Multi-dimensional wear state identification method and system based on friction nanogenerator oil

Abstract

The present invention provides a method and system for identifying the multi-dimensional wear state of friction nanogenerator oil, including: step S1: designing a dual-electrode friction nanogenerator to monitor the state of lubricating oil; step S2: measuring the state of lubricating oil through machine learning or deep learning, analyzing the specific components of lubricating oil, and predicting the wear state of the machine. The present invention can realize the coordinated identification of multiple pollutants, and can analyze the content of pollutants such as water, iron filings, and carbon deposits in lubricating oil; the friction nanogenerator is a self-powered device, which can generate charge transfer through friction between the lubricating oil and itself, and does not require external power.

Description

Technical Field

[0001] The present invention relates to the field of sensor design, and in particular to a method and system for identifying multi-dimensional wear states of friction nanogenerator oil. Background Art

[0002] The smooth operation of the machine is inseparable from the protection of lubricating oil. At the same time, the friction and wear of the machine can also be manifested through the physical characteristics of the lubricating oil (such as lubricating oil contamination, lubricating oil aging, etc.). Lubricating oil is like human blood to the machine. It is a very reliable way to reflect the operation of the machine through the real-time status of lubricating oil. Contaminants such as thermal oxidation, wear debris, carbon deposits, fuel and moisture are often present in lubricating oil. Therefore, lubricating oil analysis is an effective means to judge the health of the machine and predict whether the machine will fail.

[0003] In extreme working conditions such as industrial production and aerospace, in complex environments such as high temperature and high pressure, the friction elements of high-end equipment such as gas turbines and spacecraft play a small but critical role. Once wear and failure occur, huge economic losses may occur, but it is difficult to perform online monitoring in the operating state. Therefore, it is necessary to monitor the lubricating oil in the friction pair online, analyze the information such as the content of pollutants in the lubricating oil, and study the relationship between the lubricating oil and the wear state, so as to indirectly obtain the wear state of the friction pair, which is of great significance to improving equipment reliability and reducing major economic property losses.

[0004] Among existing technologies, vibration analysis and thermal imaging have been used to check for machine failures, but this approach requires complex data collection and calculation procedures and is therefore difficult to implement. In addition, in the early stages of wear, there is little or no change in vibration or temperature. Ferrometry has also been used in oil monitoring, but ferrometry is usually not capable of online monitoring and is not robust enough to failure. These methods are usually unable to predict and identify machine wear conditions.

[0005] Patent document CN116244966A discloses a method and system for identifying different wear stages of an industrial robot elbow joint, the method comprising: establishing a dynamic model of a robot considering joint gaps based on comprehensive gap joint contact forces; calculating the dynamic response of the robot system with different joint friction coefficients; calculating the nonlinearity value of the robot system based on a time series autoregressive (AR) model; establishing the relationship between the robot friction coefficient and the nonlinearity; and online identifying the wear stage of the robot elbow joint based on the wear threshold. However, the invention does not propose wear identification based on the oil of the friction nanogenerator. Summary of the invention

[0006] In view of the defects in the prior art, the purpose of the present invention is to provide a method and system for identifying the multi-dimensional wear state of friction nanogenerator oil.

[0007] According to the present invention, a method for identifying multi-dimensional wear state of friction nanogenerator oil is provided, comprising:

[0008] Step S1: Designing a dual-electrode friction nanogenerator to monitor the state of lubricating oil;

[0009] Step S2: Measure the lubricant status through machine learning or deep learning, analyze the specific lubricant components, and predict the machine wear status.

[0010] Preferably, in step S1:

[0011] The friction nanogenerator comprises a copper electrode and polytetrafluoroethylene;

[0012] The friction nanogenerator used for online monitoring of wear status is realized in an independent layer mode. The friction nanogenerator consists of two sheet-shaped copper electrodes distributed on a polytetrafluoroethylene sheet. Two copper electrodes with a length of 40 mm and a width of 20 mm and a distance of 10 mm are pasted up and down on a polytetrafluoroethylene sheet with a length of 40 mm and a width of 100 mm to form an independent layer friction nanogenerator, which generates a voltage signal based on the principles of friction electrification and electrostatic induction.

[0013] The copper electrode below was partially submerged when the oil rose. According to the electron transfer theory, the polytetrafluoroethylene surface and the oil formed bound charges due to the triboelectric effect. Due to the asymmetric distribution of charges, the potential between the two electrodes was unbalanced, and free electrons flowed from the upper electrode to the lower electrode until the friction nanogenerator was half submerged.

[0014] When the upper copper electrode is partially submerged in the oil, the potential distribution is balanced and the induced electrons flow back;

[0015] When the friction nanogenerator device is completely covered by oil, there is no potential difference between the two electrodes and the induced charge completely disappears.

[0016] Preferably, in step S2:

[0017] Open circuit voltage of triboelectric nanogenerator under different water mass fractions:

[0018] Different mass fractions of water were added to the experimental lubricating oil. As the water mass fraction increased, the open circuit voltage of the friction nanogenerator gradually increased, and the friction nanogenerator realized the monitoring of water in the lubricating oil.

[0019] Preferably, in step S2:

[0020] Open circuit voltage of triboelectric nanogenerator under different carbon deposit contents:

[0021] As the carbon deposit content increases, the voltage output signal first increases and then decreases. The friction nanogenerator can detect when carbon deposits just appear in the oil, and the friction nanogenerator realizes the monitoring of pollutants as carbon deposits.

[0022] Preferably, in step S2:

[0023] Open circuit voltage of triboelectric nanogenerator under different iron content:

[0024] As the iron content increases, the voltage output signal increases first and then decreases. The friction nanogenerator can detect when iron just appears in the oil, and the friction nanogenerator can monitor the pollutant as iron.

[0025] After monitoring, the friction nanogenerator transmits the generated voltage signal wirelessly to the computer terminal. Through preliminary tests, the voltage output of pollutant content in each working condition is learned. Combined with the current voltage output, the components and mass fractions of each pollutant are automatically identified through deep learning or machine learning.

[0026] After analyzing the current pollutant components and mass fractions, the wear status of the machine is predicted and warned based on the current voltage or component change trends. When the voltage or the mass fraction of a certain component is greater than the preset threshold, the alarm system automatically starts, and the staff maintains the machine and replaces the lubricant.

[0027] According to the present invention, a multi-dimensional wear state identification system based on friction nanogenerator oil is provided, comprising:

[0028] Module M1: Design a dual-electrode friction nanogenerator to monitor the lubricating oil status;

[0029] Module M2: Measure the lubricant status through machine learning or deep learning, analyze the specific lubricant components, and predict the machine wear status.

[0030] Preferably, in the module M1:

[0031] The friction nanogenerator comprises a copper electrode and polytetrafluoroethylene;

[0032] The friction nanogenerator used for online monitoring of wear status is realized in an independent layer mode. The friction nanogenerator consists of two sheet-shaped copper electrodes distributed on a polytetrafluoroethylene sheet. Two copper electrodes with a length of 40 mm and a width of 20 mm and a distance of 10 mm are pasted up and down on a polytetrafluoroethylene sheet with a length of 40 mm and a width of 100 mm to form an independent layer friction nanogenerator, which generates a voltage signal based on the principles of friction electrification and electrostatic induction.

[0033] The copper electrode below was partially submerged when the oil rose. According to the electron transfer theory, the polytetrafluoroethylene surface and the oil formed bound charges due to the triboelectric effect. Due to the asymmetric distribution of charges, the potential between the two electrodes was unbalanced, and free electrons flowed from the upper electrode to the lower electrode until the friction nanogenerator was half submerged.

[0034] When the upper copper electrode is partially submerged in the oil, the potential distribution is balanced and the induced electrons flow back;

[0035] When the friction nanogenerator device is completely covered by oil, there is no potential difference between the two electrodes and the induced charge completely disappears.

[0036] Preferably, in the module M2:

[0037] Open circuit voltage of triboelectric nanogenerator under different water mass fractions:

[0038] Different mass fractions of water were added to the experimental lubricating oil. As the water mass fraction increased, the open circuit voltage of the friction nanogenerator gradually increased, and the friction nanogenerator realized the monitoring of water in the lubricating oil.

[0039] Preferably, in the module M2:

[0040] Open circuit voltage of triboelectric nanogenerator under different carbon deposit contents:

[0041] As the carbon deposit content increases, the voltage output signal first increases and then decreases. The friction nanogenerator can detect when carbon deposits just appear in the oil, and the friction nanogenerator realizes the monitoring of pollutants as carbon deposits.

[0042] Preferably, in the module M2:

[0043] Open circuit voltage of triboelectric nanogenerator under different iron content:

[0044] As the iron content increases, the voltage output signal increases first and then decreases. The friction nanogenerator can detect when iron just appears in the oil, and the friction nanogenerator can monitor the pollutant as iron.

[0045] After monitoring, the friction nanogenerator transmits the generated voltage signal wirelessly to the computer terminal. Through preliminary tests, the voltage output of pollutant content in each working condition is learned. Combined with the current voltage output, the components and mass fractions of each pollutant are automatically identified through deep learning or machine learning.

[0046] After analyzing the current pollutant components and mass fractions, the wear status of the machine is predicted and warned based on the current voltage or component change trends. When the voltage or the mass fraction of a certain component is greater than the preset threshold, the alarm system automatically starts, and the staff maintains the machine and replaces the lubricant.

[0047] Compared with the prior art, the present invention has the following beneficial effects:

[0048] 1. The present invention can realize the coordinated identification of multiple pollutants and can analyze the content of pollutants such as water, iron filings, and carbon deposits in lubricating oil;

[0049] 2. The friction nanogenerator is a self-powered device that can generate charge transfer through friction between lubricating oil and itself, without the need for external power supply;

[0050] 3. The friction nanogenerator has high sensitivity and can sense tiny changes in the state of lubricating oil. It can detect tiny lubricating oil leaks, impurity contamination or oil aging, helping to detect potential failures early and take preventive measures, thereby improving the reliability and life of the equipment;

[0051] 4. The friction nanogenerator has a simple structure and is easy to manufacture, so it can be easily embedded in the lubricating oil system without taking up too much space;

[0052] 5. The present invention solves the problems of difficulty in online monitoring and prediction of the wear state of the machine in the existing wear process;

[0053] 6. The present invention proposes a method for identifying multi-dimensional wear states of oil based on friction nanogenerators, aiming to expand the boundaries of existing technologies and achieve accurate monitoring and prediction of wear states. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0055] Figure 1 This is a simplified diagram of the structure of the friction nanogenerator;

[0056] Figure 2 Schematic diagram of the multi-dimensional wear state identification system of oil based on friction nanogenerator;

[0057] Figure 3 Schematic diagram of the working principle of the friction nanogenerator;

[0058] Figure 4 This is a schematic diagram of the voltage output signal when the lubricating oil and water are mixed in different proportions;

[0059] Figure 5 This is a schematic diagram of the voltage output signal when the lubricating oil and carbon deposits are mixed in different proportions;

[0060] Figure 6 This is a schematic diagram of the voltage output signal when lubricating oil and iron chips are mixed in different proportions. DETAILED DESCRIPTION

[0061] The present invention is described in detail below in conjunction with specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but are not intended to limit the present invention in any form. It should be noted that, for those of ordinary skill in the art, several changes and improvements can also be made without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0062] Embodiment 1:

[0063] The present invention aims to solve the problem that the wear status is difficult to monitor online during the operation of the machine, and proposes a multi-dimensional wear status identification method for oil based on friction nanogenerators, which realizes self-powered online monitoring of the oil.

[0064] The present invention discloses a multi-dimensional wear state identification method of oil based on friction nanogenerator, which is mainly used for monitoring the wear state of friction pairs during machine operation. Different components of lubricating oil generate different voltages through friction nanogenerator, thus providing a self-powered, simple online monitoring device and method.

[0065] According to the present invention, a multi-dimensional wear state identification method based on friction nanogenerator oil is provided. Figure 1-Figure 6 As shown, including:

[0066] Step S1: Designing a dual-electrode friction nanogenerator to monitor the state of lubricating oil;

[0067] Specifically, in step S1:

[0068] The friction nanogenerator comprises a copper electrode and polytetrafluoroethylene;

[0069] The friction nanogenerator used for online monitoring of wear status is realized in an independent layer mode. The friction nanogenerator consists of two sheet-shaped copper electrodes distributed on a polytetrafluoroethylene sheet. Two copper electrodes with a length of 40 mm and a width of 20 mm and a distance of 10 mm are pasted up and down on a polytetrafluoroethylene sheet with a length of 40 mm and a width of 100 mm to form an independent layer friction nanogenerator, which generates a voltage signal based on the principles of friction electrification and electrostatic induction.

[0070] The copper electrode below was partially submerged when the oil rose. According to the electron transfer theory, the polytetrafluoroethylene surface and the oil formed bound charges due to the triboelectric effect. Due to the asymmetric distribution of charges, the potential between the two electrodes was unbalanced, and free electrons flowed from the upper electrode to the lower electrode until the friction nanogenerator was half submerged.

[0071] When the upper copper electrode is partially submerged in the oil, the potential distribution is balanced and the induced electrons flow back;

[0072] When the friction nanogenerator device is completely covered by oil, there is no potential difference between the two electrodes and the induced charge completely disappears.

[0073] Step S2: Measure the lubricant status through machine learning or deep learning, analyze the specific lubricant components, and predict the machine wear status.

[0074] Specifically, in step S2:

[0075] Open circuit voltage of triboelectric nanogenerator under different water mass fractions:

[0076] Different mass fractions of water were added to the experimental lubricating oil. As the water mass fraction increased, the open circuit voltage of the friction nanogenerator gradually increased, and the friction nanogenerator realized the monitoring of water in the lubricating oil.

[0077] Specifically, in step S2:

[0078] Open circuit voltage of triboelectric nanogenerator under different carbon deposit contents:

[0079] As the carbon deposit content increases, the voltage output signal first increases and then decreases. The friction nanogenerator can detect when carbon deposits just appear in the oil, and the friction nanogenerator realizes the monitoring of pollutants as carbon deposits.

[0080] Specifically, in step S2:

[0081] Open circuit voltage of triboelectric nanogenerator under different iron content:

[0082] As the iron content increases, the voltage output signal increases first and then decreases. The friction nanogenerator can detect when iron just appears in the oil, and the friction nanogenerator can monitor the pollutant as iron.

[0083] After monitoring, the friction nanogenerator transmits the generated voltage signal wirelessly to the computer terminal. Through preliminary tests, the voltage output of pollutant content in each working condition is learned. Combined with the current voltage output, the components and mass fractions of each pollutant are automatically identified through deep learning or machine learning.

[0084] After analyzing the current pollutant components and mass fractions, the wear status of the machine is predicted and warned based on the current voltage or component change trends. When the voltage or the mass fraction of a certain component is greater than the preset threshold, the alarm system automatically starts, and the staff maintains the machine and replaces the lubricant.

[0085] Embodiment 2:

[0086] Embodiment 2 is a preferred example of Embodiment 1, and is used to illustrate the present invention in more detail.

[0087] The present invention also provides a multi-dimensional wear state identification system based on friction nanogenerator oil. The multi-dimensional wear state identification system based on friction nanogenerator oil can be realized by executing the process steps of the multi-dimensional wear state identification method based on friction nanogenerator oil, that is, those skilled in the art can understand the multi-dimensional wear state identification method based on friction nanogenerator oil as a preferred implementation of the multi-dimensional wear state identification system based on friction nanogenerator oil.

[0088] According to the present invention, a multi-dimensional wear state identification system based on friction nanogenerator oil is provided, comprising:

[0089] Module M1: Design a dual-electrode friction nanogenerator to monitor the lubricating oil status;

[0090] Specifically, in the module M1:

[0091] The friction nanogenerator comprises a copper electrode and polytetrafluoroethylene;

[0092] The friction nanogenerator used for online monitoring of wear status is realized in an independent layer mode. The friction nanogenerator consists of two sheet-shaped copper electrodes distributed on a polytetrafluoroethylene sheet. Two copper electrodes with a length of 40 mm and a width of 20 mm and a distance of 10 mm are pasted up and down on a polytetrafluoroethylene sheet with a length of 40 mm and a width of 100 mm to form an independent layer friction nanogenerator, which generates a voltage signal based on the principles of friction electrification and electrostatic induction.

[0093] The copper electrode below was partially submerged when the oil rose. According to the electron transfer theory, the polytetrafluoroethylene surface and the oil formed bound charges due to the triboelectric effect. Due to the asymmetric distribution of charges, the potential between the two electrodes was unbalanced, and free electrons flowed from the upper electrode to the lower electrode until the friction nanogenerator was half submerged.

[0094] When the upper copper electrode is partially submerged in the oil, the potential distribution is balanced and the induced electrons flow back;

[0095] When the friction nanogenerator device is completely covered by oil, there is no potential difference between the two electrodes and the induced charge completely disappears.

[0096] Module M2: Measure the lubricant status through machine learning or deep learning, analyze the specific lubricant components, and predict the machine wear status.

[0097] Specifically, in the module M2:

[0098] Open circuit voltage of triboelectric nanogenerator under different water mass fractions:

[0099] Different mass fractions of water were added to the experimental lubricating oil. As the water mass fraction increased, the open circuit voltage of the friction nanogenerator gradually increased, and the friction nanogenerator realized the monitoring of water in the lubricating oil.

[0100] Specifically, in the module M2:

[0101] Open circuit voltage of triboelectric nanogenerator under different carbon deposit contents:

[0102] As the carbon deposit content increases, the voltage output signal first increases and then decreases. The friction nanogenerator can detect when carbon deposits just appear in the oil, and the friction nanogenerator realizes the monitoring of pollutants as carbon deposits.

[0103] Specifically, in the module M2:

[0104] Open circuit voltage of triboelectric nanogenerator under different iron content:

[0105] As the iron content increases, the voltage output signal increases first and then decreases. The friction nanogenerator can detect when iron just appears in the oil, and the friction nanogenerator can monitor the pollutant as iron.

[0106] After monitoring, the friction nanogenerator transmits the generated voltage signal wirelessly to the computer terminal. Through preliminary tests, the voltage output of pollutant content in each working condition is learned. Combined with the current voltage output, the components and mass fractions of each pollutant are automatically identified through deep learning or machine learning.

[0107] After analyzing the current pollutant components and mass fractions, the wear status of the machine is predicted and warned based on the current voltage or component change trends. When the voltage or the mass fraction of a certain component is greater than the preset threshold, the alarm system automatically starts, and the staff maintains the machine and replaces the lubricant.

[0108] Embodiment 3:

[0109] Embodiment 3 is a preferred example of Embodiment 1, and is used to illustrate the present invention in more detail.

[0110] The technical solution of the present invention is:

[0111] A method for multi-dimensional wear state identification of oil based on friction nanogenerators, which monitors the state of lubricating oil by designing a new type of friction nanogenerator with two electrodes, and predicts the state of lubricating oil by machine learning or deep learning methods, analyzes the specific components of lubricating oil and predicts the wear state of the machine. Under this patent, accurate identification of lubricating oil and wear state can be achieved.

[0112] See also Figure 1 , which is a schematic diagram of the friction nanogenerator of the present invention, Figure 2 The figure is a physical display of a friction nanogenerator. The friction nanogenerator mainly includes a copper electrode and polytetrafluoroethylene.

[0113] The friction nanogenerator used for online monitoring of wear status can be realized in an independent layer mode. This friction nanogenerator is composed of two sheet-shaped copper electrodes distributed on a polytetrafluoroethylene sheet. Two 40mm×20mm copper tapes are 10mm apart and pasted on a 40mm×100mm polytetrafluoroethylene sheet. This friction nanogenerator is simple and convenient in design. The monitoring system composed of it is easy to install and disassemble. It is also a self-powered system that uses the triboelectric effect for monitoring and partially converts mechanical energy into electrical energy. It has a promising future.

[0114] The working principle of the constructed friction nanogenerator is shown in Figure 3. Two copper electrodes are glued to the polytetrafluoroethylene sheet at a certain distance to form an independent layer friction nanogenerator. The voltage signal is generated based on the principle of friction electrification and electrostatic induction. The copper electrode below is partially submerged when the oil rises. According to the electron transfer theory, the polytetrafluoroethylene surface and the oil form a part of the bound charge due to the triboelectric effect. Therefore, due to the asymmetric distribution of charge, the potential between the two electrodes is unbalanced, which prompts free electrons to flow from the upper electrode to the lower electrode until the friction nanogenerator is half submerged. Figure 3 This corresponds to the state where the induced charge on the electrode is the largest. When the upper electrode is partially submerged in the oil, the induced electrons flow back because the potential distribution tends to be balanced. Finally, when the device is completely covered by the oil, there is no potential difference between the two electrodes. Therefore, the induced charge disappears completely, such as Figure 3 .

[0115] Open circuit voltage of triboelectric nanogenerator under different water mass fractions:

[0116] In order to simulate the corresponding working conditions, different mass fractions of water are artificially added to the test lubricating oil. When the machine is running, the influence and harm of water on the machine is huge. Water can increase the freezing point of the lubricating oil, reduce the boiling point of the lubricating oil, is not conducive to the flow of the lubricating oil at low temperatures, and produces bubbles at high temperatures; in the presence of water, the thickness of the oil film formed by the lubricating oil will be significantly reduced, and the protectiveness of the lubricating oil will be reduced; the lubricating oil mixed with water can easily cause the machinery and equipment to rust and oxidize. The water contained in the lubricating oil will also cause the dissolution of various additives in the lubricating oil, so that the oil is no longer acid-base neutral, which will accelerate the failure of the oil.

[0117] like Figure 4 As shown in the figure, with the increase of water mass fraction, the open circuit voltage of the triboelectric nanogenerator gradually increases. This shows that the increase of water will lead to the increase of voltage output, and the triboelectric nanogenerator can realize the monitoring of water in lubricating oil.

[0118] Open circuit voltage of triboelectric nanogenerator under different carbon deposit contents:

[0119] In the combustion box of some large engines of cars and ships, the fuel cannot be completely burned due to lack of oxygen or water intrusion, which will produce carbon black particles. The lubricating oil with particles undergoes a chemical reaction in the combustion chamber to form granular carbon deposits that adhere to the surface of the machine and mix in the lubricating oil, affecting the normal operation of the machine.

[0120] When carbon deposits reach a certain threshold, the oil film in the lubrication system will be destroyed, and the lubrication effect will be reduced. At the same time, the increase in carbon deposits will make large engines more unable to fully absorb fuel, resulting in reduced power and increased fuel consumption.

[0121] like Figure 5 As shown in the figure, as the carbon deposit content increases, the voltage output signal first increases and then decreases. This shows that the friction nanogenerator can detect carbon deposits as soon as they appear in the oil. Therefore, the constructed friction nanogenerator can monitor the pollutants as carbon deposits.

[0122] Open circuit voltage of triboelectric nanogenerator under different iron content:

[0123] Grinding chips in the oil circuit may cause wear to the machine. The lubricating oil moves with the grinding chips and produces friction with the surface of the machine. At this time, it is like a turning tool cutting on the surface of the machine, which will generate more debris and increase the harm to the machine. In the high-speed running lubricating oil, the grinding chips have extremely high kinetic energy with the movement of the lubricating oil, and have a large momentum when impacting the machine. According to the momentum theorem, the force loaded on the machine will be very large, which will cause material wear on the surface of the machine. When the grinding chips in the lubricating oil reach a certain content, the oil film of the lubricating oil is destroyed, and the protection of the lubricating oil is lost between the machines, thus forming dry friction and increasing the harm.

[0124] like Figure 6 As shown in the figure, as the iron content increases, the voltage output signal increases first and then decreases. This shows that the friction nanogenerator can detect iron filings as soon as they appear in the oil. Therefore, the constructed friction nanogenerator can monitor the contaminants as iron filings.

[0125] After monitoring, the friction nanogenerator will wirelessly transmit the generated voltage signal to the computer terminal. Through preliminary experiments, the voltage output of several classic working conditions of pollutant content is known, and combined with the current voltage output, the components and mass fractions of the classic pollutants are automatically identified through deep learning or machine learning.

[0126] After analyzing the current pollutant components and mass fractions, the wear status of the machine can also be predicted and warned based on the current voltage or component change trends. When the voltage or the mass fraction of a certain component is greater than a certain threshold, the alarm system will automatically start, and the staff will maintain the machine and replace the lubricant.

[0127] Those skilled in the art know that, in addition to implementing the system, device and its various modules provided by the present invention in a purely computer-readable program code, it is entirely possible to implement the same program in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers and embedded microcontrollers by logically programming the method steps. Therefore, the system, device and its various modules provided by the present invention can be considered as a hardware component, and the modules included therein for implementing various programs can also be considered as structures within the hardware component; the modules for implementing various functions can also be considered as both software programs for implementing the method and structures within the hardware component.

[0128] The above describes the specific embodiments of the present invention. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art can make various changes or modifications within the scope of the claims, which does not affect the essence of the present invention. In the absence of conflict, the embodiments of the present application and the features in the embodiments can be combined with each other arbitrarily.

Claims

1. A method for identifying multi-dimensional wear state of friction nanogenerator oil, characterized in that: include: Step S1: Designing a dual-electrode friction nanogenerator to monitor the state of lubricating oil; Step S2: measuring the lubricant status through machine learning or deep learning, analyzing the specific lubricant components, and predicting the wear status of the machine; In step S1: The friction nanogenerator comprises a copper electrode and polytetrafluoroethylene; The friction nanogenerator used for online monitoring of wear status is realized in an independent layer mode. The friction nanogenerator consists of two sheet-shaped copper electrodes distributed on a polytetrafluoroethylene sheet. Two copper electrodes with a length of 40 mm and a width of 20 mm and a distance of 10 mm are pasted up and down on a polytetrafluoroethylene sheet with a length of 40 mm and a width of 100 mm to form an independent layer friction nanogenerator, which generates a voltage signal based on the principles of friction electrification and electrostatic induction. The copper electrode below was partially submerged when the oil rose. According to the electron transfer theory, the polytetrafluoroethylene surface and the oil formed bound charges due to the triboelectric effect. Due to the asymmetric distribution of charges, the potential between the two electrodes was unbalanced, and free electrons flowed from the upper electrode to the lower electrode until the friction nanogenerator was half submerged. When the upper copper electrode is partially submerged in the oil, the potential distribution is balanced and the induced electrons flow back; When the triboelectric nanogenerator device is completely covered by oil, there is no potential difference between the two electrodes and the induced charge disappears completely; After analyzing the current pollutant components and mass fractions, the wear status of the machine is predicted and warned according to the current voltage or component change trend. When the voltage or the mass fraction of a certain component is greater than the preset threshold, the alarm system automatically starts, and the staff maintains the machine and replaces the lubricant. Among them, the multiple dimensions include moisture, iron filings and carbon deposits.

2. The multi-dimensional wear state identification method based on friction nanogenerator oil according to claim 1 is characterized in that: In step S2: Open circuit voltage of triboelectric nanogenerator under different water mass fractions: Different mass fractions of water were added to the experimental lubricating oil. As the water mass fraction increased, the open circuit voltage of the friction nanogenerator gradually increased, and the friction nanogenerator realized the monitoring of water in the lubricating oil.

3. The multi-dimensional wear state identification method based on friction nanogenerator oil according to claim 1 is characterized in that: In step S2: Open circuit voltage of triboelectric nanogenerator under different carbon deposit contents: As the carbon deposit content increases, the voltage output signal first increases and then decreases. The friction nanogenerator can detect when carbon deposits just appear in the oil, and the friction nanogenerator realizes the monitoring of pollutants as carbon deposits.

4. The multi-dimensional wear state identification method based on friction nanogenerator oil according to claim 1 is characterized in that: In step S2: Open circuit voltage of triboelectric nanogenerator under different iron content: As the iron content increases, the voltage output signal increases first and then decreases. The friction nanogenerator can detect when iron just appears in the oil, and the friction nanogenerator can monitor the pollutant as iron. After monitoring, the friction nanogenerator will wirelessly transmit the generated voltage signal to the computer terminal. Through preliminary tests, the voltage output of the pollutant content in each working condition can be understood. Combined with the current voltage output, the components and mass fractions of each pollutant can be automatically identified through deep learning or machine learning.

5. A multi-dimensional wear state identification system based on friction nanogenerator oil, characterized in that: The method for identifying the multi-dimensional wear state of the friction nanogenerator oil according to any one of claims 1 to 4 comprises: Module M1: Design a dual-electrode friction nanogenerator to monitor the lubricating oil status; Module M2: Measure the lubricant status through machine learning or deep learning, analyze the specific lubricant components, and predict the machine wear status; In the module M1: The friction nanogenerator comprises a copper electrode and polytetrafluoroethylene; The friction nanogenerator used for online monitoring of wear status is realized in an independent layer mode. The friction nanogenerator consists of two sheet-shaped copper electrodes distributed on a polytetrafluoroethylene sheet. Two copper electrodes with a length of 40 mm and a width of 20 mm and a distance of 10 mm are pasted up and down on a polytetrafluoroethylene sheet with a length of 40 mm and a width of 100 mm to form an independent layer friction nanogenerator, which generates a voltage signal based on the principles of friction electrification and electrostatic induction. The copper electrode below was partially submerged when the oil rose. According to the electron transfer theory, the polytetrafluoroethylene surface and the oil formed bound charges due to the triboelectric effect. Due to the asymmetric distribution of charges, the potential between the two electrodes was unbalanced, and free electrons flowed from the upper electrode to the lower electrode until the friction nanogenerator was half submerged. When the upper copper electrode is partially submerged in the oil, the potential distribution is balanced and the induced electrons flow back; When the triboelectric nanogenerator device is completely covered by oil, there is no potential difference between the two electrodes and the induced charge disappears completely; After analyzing the current pollutant components and mass fractions, the wear status of the machine is predicted and warned according to the current voltage or component change trend. When the voltage or the mass fraction of a certain component is greater than the preset threshold, the alarm system automatically starts, and the staff maintains the machine and replaces the lubricant. Among them, the multiple dimensions include moisture, iron filings and carbon deposits.

6. The multi-dimensional wear state identification system based on friction nanogenerator oil according to claim 5 is characterized in that: In the module M2: Open circuit voltage of triboelectric nanogenerator under different water mass fractions: Different mass fractions of water were added to the experimental lubricating oil. As the water mass fraction increased, the open circuit voltage of the friction nanogenerator gradually increased, and the friction nanogenerator realized the monitoring of water in the lubricating oil.

7. The multi-dimensional wear state identification system based on friction nanogenerator oil according to claim 5 is characterized in that: In the module M2: Open circuit voltage of triboelectric nanogenerator under different carbon deposit contents: As the carbon deposit content increases, the voltage output signal first increases and then decreases. The friction nanogenerator can detect when carbon deposits just appear in the oil, and the friction nanogenerator realizes the monitoring of pollutants as carbon deposits.

8. The multi-dimensional wear state identification system based on friction nanogenerator oil according to claim 5 is characterized in that: In the module M2: Open circuit voltage of triboelectric nanogenerator under different iron content: As the iron content increases, the voltage output signal increases first and then decreases. The friction nanogenerator can detect when iron just appears in the oil, and the friction nanogenerator can monitor the pollutant as iron. After monitoring, the friction nanogenerator will wirelessly transmit the generated voltage signal to the computer terminal. Through preliminary tests, the voltage output of the pollutant content in each working condition can be understood. Combined with the current voltage output, the components and mass fractions of each pollutant can be automatically identified through deep learning or machine learning.

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