than all of them.

[0016] Example

[0017] Please refer to the attached Figure 1 The present application provides an air compressor operating environment adaptive adjustment system, the system specifically includes the following modules:

[0018] The first dynamic detection module 1 is used to perform dynamic detection on the air compressor through a multi-probe device to obtain first target operation characteristic information.

[0019] In the embodiment of the present application, in the first dynamic detection module 1, the system terminal dynamically detects the air compressor through a multi-probe device, and acquires and collects a series of key operating parameters in real time, which comprehensively reflect the operating status of the air compressor. Subsequently, the collected operating parameters are summarized to form the first target operating characteristic information. These characteristic information include the viscosity of the lubricating oil, the moisture content in the compressed air, and the blockage rate of the air filter, which provides important data support for subsequent adjustment and control, ensuring that the air compressor can operate in the best state.

[0020] Further, if Figure 2 As shown, the present application provides the multi-probe device including a water content probe, a blockage rate probe and a viscosity probe, which are used for:

[0021] The compressed air in the air compressor is detected by the moisture content detection head to obtain the moisture content of the compressed air; the air filter in the air compressor is detected by the blockage rate detection head to obtain the blockage rate of the air filter; the lubricating oil in the air compressor is detected by the viscosity detection head to obtain the viscosity of the lubricating oil; the moisture content of the compressed air, the blockage rate of the air filter and the viscosity of the lubricating oil together constitute the first target operation characteristic information.

[0022] Preferably, the multi-probe device is specially designed to monitor the operating status of the air compressor in real time. This device contains three types of probes, namely moisture probe, blockage probe and viscosity probe. The moisture probe accurately measures the moisture content of the compressed air in the air compressor and generates the moisture content of the compressed air. This indicator is crucial to ensure the purity and quality of the compressed air, because too high moisture content will not only reduce the quality of the compressed air and affect the use of subsequent processes, but may also cause problems such as rust and icing inside the air compressor. Therefore, monitoring and controlling the moisture content of the compressed air is crucial to ensure the normal operation of the air compressor. The blockage probe detects the air filter of the air compressor and generates the air filter blockage rate. The main function of the air filter is to filter impurities and particulate matter from the air entering the air compressor to prevent them from causing damage to the inside of the air compressor. However, as the use time increases, the filter will gradually become blocked, affecting its filtering effect. By monitoring the blockage rate of the filter, the filter can be discovered and replaced in time to ensure that the air compressor can inhale clean air and maintain normal intake efficiency and performance. The viscosity probe is used to detect the viscosity of the lubricating oil in the air compressor and generate the viscosity of the lubricating oil. The viscosity of the lubricating oil is crucial to ensure that the mechanical parts of the air compressor are well lubricated and reduce wear. By monitoring the viscosity of the lubricating oil, it can be ensured that the air compressor operates in a good lubricated state, reduce the failure rate and extend the service life. The system terminal adds the data generated by the three probes to the first target operation characteristic information. This information provides the system terminal with a comprehensive view of the operating status of the air compressor, allowing precise control and adjustment in the future.

[0023] The initial discrimination result acquisition module 2 is used to input the first target operation characteristic information into the adjustment discriminator to obtain an initial discrimination result, wherein the adjustment discriminator is an intelligent model trained based on the support vector machine principle.

[0024] In one embodiment, in the initial discrimination result acquisition module 2, after the first target operation characteristic information of the air compressor is collected, the system terminal inputs the first target operation characteristic information into the adjustment discriminator for adjustment judgment. The adjustment discriminator is trained based on the support vector machine (SVM), which has powerful data analysis and pattern recognition capabilities. The adjustment discriminator analyzes and judges the input first target operation characteristic information based on the learned knowledge, and generates an initial discrimination result. This initial discrimination result is used to determine whether the current operating state of the air compressor requires some form of adjustment or optimization.

[0025] Furthermore, the present application provides a method for obtaining the adjustment discriminator, comprising:

[0026] Extract a first historical adjustment record from the historical air compressor adjustment records, where the first historical adjustment record refers to any environmental adaptive historical adjustment record of the first air compressor; perform machine learning on first training data consisting of first operating characteristic information and a first adjustment or not identification of the first air compressor in the first historical adjustment record to obtain the adjustment discriminator.

[0027] Preferably, in order to train the adjustment discriminator, the system terminal extracts the first historical adjustment record from the historical air compressor adjustment record of the first air compressor, and the first historical adjustment record is any environmental adaptive historical adjustment record of the first air compressor. This record contains the first operating characteristic information and the first adjustment or not mark of the first air compressor under specific environmental conditions. This first adjustment or not mark is a label used to identify whether the first air compressor has performed environmental adaptive adjustment. This mark is a binary value used to represent two states of yes or no. Subsequently, the system terminal constructs an adjustment discriminator based on the principle of support vector machine. Support vector machine is an effective supervised learning algorithm, which is particularly suitable for binary classification problems. Then, a part of the training data constructed by the first operating characteristic information and the first adjustment or not mark is divided as test data. Afterwards, the first operating characteristic information of the first air compressor in the training data is used as input data, and the corresponding first adjustment or not mark is used as the target output. Then, the input operating characteristic information and label data are trained using the support vector machine algorithm. During the training process, the support vector machine algorithm will look for a hyperplane that can separate different types of data, that is, data that needs to be adjusted and data that does not need to be adjusted. Then, by adjusting the parameters of the support vector machine, such as the penalty coefficient C, the type of kernel function, etc., the classification performance of the adjustment discriminator is gradually optimized. After the training is completed, the system terminal uses the test data to evaluate the adjustment discriminator and calculates the evaluation indicators such as accuracy, recall rate, and F1 score. Then compare the calculated evaluation indicators with the preset indicators to determine whether the adjustment discriminator meets the requirements. If not, reselect the hyperparameters such as the penalty coefficient and kernel function, and use the training data to train again. Otherwise, the current adjustment discriminator is output. Through this process, the adjustment discriminator can learn the law of whether the air compressor needs to be adjusted under similar operating characteristic information, and quickly give the initial judgment result of whether it needs to be adjusted.

[0028] The second dynamic monitoring module 3 is used to dynamically monitor the operating state of the air compressor to obtain second target operating characteristic information when the initial discrimination result meets the predetermined adjustment constraint.

[0029] In one embodiment, in the second dynamic monitoring module 3, when the initial discrimination result obtained by the adjustment discriminator meets the preset adjustment constraint condition, that is, when the initial discrimination result is that adjustment is required, the system terminal will enter the dynamic monitoring stage. During the dynamic monitoring process, the system terminal will collect the operating data of the air compressor in real time according to the predetermined characteristic indicators, and summarize these data into the second target operating characteristic information. This second target operating characteristic information includes various performance indicators of the air compressor related to energy consumption and efficiency. Through real-time tracking and analysis of this information, the operating status of the air compressor can be more accurately grasped, and more accurate adjustment decisions can be made accordingly.

[0030] Furthermore, the present application provides obtaining the second target operation characteristic information, including:

[0031] The predetermined characteristic index is read, and the operating state of the air compressor is dynamically monitored based on the predetermined characteristic index to obtain the second target operating characteristic information, wherein the predetermined characteristic index includes unit energy consumption and operating efficiency.

[0032] Preferably, when monitoring the operating status of the air compressor, the system terminal first reads a predetermined characteristic index as a reference standard. These predetermined characteristic indicators are set to evaluate the performance and efficiency of the air compressor, including unit energy consumption and operating efficiency, which can directly reflect the operating status of the air compressor. Among them, the unit energy consumption measures the amount of energy consumed by the air compressor for each unit of work produced during operation. Low unit energy consumption means that the air compressor has a higher energy utilization rate and is more energy-saving. Operating efficiency reflects the ability of the air compressor to complete operating tasks within a given time. High-efficiency air compressors can complete more work tasks in a shorter time and improve production efficiency. During the dynamic monitoring process, the system terminal will collect data related to these predetermined characteristic indicators in real time, and summarize these data to obtain the second target operating characteristic information. This information can intuitively display the current operating status of the air compressor, including whether its unit energy consumption and operating efficiency have reached the predetermined standards, which helps to accurately understand the performance and efficiency of the air compressor.

[0033] The weighted analysis module 4 is used to perform weighted analysis on the second target operation characteristic information after normalization to obtain a target operation index.

[0034] In one embodiment, in the weighted analysis module 4, when processing the monitoring data of the operating state of the air compressor, the system terminal extracts the maximum and minimum values ​​of each indicator from the second target operating characteristic information, and then traverses the second target operating characteristic information, performs difference calculation between each traversed indicator data and the corresponding minimum value, and performs ratio calculation between the calculated difference and the difference between the maximum and minimum values ​​of the corresponding indicator. By repeating this process, the system terminal can obtain the normalized second target operating characteristic information to eliminate the differences between different characteristic indicators due to different dimensions or units. After obtaining the normalized second target operating characteristic information, in order to more comprehensively evaluate the operating state of the air compressor, the system terminal assigns different weights to each characteristic indicator according to its importance and relevance. This is set according to actual needs and historical experience. For example, in the scenario of energy saving, the system terminal will assign a higher weight to the indicators related to unit energy consumption and a lower weight to the remaining indicators. After the weight assignment is completed, the system terminal multiplies each indicator data in the normalized second target operating characteristic information by the corresponding weight, and then adds all the products to obtain a comprehensive evaluation value, i.e., the target operating index. The target operation index can reflect the overall operating status of the air compressor. The higher the value, the better the operating status.

[0035] Furthermore, the present application provides for adjusting the target operation index, including:

[0036] Read the predetermined multi-dimensional environmental characteristics, and dynamically monitor the operating environment based on the predetermined multi-dimensional environmental characteristics to obtain target environmental characteristic information, where the operating environment refers to the operating environment of the air compressor; extract the target electromagnetic interference index in the target environmental characteristic information, and adjust the target operating index based on the target electromagnetic interference index.

[0037] Preferably, in order to more accurately evaluate the operating state of the air compressor, the system terminal first reads predetermined multi-dimensional environmental features, which describe multiple aspects of the operating environment of the air compressor, including temperature, humidity, electromagnetic field strength, etc. Subsequently, the system terminal dynamically monitors the operating environment of the air compressor, that is, the actual working environment in which the air compressor is located, based on these multi-dimensional environmental features, obtains environmental feature information corresponding to these multi-dimensional environmental features in real time, and adds these environmental feature information to the target environmental feature information. After obtaining the target environmental feature information, the system terminal extracts the target electromagnetic interference index from the target environmental feature information. This target electromagnetic interference index is collected based on the magnetic field intensity environmental features. When the magnetic field intensity is too large or fluctuates, it will cause magnetic field interference to the air compressor, thereby affecting the power supply stability of the air compressor, and the stability of the power supply is one of the key factors affecting the comprehensive operating index of the air compressor. Unstable power supply may cause unstable operation, reduced efficiency or even damage to the air compressor. In order to more comprehensively and accurately reflect the operating state of the air compressor, the system terminal adjusts the previously calculated target operating index according to the extracted target electromagnetic interference index. The adjustment process is to multiply the target operation index by the target electromagnetic interference index, and then subtract the target operation index from the calculated product. This adjustment is designed to take into account the impact of environmental factors and ensure that the target operation index can more truly reflect the actual operating conditions of the air compressor. In this way, potential operating problems can be discovered in a timely manner and the operating efficiency and reliability of the air compressor can be improved.

[0038] Furthermore, the present application provides that the operating environment includes a plurality of electromagnetic interference sources with location identifiers, which are used to:

[0039] Extract a first electromagnetic interference source from the multiple electromagnetic interference sources with position identifiers, wherein the first electromagnetic interference source has a first interference source position; obtain a first distance from the first interference source position to a target position, wherein the target position refers to the position of the air compressor.

[0040] Optionally, when evaluating the operating environment of the air compressor, an important factor analyzed by the system terminal is electromagnetic interference. This interference comes from multiple different electromagnetic interference sources in the operating environment, and each electromagnetic interference source has a location identifier. These electromagnetic interference sources with location identifiers may have an adverse effect on the normal operation of the air compressor. In order to more accurately evaluate this impact, the system terminal randomly selects one from these electromagnetic interference sources as the first electromagnetic interference source, and uses the location identifier of this electromagnetic interference source as the first interference source position. Subsequently, the system terminal determines the distance between the first electromagnetic interference source and the air compressor, that is, the first distance, based on the first interference source position of the first electromagnetic interference source and the target position, that is, the position of the air compressor. This first distance can help the system terminal understand the intensity of the electromagnetic interference and its potential impact on the air compressor.

[0041] A first interference intensity of the first electromagnetic interference source is obtained, and the first distance is weighted to obtain a comprehensive electromagnetic interference index of the operating environment; and the comprehensive electromagnetic interference index is recorded as the target electromagnetic interference index.

[0042] Optionally, the system terminal first identifies and obtains the first interference intensity of the first electromagnetic interference source. Subsequently, the obtained first distance is squared and the calculation result is converted into a reciprocal. After that, the system terminal uses this reciprocal as the weight of the first electromagnetic interference source, multiplies it by the first interference intensity, and obtains a comprehensive electromagnetic interference index. This comprehensive electromagnetic interference index takes into account two factors, interference intensity and distance, and can more accurately reflect the actual impact of electromagnetic interference on the operating environment of the air compressor. Then, the system terminal records this comprehensive electromagnetic interference index as a target electromagnetic interference index as an important basis for evaluating the operating environment of the air compressor. Through this index, the degree of impact of electromagnetic interference on the operation of the air compressor can be more intuitively understood.

[0043] Furthermore, the present application provides a target adjustment strategy, including:

[0044] A first adjustment strategy is randomly generated; and an adjustment simulation is performed on the operating environment based on the first adjustment strategy to obtain a first simulation record.

[0045] Optionally, when optimizing the operating environment of the air compressor, the system terminal first randomly generates an initial adjustment strategy. This strategy involves humidity, temperature, air quality and other aspects. Subsequently, the system terminal uses simulation components to establish its mathematical model based on the actual working principle and structure of the air compressor. This includes the thermodynamic model and kinetic model of the air compressor, and then sets the key parameters of the model, such as speed, compression ratio, efficiency, etc., to reflect the actual performance of the air compressor. After that, an environmental model is established based on the environmental parameter data to simulate the external environmental conditions when the air compressor is running, and then the adjustable parameters of the model, such as temperature setting value, humidity setting value, air quality, etc., are set so as to be adjusted during the simulation process. Then, the system terminal integrates the air compressor model and the environmental model to establish a complete operating environment simulation model. After obtaining the operating environment simulation model, the system terminal applies the randomly generated first adjustment strategy to the operating environment simulation model, adjusts the operating environment accordingly according to the specific requirements of the first adjustment strategy, and records the adjusted environmental parameters and performance data of the air compressor. Through the simulation operation, the system terminal can obtain the first simulation record. This record contains the changes in environmental parameters and the performance of the air compressor after the implementation of the first adjustment strategy. By comparing the simulation records before and after the adjustment, it is possible to evaluate whether the randomly generated first adjustment strategy is effective and how it affects the performance of the air compressor.

[0046] The first simulation record is analyzed to obtain a first simulation operation index of the air compressor; when the first simulation operation index reaches the operation index limit, the first adjustment strategy is recorded as a target adjustment strategy.

[0047] Preferably, after the operation environment simulation of the air compressor is performed, the system terminal obtains a first simulation record, which describes in detail the operation status of the air compressor under different environmental parameters. Subsequently, these simulation data are analyzed to evaluate the performance of the air compressor and determine whether the preset operation standard is reached. First, the system terminal extracts key operation data from the first simulation record and calculates the specific values ​​of each performance parameter, such as the efficiency and power consumption of the air compressor. For example, the efficiency of the air compressor is obtained by calculating the ratio of the output power to the input power in the simulation; the power consumption of the air compressor is directly obtained by reading the value of the simulation record. Subsequently, the system terminal assigns a weight to each performance parameter according to the professional knowledge and actual needs in this field, and multiplies the value of each performance parameter by the corresponding weight, and then sums to obtain the first simulation operation index. After that, the system terminal compares the calculated first simulation operation index with the preset operation index limit. This limit is set based on factors such as the design standard of the air compressor, user needs, and the actual operation environment, and it represents the minimum performance level that the air compressor should achieve under specific conditions. If the first simulation operation index reaches or exceeds the operation index limit, the system terminal determines that the first adjustment strategy is valid and records it as the target adjustment strategy. This adjustment strategy will be used to adjust the operating environment of the air compressor to ensure that it reaches or exceeds the predetermined performance level. On the contrary, it means that the first adjustment strategy is invalid. At this time, the system terminal will regenerate an adjustment strategy and repeat the above process until the requirements of the operation index limit are met.

[0048] Further, the present application provides a first regulation strategy, comprising:

[0049] The first adjustment strategy includes a first humidity adjustment strategy, a first temperature adjustment strategy and a first air quality adjustment strategy, wherein the first humidity adjustment strategy is used to adaptively adjust the ambient humidity in the target environment characteristic information, the first temperature adjustment strategy is used to adaptively adjust the ambient temperature in the target environment characteristic information, and the first air quality adjustment strategy is used to adaptively adjust the ambient air quality in the target environment characteristic information.

[0050] Optionally, the randomly generated first adjustment strategy includes three main components, namely, a first humidity adjustment strategy, a first temperature adjustment strategy and a first air quality adjustment strategy. The first humidity adjustment strategy is used to adjust the humidity in the operating environment of the air compressor. This strategy can automatically adjust the operating state of the humidity control device according to the humidity data in the target environment characteristic information to ensure that the humidity in the operating environment of the air compressor is maintained within a suitable range. The first temperature adjustment strategy is responsible for regulating the temperature in the environment. By monitoring the temperature data in the target environment characteristic information, the setting of the temperature control device is automatically adjusted accordingly to keep the operating environment of the air compressor within a suitable temperature range. The first air quality adjustment strategy focuses on the ambient air quality. This strategy uses the air quality monitoring device to obtain the air quality data in the target environment characteristic information, and automatically adjusts the working state of the air purification device accordingly to improve or maintain the air quality of the operating environment of the air compressor. The first adjustment strategy is a comprehensive adaptive adjustment scheme, which includes adjustment strategies for humidity, temperature and air quality, and can automatically adjust the operating state of related equipment according to the target environment characteristic information, thereby ensuring the stability and suitability of the operating environment of the air compressor.

[0051] The instruction issuing module 5 is used to issue an adaptive adjustment instruction when the target operation index does not meet the operation index limit.

[0052] In one embodiment, when the air compressor operation index obtained by simulation fails to reach the preset operation index limit, the system terminal will automatically trigger an adaptive adjustment instruction. The purpose of this instruction is to read the predetermined adjustment strategy and adjust the environmental parameters according to the current operating environment conditions in order to improve the operating performance of the air compressor until the operation index meets or exceeds the preset limit.

[0053] The adaptive adjustment module 6 is used to read a predetermined adjustment strategy based on the adaptive adjustment instruction, and perform adaptive adjustment processing on the operating environment of the air compressor according to the predetermined adjustment strategy.

[0054] In one embodiment, when the operating index of the air compressor does not meet the preset limit, the system terminal reads the predetermined adjustment strategy according to the adaptive adjustment instruction, and the predetermined adjustment strategy is generated after the target adjustment strategy is continuously optimized. Subsequently, the system terminal adjusts the operating environment of the air compressor accordingly according to the predetermined humidity adjustment strategy, the predetermined temperature adjustment strategy and the predetermined air quality adjustment strategy within the predetermined adjustment strategy, so as to improve the operating environment of the air compressor and thus improve its operating performance.

[0055] In summary, the air compressor operating environment adaptive adjustment system provided by the present application has the following technical effects:

[0056] The present application uses a multi-probe device to perform real-time detection of the air compressor through the first dynamic detection module 1, and collects key operating characteristic information including compressed air moisture content, air filter blockage rate and lubricating oil viscosity. Subsequently, the initial discrimination result acquisition module 2 inputs these operating characteristic information into the adjustment discriminator trained based on the support vector machine principle to obtain the initial discrimination result of whether adjustment is needed. This discriminator is obtained by training the data in the historical adjustment record of machine learning, and can accurately judge whether the current air compressor needs to be adjusted. If the initial discrimination result meets the predetermined adjustment constraint, the second dynamic monitoring module 3 will further monitor the operating state of the air compressor and obtain the second target operating characteristic information according to the predetermined characteristic index. Afterwards, the weighted analysis module 4 will perform weighted analysis on these normalized operating characteristic information to obtain a comprehensive target operating index to evaluate the operating state of the air compressor. If the target operating index does not meet the preset operating index limit, the instruction issuing module 5 will issue an adaptive adjustment instruction. The adaptive adjustment module 6 will read the predetermined adjustment strategy according to the adaptive adjustment instruction, and then make corresponding adjustments to the operating environment of the air compressor according to these strategies to improve its operating efficiency. In addition, the electromagnetic interference sources in the operating environment are monitored, the comprehensive electromagnetic interference index is calculated, and the target operating index is adjusted based on this index to ensure the accuracy of the evaluation results. These technical effects jointly solve the technical problems that traditional air compressors are difficult to automatically adjust their operating status according to changes in the operating environment, resulting in high energy consumption and unstable performance, and realize the adaptive adjustment of the air compressor operating environment, ensuring that the air compressor can operate stably in different environments, reducing energy consumption and extending the service life.

[0057] 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.

[0058] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application belong to the scope of the present application and its equivalent technology, the present application is also intended to include these modifications and variations.

Claims

1. The air compressor operating environment adaptive adjustment system is characterized by: include: A first dynamic detection module is used to perform dynamic detection on the air compressor through a multi-probe device to obtain first target operation characteristic information; An initial discrimination result acquisition module, used for inputting the first target operation characteristic information into an adjustment discriminator to obtain an initial discrimination result, wherein the adjustment discriminator is an intelligent model trained based on the support vector machine principle; A second dynamic monitoring module is used to dynamically monitor the operating state of the air compressor to obtain second target operating characteristic information when the initial discrimination result meets the predetermined adjustment constraint; A weighted analysis module, used for performing weighted analysis on the second target operation characteristic information after normalization to obtain a target operation index; An instruction issuing module, used for issuing an adaptive adjustment instruction when the target operation index does not meet the operation index limit; An adaptive adjustment module, used for reading a predetermined adjustment strategy based on the adaptive adjustment instruction, and performing adaptive adjustment processing on the operating environment of the air compressor according to the predetermined adjustment strategy; After obtaining the target operation index, the method further includes: Reading predetermined multi-dimensional environmental features, and dynamically monitoring the operating environment based on the predetermined multi-dimensional environmental features to obtain target environmental feature information, wherein the operating environment refers to the operating environment of the air compressor; Extracting a target electromagnetic interference index from the target environment characteristic information, and adjusting the target operation index based on the target electromagnetic interference index; The operating environment includes multiple electromagnetic interference sources with location identifiers, including: Extracting a first electromagnetic interference source from the plurality of electromagnetic interference sources having position identifiers, wherein the first electromagnetic interference source has a first interference source position; Obtaining a first distance from the first interference source position to a target position, where the target position refers to the position of the air compressor; Obtaining a first interference intensity of the first electromagnetic interference source, and weighting the first distance to obtain a comprehensive electromagnetic interference index of the operating environment; The comprehensive electromagnetic interference index is recorded as the target electromagnetic interference index.

2. The air compressor operating environment adaptive adjustment system according to claim 1 is characterized in that: The multi-probe device includes a water content probe, a blockage rate probe and a viscosity probe, including: The compressed air in the air compressor is detected by the moisture content detection head to obtain the moisture content of the compressed air; The air filter in the air compressor is detected by the blockage rate detection head to obtain the blockage rate of the air filter; The lubricating oil in the air compressor is detected by the viscosity detection head to obtain the viscosity of the lubricating oil; The compressed air moisture content, the air filter blockage rate and the lubricating oil viscosity together constitute the first target operation characteristic information.

3. The air compressor operating environment adaptive adjustment system according to claim 1 is characterized in that: include: Extracting a first historical adjustment record from the historical air compressor adjustment records, wherein the first historical adjustment record refers to any environmental self-adaptation historical adjustment record of the first air compressor; The adjustment discriminator is obtained by performing machine learning on first training data consisting of first operation feature information of the first air compressor and a first adjustment or not identification in the first historical adjustment record.

4. The air compressor operating environment adaptive adjustment system according to claim 1, characterized in that: The predetermined characteristic index is read, and the operating state of the air compressor is dynamically monitored based on the predetermined characteristic index to obtain the second target operating characteristic information, wherein the predetermined characteristic index includes unit energy consumption and operating efficiency.

5. The air compressor operating environment adaptive adjustment system according to claim 1, characterized in that: include: randomly generating a first adjustment strategy; Performing adjustment simulation on the operating environment based on the first adjustment strategy to obtain a first simulation record; Analyzing the first simulation record to obtain a first simulation operation index of the air compressor; When the first simulation operation index reaches the operation index limit, the first adjustment strategy is recorded as the target adjustment strategy.

6. The air compressor operating environment adaptive adjustment system according to claim 5, characterized in that: The first adjustment strategy includes a first humidity adjustment strategy, a first temperature adjustment strategy and a first air quality adjustment strategy, wherein the first humidity adjustment strategy is used to adaptively adjust the ambient humidity in the target environment characteristic information, the first temperature adjustment strategy is used to adaptively adjust the ambient temperature in the target environment characteristic information, and the first air quality adjustment strategy is used to adaptively adjust the ambient air quality in the target environment characteristic information.

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