Lubricating oil product detection device based on mid-infrared spectrum technology

Abstract

The embodiment of the invention discloses a lubricating oil product detection device based on an intermediate infrared spectrum technology. The lubricating oil product detection device comprises a data processing module, a photoelectric conversion module, a light source module and an oil sample cavity, the data processing module is used for sending a light source control signal to the light source module; the light source module is used for responding to the light source control signal and transmitting a first light signal to the oil sample cavity; the oil liquid sample cavity is used for accommodating oil liquid to be detected and outputting a second optical signal to the photoelectric conversion module in response to the first optical signal; the photoelectric conversion module is used for converting the second optical signal into a plurality of digital electric signals and sending the digital electric signals to the data processing module; and the data processing module is also used for obtaining the content of each index of the oil liquid to be detected according to the plurality of digital electric signals.

Description

Technical Field

[0001] This invention relates to the field of lubricating oil quality testing and condition monitoring technology. More specifically, it relates to a lubricating oil testing device based on mid-infrared spectroscopy technology. Background Technology

[0002] Lubricating oil is hailed as the "blood" of industrial equipment, its core functions being to reduce friction, lower wear, cool and dissipate heat, seal and prevent corrosion, and clean and disperse. The deterioration of lubricating oil quality directly affects the reliability, safety, and service life of equipment. In actual operation, lubricating oil performance can decline due to oxidation, nitration, additive loss, fuel dilution, moisture intrusion, and wear debris contamination, potentially leading to equipment failure, reduced energy efficiency, or even catastrophic shutdowns. Therefore, timely and accurate monitoring of lubricating oil quality is a crucial step in achieving predictive maintenance, ensuring production safety, and optimizing operating costs.

[0003] The testing methods for lubricating oils are mainly divided into two categories: offline laboratory testing and online monitoring. Offline laboratory testing, as the traditional mainstream method, relies on manual sampling and professional instrument analysis. Although the results are accurate, it has inherent limitations such as cumbersome procedures, long cycles, high costs, and insufficient sample representativeness. Summary of the Invention

[0004] The purpose of this invention is to provide a lubricating oil detection device based on mid-infrared spectroscopy technology to solve at least one of the problems existing in the prior art.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: The first aspect of the present invention provides a lubricating oil detection device based on mid-infrared spectroscopy technology, comprising: a data processing module, a photoelectric conversion module, a light source module, and an oil sample chamber; The data processing module is used to send light source control signals to the light source module; The light source module is used to emit a first light signal to the oil sample chamber in response to the light source control signal; The oil sample chamber is used to contain the oil to be tested and to output a second optical signal to the photoelectric conversion module in response to the first optical signal; The photoelectric conversion module is used to convert the second optical signal into multiple digital electrical signals and send them to the data processing module; The data processing module is also used to obtain the content of each index of the oil to be tested based on the plurality of digital electrical signals.

[0006] Optionally, the light source module includes a mid-infrared light source unit, a driving and modulation unit, a collimation and shaping optical unit, and a temperature control and current stabilization unit; The driving and modulation unit is used to receive the light source control signal and modulate the mid-infrared light source unit. The mid-infrared light source unit is used to emit mid-infrared scattered light signals according to the modulation result; The collimation and shaping optical unit is used to shape the mid-infrared scattered light signal into a first light signal; The temperature control and current stabilization unit is used to control the temperature and current of the mid-infrared light source unit.

[0007] Optionally, the photoelectric conversion module includes an analog-to-digital conversion unit, a multi-channel infrared detector array, an array filter, and a signal conditioning unit; The array-type filter is used to receive the second optical signal and output the target wavelength optical signal; The multi-channel infrared detector array is used to receive the target wavelength optical signal and output multiple analog electrical signals; The signal conditioning unit is used to amplify and filter the plurality of analog electrical signals to obtain a plurality of conditioned electrical signals; The analog-to-digital conversion unit is used to perform analog-to-digital conversion on the multiple conditioned electrical signals to obtain multiple digital electrical signals.

[0008] Optionally, the array-type filter is disposed on the incident light side of the multi-channel infrared detector array by a patch process.

[0009] Optionally, the data processing module includes a microcontroller and a host computer; The microcontroller is used to send light source control signals to the light source module; The host computer is used to obtain the content of each index of the oil to be tested based on the multiple digital electrical signals.

[0010] Optionally, the microcontroller includes a signal preprocessing unit; The signal preprocessing unit is used to perform digital filtering, dark current subtraction, first baseline correction, and drift compensation on the multiple digital electrical signals to obtain multiple effective light intensity signals, and to calculate multiple transmittance ratios based on the reference light intensity signal and the multiple effective light intensity signals.

[0011] Optionally, the host computer includes an absorbance calculation and feature extraction unit; The absorbance calculation and feature extraction unit is used to calculate multiple absorbances based on the multiple transmittances, and to perform noise suppression and second baseline correction on the multiple absorbances to obtain an absorbance spectrum.

[0012] Optionally, the host computer includes an oil index analysis and model calculation unit; The oil index analysis and model calculation unit is used to obtain the concentration of oil indexes based on the absorbance spectrum using a pre-trained model.

[0013] Optionally, the pre-trained model is a pre-trained multiple linear regression model.

[0014] Optionally, the concentration of the oil product indicators includes oxidation value, sulfidation value, moisture content, acid value, and alkalinity value.

[0015] The beneficial effects of this invention are as follows: The technical solution described in this invention successfully transplants laboratory-level mid-infrared spectroscopy analysis capabilities to industrial sites through highly integrated optical path and structural design; it can be directly installed on lubricating oil circulation pipelines to monitor multiple key physicochemical indicators of oil in real time and continuously; it completely overcomes the problem of poor timeliness in traditional laboratory analysis; based on independent technology research and development, it is the first to realize the development of online detection equipment for lubricating oil quality, promoting the industry towards a new stage of real-time and accurate equipment status monitoring. Attached Figure Description

[0016] The specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings.

[0017] Figure 1 This diagram illustrates a lubricating oil detection device based on mid-infrared spectroscopy technology provided in an embodiment of the present invention. Detailed Implementation

[0018] To more clearly illustrate the present invention, the following description, in conjunction with embodiments and accompanying drawings, further explains the invention. Similar components in the drawings are indicated by the same reference numerals. Those skilled in the art should understand that the specific description below is illustrative rather than restrictive and should not be construed as limiting the scope of protection of the present invention.

[0019] The testing methods for lubricating oils are mainly divided into two categories: offline laboratory testing and online monitoring. Offline laboratory testing, as the traditional mainstream method, relies on manual sampling and professional instrument analysis. Although the results are accurate, it has inherent limitations such as cumbersome procedures, long cycles, high costs, and insufficient sample representativeness.

[0020] In view of this, one embodiment of the present invention provides a lubricating oil detection device based on mid-infrared spectroscopy technology, comprising: a data processing module, a photoelectric conversion module, a light source module, and an oil sample chamber; the data processing module is used to send a light source control signal to the light source module; the light source module is used to emit a first light signal to the oil sample chamber in response to the light source control signal; the oil sample chamber is used to contain the oil to be tested and output a second light signal to the photoelectric conversion module in response to the first light signal; the photoelectric conversion module is used to convert the second light signal into multiple digital electrical signals and send them to the data processing module; the data processing module is further used to obtain the content of various indicators of the oil to be tested based on the multiple digital electrical signals.

[0021] In a specific example, such as Figure 1 As shown, the core components include a mid-infrared light source, an oil sample chamber, a filter, an infrared sensor, a signal conditioning circuit, a microcontroller, and a host computer platform. The mid-infrared light source illuminates the oil sample chamber; the oil sample chamber contains and transmits the oil to be tested; the filter is fixed to the detector surface using a patch process, selectively transmitting or blocking infrared light of specific wavelengths; the infrared sensor converts the light signal after passing through the oil sample chamber and filter into an electrical signal; the signal conditioning circuit amplifies and filters the signal after photoelectric conversion; the microcontroller controls the light source intensity and signal acquisition process; and the host computer platform is used for data processing, analysis, and visualization, thereby obtaining the composition information of the oil and realizing online real-time detection of lubricating oil.

[0022] In a specific example, the detection principle is derived from mid-infrared absorption spectroscopy. Its core is to utilize the selective absorption characteristics of different chemical components in oil molecules to specific mid-infrared light bands, thereby achieving qualitative and quantitative analysis of key indicators of oil products.

[0023] In a specific example, lubricating oil is a complex mixture of base oil and various additives, in which various molecules (such as hydrocarbons, water, alcohols, acids, sulfur / phosphorus compounds, etc.) have their unique molecular structures. When a beam of broadband mid-infrared light irradiates the oil, the chemical bonds in the oil molecules (such as CH, OH, C=O, S=O, etc.) absorb photons of specific wavelengths that match their vibrational frequencies (or energy level transitions), thus causing bond stretching, bending, and other vibrations. The specific wavelength of infrared light absorbed by each chemical bond or functional group (usually expressed in wavenumbers cm⁻¹) is... -1 The molecular fingerprint (of a molecular bond) is fixed and unique. For example, the OH bond is located at approximately 3400 cm⁻¹. -1 and 1640 cm -1 Strong absorption occurs at this location, highly correlated with moisture content; C=O bond: at approximately 1700 cm⁻¹ -1The appearance of an absorption peak at this point is an important indicator of oil oxidation and deterioration; S=O bond: at approximately 1150 cm⁻¹ -1 Nearby absorption reflects changes in sulfur-containing byproducts or additives.

[0024] In a concrete example, the Lambert-Beer law forms the basis of quantitative analysis. At a specific wavelength, the attenuation of light intensity (absorbance) is directly proportional to the concentration of the absorbing substance and the optical path length. Its mathematical expression is:

[0025] In the formula, A is the absorbance, ε is the molar absorptivity (constant) of the substance, c is the concentration of the substance to be measured, l is the optical path length of light passing through the sample, and the transmitted light intensity.

[0026] Therefore, by measuring absorbance at a specific wavelength, a quantitative relationship between absorbance and substance concentration can be established.

[0027] In a specific example, the system uses a microcontroller as the core control unit. According to a set scanning strategy, it dynamically modulates a mid-infrared light source to periodically output light signals with stable and adjustable intensity for spectral scanning analysis. The modulated beam, after collimation, illuminates the oil sample to be tested. Because oils have different absorption characteristics for different wavelengths of light, the transmitted light carries spectral information reflecting the molecular composition and physicochemical properties of the oil. The transmitted light passes through an array of wavelength-selective filters to achieve selective detection of the target wavelength band. The transmitted light after passing through the filters is received by an infrared sensor and converted into an electrical signal. This electrical signal is amplified, filtered, and noise-suppressed by a signal conditioning circuit before being sent to an analog-to-digital converter (ADC) for digital acquisition. The acquired digital signal is buffered and synchronized by the microcontroller and transmitted to a host computer platform. The host computer analyzes and processes the received spectral data. First, according to the system's preset filter parameters, it selects the corresponding characteristic wavelength data. The transmitted light intensity I measured by the infrared sensor at these wavelengths was then read and compared with the pre-measured reference light intensity I0 of the blank background light filled with clean reference oil, and the absorbance was calculated. By using a pre-established calibration model between absorbance A and the concentration c of various physicochemical indicators (such as moisture, oxidation value, etc.), the precise content of each indicator in the current oil can be calculated in real time.

[0028] The technical solution described in this invention successfully transplants laboratory-level mid-infrared spectroscopy analysis capabilities to industrial sites through highly integrated optical path and structural design; it can be directly installed on lubricating oil circulation pipelines to monitor multiple key physicochemical indicators of oil in real time and continuously; it completely overcomes the problem of poor timeliness in traditional laboratory analysis; based on independent technology research and development, it is the first to realize the development of online detection equipment for lubricating oil quality, promoting the industry towards a new stage of real-time and accurate equipment status monitoring.

[0029] In one possible implementation, the concentrations of the oil indicators include oxidation value, sulfidation value, moisture content, acid value, and alkalinity value.

[0030] In one possible implementation, the light source module includes a mid-infrared light source unit, a driving and modulation unit, a collimating and shaping optical unit, and a temperature control and current stabilization unit; the driving and modulation unit is used to receive the light source control signal and modulate the mid-infrared light source unit; the mid-infrared light source unit is used to emit a mid-infrared scattered light signal according to the modulation result; the collimating and shaping optical unit is used to shape the mid-infrared scattered light signal into a first light signal; and the temperature control and current stabilization unit is used to control the temperature and current of the mid-infrared light source unit.

[0031] In a specific example, the light source module is the energy source and signal origin of the infrared spectroscopy detection system, and its performance directly affects the overall spectral quality and detection accuracy of the system. This module is responsible for generating mid-infrared radiation with specific spectral characteristics to irradiate the oil sample chamber, thereby enabling the absorption detection of the chemical components of the oil.

[0032] In a specific example, the light source module mainly consists of a mid-infrared light source unit, a driving and modulation circuit, a collimation and shaping optical system, and a temperature control and current stabilization device. The mid-infrared light source unit uses a mid-infrared radiation source, and its core light-emitting element is a micro-heated resistance film, which can generate continuous and stable mid-infrared radiation in the mid-infrared band. This device has the advantages of small size, low power consumption, fast response speed, and high mechanical strength, making it suitable for long-term online operation. The driving and modulation circuit is responsible for precisely controlling the on / off state, duty cycle, and output power of the light source. The system can use square wave, pulse width, or sine modulation according to sampling requirements to achieve synchronous detection and signal phase-locked amplification. The optical collimation component uses a gold-plated ellipsoidal reflector structure to shape the scattered light emitted by the light source into an approximately parallel beam, improving the luminous flux utilization and optical path stability. The temperature control and current stabilization device maintains a constant light source temperature and driving current through closed-loop control, reducing detection errors caused by output power fluctuations.

[0033] In a specific example, the light source module is activated under the control of a microcontroller and electrically modulated at a set frequency. When current passes through the heating film of the light source, its surface temperature rises and it emits mid-infrared radiation. After being shaped by an optical collimation component, the infrared light passes through the oil sample chamber along a fixed optical path, and then reaches the infrared detector after being split by a filter. The modulation circuit can periodically modulate the light source output, thereby effectively suppressing ambient light and low-frequency noise interference in subsequent signal processing stages through synchronous detection or lock-in amplification, significantly improving the signal-to-noise ratio.

[0034] In a specific example, the light source features a wide spectral coverage: the emission band covers the mid-infrared band, satisfying the absorption characteristic detection of most organic molecular functional groups (CH, OH, C=O, S=O, etc.); fast response speed: the thermal response time of the light source is less than 10ms, supporting modulation frequencies up to 100Hz, adapting to the needs of online rapid sampling; high optical power stability: the constant current control system ensures that the output light intensity drift rate is less than ±1% / h, ensuring the reliability of long-term continuous operation; long lifespan and strong environmental resistance: the light source adopts a vacuum or inert gas encapsulation structure, possessing good anti-oxidation, anti-vibration, and high-temperature resistance properties, making it suitable for industrial environments.

[0035] In a specific example, the light source module, microcontroller, and signal conditioning circuit achieve closed-loop linkage. The microcontroller can adjust the light source brightness or duty cycle according to the real-time detection status to prevent excessive light intensity from causing detector saturation or a decrease in signal-to-noise ratio. When the system performs self-calibration or baseline detection, the light source module can enter low-power or reference light mode. In conjunction with the reference detection channel, it can be used to monitor light source attenuation and output stability, enabling automatic power compensation and lifetime prediction.

[0036] In one possible implementation, the photoelectric conversion module includes an analog-to-digital conversion unit, a multi-channel infrared detector array, an array filter, and a signal conditioning unit; the array filter is used to receive the second optical signal and output a target wavelength optical signal; the multi-channel infrared detector array is used to receive the target wavelength optical signal and output multiple analog electrical signals; the signal conditioning unit is used to amplify and filter the multiple analog electrical signals to obtain multiple conditioned electrical signals; and the analog-to-digital conversion unit is used to perform analog-to-digital conversion on the multiple conditioned electrical signals to obtain multiple digital electrical signals.

[0037] In one possible implementation, the array-type filter is disposed on the incident light side of the multi-channel infrared detector array using a patch process.

[0038] In a specific example, the photoelectric conversion module is a key unit for realizing infrared signal detection and quantitative analysis. Its function is to accurately convert the mid-infrared light signal after passing through the oil sample chamber into an electrical signal that can be processed by the host computer platform. The performance of this module directly determines the system's detection sensitivity, signal stability, and measurement accuracy.

[0039] In a specific example, the photoelectric conversion module mainly consists of an analog-to-digital converter (ADC), a multi-channel infrared detector array, an array-type filter, and a signal conditioning circuit (including filtering and amplification units). The ADC is responsible for converting the analog voltage signal output by the photoelectric conversion module into a digital signal; the infrared detector array is made of high-sensitivity lead selenide (PbSe) material, possessing excellent response performance in the mid-infrared band. To meet the requirement of simultaneous detection of multiple component characteristic wavelengths, the detector is designed as a multi-channel array structure, with each channel corresponding to a filter channel for a specific wavelength. The array-type filter is directly fixed to the sensitive surface of the detector using a patch process, which not only ensures high alignment of the optical path but also effectively reduces external stray light and environmental interference, achieving structural integration and high stability.

[0040] In a specific example, when mid-infrared light passing through the oil sample chamber is incident on the surface of the photodetector, the photosensitive material inside the detector absorbs the light energy and generates charge carriers, thus forming a photocurrent in the circuit. Different wavelength filter channels only allow infrared light of specific wavelengths to enter the detection area; therefore, the output photoelectric signal represents the transmitted light intensity at that wavelength. The system employs a time-division multiplexing sampling method, with the microcontroller sequentially activating the sampling circuits corresponding to each filter channel to achieve synchronous multi-wavelength measurement. After post-amplification and low-pass filtering, a stable voltage signal is output for subsequent analog-to-digital converter (ADC) acquisition.

[0041] In a specific example, high precision and high resolution are achieved: the device employs a high-resolution 16-bit successive approximation (SAR) ADC, featuring high linearity and low noise characteristics, with a sampling accuracy of ±0.003%FS. This unit supports multi-channel simultaneous sampling, with a typical sampling rate of 10 kS / s, and can dynamically adjust the sampling rate and number of channels according to the detection mode to balance real-time performance and resolution. High sensitivity and low noise design: through optimized detector materials and amplification circuitry, the system can achieve microwatt-level optical power detection, with a minimum resolvable absorbance of 10... -4 Scale; Multi-band parallel detection: It can simultaneously monitor multiple characteristic wavelength points, realizing the synchronous calculation of multiple indicators such as oxidation value, sulfide value, moisture content, acid value and alkalinity value; Fast response and real-time performance: The single-channel response time is less than 10ms, meeting the requirements of online real-time monitoring; Strong environmental adaptability: The module shell is metal-encapsulated and has dustproof, oil-proof and electromagnetic interference (EMI) protection design, which is suitable for industrial field environments such as high temperature and vibration.

[0042] In a specific example, to further ensure measurement accuracy, the module includes a reference optical channel for real-time monitoring of fluctuations in the light source output power, thereby normalizing and correcting the measured sample signal. Furthermore, the system performs automatic zero-point calibration and baseline drift compensation upon power-on to ensure consistency across different detection cycles.

[0043] In one possible implementation, the data processing module includes a microcontroller and a host computer; the microcontroller is used to send light source control signals to the light source module; the host computer is used to obtain the content of each index of the oil to be tested based on the plurality of digital electrical signals.

[0044] In one possible implementation, the microcontroller includes a signal preprocessing unit; the signal preprocessing unit is used to perform digital filtering, dark current subtraction, first baseline correction, and drift compensation on the plurality of digital electrical signals to obtain a plurality of effective light intensity signals, and to calculate a plurality of transmittance ratios based on a reference light intensity signal and the plurality of effective light intensity signals.

[0045] In a specific example, the data processing module is the core unit for realizing spectral signal analysis and oil parameter calculation. Its main functions are to sample, digitally filter, extract features, and calculate absorbance of the voltage signal output by the photoelectric conversion module, and to perform quantitative evaluation of oil indicators (such as oxidation value, sulfide value, water content, acid value, and alkalinity value) based on the calibration model. This module directly determines the calculation accuracy and real-time response capability of the detection system.

[0046] In a specific example, the data processing module mainly consists of a signal preprocessing unit, an absorbance calculation and feature extraction unit, and an oil index analysis and model calculation unit. The signal preprocessing unit runs in the MCU and includes functions such as digital filtering, dark current subtraction, baseline correction, drift compensation, and data transmission. The absorbance calculation and feature extraction unit runs in the host computer's processing core and is responsible for calculating the absorbance values ​​of each wavelength channel and performing oil composition modeling and analysis. The oil index analysis and model calculation unit can map multi-wavelength absorbance features to specific physical or chemical index values. The system supports model updates and adaptive corrections, making it suitable for different types of lubricating oil testing scenarios.

[0047] In a specific example, a mid-infrared detector converts the light signal penetrating the oil into a weak analog electrical signal. This signal is amplified by a preamplifier and then precisely sampled and digitized by an ADC to obtain the raw voltage reading V. raw,i , where i represents the i-th pixel channel of the spectrometer (i.e., a specific wavelength point). To obtain an effective signal that accurately reflects light intensity, two key processing steps are required: dark current subtraction, and the dark voltage V measured under dark conditions (achieved through the built-in shutter).dark,i It consists of the detector's thermal noise and circuit background noise; this value is subtracted to eliminate inherent system bias. The optical system is normalized, and a blank reference signal V is acquired when the oil sample chamber is filled with clean reference oil. 0,i It defines a 100% transmittance benchmark for each channel. Ultimately, the transmittance I for each channel is... i The following formula can be used to calculate:

[0048] In the formula, Let be the transmittance of the i-th pixel channel; This is the raw voltage reading for the i-th pixel channel; Let be the dark voltage of the i-th pixel channel; This is the blank reference signal for the i-th pixel channel.

[0049] In a specific example, absorbance is calculated according to the Lambert-Beer law, where the absorbance of a substance is proportional to its concentration. Based on the transmittance obtained in the previous step, the original absorbance sequence of the i-th pixel channel is calculated: .

[0050] In one possible implementation, the host computer includes an absorbance calculation and feature extraction unit; the absorbance calculation and feature extraction unit is used to calculate multiple absorbances based on the multiple transmittances, and to perform noise suppression and second baseline correction on the multiple absorbances to obtain an absorbance spectrum.

[0051] In a specific example, the original absorbance signal contains high-frequency random noise and low-frequency baseline drift, which must be suppressed: High-frequency noise suppression is achieved using a Savitzky-Golay smoothing filter. This filter, through polynomial least squares fitting within a moving window, effectively suppresses random noise while preserving the original peak shape characteristics of the spectrum to the maximum extent, avoiding peak shifting or broadening caused by filtering; Baseline correction is necessary because the spectral baseline can drift due to factors such as light path scattering, particulate suspension, or window contamination. Automatic baseline correction is performed using the asymmetric least squares (ALS) method. This method iteratively separates the smoothed baseline from the original spectrum by setting asymmetric weights, thereby obtaining a high-quality absorbance spectrum A with a flat baseline and prominent characteristic peaks. corrected,i .

[0052] In one possible implementation, the host computer includes an oil index analysis and model calculation unit; the oil index analysis and model calculation unit is used to obtain the concentration of oil indexes based on the absorbance spectrum using a pre-trained model.

[0053] In one possible implementation, the pre-trained model is a pre-trained multiple linear regression model.

[0054] In a specific example, modeling and index calculation are the core of quantitative analysis, aiming to establish the mathematical relationship between spectral characteristics and key oil indicators (such as oxidation value, sulfide value, water content, acid value, and base value). Different methods are selected to build models depending on the type of lubricating oil: for scenarios with significant linear relationships and fewer features than samples, multiple linear regression (MLR) is used, as it is simple and highly interpretable. During the calibration phase, the model is trained using the spectra of a batch of oil samples with known accurate chemical values ​​and their corresponding index values. Before online detection of new oil products, the system projects the collected and preprocessed spectral data onto the trained MLR model, subsequently directly calculating the precise values ​​of various oil indicators and outputting them to the monitoring system, achieving online, continuous diagnosis and early warning of oil quality.

[0055] In a specific example, the system features self-calibration and drift compensation: It has an automatic zero-point calibration and baseline drift correction mechanism. By monitoring changes in light source intensity through a reference optical channel, it performs real-time normalization compensation to ensure measurement consistency. Intelligent modeling includes a built-in multi-model management mechanism, supporting automatic matching and switching between different oil product models. The model can be incrementally learned and updated via a host computer, enabling online detection of different types of oil products. Simultaneous multi-index calculation capability allows for the simultaneous calculation and output of multiple indicators such as oxidation value, sulfide value, moisture content, acid value, and alkalinity, with a quantitative error better than 5% of the standard laboratory method.

[0056] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the implementation of the present invention. For those skilled in the art, other variations or modifications can be made based on the above description. It is impossible to exhaustively list all the implementation methods here. All obvious variations or modifications derived from the technical solutions of the present invention are still within the protection scope of the present invention.

Claims

1. A lubricating oil detection device based on mid-infrared spectroscopy technology, characterized in that, include: Data processing module, photoelectric conversion module, light source module, oil sample chamber; The data processing module is used to send light source control signals to the light source module; The light source module is used to emit a first light signal to the oil sample chamber in response to the light source control signal; The oil sample chamber is used to contain the oil to be tested and to output a second optical signal to the photoelectric conversion module in response to the first optical signal; The photoelectric conversion module is used to convert the second optical signal into multiple digital electrical signals and send them to the data processing module; The data processing module is also used to obtain the content of each index of the oil to be tested based on the plurality of digital electrical signals.

2. The lubricating oil detection device based on mid-infrared spectroscopy technology according to claim 1, characterized in that, The light source module includes a mid-infrared light source unit, a driving and modulation unit, a collimation and shaping optical unit, and a temperature control and current stabilization unit. The driving and modulation unit is used to receive the light source control signal and modulate the mid-infrared light source unit. The mid-infrared light source unit is used to emit mid-infrared scattered light signals according to the modulation result; The collimation and shaping optical unit is used to shape the mid-infrared scattered light signal into a first light signal; The temperature control and current stabilization unit is used to control the temperature and current of the mid-infrared light source unit.

3. The lubricating oil detection device based on mid-infrared spectroscopy technology according to claim 2, characterized in that, The photoelectric conversion module includes an analog-to-digital conversion unit, a multi-channel infrared detector array, an array filter, and a signal conditioning unit; The array-type filter is used to receive the second optical signal and output the target wavelength optical signal; The multi-channel infrared detector array is used to receive the target wavelength optical signal and output multiple analog electrical signals; The signal conditioning unit is used to amplify and filter the plurality of analog electrical signals to obtain a plurality of conditioned electrical signals; The analog-to-digital conversion unit is used to perform analog-to-digital conversion on the multiple conditioned electrical signals to obtain multiple digital electrical signals.

4. The lubricating oil detection device based on mid-infrared spectroscopy technology according to claim 3, characterized in that, The array-type filter is applied to the light-incident side of the multi-channel infrared detector array using a patch process.

5. The lubricating oil detection device based on mid-infrared spectroscopy technology according to claim 4, characterized in that, The data processing module includes a microcontroller and a host computer; The microcontroller is used to send light source control signals to the light source module; The host computer is used to obtain the content of each index of the oil to be tested based on the multiple digital electrical signals.

6. The lubricating oil detection device based on mid-infrared spectroscopy technology according to claim 5, characterized in that, The microcontroller includes a signal preprocessing unit; The signal preprocessing unit is used to perform digital filtering, dark current subtraction, first baseline correction, and drift compensation on the multiple digital electrical signals to obtain multiple effective light intensity signals, and to calculate multiple transmittance ratios based on the reference light intensity signal and the multiple effective light intensity signals.

7. The lubricating oil detection device based on mid-infrared spectroscopy technology according to claim 6, characterized in that, The host computer includes an absorbance calculation and feature extraction unit; The absorbance calculation and feature extraction unit is used to calculate multiple absorbances based on the multiple transmittances, and to perform noise suppression and second baseline correction on the multiple absorbances to obtain an absorbance spectrum.

8. The lubricating oil detection device based on mid-infrared spectroscopy technology according to claim 7, characterized in that, The host computer includes an oil index analysis and model calculation unit; The oil index analysis and model calculation unit is used to obtain the concentration of oil indexes based on the absorbance spectrum using a pre-trained model.

9. The lubricating oil detection device based on mid-infrared spectroscopy technology according to claim 8, characterized in that, The pre-trained model is a pre-trained multiple linear regression model.

10. The lubricating oil detection device based on mid-infrared spectroscopy technology according to claim 9, characterized in that, The concentrations of the oil product indicators include oxidation value, sulfidation value, moisture content, acid value, and alkalinity value.

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