Gearbox fault early warning method and system based on oil sample online analysis

Abstract

The invention discloses a gearbox fault early warning method and system based on oil sample online analysis, and relates to the technical field of gearbox fault early warning, the system comprises an oil sample extraction module, an oil sample analysis module, a data processing module, an analysis and judgment module and an early warning generation module; the oil sample extraction module is used for extracting gearbox lubricating oil as an oil sample at a fixed frequency; analyzing components in the extracted oil sample through the oil sample analysis module, detecting the abrasive particle concentration and the particle size in the oil sample, and analyzing the particle uniformity; the data processing module is used for setting a critical value of a gear in a gear box in a normal wear state; the concentration, the particle size and the particle uniformity of the abrasive particles in the oil sample are compared with critical values through the analysis and judgment module, and an early warning instruction is generated; a corresponding fault early warning is generated through the early warning generation module according to the instruction; by analyzing the components of the oil sample, the gear wear degree can be more accurately judged, and early warning is generated in time.

Description

Technical Field

[0001] The present invention relates to the technical field of gearbox fault warning, and in particular to a gearbox fault warning method and system based on online oil sample analysis. Background Art

[0002] In a wind turbine, the gearbox is the core component of the wind turbine. Its main function is to transmit the rotational power of the wind wheel to the generator to realize the conversion of wind power and electrical energy. Because the gearbox operates in a high temperature, high humidity and high load working environment for a long time, it is easy to fail. If it is not discovered in time, it will seriously affect the operating efficiency and stability of the wind turbine. Therefore, studying the method of timely detection and early warning of gearbox failures is of great significance to maintaining the normal operation of wind turbines.

[0003] There are many methods currently available for determining gearbox failures, including vibration signal analysis methods and temperature signal analysis methods. These methods can determine the status of gearbox components through sensors to determine whether the gearbox has failed. There are still some problems that need to be solved in the current technology, such as the need to improve the accuracy of fault judgment and the timeliness of early warning, especially in terms of gear wear. The degree of gear wear may not be accurately determined by vibration signals in order to provide early warning of faults. Therefore, a method that can more accurately determine the degree of gear wear is currently needed. Summary of the invention

[0004] The object of the present invention is to provide a gearbox fault early warning method and system based on online analysis of oil samples to solve the problems raised in the prior art.

[0005] To achieve the above object, the present invention provides the following technical solutions: a gearbox fault warning system based on online oil sample analysis, the system comprising an oil sample extraction module, an oil sample analysis module, a data processing module, an analysis and judgment module and a warning generation module;

[0006] The gear lubricating oil is extracted as an oil sample at a fixed frequency by the oil sample extraction module;

[0007] Analyzing the components in the extracted oil sample by the oil sample analysis module, detecting the concentration of abrasive particles and the particle size of the abrasive particles contained therein, and analyzing the particle uniformity of the abrasive particles;

[0008] The data processing module is used to set the critical value of the abrasive particle concentration in the lubricating oil, the critical value of the abrasive particle size and the critical value of the particle uniformity when the gears in the gear box are in a normal wear state;

[0009] The analysis and judgment module compares the abrasive particle concentration, abrasive particle size and abrasive particle uniformity in the extracted oil sample with the set critical value to determine whether the gearbox fails and generate a corresponding warning instruction;

[0010] The warning generation module generates a gearbox fault warning according to the instruction.

[0011] Furthermore, the oil sample extraction module extracts the lubricating oil of the gearbox as an oil sample at a fixed frequency, and stores the oil sample in an oil sample analyzer for further processing; the oil sample analyzer can analyze whether the oil sample contains abrasive particles generated by gear wear through spectral analysis and iron spectrum analysis, and analyze parameters such as the concentration of magic and the particle size of the abrasive particles for subsequent analysis and processing.

[0012] Furthermore, the oil sample analysis module analyzes and processes the oil sample extracted from the lubricating oil of the gear, mainly analyzes the composition of the oil sample to determine whether there are abrasive particles generated by wear of gear components, detects the concentration of the abrasive particles in the oil sample, analyzes the particle size of the abrasive particles, and analyzes the uniformity of the particle size of the abrasive particles, generates and saves data on the concentration of the abrasive particles, the particle size of the abrasive particles, and the particle uniformity of the abrasive particles. These data are used for subsequent analysis and processing and the wear state of the gear and the severity of the gear wear are determined based on the analysis results.

[0013] Furthermore, the data processing module sets a critical value of relevant data of abrasive particles in the oil sample when the gearbox is in a normal wear state, that is, a gear wear state that will not cause the gearbox to malfunction; a model is established to analyze the degree of gear wear of the gearbox through the concentration data of the abrasive particles in the oil sample, and a critical value is set as a standard for comparative analysis. Under the normal wear state of the gear, the critical value of the gear wear degree that requires an early warning is set to G0, and the corresponding critical value of the abrasive concentration is L0.

[0014] Furthermore, the comparative analysis module compares the abrasive concentration analyzed from the oil sample with the critical abrasive concentration in the oil sample corresponding to the critical value of the gear wear degree for which an early warning is required, and then compares the abrasive particle size and particle uniformity with the critical value of the abrasive particle size and particle uniformity generated by the gearbox under normal wear conditions, and analyzes and judges the degree of gearbox failure based on the comparison results, and generates an early warning instruction based on the judgment result.

[0015] Furthermore, the warning generation module generates warning information according to the generated warning instruction. If the abrasive concentration exceeds the critical value, a red warning indicator light will be turned on; if the particle size of the abrasive exceeds the critical value, a yellow warning indicator light will be turned on; if the particle uniformity of the abrasive exceeds the critical value, a blue warning indicator light will be turned on; when the three warning lights are on at the same time, the buzzer alarm will be triggered at the same time.

[0016] A gearbox fault early warning method based on online oil sample analysis comprises the following steps:

[0017] S1: Extract gear lubricating oil as oil sample at a fixed frequency;

[0018] S2: Detect the concentration and particle size of abrasive particles in the oil sample, and analyze the particle uniformity of the abrasive particles;

[0019] S3: Compare and analyze the abrasive particle concentration, abrasive particle size and abrasive particle uniformity collected in the oil sample with the set critical value to determine whether the gear has abnormal wear;

[0020] S4: Generate corresponding warning information based on the comparative analysis results.

[0021] Further, in step S2: analyzing the components in the extracted oil sample to detect whether it contains abrasive particles generated by gearbox wear, and detecting the concentration L of the abrasive particles and the particle size x of the abrasive particles. i ; and according to the formula:

[0022]

[0023]

[0024] Wherein, i=1, 2, 3...n, i represents the serial number of different abrasive particles in the oil sample, and n represents the total number of abrasive particles in the oil sample. The particle uniformity W of the abrasive particles can be analyzed according to the above formula.

[0025] Further, in step S3: a model is established to represent the relationship between the abrasive concentration in the oil sample and the degree of wear of the gear; there is a linear relationship between the abrasive concentration and the degree of wear of the gearbox gears, and the relationship between the two is analyzed using historical data to establish a relationship model between the abrasive concentration and the degree of wear of the gears:

[0026] Y = A + BX;

[0027] Among them, Y represents the gear wear degree of the gearbox, X represents the abrasive concentration in the oil sample, A and B are constant coefficients, and this model represents the relationship between the abrasive concentration in the oil sample and the gear wear degree of the gearbox; the gear wear degree is detected by the vibration signal analysis method, and under the normal wear state of the gearbox, that is, the gear wear degree does not cause the gearbox to fail, the critical value of the gear wear degree in the gearbox when a fault warning is required is set to G0, and it is brought into the above model, that is, Y=G0, and the critical abrasive concentration corresponding to the gear wear degree of the gearbox that requires a warning is L0:

[0028] The influence of the abrasive particles in the oil sample on the wear degree of the gearbox is judged by the particle size and particle uniformity of the abrasive particles in the oil sample. When the gear is in the normal wear state, the critical value of the abrasive particle size is x0, and the critical value of the particle uniformity of all abrasive particles is W0. The abrasive particle concentration extracted from the oil sample is compared with the critical abrasive particle concentration corresponding to the normal wear degree of the gearbox, and the particle size x i The critical particle diameter size x0 of the abrasive particles corresponding to the normal wear of the gearbox is compared; and the particle uniformity W of the abrasive particles in the oil sample is compared with the critical value W0 of the particle uniformity of the abrasive particles to determine whether an early warning needs to be generated and the type of early warning to be generated.

[0029] Further, in step S4: an early warning is generated according to the comparative analysis results. If the abrasive concentration exceeds the critical value of the abrasive concentration, a red early warning indicator light is on; if the abrasive particle size exceeds the critical value of the abrasive particle size, a yellow early warning indicator light is on; if the abrasive particle uniformity exceeds the critical value of the abrasive particle uniformity, a blue early warning indicator light is on; when the three early warning lights are on at the same time, a buzzer alarm is triggered at the same time; and a corresponding early warning instruction is generated according to the comparative analysis results:

[0030] When L≤L0∩x i When ≤x0∩W≤W0, the gearbox wear degree is judged to be normal wear degree, and no warning instruction is generated;

[0031] When L>L0, it is judged that the concentration of abrasive particles in the lubricating oil of the gearbox is too high, and a warning instruction is generated to control the red warning indicator to light up;

[0032] When x i >x0, it is judged that the particle size of some abrasive particles in the lubricating oil of the gearbox is too large, and a warning instruction is generated to control the yellow warning indicator to light up;

[0033] when When the gearbox is in a state of poor uniformity of abrasive particles in the lubricating oil, a warning instruction is generated to control the blue warning indicator to light up;

[0034] When L>L0∩x i >x0∩W>W0, that is, when all three indicator lights are on, the gearbox is judged to be in a state of severe wear, a buzzer alarm command is generated, and the buzzer is controlled to sound for emergency warning.

[0035] Compared with the prior art, the present invention has the following beneficial effects:

[0036] 1. The present invention extracts the gear lubricating oil in the gear box for oil sample analysis, and judges the wear state of the gear from the oil sample analysis result, so as to achieve the effect of more accurate and timely detection of gear box failure and early warning.

[0037] 2. The present invention is equipped with two warning means, namely indicator light warning and buzzer warning. Different warning types can more accurately determine the degree of wear of the gears in the gearbox or the type of fault, making the fault judgment more efficient and accurate. The combination of buzzer and indicator light warning types makes the warning more timely. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is a structural schematic diagram of a gearbox fault early warning system based on online oil sample analysis of the present invention;

[0039] Figure 2 The present invention is a flow chart of a gearbox fault early warning method based on online oil sample analysis. DETAILED DESCRIPTION

[0040] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0041] like Figure 1-Figure 2 As shown, the present invention provides a technical solution, a gearbox fault warning system based on online oil sample analysis, the system includes an oil sample extraction module, an oil sample analysis module, a data processing module, an analysis and judgment module and a warning generation module;

[0042] The gear lubricating oil is extracted as an oil sample at a fixed frequency by the oil sample extraction module;

[0043] Analyzing the components in the extracted oil sample by the oil sample analysis module, detecting the concentration of abrasive particles and the particle size of the abrasive particles contained therein, and analyzing the particle uniformity of the abrasive particles;

[0044] The data processing module is used to set the critical value of the abrasive particle concentration in the lubricating oil, the critical value of the abrasive particle size and the critical value of the particle uniformity when the gears in the gear box are in a normal wear state;

[0045] The analysis and judgment module compares the abrasive particle concentration, abrasive particle size and abrasive particle uniformity in the extracted oil sample with the set critical value to determine whether the gearbox fails and generate a corresponding warning instruction;

[0046] The warning generation module generates a gearbox fault warning according to the instruction.

[0047] The oil sample extraction module extracts the lubricating oil of the gearbox as an oil sample at a fixed frequency, and stores the oil sample in an oil sample analyzer for further processing; the oil sample analyzer can analyze whether the oil sample contains abrasive particles generated by gear wear through spectral analysis and iron spectrum analysis, and analyze parameters such as the concentration of magic and the particle size of the abrasive particles for subsequent analysis and processing.

[0048] The oil sample analysis module analyzes and processes the oil sample extracted from the lubricating oil of the gear, mainly analyzing the composition of the oil sample to determine whether there are abrasive particles generated by wear of gear components, and detects the concentration of the abrasive particles in the oil sample, as well as analyzes the particle size of the abrasive particles and the uniformity of the particle size of the abrasive particles, generates and saves data on the concentration of the abrasive particles, the particle size of the abrasive particles and the particle uniformity of the abrasive particles. These data are used for subsequent analysis and processing and the wear state of the gear and the severity of the gear wear are determined based on the analysis results.

[0049] The data processing module sets a critical value of relevant data of abrasive particles in the oil sample when the gearbox is in a normal wear state, and the normal wear state of the gear is a gear wear state that will not cause the gearbox to malfunction; a model is established to analyze the degree of gear wear of the gearbox through the concentration data of the abrasive particles in the oil sample, and a critical value is set as a standard for comparative analysis. Under the normal wear state of the gear, the critical value of the gear wear degree that requires an early warning is set to G0, and the corresponding abrasive concentration critical value is L0.

[0050] The comparative analysis module compares the abrasive concentration analyzed from the oil sample with the critical abrasive concentration in the oil sample corresponding to the critical value of the gear wear degree for which an early warning is required, and then compares the abrasive particle size and particle uniformity with the critical value of the abrasive particle size and particle uniformity generated by the gearbox under normal wear conditions, and analyzes and judges the degree of gearbox failure based on the comparison results, and generates an early warning instruction based on the judgment result.

[0051] The warning generation module generates warning information according to the generated warning instruction. When the abrasive concentration exceeds the critical value, a red warning indicator light is turned on; when the particle size of the abrasive exceeds the critical value, a yellow warning indicator light is turned on; when the particle uniformity of the abrasive exceeds the critical value, a blue warning indicator light is turned on; when the three warning lights are on at the same time, the buzzer alarm is triggered at the same time.

[0052] A gearbox fault early warning method based on online oil sample analysis comprises the following steps:

[0053] S1: Extract gear lubricating oil as oil sample at a fixed frequency;

[0054] S2: Detect the concentration and particle size of abrasive particles in the oil sample, and analyze the particle uniformity of the abrasive particles;

[0055] S3: Compare and analyze the abrasive particle concentration, abrasive particle size and abrasive particle uniformity collected in the oil sample with the set critical value to determine whether the gear has abnormal wear;

[0056] S4: Generate corresponding warning information based on the comparative analysis results.

[0057] In step S2: Analyze the components in the extracted oil sample to detect whether it contains abrasive particles generated by gearbox wear, and detect the concentration L and particle size x of the abrasive particles. i ; and according to the formula:

[0058]

[0059] Wherein, i=1, 2, 3...n, i represents the serial number of different abrasive particles in the oil sample, and n represents the total number of abrasive particles in the oil sample. The particle uniformity W of the abrasive particles can be analyzed according to the above formula.

[0060] In step S3: a model is established to represent the relationship between the abrasive concentration in the oil sample and the degree of wear of the gears; there is a linear relationship between the abrasive concentration and the degree of wear of the gearbox gears, and the relationship between the two is analyzed using historical data to establish a relationship model between the abrasive concentration and the degree of wear of the gears:

[0061] Y = A + BX;

[0062] Among them, Y represents the gear wear degree of the gearbox, X represents the abrasive concentration in the oil sample, A and B are constant coefficients, and this model represents the relationship between the abrasive concentration in the oil sample and the gear wear degree of the gearbox; the gear wear degree is detected by the vibration signal analysis method, and under the normal wear state of the gearbox, that is, the gear wear degree does not cause the gearbox to fail, the critical value of the gear wear degree in the gearbox when a fault warning is required is set to G0, and it is brought into the above model, that is, Y=G0, and the critical abrasive concentration corresponding to the gear wear degree of the gearbox that requires a warning is L0:

[0063] The influence of the abrasive particles in the oil sample on the wear degree of the gearbox is judged by the particle size and particle uniformity of the abrasive particles in the oil sample. When the gear is in the normal wear state, the critical value of the abrasive particle size is x0, and the critical value of the particle uniformity of all abrasive particles is W0. The abrasive particle concentration extracted from the oil sample is compared with the critical abrasive particle concentration corresponding to the normal wear degree of the gearbox, and the particle size x i The critical particle diameter size x0 of the abrasive particles corresponding to the normal wear of the gearbox is compared; and the particle uniformity W of the abrasive particles in the oil sample is compared with the critical value W0 of the particle uniformity of the abrasive particles to determine whether an early warning needs to be generated and the type of early warning to be generated.

[0064] In step S4: an early warning is generated according to the comparative analysis results. If the abrasive concentration exceeds the critical value of the abrasive concentration, a red early warning indicator light is on; if the abrasive particle size exceeds the critical value of the abrasive particle size, a yellow early warning indicator light is on; if the abrasive particle uniformity exceeds the critical value of the abrasive particle uniformity, a blue early warning indicator light is on; when the three early warning lights are on at the same time, a buzzer alarm is triggered at the same time; a corresponding early warning instruction is generated according to the comparative analysis results:

[0065] When L≤L0∩x i When ≤x0∩W≤W0, the gearbox wear degree is judged to be normal wear degree, and no warning instruction is generated;

[0066] When L>L0, it is judged that the concentration of abrasive particles in the lubricating oil of the gearbox is too high, and a warning instruction is generated to control the red warning indicator to light up;

[0067] When x i >x0, it is judged that the particle size of some abrasive particles in the lubricating oil of the gearbox is too large, and a warning instruction is generated to control the yellow warning indicator to light up;

[0068] when When the gearbox is in a state of poor uniformity of abrasive particles in the lubricating oil, a warning instruction is generated to control the blue warning indicator to light up;

[0069] When L>L0∩x i >x0∩W>W0, that is, when all three indicator lights are on, the gearbox is judged to be in a state of severe wear, a buzzer alarm command is generated, and the buzzer is controlled to sound for emergency warning.

[0070] Embodiment 1:

[0071] A gearbox fault early warning method based on online oil sample analysis comprises the following steps:

[0072] S1: Gear lubricating oil is extracted as oil sample every 200 hours;

[0073] S2: Detect the concentration and particle size of abrasive particles in the oil sample, and analyze the particle uniformity of the abrasive particles;

[0074] S3: Compare and analyze the abrasive particle concentration, abrasive particle size and abrasive particle uniformity collected in the oil sample with the set critical value to determine whether the gear has abnormal wear;

[0075] S4: Generate corresponding warning information based on the comparative analysis results.

[0076] In step S2: Analyze the components in the extracted oil sample to detect whether it contains abrasive particles generated by gearbox wear, and detect the concentration of the abrasive particles L = 24 mg / mL and the particle size x of the abrasive particles.i ={3.2, 4.1, 3.8, 6.4, 7.3, 4.6}; and according to the formula:

[0077]

[0078] Among them, i=1, 2, 3, 4, 5, 6; according to the above formula, it can be analyzed that the particle uniformity of the abrasive particles is W=2.14.

[0079] In step S3: a model is established to represent the relationship between the abrasive concentration in the oil sample and the degree of wear of the gear; there is a linear relationship between the abrasive concentration and the degree of wear of the gearbox gears, and the linear relationship between the two is analyzed using historical data, and the relationship between the two is analyzed using historical data to establish a relationship model between the abrasive concentration and the degree of wear of the gears:

[0080] Y = A + BX;

[0081] Among them, Y represents the gear wear degree of the gearbox, X represents the abrasive concentration in the oil sample, A and B are constant coefficients, and this model can represent the relationship between the abrasive concentration in the oil sample and the gear wear degree of the gearbox; the gear wear degree is detected by the vibration signal analysis method, and the historical data of the abrasive concentration value extracted from the gearbox under normal conditions L′={10, 12, 14, 16}, the unit is mg / mL, and the corresponding gear wear degree value of the gearbox obtained by vibration signal analysis G′={5%, 6%, 7%, 8%} can be obtained to obtain the constant value in the above model, and the value of A is 0 and the value of B is 0.005; then the relationship model between the abrasive concentration and the gear wear degree can be expressed as:

[0082] Y = 0.005X;

[0083] Set in the normal wear state of the gearbox, that is, the gear wear degree does not cause the gear to fail, the critical value of the gear wear degree when a fault warning is required is G0=10%. Substitute it into the above model, that is, let Y=10%, and the critical abrasive concentration L0 corresponding to the gear wear degree that requires a warning is obtained: 20mg / mL.

[0084] The influence of the abrasive particles in the oil sample on the wear degree of the gearbox needs to be judged by the particle size and particle uniformity of the abrasive particles in the oil sample. The critical value of the abrasive particle size is set to x0 = 5μm, and the critical value of the particle uniformity of Magic is set to W0 = 0.3; the abrasive particle concentration extracted from the oil sample is compared with the critical value of the abrasive particle concentration corresponding to the normal wear degree of the gearbox, and the particle size of the abrasive particles x iThe particle size critical value x0=5 μm of the abrasive particles corresponding to normal wear of the gearbox is compared; and the particle uniformity W of the abrasive particles in the oil sample is compared with the particle uniformity critical value W0 of the abrasive particles to determine whether an early warning needs to be generated and the type of early warning to be generated.

[0085] In step S4: an early warning is generated according to the comparative analysis results. If the abrasive concentration exceeds the critical value of the abrasive concentration, a red early warning indicator light is on; if the abrasive particle size exceeds the critical value of the abrasive particle size, a yellow early warning indicator light is on; if the abrasive particle uniformity exceeds the critical value of the abrasive particle uniformity, a blue early warning indicator light is on; when the three early warning indicators light up at the same time, a buzzer alarm is triggered at the same time; a corresponding early warning instruction is generated according to the comparative analysis results. The comparative analysis results of this implementation case are as follows:

[0086] L=25mg / mL>L0=20mg / mL, indicating that the concentration of abrasive particles in the oil sample is too high and has exceeded the critical value, generating an instruction to light up the red warning indicator;

[0087] x i ={3.2, 4.1, 3.8, 6.4, 7.3, 4.6}, where the values ​​6.4 and 7.3 are greater than x0, indicating that the oil sample contains excessively large abrasive particles, and an instruction is generated to light up the yellow warning indicator light;

[0088] W=2.14>W0=0.3, indicating that the uniformity of the abrasive particles in the oil sample is very poor and the sizes are different, which exceeds the small and uniform standard in the normal wear state, and generates an instruction to light up the blue warning indicator;

[0089] Therefore, at this time, the red warning indicator light, the yellow warning indicator light, and the blue warning indicator light are all on, triggering the buzzer to sound an emergency warning, reminding the staff that the gears in the gearbox are in a state of severe wear and the fault needs to be dealt with urgently.

[0090] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

Claims

1. A gearbox fault early warning system based on online oil sample analysis, characterized in that: The system includes an oil sample extraction module, an oil sample analysis module, a data processing module, an analysis and judgment module, and an early warning generation module; The gear lubricating oil is extracted as an oil sample at a fixed frequency by the oil sample extraction module; Analyzing the components in the extracted oil sample by the oil sample analysis module, detecting the concentration of abrasive particles and the particle size of the abrasive particles contained therein, and analyzing the particle uniformity of the abrasive particles; The data processing module is used to set the critical value of the abrasive particle concentration in the lubricating oil, the critical value of the abrasive particle size and the critical value of the particle uniformity when the gears in the gear box are in a normal wear state; The analysis and judgment module compares the abrasive particle concentration, abrasive particle size and abrasive particle uniformity in the extracted oil sample with the set critical value to determine whether the gearbox fails and generate a corresponding warning instruction; The warning generation module generates a gearbox fault warning according to the instruction.

2. The gearbox fault early warning system based on online oil sample analysis according to claim 1 is characterized in that: The oil sample extraction module extracts lubricating oil from the gearbox as oil samples at a fixed frequency, and stores the oil samples in an oil sample analyzer for further processing.

3. The gearbox fault early warning system based on online oil sample analysis according to claim 1 is characterized in that: The oil sample analysis module analyzes and processes the oil sample extracted from the lubricating oil of the gear, analyzes the composition of the oil sample, determines whether there are abrasive particles generated by wear of the gear parts, detects the concentration of the abrasive particles in the oil sample and the particle size of the abrasive particles, analyzes the particle uniformity of the abrasive particles, generates and saves the data of the concentration, particle size and particle uniformity of the abrasive particles.

4. The gearbox fault early warning system based on online oil sample analysis according to claim 1 is characterized in that: The data processing module sets a critical value of relevant data of abrasive particles in the oil sample when the gearbox is in a normal wear state, and the normal wear state of the gear is a gear wear state that will not cause the gearbox to malfunction; a model is established to analyze the degree of gear wear of the gearbox through the concentration data of the abrasive particles in the oil sample, and a critical value is set as a standard for comparative analysis. Under the normal wear state of the gear, the critical value of the gear wear degree that requires an early warning is set to G0, and the corresponding abrasive concentration critical value is L0.

5. The gearbox fault early warning system based on online oil sample analysis according to claim 1 is characterized in that: The comparative analysis module compares the abrasive concentration analyzed from the oil sample with the critical abrasive concentration in the oil sample corresponding to the critical value of the gear wear degree for which an early warning is required, and then compares the abrasive particle size and particle uniformity with the critical value of the abrasive particle size and particle uniformity generated by the gearbox under normal wear conditions, and analyzes and judges the degree of gearbox failure based on the comparison results, and generates an early warning instruction based on the judgment result.

6. The gearbox fault early warning system based on online oil sample analysis according to claim 1 is characterized in that: The warning generation module generates warning information according to the generated warning instruction. When the abrasive concentration exceeds the critical value, a red warning indicator light is turned on; when the particle size of the abrasive exceeds the critical value, a yellow warning indicator light is turned on; when the particle uniformity of the abrasive exceeds the critical value, a blue warning indicator light is turned on; when the three warning lights are on at the same time, the buzzer alarm is triggered at the same time.

7. A gearbox fault early warning method based on online oil sample analysis, characterized in that: The following steps are involved: S1: Extract gear lubricating oil as oil sample at a fixed frequency; S2: Detect the concentration and particle size of abrasive particles in the oil sample, and analyze the particle uniformity of the abrasive particles; S3: Compare and analyze the abrasive particle concentration, abrasive particle size and abrasive particle uniformity collected in the oil sample with the set critical value to determine whether the gear has abnormal wear; S4: Generate corresponding warning information based on the comparative analysis results.

8. The gearbox fault early warning method based on online oil sample analysis according to claim 7 is characterized in that: In step S2: Analyze the components in the extracted oil sample to detect whether it contains abrasive particles generated by gearbox wear, and detect the concentration L and particle size x of the abrasive particles. i ; and according to the formula: Wherein, i=1, 2, 3...n, i represents the serial number of different abrasive particles in the oil sample, and n represents the total number of abrasive particles in the oil sample. The particle uniformity W of the abrasive particles can be analyzed according to the above formula.

9. The gearbox fault early warning method based on online oil sample analysis according to claim 8 is characterized in that: In step S3: a model is established to represent the relationship between the abrasive concentration in the oil sample and the degree of wear of the gears; there is a linear relationship between the abrasive concentration and the degree of wear of the gearbox gears, and the relationship between the two is analyzed using historical data to establish a relationship model between the abrasive concentration and the degree of wear of the gears: Y = A + BX; Among them, Y represents the gear wear degree of the gearbox, X represents the abrasive concentration in the oil sample, A and B are constant coefficients, and this model represents the relationship between the abrasive concentration in the oil sample and the gear wear degree of the gearbox; the gear wear degree is detected by the vibration signal analysis method, and under the normal wear state of the gearbox, that is, the gear wear degree does not cause the gearbox to fail, the critical value of the gear wear degree in the gearbox when a fault warning is required is set to G0, and it is brought into the above model, that is, Y=G0, and the critical abrasive concentration corresponding to the gear wear degree of the gearbox that requires a warning is L0: The influence of the abrasive particles in the oil sample on the wear degree of the gearbox is judged by the particle size and particle uniformity of the abrasive particles in the oil sample. When the gear is in the normal wear state, the critical value of the abrasive particle size is x0, and the critical value of the particle uniformity of all abrasive particles is W0. The abrasive particle concentration extracted from the oil sample is compared with the critical abrasive particle concentration corresponding to the normal wear degree of the gearbox, and the particle size x i The critical particle diameter size x0 of the abrasive particles corresponding to the normal wear of the gearbox is compared; and the particle uniformity W of the abrasive particles in the oil sample is compared with the critical value W0 of the particle uniformity of the abrasive particles to determine whether an early warning needs to be generated and the type of early warning to be generated.

10. The gearbox fault early warning method based on online oil sample analysis according to claim 9, characterized in that: In step S4: an early warning is generated according to the comparative analysis results. If the abrasive concentration exceeds the critical value of the abrasive concentration, a red early warning indicator light is on; if the abrasive particle size exceeds the critical value of the abrasive particle size, a yellow early warning indicator light is on; if the abrasive particle uniformity exceeds the critical value of the abrasive particle uniformity, a blue early warning indicator light is on; when the three early warning lights are on at the same time, a buzzer alarm is triggered at the same time; a corresponding early warning instruction is generated according to the comparative analysis results: When L≤L0∩x i When ≤x0∩W≤W0, the gear wear degree is judged to be normal wear degree, and no warning instruction is generated; When L>L0, it is judged that the concentration of abrasive particles in the lubricating oil of the gearbox is too high, and a warning instruction is generated to control the red warning indicator to light up; When x i >x0, it is judged that the particle size of some abrasive particles in the lubricating oil of the gearbox is too large, and a warning instruction is generated to control the yellow warning indicator to light up; when When the gearbox is in a state of poor uniformity of abrasive particles in the lubricating oil, a warning instruction is generated to control the blue warning indicator to light up; When L>L0∩x i >x0∩W>W0, that is, when all three indicator lights are on, the gearbox is judged to be in a state of severe wear, a buzzer alarm command is generated, and the buzzer is controlled to sound for emergency warning.

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