Device and method for detecting water content of oil and water based on terahertz photoacoustic

Abstract

By constructing the terahertz excitation-photoacoustic detection integrated device, the full-range water content quantitative measurement of an oil-water system can be realized in a static state. In a dynamic flow state, the invention provides a bimodal identification mechanism based on photoacoustic signal amplitude and time delay characteristics, and real-time identification and quantitative analysis can be carried out on typical flow patterns such as slug flow and stratified flow. The whole device has the advantages of being high in sensitivity, non-invasive, capable of penetrating through opaque plastic pipelines, fast in signal response and adaptive to multiple working conditions, and is suitable for on-site online monitoring requirements in industries such as petroleum refining, edible oil production and liquid logistics.

Description

Technical Field

[0001] The present invention belongs to the field of nondestructive detection of water content in an oil-water two-phase system, and in particular relates to a terahertz photoacoustic detection device and method for detecting the water content in an oil-water two-phase system. Background Art

[0002] Water content is a critical parameter in oil-water multiphase systems, widely used in fields such as oil extraction, food processing, and liquid logistics, and is directly related to product quality control and transportation safety. During storage, oil products are often kept closed and static. Water infiltration can cause oxidation, emulsification, and microbial contamination, threatening storage stability. During transportation, especially in plastic pipes, water content becomes a key indicator for ensuring fluid quality and system safety. Therefore, developing a nondestructive testing technology that can be used under both static and dynamic conditions, adapt to the plastic pipe environment, and cover a water content range of 0–100% has important practical significance and engineering value.

[0003] Existing water content detection technologies are primarily categorized as invasive and non-invasive. While invasive methods such as conductivity and capacitance probes offer a certain degree of accuracy, they are susceptible to damage to pipeline structures, have limited measurement points, and are susceptible to corrosion and contamination, leading to reduced accuracy and increased maintenance costs. Non-invasive technologies such as microwave, optical, ultrasonic, and infrared methods, while not destructive to the system structure, all suffer from limitations such as poor material adaptability, significant interference, and insufficient penetration, making it difficult to achieve high-precision, real-time detection of complex oil-water conditions in opaque pipelines.

[0004] Terahertz waves (0.1–10 THz) lie between microwaves and infrared. They are non-ionizing, highly safe, can penetrate non-metallic materials like plastics, and have strong absorption properties for water, giving them unique advantages in oil-water identification. Previous studies have shown that terahertz spectroscopy can be used for nondestructive testing in low-water content environments and can identify flow states. However, in systems with high water content, the strong absorption of terahertz waves by water still poses a significant challenge, leading to signal flooding.

[0005] Photoacoustic technology generates acoustic signals through photothermal expansion, combining optical contrast with acoustic penetration, making it suitable for deep-level information detection in complex media. Combining terahertz excitation with photoacoustic detection is expected to overcome the limitations of strong water absorption and enable full-scale, non-destructive testing of complex oil-water systems.

[0006] Therefore, there is an urgent need for a new technology that combines the advantages of terahertz and photoacoustics, which can not only penetrate plastic pipes to achieve real-time detection, but also accurately measure the water content under different flow patterns, to meet the core needs of the petroleum and food industries for full-process quality control and system safety monitoring. Summary of the Invention

[0007] The present invention aims to provide a terahertz photoacoustic detection device and method for detecting the water content of an oil-water two-phase system, overcoming the limitations of existing water content detection technologies in terms of non-destructiveness, material adaptability, detection range, and real-time capabilities, and in particular, overcoming the technical bottleneck of achieving high-precision detection in opaque plastic pipes and high-water content environments. The technical solution proposed in the present invention fully utilizes the good penetration of terahertz waves in non-metallic materials and their strong absorption of polar molecules (such as water) to achieve a sensitive response to the water content in the oil-water system; at the same time, combined with the acoustic penetration advantage of photoacoustic signals, it overcomes the problem of terahertz waves being easily submerged in high-water content environments, thereby establishing a new non-destructive detection solution that is applicable to the 0-100% water content range, takes into account both static and dynamic multiphase flow conditions, and can adapt to a variety of oil types (such as petroleum, peanut oil, and soybean oil).

[0008] The present invention provides a terahertz photoacoustic detection device for detecting the water content of an oil-water two-phase system. The device comprises the following functional modules: a terahertz excitation and shaping module, a photoacoustic signal receiving module, and a data acquisition and processing module.

[0009] The terahertz excitation and shaping module is used to generate terahertz pulses, which non-contactly excite the oil-water mixture system to generate photoacoustic signals.

[0010] The photoacoustic signal receiving module is used to receive the photoacoustic signal, convert the photoacoustic signal into an electrical signal and output it to the data acquisition and processing module.

[0011] The data acquisition and processing module is used to analyze and process the electrical signals, extract the photoacoustic signal amplitude and time delay from the electrical signals as key characteristic parameters, and call the two-dimensional characteristic water content inversion model to calculate the water content and output the calculation results.

[0012] The two-dimensional characteristic water content inversion model includes the amplitude inversion model and the time-delay inversion model; the amplitude inversion model is:

[0013] V ∝ R w *μ w +(1-R w )*μ o

[0014] Where V is the photoacoustic signal amplitude, R w is the water content, μ w 、μ o are the absorption coefficients of water and oil, respectively;

[0015] The time-delay inversion model is:

[0016]

[0017] Where a is Δt is the time delay of the photoacoustic signal at that moment, and Δt0 is the reference time delay obtained by calibration with water before the formal measurement.

[0018] The two-dimensional characteristic water content inversion model is established based on the standard sample database obtained from the calibration experiment. By fitting the photoacoustic signal amplitude and time delay parameters of water-oil mixed samples at different water contents, the function of high-precision inversion of water content is achieved.

[0019] The present invention provides a terahertz photoacoustic detection method for detecting the water content of an oil-water two-phase system, the method specifically comprising the following steps:

[0020] Step 1: Input samples with known moisture content; that is, select a series of standard samples with known moisture content, covering the moisture content range of 0–100%, as the benchmark data set required for modeling and system calibration.

[0021] Step 2: Obtain the amplitude and time delay of the photoacoustic signal; for each set of standard samples, use a terahertz photoacoustic detection device to perform photoacoustic excitation and detection, and collect the corresponding photoacoustic signal; extract the two characteristic parameters of the photoacoustic signal amplitude and time delay.

[0022] Step 3: Establish a two-dimensional characteristic water content inversion model; based on the amplitude and time delay of the photoacoustic signal recorded in the standard sample, fit them with the corresponding real water content data to construct a two-dimensional characteristic water content inversion model.

[0023] Step 4: Input an oil-water mixture with unknown water content; place the actual oil-water mixture sample to be tested into the terahertz photoacoustic detection device to stimulate and generate a photoacoustic signal.

[0024] Step 5: Collect the photoacoustic signal and extract the amplitude and time delay of the photoacoustic signal as the photoacoustic characteristic parameters; that is, perform terahertz photoacoustic detection on the unknown sample, collect and record the corresponding photoacoustic signal; analyze the signal to extract the two characteristic indicators of amplitude and time delay, and prepare to input them into the inversion model.

[0025] Step 6: Input the inversion model to calculate the water content; input the photoacoustic characteristic parameters obtained in step 5 into the established inversion model to calculate the water content of the sample and realize quantitative detection of the water phase content.

[0026] Step 7: Determine whether the amplitude of the photoacoustic signal has periodic variation; if it has periodic variation, execute step 8-1; if not, execute step 8-2.

[0027] Step 8-1: The system determines that the current flow type is slug flow and outputs the final water content in combination with the amplitude inversion model.

[0028] Step 8-2: The system determines that the current flow type is stratified flow and outputs the final water content in combination with the time-delay inversion model.

[0029] Step 9: Output the test results; output the inverted water content result and the flow pattern judgment result together to provide the water content and flow pattern information of the oil-water mixture.

[0030] By constructing an integrated terahertz excitation-photoacoustic detection device, the present invention can achieve full-range quantitative measurement of the water content of oil-water systems under static conditions. Under dynamic flow conditions, the present invention proposes a two-dimensional characteristic water content inversion model. Based on a dual-modal recognition mechanism based on the amplitude and time delay characteristics of the photoacoustic signal, it can perform real-time identification and quantitative analysis of typical flow patterns such as slug flow and stratified flow. The overall device has the advantages of high sensitivity, non-invasiveness, ability to penetrate opaque plastic pipes, fast signal response, and adaptability to multiple working conditions. It is suitable for on-site online monitoring needs in industries such as petroleum refining, edible oil production, and liquid logistics. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0032] Figure 1 This is a schematic diagram of the structure of a terahertz photoacoustic detection device for detecting the water content of an oil-water two-phase system.

[0033] Figure 2 The figure is a flow chart of a terahertz photoacoustic detection method for detecting the water content of an oil-water two-phase system.

[0034] Figure 3 This is a flow chart of the terahertz photoacoustic detection method for distinguishing oil water content and flow pattern.

[0035] Figure 4 This is the result of detecting the water content of industrial No. 3 white oil in plug flow conditions using the terahertz photoacoustic detection method.

[0036] Figure 5 This is the result of detecting the water content of industrial No. 3 white oil in stratified flow conditions using the terahertz photoacoustic detection method.

[0037] Figure 6 This is the detection result of the water content of peanut oil under static conditions using the terahertz photoacoustic detection method.

[0038] Figure 7 This is the detection result of the moisture content of soybean oil under static conditions using the terahertz photoacoustic detection method. DETAILED DESCRIPTION

[0039] In the following description, specific details such as particular system structures and techniques are provided for purposes of illustration, not limitation, to facilitate a thorough understanding of the embodiments of the present invention. However, it will be apparent to those skilled in the art that the present invention may be practiced in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.

[0040] The present invention provides a terahertz photoacoustic detection device for detecting the water content of an oil-water two-phase system. Figure 1 The device includes the following functional modules: a terahertz excitation and shaping module 1, a photoacoustic signal receiving module 2, and a data acquisition and processing module 3.

[0041] The terahertz excitation and shaping module 1 is used to generate terahertz pulses, which non-contactly excite the oil-water mixture system to generate photoacoustic signals.

[0042] The photoacoustic signal receiving module 2 is used to receive the photoacoustic signal, convert the photoacoustic signal into an electrical signal and output it to the data acquisition and processing module 3.

[0043] The data acquisition and processing module 3 is used to analyze and process the electrical signal, extract the photoacoustic signal amplitude and time delay from the electrical signal as key characteristic parameters, and call the two-dimensional characteristic water content inversion model to calculate the water content and output the calculation results.

[0044] The two-dimensional characteristic water content inversion model includes the amplitude inversion model and the time-delay inversion model; the amplitude inversion model is:

[0045] V ∝ R w *μ w +(1-R w )*μ o

[0046] Where V is the photoacoustic signal amplitude, R w is the water content, μ w 、μ o are the absorption coefficients of water and oil, respectively;

[0047] The time-delay inversion model is:

[0048]

[0049] Where a is Δt is the time delay of the photoacoustic signal at that moment, and Δt0 is the reference time delay obtained by calibration with water before the formal measurement.

[0050] The two-dimensional characteristic water content inversion model is established based on the standard sample database obtained from the calibration experiment. By fitting the photoacoustic signal amplitude and time delay parameters of water-oil mixed samples at different water contents, the function of high-precision inversion of water content is achieved.

[0051] The above modules work together to achieve full-range, high-precision, non-contact detection of water content in oil-water systems, suitable for both static and dynamic detection scenarios.

[0052] Specifically, the terahertz excitation and shaping module 1 generates and focuses high-energy, broadband (0.2–1.5 THz) terahertz pulses, non-contactly exciting the interior of the oil-water mixture. This causes the water phase to absorb energy locally, generating a thermal expansion effect, which triggers initial acoustic pressure fluctuations and forms a photoacoustic signal that can be detected by the subsequent photoacoustic signal receiving module 2. The photoacoustic signal receiving module 2 receives the photoacoustic signal caused by the local thermal expansion generated by the terahertz excitation, converts the photoacoustic signal into an electrical signal, and outputs it to the data acquisition and processing module 3. The data acquisition and processing module 3 filters, samples, and analyzes the received photoacoustic electrical signal. The signal is digitized using a high-speed data acquisition card and input into a computer, where the photoacoustic signal amplitude and time delay are extracted as key characteristic parameters. Based on the photoacoustic signal amplitude variation trend and time delay distribution characteristics, the device can automatically identify flow patterns and calculate the water content using a two-dimensional characteristic water content inversion model, outputting the calculated results.

[0053] like Figure 2 As shown, the terahertz excitation and shaping module 1 includes a femtosecond laser, a collimating lens, a nonlinear crystal, a parabolic reflector assembly, and an off-axis profiler. The nonlinear crystal, along with the subsequent parabolic reflector assembly and off-axis profiler, together form the optical system for shaping terahertz radiation. The module generates terahertz pulses with a central frequency of 0.2–1.5 THz and an energy of 4 μJ per pulse. These pulses are focused onto the outer wall of the plastic sample under test via an optical system, achieving non-contact excitation. The excitation spot diameter is controlled at 1.5 mm, penetrating the plastic tube and acting on the oil-water mixture within.

[0054] The photoacoustic signal receiving module 2 includes an acoustic impedance matching layer and a piezoelectric ultrasonic transducer (center frequency 1 MHz), which is used to receive the photoacoustic signal caused by the local thermal expansion generated by terahertz excitation and obtain dynamic information of the medium absorption characteristics.

[0055] Data acquisition and processing module 3 consists of an optical delay line, a data acquisition card, a filter, and a computer. The data acquisition card uses a high-speed ADC sampling card with a sampling rate exceeding 50MS / s. The filter is a 2MHz low-pass filter. After filtering and shaping, the signal is input into the computer, which outputs quantitative water content based on the constructed two-dimensional characteristic water content inversion model.

[0056] In the working process of the device, the terahertz excitation and shaping module 1 first generates an ultrashort pulse laser from a femtosecond laser, which is shaped into a collimated beam by a collimating lens and irradiated to the nonlinear crystal. Under the excitation of the femtosecond laser, the nonlinear crystal radiates a broadband terahertz pulse. Subsequently, the terahertz wave is focused by a parabolic reflector group, and is reflected by the off-axis profile mirror M1 and vertically irradiated to the surface of the plastic pipe. The polar molecules in the sample, especially water molecules, strongly absorb terahertz energy. After absorbing energy, the local area heats up instantaneously and produces thermal expansion, thereby exciting the initial pressure and forming an ultrasonic signal, that is, a photoacoustic signal. In time-domain photoacoustic technology, the pulse width of the excitation light is much shorter than the thermal relaxation time and the acoustic pressure relaxation time, satisfying the thermal constraint and the acoustic pressure constraint. Under this condition, the generation of the photoacoustic signal can ignore the influence of thermal diffusion and acoustic pressure propagation in the excitation area. At this time, the photoacoustic equation satisfied by the time-domain photoacoustic technology is as follows:

[0057]

[0058] in, It represents the energy density of light absorption converted into heat per unit volume and per unit time; parameter β, V S and C P represent the thermal coefficient of volume expansion, speed of sound and specific heat capacity of the absorbent material respectively; Refers to the sound pressure of the photoacoustic signal.

[0059] The photoacoustic signal propagates vertically, penetrates the plastic tube wall of the sample, and is received by a piezoelectric ultrasonic transducer mounted on the back of the sample. This piezoelectric ultrasonic transducer converts the acoustic signal into an electrical signal, which is then output to the data acquisition and processing module 3. The initial sound pressure of the photoacoustic signal is obtained by calculating the amplitude of the electrical signal. The initial sound pressure can be expressed as:

[0060]

[0061] In the formula, the parameters β, V S and C P μ represents the thermal coefficient of volume expansion, speed of sound and specific heat capacity of the absorbing material respectively. α Represents the light absorption coefficient, which is determined by the absorption characteristics of the material at a given electromagnetic wave frequency. th Defines the percentage of absorbed energy converted to heat, which is usually characteristic of a given material but is usually considered to be 1. F usually refers to the laser pulse energy per unit area, i.e., the flux density (unit: J / m 2 ).

[0062] An optical delay line synchronizes the acquisition card with the femtosecond laser, enabling the system to acquire photoacoustic signals with femtosecond time resolution. Data acquisition and processing module 3 filters, samples, and analyzes the received signals, extracting the photoacoustic signal amplitude and time delay as key features for calculating the flow pattern within the pipeline and inverting the water content in the sample.

[0063] In a slug flow structure, water is a highly polar molecule that strongly absorbs terahertz waves, generating a significant photoacoustic signal. Oil (such as white oil, peanut oil, and soybean oil) is non-polar or weakly polar and absorbs terahertz waves less strongly, resulting in a smaller photoacoustic signal amplitude. Therefore, it can be inferred that the photoacoustic signal amplitude generated in the sample is approximately linearly related to the water content:

[0064] V ∝ R w *μ w +(1-R w )*μ o

[0065] Where V is the photoacoustic signal amplitude, R w is the water content, μ w 、μ o are the absorption coefficients of water and oil, respectively.

[0066] In stratified flow structures, the difference in acoustic wave propagation speed in different media and the initial time delay of the photoacoustic signal can be used to construct an inversion model to calculate the water layer thickness:

[0067]

[0068] Where Δt is the time delay of the photoacoustic signal at that moment, d w is the actual thickness of the water layer, V w is the propagation speed of the photoacoustic signal in water. Since oil has almost no absorption of terahertz and terahertz penetrates oil very quickly, the time delay of the photoacoustic signal is approximately equal to the time delay of the photoacoustic signal in water. Since water is passed through the sample for calibration before the formal measurement, the time delay is Δt0. By establishing a relationship between the time delay ratio a and the water content, the water content R can be obtained. w for:

[0069]

[0070] Where a is

[0071] In practical applications, to accurately identify flow patterns and invert water content, the system must be calibrated using a series of standard samples with water contents ranging from 0–100% before measurement. By recording the photoacoustic signal amplitude and delay of each standard sample under identical experimental conditions, a mapping relationship between the photoacoustic signal amplitude and delay and the actual water content is established, forming a calibration curve for rapid inversion and quantitative analysis of subsequent water content samples.

[0072] Due to the varying distribution of oil and water in different flow patterns, the resulting photoacoustic signals exhibit distinct characteristics. Slug flow typically exhibits periodic, strong signal fluctuations, while stratified flow exhibits relatively stable signal amplitudes, but time delays that vary with dielectric thickness. This device automatically identifies flow patterns based on the amplitude trends and time delay distribution of the photoacoustic signals, and invokes the corresponding inversion model, thereby improving identification accuracy and stability.

[0073] Figure 3 The present invention provides a terahertz photoacoustic detection method for detecting the water content of an oil-water two-phase system, the method specifically comprising the following steps:

[0074] Step 1: Input samples with known moisture content; that is, select a series of standard samples with known moisture content, covering the moisture content range of 0–100%, as the benchmark data set required for modeling and system calibration.

[0075] Step 2: Obtain the photoacoustic signal amplitude and time delay. For each set of standard samples, use a terahertz photoacoustic detection device to perform photoacoustic excitation and detection, and collect the corresponding photoacoustic signal. Extract the two characteristic parameters of the photoacoustic signal amplitude and time delay as the data basis for subsequent modeling.

[0076] Step 3: Establish a two-dimensional characteristic water content inversion model; based on the amplitude and time delay of the photoacoustic signal recorded in the standard sample, fit the corresponding real water content data to construct a two-dimensional characteristic water content inversion model; this model is used to predict the water content of subsequent unknown samples, taking into account the characteristic differences under different flow patterns and water contents.

[0077] Step 4: Input an oil-water mixture with unknown water content; place the actual oil-water mixture sample to be tested into the terahertz photoacoustic detection device to stimulate the generation of photoacoustic signals, preparing for subsequent feature extraction and water content inversion.

[0078] Step 5: Collect the photoacoustic signal and extract the amplitude and time delay of the photoacoustic signal as the photoacoustic characteristic parameters; that is, perform terahertz photoacoustic detection on the unknown sample, collect and record the corresponding photoacoustic signal; analyze the signal to extract the two characteristic indicators of amplitude and time delay, and prepare to input them into the inversion model.

[0079] Step 6: Input the inversion model to calculate the water content; input the photoacoustic characteristic parameters obtained in step 5 into the established inversion model to calculate the water content value of the sample and realize the quantitative detection of the water phase content.

[0080] Step 7: Determine whether the amplitude of the photoacoustic signal has periodic changes; analyze the change characteristics of the amplitude of the photoacoustic signal over time and determine whether the signal shows periodic fluctuations as the basis for flow type identification.

[0081] Step 8-1: If the photoacoustic signal has periodic changes, the flow type is determined to be slug flow and the water content is output; if the signal amplitude has obvious periodic changes, the system determines that the current flow type is slug flow and outputs the final water content in combination with the amplitude inversion model.

[0082] Step 8-2: If the photoacoustic signal shows no obvious periodic changes, the flow pattern is determined to be stratified and the water content is output. If the signal amplitude is stable and shows no obvious periodic fluctuations, the system determines the current flow pattern to be stratified and outputs the final water content using the time-delay inversion model.

[0083] Step 9: Output the test results; output the inverted water content result and the flow pattern judgment result together to provide the water content and flow pattern information of the oil-water mixture.

[0084] like Figure 4 As shown in the figure, the oil-water pump speed ratio is adjusted to gradually increase the water content from 0% to 40%, and a water content model under slug flow conditions is established. As the water content increases, the amplitude of the photoacoustic signal gradually decreases. The determination coefficient R of the linear fitting result is 2 The average absolute error (MAE) is 0.985 and 2.1%, indicating that there is a significant linear relationship between the water content in the slug flow and the amplitude of the photoacoustic signal.

[0085] like Figure 5 As shown in the figure, the oil-water pump speed ratio is adjusted to gradually increase the water content from 30% to 100%, and a water content model under stratified flow conditions is established. The experimental results show that the time delay of the photoacoustic signal increases quadratically with the increase of water content, and the coefficient of determination of the fitting curve R 2 The average absolute error (MAE) is as high as 0.996 and 1.5%, which shows that the method has high measurement accuracy and stability.

[0086] like Figure 6 As shown in the figure, peanut oil and water were placed in a plastic barrel and the water content was gradually adjusted from 0% to 100% to simulate the daily storage environment of edible oil. A water content detection model suitable for peanut oil was established. The experimental results showed that as the water content increased, the time delay of the terahertz photoacoustic signal continued to increase, and the determination coefficient of the linear fitting result was R 2=0.994, which verifies the good accuracy and reliability of this method in detecting the moisture content of peanut oil.

[0087] like Figure 7 As shown in the figure, under the same experimental conditions, soybean oil was mixed with water and the water content was adjusted. A water content detection model suitable for soybean oil was also established. The results show that the signal delay increases steadily with the increase of water content, and the R 2 As high as 0.996, it further proves the wide applicability of this technology in different oil products and the stability of the detection effect.

[0088] It should be understood that the order of execution of the steps in the above embodiments does not necessarily mean the order of execution. The order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0089] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0090] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant description of other embodiments.

[0091] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present invention.

[0092] In the embodiments provided by the present invention, it should be understood that the disclosed devices / terminal equipment and methods can be implemented in other ways. For example, the device / terminal equipment embodiments described above are merely illustrative. For example, the division of the modules or units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0093] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0094] In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0095] If the integrated module / unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention can implement all or part of the process of the above-mentioned method embodiment by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, it can implement the steps of each of the above-mentioned method embodiments. The computer program includes computer program code, which can be in source code form, object code form, executable file, or some intermediate form. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal, and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media does not include electric carrier signals and telecommunication signals.

[0096] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention, and should all be included in the scope of protection of the present invention.

Claims

1. A terahertz photoacoustic detection device for detecting the water content of an oil-water two-phase system, characterized in that: The device comprises the following functional modules: a terahertz excitation and shaping module (1), a photoacoustic signal receiving module (2), and a data acquisition and processing module (3); The terahertz excitation and shaping module (1) is used to generate terahertz pulses, which non-contactly excite the oil-water mixture system to generate photoacoustic signals; The photoacoustic signal receiving module (2) is used to receive the photoacoustic signal, convert the photoacoustic signal into an electrical signal and output it to the data acquisition and processing module (3); The data acquisition and processing module (3) is used to analyze and process the electrical signal, extract the photoacoustic signal amplitude and time delay from the electrical signal as key characteristic parameters, and call the two-dimensional characteristic water content inversion model to calculate the water content and output the calculation results; The two-dimensional characteristic water content inversion model includes the amplitude inversion model and the time-delay inversion model; the amplitude inversion model is: V∝R w *m w +(1-R w )*m o Where V is the photoacoustic signal amplitude, R w is the water content, μ w 、μ o are the absorption coefficients of water and oil, respectively; The time-delay inversion model is: Where a is Δt is the time delay of the photoacoustic signal at that moment, and Δt0 is the reference time delay obtained by calibration with water before the formal measurement.

2. According to the terahertz photoacoustic detection device of claim 1, the two-dimensional characteristic water content inversion model is established based on a standard sample database obtained from a calibration experiment, and the function of high-precision inversion of water content is achieved by fitting the photoacoustic signal amplitude and delay parameters of water-oil mixed samples at different water content ratios.

3. The terahertz photoacoustic detection device according to claim 1, wherein the terahertz excitation and shaping module (1) comprises a femtosecond laser, a collimating lens, a nonlinear crystal, a parabolic reflector group and an off-axis profile mirror; the nonlinear crystal and the subsequent parabolic reflector group and the off-axis profile mirror together constitute an optical system for terahertz radiation shaping; The terahertz excitation and shaping module (1) generates terahertz pulses, which are focused onto the outer wall of the plastic sample to be tested through an optical system, thereby achieving non-contact excitation.

4. The terahertz photoacoustic detection device according to claim 1, wherein the photoacoustic signal receiving module (2) comprises an acoustic impedance matching layer and a piezoelectric ultrasonic transducer, and is used to receive the photoacoustic signal caused by the local thermal expansion generated by the terahertz excitation, and obtain dynamic information of the medium absorption characteristics.

5. The terahertz photoacoustic detection device according to claim 1, wherein the data acquisition and processing module (3) is composed of an optical delay line, a data acquisition card, a filter and a computer.

6. The terahertz photoacoustic detection device according to claim 5, wherein the optical delay line is connected to an acquisition card and a femtosecond laser, so that the acquisition card and the femtosecond laser are synchronized to achieve femtosecond-level time-resolved acquisition of the photoacoustic signal by the system.

7. A terahertz photoacoustic detection method for detecting the water content of an oil-water two-phase system, characterized in that: The method specifically comprises the following steps: Step 1: Input a sample with known water content; Step 2: Obtain the photoacoustic signal amplitude and time delay. For each set of standard samples, use a terahertz photoacoustic detection device to perform photoacoustic excitation and detection, collect the corresponding photoacoustic signal, and extract the two characteristic parameters of the photoacoustic signal amplitude and time delay. Step 3: Establish a two-dimensional characteristic water content inversion model; based on the amplitude and time delay of the photoacoustic signal recorded in the standard sample, fit the corresponding real water content data to construct a two-dimensional characteristic water content inversion model; Step 4: Input an oil-water mixture with unknown water content; place the actual oil-water mixture sample to be tested into the terahertz photoacoustic detection device to excite and generate a photoacoustic signal; Step 5: Acquire the photoacoustic signal and extract the amplitude and time delay of the photoacoustic signal as photoacoustic characteristic parameters; that is, perform terahertz photoacoustic detection on the unknown sample, acquire and record the corresponding photoacoustic signal; analyze the signal to extract the two characteristic indicators of amplitude and time delay, and prepare to input them into the inversion model; Step 6: Input the inversion model to calculate the water content; input the photoacoustic characteristic parameters obtained in step 5 into the established inversion model to calculate the water content of the sample and achieve quantitative detection of the water content; Step 7: Determine whether the photoacoustic signal amplitude has periodic variation; if it has periodic variation, execute step 8-1; if not, execute step 8-2; Step 8-1: The system determines that the current flow type is slug flow and outputs the final water content in combination with the amplitude inversion model; Step 8-2: The system determines that the current flow type is stratified flow and outputs the final water content in combination with the time-lapse inversion model; Step 9: Output the test results; output the inverted water content result and the flow pattern judgment result together to provide the water content and flow pattern information of the oil-water mixture.

8. The terahertz photoacoustic detection method according to claim 7, wherein in step 1, a series of standard samples with known water content, covering a water content range of 0-100%, are selected as a benchmark data set required for modeling and system calibration.

9. The terahertz photoacoustic detection method according to claim 7, wherein the amplitude inversion model and the time delay inversion model in step 3 are: V∝R w *m w +(1-R w )*m o in, V is the photoacoustic signal amplitude, R w is the water content, μ w 、μ o are the absorption coefficients of water and oil, respectively; The time-delay inversion model is: Where a is Δt is the time delay of the photoacoustic signal at that moment, and Δt0 is the reference time delay obtained by calibration with water before the formal measurement.

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