Performance evaluation and control method and system for oxygen generation instrument

Abstract

The invention relates to a performance evaluation and control method and system for an oxygen generation instrument, and belongs to the technical field of oxygen generation instrument control. According to the maximum oxygen production performance change characteristic data of the current oxygen production instrument in the previous preset time and the knowledge graph, the maximum oxygen production performance characteristic data of the oxygen production instrument in the current preset time is obtained, and finally the current oxygen production demand information is obtained. And making a related oxygen generation strategy according to the maximum oxygen generation performance characteristic data of the oxygen generation instrument within the current preset time and the current oxygen generation demand information, and performing oxygen generation control based on the related oxygen generation strategy. According to the method, the performance of the oxygen generation instrument is evaluated, so that the related oxygen generation strategy is formulated according to the evaluation result, the oxygen generation instrument can be within the allowable maximum oxygen generation amount, oxygen supply to the oxygen supply target is more reasonable, and the control precision of oxygen supply to the oxygen generation instrument is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of oxygen concentrator control, and in particular to a performance evaluation and control method and system for an oxygen concentrator. Background Art

[0002] Oxygen concentrator is a type of machine that produces oxygen. Its principle is to use air separation technology. First, the air is compressed at a high density, and then the different condensation points of the various components in the air are used to separate the gas and liquid at a certain temperature, and then distilled to separate it into oxygen and nitrogen. In general, people are used to calling it an oxygen concentrator because it is mostly used to produce oxygen. Since oxygen and nitrogen are widely used, oxygen concentrators are also widely used in the national economy. Especially in metallurgy, chemical industry, petroleum, national defense and other industries, they are most used. The first countries in the world to produce oxygen concentrators are Germany and France. This high-concentration oxygen can be used for oxygen therapy to treat some diseases, such as surgical recovery, chronic obstructive pulmonary disease (COPD), sleep apnea and anemia, to increase the oxygen content in the blood, help patients improve oxygen supply and improve health. Oxygen concentrators play an important role in the medical and health fields. However, after a certain number of years of use, the oxygen production performance of the oxygen concentrator will deteriorate, and in the process of oxygen supply, due to changes in oxygen production performance, insufficient oxygen supply will occur, so that oxygen cannot be effectively increased, which is not conducive to the use of medical and health fields. Summary of the invention

[0003] The present invention overcomes the deficiencies of the prior art and provides a performance evaluation and control method and system for an oxygen generator.

[0004] To achieve the above object, the technical solution adopted by the present invention is: A first aspect of the present invention provides a performance evaluation and control method for an oxygen generator, comprising the following steps: Acquire historical maximum oxygen production performance change characteristic data of the oxygen concentrator, construct maximum oxygen production performance trajectory state vector characteristic change data according to the historical maximum oxygen production performance change characteristic data of the oxygen concentrator, and construct a performance change graph of the oxygen concentrator based on the maximum oxygen production performance trajectory state vector characteristic change data; Constructing a knowledge graph according to the performance change graph of the oxygen concentrator to obtain the maximum oxygen production performance change characteristic data of the current oxygen concentrator within the last preset time; Acquire the maximum oxygen production performance characteristic data of the oxygen concentrator within the current preset time according to the maximum oxygen production performance change characteristic data of the current oxygen concentrator within the previous preset time and the knowledge graph; The current oxygen production demand information is obtained, and a relevant oxygen production strategy is formulated according to the maximum oxygen production performance characteristic data of the oxygen concentrator within the current preset time and the current oxygen production demand information, and oxygen production control is performed based on the relevant oxygen production strategy.

[0005] Furthermore, in the performance evaluation and control method of the oxygen concentrator, the historical maximum oxygen production performance change characteristic data of the oxygen concentrator is obtained, and the maximum oxygen production performance trajectory state vector characteristic change data is constructed according to the historical maximum oxygen production performance change characteristic data of the oxygen concentrator, specifically including: Acquire the historical maximum oxygen production performance change characteristic data of the oxygen concentrator, construct a timestamp, and sort the historical maximum oxygen production performance change characteristic data of the oxygen concentrator according to the order of the timestamps; By sorting, the historical maximum oxygen production performance change characteristic data of the oxygen concentrator based on the time series is obtained, and the maximum oxygen production performance change characteristic data in each timestamp is used as a state value to generate a state vector, and a state vector change characteristic is generated based on the state vector; Input the state vector change feature into the Markov chain, calculate the state transition probability value of each state vector transferring to another state vector, and if the state transition probability value is greater than a preset state transition probability value, update the corresponding state to another state vector; If the state transition probability value is not greater than the preset state transition probability value, the corresponding state vector is maintained unchanged, and the final state vector change characteristics are counted to construct the maximum oxygen production performance trajectory state vector characteristic change data.

[0006] Furthermore, in the performance evaluation and control method of the oxygen concentrator, a performance change diagram of the oxygen concentrator is constructed based on the maximum oxygen production performance trajectory state vector characteristic change data, specifically including: Constructing a performance change graph of the oxygen concentrator, and inputting the maximum oxygen production performance data of each timestamp in the maximum oxygen production performance trajectory state vector characteristic change data into the performance change graph of the oxygen concentrator; Find the corresponding position points in the performance change diagram of the oxygen concentrator for point representation, calculate the local outlier factor value of each point by using the outlier detection algorithm, and delete the points whose local outlier factor value is greater than the preset local outlier factor value; After the deletion, the adjacent points are connected by a smooth curve, and each adjacent curve is connected to form a performance change graph of the oxygen generator, and the performance change graph of the oxygen generator is output.

[0007] Furthermore, in the performance evaluation and control method of the oxygen concentrator, the maximum oxygen production performance characteristic data of the oxygen concentrator within the current preset time is obtained according to the maximum oxygen production performance change characteristic data of the current oxygen concentrator within the previous preset time and the knowledge graph, specifically including: Constructing a maximum oxygen production performance change curve graph according to the maximum oxygen production performance change characteristic data of the current oxygen concentrator within the last preset time, and inputting the maximum oxygen production performance change curve graph into the knowledge graph for data matching; By data matching, a performance change graph of the oxygen concentrator with the highest similarity is obtained, and maximum oxygen production performance characteristic data within a predetermined time period is obtained from the performance change graph of the oxygen concentrator with the highest similarity; The maximum oxygen production performance characteristic data within a predetermined time period in the performance change diagram of the oxygen concentrator with the highest similarity is used as the maximum oxygen production performance characteristic data of the oxygen concentrator within the current preset time.

[0008] Furthermore, in the performance evaluation and control method of the oxygen concentrator, the current oxygen production demand information is obtained, and a relevant oxygen production strategy is formulated according to the maximum oxygen production performance characteristic data of the oxygen concentrator within the current preset time and the current oxygen production demand information, specifically including: Obtaining current oxygen demand information, randomly selecting a number of oxygen supply targets according to the current oxygen demand information, introducing a particle swarm algorithm, and setting the number of iterations based on the particle swarm algorithm; Obtaining oxygen supply information of each oxygen supply target, and calculating real-time estimated total oxygen supply data according to the oxygen supply information of each oxygen supply target, and determining whether the real-time estimated oxygen supply data is greater than the maximum oxygen production performance characteristic data of the oxygen concentrator within the current preset time; When the real-time predicted oxygen supply data is greater than the maximum oxygen production performance characteristic data of the oxygen concentrator within the current preset time, the oxygen supply target is readjusted until the real-time predicted oxygen supply data is greater than the current oxygen production demand information, the oxygen supply target is output, and a related oxygen production strategy is generated; When the real-time estimated oxygen supply data is not greater than the maximum oxygen production performance characteristic data of the oxygen concentrator within the current preset time, the oxygen supply target is iterated based on the number of iterations, the oxygen supply target is updated and readjusted, the oxygen supply target is output, and a related oxygen production strategy is generated.

[0009] Furthermore, in the performance evaluation and control method of the oxygen generator, oxygen production control is performed based on the relevant oxygen production strategy, specifically including: Obtaining the location information of the oxygen supply target in the relevant oxygen production strategy, and obtaining the location information of each oxygen concentrator, calculating the location information of the oxygen supply target in the relevant oxygen production strategy and the location information of the oxygen concentrator, and calculating the Euclidean distance value between the oxygen supply target and the oxygen concentrator; Obtaining oxygen production control delay data of the oxygen concentrator under each Euclidean distance value, and setting a control delay data threshold, and calculating the control delay data according to the oxygen production control delay data of the oxygen concentrator under each Euclidean distance value and the Euclidean distance value between the oxygen supply target and the oxygen concentrator; Determining whether the control delay data is greater than a control delay data threshold, and when the control delay data is not greater than the control delay data threshold, performing oxygen production control according to the original related oxygen production strategy; When the control delay data is greater than the control delay data threshold, the oxygen supply target in the relevant oxygen production strategy is updated until the control delay data is no greater than the control delay data threshold.

[0010] A second aspect of the present invention provides a performance evaluation and control system for an oxygen concentrator, the system comprising a memory and a processor, the memory comprising a performance evaluation and control method program for the oxygen concentrator, and when the performance evaluation and control method program for the oxygen concentrator is executed by the processor, the steps of any one of the performance evaluation and control methods for the oxygen concentrator are implemented.

[0011] A fourth aspect of the present invention provides a computer-readable storage medium, comprising a performance evaluation and control method program for an oxygen concentrator. When the performance evaluation and control method program for an oxygen concentrator is executed by a processor, the steps of any one of the performance evaluation and control methods for an oxygen concentrator are implemented.

[0012] The present invention solves the defects existing in the background technology and has the following beneficial effects: The present invention obtains the historical maximum oxygen production performance change characteristic data of the oxygen concentrator, and constructs the maximum oxygen production performance trajectory state vector characteristic change data according to the historical maximum oxygen production performance change characteristic data of the oxygen concentrator, constructs the performance change graph of the oxygen concentrator based on the maximum oxygen production performance trajectory state vector characteristic change data, and then constructs the knowledge graph according to the performance change graph of the oxygen concentrator, obtains the maximum oxygen production performance change characteristic data of the current oxygen concentrator within the previous preset time, and then obtains the maximum oxygen production performance characteristic data of the oxygen concentrator within the current preset time according to the maximum oxygen production performance change characteristic data of the current oxygen concentrator within the previous preset time and the knowledge graph, and finally obtains the current oxygen production demand information, and formulates the relevant oxygen production strategy according to the maximum oxygen production performance characteristic data of the oxygen concentrator within the current preset time and the current oxygen production demand information, and performs oxygen production control based on the relevant oxygen production strategy. The present invention evaluates the performance of the oxygen concentrator, and then formulates the relevant oxygen production strategy according to the evaluation result, so that the oxygen concentrator can be within the maximum oxygen production allowed, so that the oxygen supply to the oxygen supply target is more reasonable, and the control accuracy of the oxygen supply of the oxygen concentrator is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in 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 described below are only some embodiments of the present invention. For ordinary technicians in this field, drawings of other embodiments can be obtained based on these drawings without paying creative work.

[0014] Figure 1 An overall flow chart of the performance evaluation and control method of the oxygen generator is shown; Figure 2 A partial flow chart of a method for evaluating and controlling the performance of an oxygen concentrator is shown; Figure 3 The system block diagram of the performance evaluation and control system of the oxygen generator is shown. DETAILED DESCRIPTION

[0015] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0016] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0017] like Figure 1 As shown, the first aspect of the present invention provides a performance evaluation and control method for an oxygen generator, comprising the following steps: S102: Acquire historical maximum oxygen production performance change characteristic data of the oxygen concentrator, construct maximum oxygen production performance trajectory state vector characteristic change data according to the historical maximum oxygen production performance change characteristic data of the oxygen concentrator, and construct a performance change graph of the oxygen concentrator based on the maximum oxygen production performance trajectory state vector characteristic change data; S104: constructing a knowledge graph according to the performance change graph of the oxygen concentrator, and obtaining the maximum oxygen production performance change characteristic data of the current oxygen concentrator within the last preset time; S106: Acquire the maximum oxygen production performance characteristic data of the oxygen concentrator within the current preset time according to the maximum oxygen production performance change characteristic data of the current oxygen concentrator within the previous preset time and the knowledge graph; S108: Obtain current oxygen production demand information, and formulate relevant oxygen production strategies according to the maximum oxygen production performance characteristic data of the oxygen concentrator within the current preset time and the current oxygen production demand information, and perform oxygen production control based on the relevant oxygen production strategies.

[0018] It should be noted that the present invention evaluates the performance of the oxygen concentrator and formulates relevant oxygen production strategies based on the evaluation results, so that the oxygen concentrator can produce oxygen within the maximum allowable oxygen production, making the oxygen supply to the oxygen supply target more reasonable and improving the control accuracy of the oxygen supply of the oxygen concentrator.

[0019] like Figure 2 As shown, further, in the performance evaluation and control method of the oxygen concentrator, the historical maximum oxygen production performance change characteristic data of the oxygen concentrator is obtained, and the maximum oxygen production performance trajectory state vector characteristic change data is constructed according to the historical maximum oxygen production performance change characteristic data of the oxygen concentrator, specifically including: S202: Acquire the historical maximum oxygen production performance change characteristic data of the oxygen concentrator, construct a timestamp, and sort the historical maximum oxygen production performance change characteristic data of the oxygen concentrator according to the order of the timestamps; S204: obtaining the historical maximum oxygen production performance change characteristic data of the oxygen concentrator based on the time series by sorting, and taking the maximum oxygen production performance change characteristic data in each timestamp as a state value to generate a state vector, and generating a state vector change characteristic based on the state vector; S206: Input the state vector change feature into the Markov chain, calculate the state transition probability value of each state vector transferring to another state vector, and if the state transition probability value is greater than a preset state transition probability value, update the corresponding state to another state vector; S208: If the state transition probability value is not greater than the preset state transition probability value, the corresponding state vector is maintained unchanged, and the final state vector change characteristics are counted to construct the maximum oxygen production performance trajectory state vector characteristic change data.

[0020] It should be noted that the oxygen production performance data includes the oxygen production amount per unit time, the maximum oxygen production amount per unit time, the oxygen supply amount per unit time, etc. By inputting the state vector change characteristics into the Markov chain, the state transition probability value of each state vector transferring to another state vector is calculated. If the state transition probability value is greater than the preset state transition probability value, the corresponding state is updated to another state vector. The maximum oxygen production performance trajectory state vector characteristic change data can be updated in time, which can improve the estimation accuracy of the maximum oxygen production performance.

[0021] Furthermore, in the performance evaluation and control method of the oxygen concentrator, a performance change diagram of the oxygen concentrator is constructed based on the maximum oxygen production performance trajectory state vector characteristic change data, specifically including: Constructing a performance change graph of the oxygen concentrator, and inputting the maximum oxygen production performance data of each timestamp in the maximum oxygen production performance trajectory state vector characteristic change data into the performance change graph of the oxygen concentrator; Find the corresponding position points in the performance change diagram of the oxygen concentrator for point representation, calculate the local outlier factor value of each point by using the outlier detection algorithm, and delete the points whose local outlier factor value is greater than the preset local outlier factor value; After the deletion, the adjacent points are connected by a smooth curve, and each adjacent curve is connected to form a performance change graph of the oxygen generator, and the performance change graph of the oxygen generator is output.

[0022] It should be noted that after finding the corresponding position point in the performance change diagram of the oxygen concentrator for point representation, there may be a situation where an accidental failure occurs at the corresponding point, so the point whose local outlier factor value is greater than the preset local outlier factor value is deleted, which can improve the estimated accuracy of the performance of the oxygen concentrator.

[0023] Furthermore, in the performance evaluation and control method of the oxygen concentrator, the maximum oxygen production performance characteristic data of the oxygen concentrator within the current preset time is obtained according to the maximum oxygen production performance change characteristic data of the current oxygen concentrator within the previous preset time and the knowledge graph, specifically including: Constructing a maximum oxygen production performance change curve graph according to the maximum oxygen production performance change characteristic data of the current oxygen concentrator within the last preset time, and inputting the maximum oxygen production performance change curve graph into the knowledge graph for data matching; By data matching, a performance change graph of the oxygen concentrator with the highest similarity is obtained, and maximum oxygen production performance characteristic data within a predetermined time period is obtained from the performance change graph of the oxygen concentrator with the highest similarity; The maximum oxygen production performance characteristic data within a predetermined time period in the performance change diagram of the oxygen concentrator with the highest similarity is used as the maximum oxygen production performance characteristic data of the oxygen concentrator within the current preset time.

[0024] Furthermore, in the performance evaluation and control method of the oxygen concentrator, the current oxygen production demand information is obtained, and a relevant oxygen production strategy is formulated according to the maximum oxygen production performance characteristic data of the oxygen concentrator within the current preset time and the current oxygen production demand information, specifically including: Obtaining current oxygen demand information, randomly selecting a number of oxygen supply targets according to the current oxygen demand information, introducing a particle swarm algorithm, and setting the number of iterations based on the particle swarm algorithm; Obtaining oxygen supply information of each oxygen supply target, and calculating real-time estimated total oxygen supply data according to the oxygen supply information of each oxygen supply target, and determining whether the real-time estimated oxygen supply data is greater than the maximum oxygen production performance characteristic data of the oxygen concentrator within the current preset time; When the real-time predicted oxygen supply data is greater than the maximum oxygen production performance characteristic data of the oxygen concentrator within the current preset time, the oxygen supply target is readjusted until the real-time predicted oxygen supply data is greater than the current oxygen production demand information, the oxygen supply target is output, and a related oxygen production strategy is generated; When the real-time estimated oxygen supply data is not greater than the maximum oxygen production performance characteristic data of the oxygen concentrator within the current preset time, the oxygen supply target is iterated based on the number of iterations, the oxygen supply target is updated and readjusted, the oxygen supply target is output, and a related oxygen production strategy is generated.

[0025] It should be noted that after a certain number of years of use, the maximum oxygen supply data of the oxygen concentrator will change. This method can optimize the selection of several oxygen supply targets so that the real-time estimated oxygen supply data is no greater than the maximum oxygen production performance characteristic data of the oxygen concentrator within the current preset time, thereby improving the control rationality of the oxygen concentrator.

[0026] Furthermore, in the performance evaluation and control method of the oxygen generator, oxygen production control is performed based on the relevant oxygen production strategy, specifically including: Obtaining the location information of the oxygen supply target in the relevant oxygen production strategy, and obtaining the location information of each oxygen concentrator, calculating the location information of the oxygen supply target in the relevant oxygen production strategy and the location information of the oxygen concentrator, and calculating the Euclidean distance value between the oxygen supply target and the oxygen concentrator; Obtaining oxygen production control delay data of the oxygen concentrator under each Euclidean distance value, and setting a control delay data threshold, and calculating the control delay data according to the oxygen production control delay data of the oxygen concentrator under each Euclidean distance value and the Euclidean distance value between the oxygen supply target and the oxygen concentrator; Determining whether the control delay data is greater than a control delay data threshold, and when the control delay data is not greater than the control delay data threshold, performing oxygen production control according to the original related oxygen production strategy; When the control delay data is greater than the control delay data threshold, the oxygen supply target in the relevant oxygen production strategy is updated until the control delay data is no greater than the control delay data threshold.

[0027] It should be noted that different Euclidean distances will result in different control delays between the oxygen supply target and the oxygen generator. This method can improve the control rationality of the oxygen generator.

[0028] Additionally, it includes: Acquire historical service data of the oxygen concentrator, build a fault prediction model for the oxygen concentrator based on a neural network, and input the historical service data of the oxygen concentrator into the fault prediction model for training; Through training, a trained oxygen concentrator fault prediction model is obtained, service data of each oxygen concentrator within a preset time is obtained, and the service data of each oxygen concentrator within the preset time is input into the trained oxygen concentrator fault prediction model for prediction; By prediction, the failure time information of each oxygen concentrator is obtained, and the working time period required by the oxygen concentrator is obtained. When the failure time information of the oxygen concentrator falls within the working time period required by the oxygen concentrator, the corresponding oxygen concentrator is not used as a working oxygen concentrator; When the fault time information of the oxygen concentrator does not fall within the working period required by the oxygen concentrator, the corresponding oxygen concentrator is used as the working oxygen concentrator.

[0029] It should be noted that this method can improve the working rationality of the oxygen concentrator, so that the working requirements of the oxygen concentrator can be met at all times.

[0030] In addition, the method further comprises: Obtaining oxygen production data of the oxygen concentrator under various working environment characteristics and various working parameters, and introducing a graph neural network, and inputting the oxygen production data of the oxygen concentrator under various working environment characteristics and various working parameters into the graph neural network; The working environment feature is used as the first node, the working parameter is used as the second node, the oxygen production data is used as the third node, and the first node, the second node and the third node are connected to form a topological structure diagram; Based on the topological structure diagram, a relevant adjacency matrix is ​​obtained, a knowledge graph is constructed, the relevant adjacency matrix is ​​input into the knowledge graph for storage, and real-time working environment characteristics and oxygen production demand information of the oxygen generator are obtained; The real-time working environment characteristics of the oxygen generator are input into the knowledge graph as oxygen production demand information for data matching. Through data matching, the corresponding working parameters are obtained, and the working parameters are displayed in a preset manner.

[0031] It should be noted that the amount of oxygen produced is different under various working environment characteristics (temperature, humidity) and various working parameters (such as voltage, gas flow). This method can adjust the working parameters of the oxygen concentrator according to the oxygen production demand, and can control the equipment according to actual needs, thereby reducing the energy consumption of the equipment and increasing the service life of the equipment.

[0032] like Figure 3 As shown, the second aspect of the present invention provides a performance evaluation and control system 4 for an oxygen concentrator, the system 4 comprising a memory 41 and a processor 42, the memory 41 comprising a performance evaluation and control method program for an oxygen concentrator, and when the performance evaluation and control method program for an oxygen concentrator is executed by the processor 42, the following steps are implemented: Acquire historical maximum oxygen production performance change characteristic data of the oxygen concentrator, construct maximum oxygen production performance trajectory state vector characteristic change data according to the historical maximum oxygen production performance change characteristic data of the oxygen concentrator, and construct a performance change graph of the oxygen concentrator based on the maximum oxygen production performance trajectory state vector characteristic change data; Constructing a knowledge graph according to the performance change graph of the oxygen concentrator to obtain the maximum oxygen production performance change characteristic data of the current oxygen concentrator within the last preset time; Acquire the maximum oxygen production performance characteristic data of the oxygen concentrator within the current preset time according to the maximum oxygen production performance change characteristic data of the current oxygen concentrator within the previous preset time and the knowledge graph; The current oxygen production demand information is obtained, and a relevant oxygen production strategy is formulated according to the maximum oxygen production performance characteristic data of the oxygen concentrator within the current preset time and the current oxygen production demand information, and oxygen production control is performed based on the relevant oxygen production strategy.

[0033] Furthermore, in the performance evaluation and control system of the oxygen concentrator, the historical maximum oxygen production performance change characteristic data of the oxygen concentrator is obtained, and the maximum oxygen production performance trajectory state vector characteristic change data is constructed according to the historical maximum oxygen production performance change characteristic data of the oxygen concentrator, specifically including: Acquire the historical maximum oxygen production performance change characteristic data of the oxygen concentrator, construct a timestamp, and sort the historical maximum oxygen production performance change characteristic data of the oxygen concentrator according to the order of the timestamps; By sorting, the historical maximum oxygen production performance change characteristic data of the oxygen concentrator based on the time series is obtained, and the maximum oxygen production performance change characteristic data in each timestamp is used as a state value to generate a state vector, and a state vector change characteristic is generated based on the state vector; Input the state vector change feature into the Markov chain, calculate the state transition probability value of each state vector transferring to another state vector, and if the state transition probability value is greater than a preset state transition probability value, update the corresponding state to another state vector; If the state transition probability value is not greater than the preset state transition probability value, the corresponding state vector is maintained unchanged, and the final state vector change characteristics are counted to construct the maximum oxygen production performance trajectory state vector characteristic change data.

[0034] Furthermore, in the performance evaluation and control system of the oxygen concentrator, a performance change diagram of the oxygen concentrator is constructed based on the maximum oxygen production performance trajectory state vector characteristic change data, specifically including: Constructing a performance change graph of the oxygen concentrator, and inputting the maximum oxygen production performance data of each timestamp in the maximum oxygen production performance trajectory state vector characteristic change data into the performance change graph of the oxygen concentrator; Find the corresponding position points in the performance change diagram of the oxygen concentrator for point representation, calculate the local outlier factor value of each point by using the outlier detection algorithm, and delete the points whose local outlier factor value is greater than the preset local outlier factor value; After the deletion, the adjacent points are connected by a smooth curve, and each adjacent curve is connected to form a performance change graph of the oxygen generator, and the performance change graph of the oxygen generator is output.

[0035] Further, in the performance evaluation and control system of the oxygen concentrator, the maximum oxygen production performance characteristic data of the oxygen concentrator within the current preset time is obtained according to the maximum oxygen production performance change characteristic data of the current oxygen concentrator within the previous preset time and the knowledge graph, specifically including: Constructing a maximum oxygen production performance change curve graph according to the maximum oxygen production performance change characteristic data of the current oxygen concentrator within the last preset time, and inputting the maximum oxygen production performance change curve graph into the knowledge graph for data matching; By data matching, a performance change graph of the oxygen concentrator with the highest similarity is obtained, and maximum oxygen production performance characteristic data within a predetermined time period is obtained from the performance change graph of the oxygen concentrator with the highest similarity; The maximum oxygen production performance characteristic data within a predetermined time period in the performance change diagram of the oxygen concentrator with the highest similarity is used as the maximum oxygen production performance characteristic data of the oxygen concentrator within the current preset time.

[0036] Furthermore, in the performance evaluation and control system of the oxygen concentrator, the current oxygen production demand information is obtained, and a relevant oxygen production strategy is formulated according to the maximum oxygen production performance characteristic data of the oxygen concentrator within the current preset time and the current oxygen production demand information, specifically including: Obtaining current oxygen demand information, randomly selecting a number of oxygen supply targets according to the maximum oxygen production performance characteristic data of the oxygen concentrator within the current preset time, introducing a particle swarm algorithm, and setting the number of iterations based on the particle swarm algorithm; Obtaining oxygen supply information of each oxygen supply target, and calculating real-time estimated total oxygen supply data according to the oxygen supply information of each oxygen supply target, and determining whether the real-time estimated oxygen supply data is greater than the current oxygen production demand information; When the real-time predicted oxygen supply data is greater than the current oxygen production demand information, the oxygen supply target is readjusted until the real-time predicted oxygen supply data is greater than the current oxygen production demand information, the oxygen supply target is output, and a related oxygen production strategy is generated; When the real-time estimated oxygen supply data is not greater than the current oxygen production demand information, the oxygen supply target is iterated based on the iteration number, the oxygen supply target is updated and readjusted, the oxygen supply target is output, and a related oxygen production strategy is generated.

[0037] Furthermore, in the performance evaluation and control system of the oxygen generator, oxygen production control is performed based on the relevant oxygen production strategy, specifically including: Obtaining the location information of the oxygen supply target in the relevant oxygen production strategy, and obtaining the location information of each oxygen concentrator, calculating the location information of the oxygen supply target in the relevant oxygen production strategy and the location information of the oxygen concentrator, and calculating the Euclidean distance value between the oxygen supply target and the oxygen concentrator; Obtaining oxygen production control delay data of the oxygen concentrator under each Euclidean distance value, and setting a control delay data threshold, and calculating the control delay data according to the oxygen production control delay data of the oxygen concentrator under each Euclidean distance value and the Euclidean distance value between the oxygen supply target and the oxygen concentrator; Determining whether the control delay data is greater than a control delay data threshold, and when the control delay data is not greater than the control delay data threshold, performing oxygen production control according to the original related oxygen production strategy; When the control delay data is greater than the control delay data threshold, the oxygen supply target in the relevant oxygen production strategy is updated until the control delay data is no greater than the control delay data threshold.

[0038] A fourth aspect of the present invention provides a computer-readable storage medium, comprising a performance evaluation and control method program for an oxygen concentrator. When the performance evaluation and control method program for an oxygen concentrator is executed by a processor, the steps of any one of the performance evaluation and control methods for an oxygen concentrator are implemented.

[0039] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0040] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed on multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0041] In addition, all functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately used as a unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0042] A person of ordinary skill in the art can understand that: all or part of the steps of implementing the above method embodiment can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above method embodiment; and the aforementioned storage medium includes: a mobile storage device, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and other media that can store program codes.

[0043] Alternatively, if the above-mentioned integrated unit of the present invention is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present invention can be essentially or partly reflected in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the methods of each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, disks or optical disks.

[0044] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art who is familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A performance evaluation and control method for an oxygen generator, characterized in that: The following steps are involved: Acquire historical maximum oxygen production performance change characteristic data of the oxygen concentrator, construct maximum oxygen production performance trajectory state vector characteristic change data according to the historical maximum oxygen production performance change characteristic data of the oxygen concentrator, and construct a performance change graph of the oxygen concentrator based on the maximum oxygen production performance trajectory state vector characteristic change data; Constructing a knowledge graph according to the performance change graph of the oxygen concentrator to obtain the maximum oxygen production performance change characteristic data of the current oxygen concentrator within the last preset time; Acquire the maximum oxygen production performance characteristic data of the oxygen concentrator within the current preset time according to the maximum oxygen production performance change characteristic data of the current oxygen concentrator within the previous preset time and the knowledge graph; The current oxygen production demand information is obtained, and a relevant oxygen production strategy is formulated according to the maximum oxygen production performance characteristic data of the oxygen concentrator within the current preset time and the current oxygen production demand information, and oxygen production control is performed based on the relevant oxygen production strategy.

2. The performance evaluation and control method of an oxygen generator according to claim 1, characterized in that: Acquiring the historical maximum oxygen production performance change characteristic data of the oxygen concentrator, and constructing the maximum oxygen production performance trajectory state vector characteristic change data according to the historical maximum oxygen production performance change characteristic data of the oxygen concentrator, specifically including: Acquire the historical maximum oxygen production performance change characteristic data of the oxygen concentrator, construct a timestamp, and sort the historical maximum oxygen production performance change characteristic data of the oxygen concentrator according to the order of the timestamps; By sorting, the historical maximum oxygen production performance change characteristic data of the oxygen concentrator based on the time series is obtained, and the maximum oxygen production performance change characteristic data in each timestamp is used as a state value to generate a state vector, and a state vector change characteristic is generated based on the state vector; Input the state vector change feature into the Markov chain, calculate the state transition probability value of each state vector transferring to another state vector, and if the state transition probability value is greater than a preset state transition probability value, update the corresponding state to another state vector; If the state transition probability value is not greater than the preset state transition probability value, the corresponding state vector is maintained unchanged, and the final state vector change characteristics are counted to construct the maximum oxygen production performance trajectory state vector characteristic change data.

3. The performance evaluation and control method of an oxygen generator according to claim 1, characterized in that: Constructing a performance change graph of the oxygen generator based on the maximum oxygen production performance trajectory state vector characteristic change data specifically includes: Constructing a performance change graph of the oxygen concentrator, and inputting the maximum oxygen production performance data of each timestamp in the maximum oxygen production performance trajectory state vector characteristic change data into the performance change graph of the oxygen concentrator; Find the corresponding position points in the performance change diagram of the oxygen concentrator for point representation, calculate the local outlier factor value of each point by using the outlier detection algorithm, and delete the points whose local outlier factor value is greater than the preset local outlier factor value; After the deletion, the adjacent points are connected by a smooth curve, and each adjacent curve is connected to form a performance change graph of the oxygen generator, and the performance change graph of the oxygen generator is output.

4. The performance evaluation and control method of an oxygen generator according to claim 1, characterized in that: Acquiring the maximum oxygen production performance characteristic data of the oxygen concentrator within the current preset time according to the maximum oxygen production performance change characteristic data of the current oxygen concentrator within the previous preset time and the knowledge graph specifically includes: Constructing a maximum oxygen production performance change curve graph according to the maximum oxygen production performance change characteristic data of the current oxygen concentrator within the last preset time, and inputting the maximum oxygen production performance change curve graph into the knowledge graph for data matching; By data matching, a performance change graph of the oxygen concentrator with the highest similarity is obtained, and maximum oxygen production performance characteristic data within a predetermined time period is obtained from the performance change graph of the oxygen concentrator with the highest similarity; The maximum oxygen production performance characteristic data within a predetermined time period in the performance change diagram of the oxygen concentrator with the highest similarity is used as the maximum oxygen production performance characteristic data of the oxygen concentrator within the current preset time.

5. The performance evaluation and control method of an oxygen generator according to claim 1, characterized in that: Obtain the current oxygen production demand information, and formulate relevant oxygen production strategies according to the maximum oxygen production performance characteristic data of the oxygen generator within the current preset time and the current oxygen production demand information, specifically including: Obtaining current oxygen demand information, randomly selecting a number of oxygen supply targets according to the current oxygen demand information, introducing a particle swarm algorithm, and setting the number of iterations based on the particle swarm algorithm; Obtaining oxygen supply information of each oxygen supply target, and calculating real-time estimated total oxygen supply data according to the oxygen supply information of each oxygen supply target, and determining whether the real-time estimated oxygen supply data is greater than the maximum oxygen production performance characteristic data of the oxygen concentrator within the current preset time; When the real-time predicted oxygen supply data is greater than the maximum oxygen production performance characteristic data of the oxygen concentrator within the current preset time, the oxygen supply target is readjusted until the real-time predicted oxygen supply data is greater than the current oxygen production demand information, the oxygen supply target is output, and a related oxygen production strategy is generated; When the real-time estimated oxygen supply data is not greater than the maximum oxygen production performance characteristic data of the oxygen concentrator within the current preset time, the oxygen supply target is iterated based on the number of iterations, the oxygen supply target is updated and readjusted, the oxygen supply target is output, and a related oxygen production strategy is generated.

6. The performance evaluation and control method of an oxygen generator according to claim 1, characterized in that: Oxygen production control is performed based on the relevant oxygen production strategy, specifically including: Obtaining the location information of the oxygen supply target in the relevant oxygen production strategy, and obtaining the location information of each oxygen concentrator, calculating the location information of the oxygen supply target in the relevant oxygen production strategy and the location information of the oxygen concentrator, and calculating the Euclidean distance value between the oxygen supply target and the oxygen concentrator; Obtaining oxygen production control delay data of the oxygen concentrator under each Euclidean distance value, and setting a control delay data threshold, and calculating the control delay data according to the oxygen production control delay data of the oxygen concentrator under each Euclidean distance value and the Euclidean distance value between the oxygen supply target and the oxygen concentrator; Determining whether the control delay data is greater than a control delay data threshold, and when the control delay data is not greater than the control delay data threshold, performing oxygen production control according to the original related oxygen production strategy; When the control delay data is greater than the control delay data threshold, the oxygen supply target in the relevant oxygen production strategy is updated until the control delay data is no greater than the control delay data threshold.

7. A performance evaluation and control system for an oxygen generator, characterized in that: The system includes a memory and a processor, wherein the memory includes a performance evaluation and control method program for an oxygen concentrator, and when the performance evaluation and control method program for an oxygen concentrator is executed by the processor, the steps of the performance evaluation and control method for an oxygen concentrator as described in any one of claims 1 to 6 are implemented.

8. A computer-readable storage medium, characterized in that: It includes a performance evaluation and control method program for an oxygen concentrator, and when the performance evaluation and control method program for an oxygen concentrator is executed by a processor, the steps of the performance evaluation and control method for an oxygen concentrator as described in any one of claims 1 to 6 are implemented.

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