Taste recognition method and device based on terahertz wireless perception

Abstract

The application provides a taste recognition method and device based on terahertz wireless sensing, comprising: transmitting a signal to a to-be-measured object by using a transceiving antenna of a preset terahertz source, and receiving a reflected terahertz reflection signal; performing Fourier transform on the preprocessed terahertz reflection signal to generate a corresponding frequency domain signal; extracting an absorption peak and a frequency spectrum feature of the frequency domain signal by using a preset neural network to generate a fingerprint spectrum; determining a taste component of the to-be-measured object according to a specific frequency region and a frequency spectrum feature of each absorption peak in the fingerprint spectrum; obtaining a frequency spectrum amplitude of the absorption peak of each taste component in the corresponding specific frequency region, and calculating a concentration of each taste component. The taste recognition method and device based on terahertz wireless sensing provided by the application realize non-contact high-sensitivity taste component and taste concentration recognition.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of wireless identification technology, in particular to a taste identification method and device based on terahertz wireless perception. BACKGROUND

[0002] Taste is a special physiological sensation produced by the stimulation of soluble chemicals in food to taste buds in the oral cavity, which plays a crucial role in the survival, reproduction and evolution of mammals. Using taste identification technology to identify the taste of food can help the human body maintain normal physiological functions. Traditional taste identification methods usually use biological materials, inert electrodes and field effect devices to contact the measured substances for identification. These contact identification methods not only require sufficient measured substances and a long identification time, but also their sensitivity and effect are often limited by the development of biological technology and material science.

[0003] Existing taste identification technologies are mainly divided into two categories based on biological sensors and non-biological sensors. The taste identification technology based on biological sensors identifies taste by detecting the potential changes of biological materials such as taste tissues, taste cells, nanocapsules and biological enzymes after contacting with measured substances. Its shortcomings are long identification time, limited sensitivity, difficult preparation and poor stability. The taste identification technology based on biological sensors identifies taste by detecting the changes of potential and current of biomimetic materials (such as lipid membranes), inert electrodes and field effect devices after contacting with measured substances. Its shortcomings are the need to contact measured food, easy to cause food waste and difficult to quickly detect. SUMMARY

[0004] In view of this, the present application provides a taste identification method and device based on terahertz wireless perception to eliminate or improve one or more defects in the prior art, solve the problems of long identification time, limited sensitivity, difficult preparation and need to contact measured objects to cause waste in existing taste identification technology.

[0005] In one aspect, the present application provides a taste identification method based on terahertz wireless perception, characterized in that the method comprises the following steps:

[0006] The transceiving antenna of the preset terahertz source is used to emit signals to the measured object, and the terahertz reflection signals reflected by the measured object are received; the measured object is fixed at a preset distance from the transceiving antenna;

[0007] The terahertz reflection signals are subjected to Fourier transform to generate corresponding frequency domain signals;

[0008] extracting absorption peaks and spectral features of the frequency domain signal by using a preset neural network to generate a fingerprint spectrum; determining the taste components of the object to be measured according to specific frequency regions where the absorption peaks in the fingerprint spectrum are located and the spectral features; wherein each specific frequency region corresponds to a taste component;

[0009] Obtaining the spectral amplitudes of the absorption peaks of each taste component in the corresponding specific frequency region to calculate the concentration of each taste component.

[0010] In some embodiments of the present application, the sensing distance of the transceiving antenna to the object to be measured is set to 9-11 cm.

[0011] In some embodiments of the present application, before the Fourier transform of the terahertz reflection signal is performed to generate the corresponding frequency domain signal, the method further comprises:

[0012] The data preprocessing of the terahertz reflection signal at least includes band-pass filtering processing and signal amplification processing.

[0013] In some embodiments of the present application, before the taste recognition method based on terahertz wireless sensing is performed, the method further comprises:

[0014] Obtaining a plurality of single taste objects to be measured, wherein the single taste object to be measured contains only one taste component; using the transceiving antenna to emit a signal to the single taste object to be measured and receive a single taste reflection signal reflected by the single taste object to be measured;

[0015] Performing Fourier transform on the single taste reflection signal to generate a corresponding single taste frequency domain signal;

[0016] Inputting the single taste frequency domain signal into the preset neural network to extract the absorption peaks of the single taste frequency domain signal and generate a corresponding fingerprint spectrum to determine the specific frequency region corresponding to the absorption peaks of each taste component.

[0017] In some embodiments, when the absorption peak corresponding to the taste component of the object to be measured belongs to the preset terahertz source frequency band, the taste component of the object to be measured is determined according to the specific frequency region where the absorption peak extracted by the preset neural network is located; when the absorption peak corresponding to the taste component of the object to be measured does not belong to the preset terahertz source frequency band, the taste component of the object to be measured is determined according to the spectral features extracted by the preset neural network.

[0018] On the other hand, the present application also provides a taste recognition device based on terahertz wireless sensing, characterized in that the device is used to perform the steps of the taste recognition method based on terahertz wireless sensing as described in any of the above embodiments, and the device comprises:

[0019] A terahertz source for providing a terahertz signal;

[0020] A transceiving antenna for transmitting the terahertz signal to a to-be-tested object and receiving a reflected signal reflected back;

[0021] A signal conversion module for performing Fourier transform on the reflected signal to generate a corresponding frequency domain signal;

[0022] A taste component extraction module for extracting an absorption peak and a spectral feature of the frequency domain signal by using a preset neural network to generate a fingerprint spectrum, and determining a taste component of the to-be-tested object according to a specific frequency region where each absorption peak in the fingerprint spectrum is located and the spectral feature;

[0023] A taste concentration extraction module for extracting a spectral amplitude of the absorption peak of each taste component in the corresponding specific frequency region to calculate a concentration of each taste component.

[0024] In some embodiments of the present application, a support tube with a preset length is arranged between the transceiving antenna and the to-be-tested object, so that a set distance is maintained between the transceiving antenna and the to-be-tested object.

[0025] In some embodiments of the present application, a specimen slide is arranged on top of the support tube to hold the to-be-tested object; the specimen slide is a non-polar specimen slide without obvious absorption peak in the terahertz wave band.

[0026] In some embodiments of the present application, the device further comprises a band-pass filter and a signal amplifier for performing band-pass filtering and signal amplification on the reflected signal in the data processing module.

[0027] In another aspect, the present application further provides a computer readable storage medium having a computer program stored thereon, the program being executed by a processor to implement the steps of the method according to any one of the above-mentioned aspects.

[0028] The present application has at least the following advantages:

[0029] The application provides a taste recognition method and device based on terahertz wireless perception, which emits a signal to a to-be-measured object through a transceiving antenna of a preset terahertz source, and receives a reflected terahertz reflection signal; performs Fourier transform on the terahertz reflection signal after preprocessing, to generate a corresponding frequency domain signal; extracts an absorption peak and a spectrum feature of the frequency domain signal by using a preset neural network, to generate a fingerprint spectrum; determines a taste component of the to-be-measured object according to a specific frequency region and the spectrum feature where each absorption peak in the fingerprint spectrum is located; and obtains a spectrum amplitude of the absorption peak of each taste component in the corresponding specific frequency region, to calculate a concentration of each taste component. The taste recognition method and device based on terahertz wireless perception provided by the application realize non-contact high-sensitivity taste component and taste concentration recognition, have high recognition speed and high accuracy, and can be widely applied to food component analysis, bionic machines, virtual reality, and intelligent medical treatment, etc.

[0030] Additional advantages, objects, and features of the application will be set forth in part by the description that follows, and will become apparent to those skilled in the art upon examination of the following detailed description and drawings. The objects and other advantages of the present application can be realized and attained by means of the instrumentalities particularly pointed out in the description and claims to follow.

[0031] Those skilled in the art will appreciate that the objects and advantages of the application can be realized and attained by means of the instrumentalities and combinations particularly pointed out in the appended claims. Accordingly, the drawings and descriptions are to be regarded as illustrative in nature, and not as restrictive. BRIEF DESCRIPTION OF DRAWINGS

[0032] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description, serve to explain the principles of the application. In the drawings:

[0033] Figure 1 A step schematic diagram of the taste recognition method based on terahertz wireless perception in an embodiment of the application.

[0034] Figure 2 A flowchart of the taste recognition method based on terahertz wireless perception in an embodiment of the application.

[0035] Figure 3 A fingerprint spectrum graph of the to-be-measured object in an embodiment of the application. DETAILED DESCRIPTION

[0036] In order to make the objects, technical solutions and advantages of the application clearer, the following further describes the application in conjunction with the embodiments and drawings. Herein, the illustrative embodiments of the application and the descriptions thereof are used to explain the application, but are not used to limit the application.

[0037] It is also noted herein that, while the above describes example embodiments, there are several variations and modifications which can be made to the disclosed solution without departing from the scope of the application as defined by the appended claims.

[0038] It should be emphasized that the term "comprises / comprising" when used in this specification is taken to specify the presence of stated features, elements, steps or components but does not preclude the presence or addition of one or more other features, elements, steps, components or groups thereof.

[0039] It is also noted herein that, if not otherwise specified, the terms "connected" and "coupled" are used herein to indicate either a direct connection between two elements or an indirect connection through one or more intermediate elements.

[0040] In the following, embodiments of the application will be described with reference to the accompanying drawings. In the drawings, like reference numerals designate like or similar parts throughout the several views.

[0041] It is to be emphasized that the step designations mentioned in the following are not a limitation of the order of the steps, but it is to be understood that the steps can be performed in the order mentioned in the embodiments, but also in a different order, or that several steps are performed simultaneously.

[0042] In view of the problems of long recognition time, limited sensitivity, difficulty in preparation and waste caused by contacting the object to be measured in the existing taste recognition technology, in recent years, the feasibility of using terahertz recognition molecules to identify the fingerprint spectrum and object damage has been explored, which proves the great potential of terahertz as a new type of non-contact recognition device in recognition. However, the current terahertz-based recognition method needs to know the thickness of the object to be measured, and cannot directly recognize the taste and concentration of the object to be measured. Therefore, the present application provides a taste recognition method based on terahertz wireless perception. Terahertz waves refer to electromagnetic waves with a frequency of 0.1-10 THz and a wavelength of 3000-30 μm. In the long wave band, it coincides with the millimeter wave, and in the short wave band, it coincides with the infrared light. Compared with the existing wireless perception method, terahertz perception has the unique advantages of higher frequency and smaller spatial resolution, and the frequency band of terahertz is much larger than the existing wireless perception bandwidth. The wave band of terahertz wave can cover the characteristic spectrum of semiconductor, plasma, organic body and biological macromolecule, etc. In the present application, the characteristic energy of the taste molecule itself also falls within the terahertz frequency range, so the application uses terahertz wave to recognize the taste of the object to be measured, and recognizes the taste component and taste concentration of the object to be measured by recording and analyzing the position of the characteristic resonance peak of the taste molecule and its spectral amplitude characteristics. Specifically, as shown in Figure 1 and Figure 2 The method comprises the following steps S101-S106:

[0043] Step S101: A preset terahertz source transmits a signal to a to-be-detected object by using a transceiving antenna, and receives a terahertz reflection signal reflected by the to-be-detected object. The to-be-detected object is fixed at a preset distance from the transceiving antenna.

[0044] Step S102: The terahertz reflection signal is subjected to Fourier transform to generate a corresponding frequency domain signal.

[0045] Step S103: A preset neural network is used to extract absorption peaks and spectral features of the frequency domain signal to generate a fingerprint spectrum, and the taste components of the to-be-detected object are determined according to specific frequency regions and spectral features of the absorption peaks in the fingerprint spectrum. Each specific frequency region corresponds to a taste component.

[0046] Step S104: The spectral amplitudes of the absorption peaks of each taste component in the corresponding specific frequency region are obtained to calculate the concentration of each taste component.

[0047] In step S101, the preset terahertz source can be a terahertz time-domain spectrometer. The terahertz time-domain spectrometer is an analytical instrument used in the field of earth science. It uses a femtosecond laser to excite an antenna to generate electromagnetic radiation in the terahertz waveband, transmits a terahertz signal to a to-be-detected object, and receives a terahertz reflection signal reflected by the to-be-detected object.

[0048] In some embodiments, the terahertz time-domain spectrometer with a frequency range of 0.1 THz to 4 THz is selected.

[0049] Considering that the signal intensity of the terahertz source is low and the signal attenuates quickly with distance, in order to reduce the impact of distance change on taste recognition, only the terahertz reflection signal of the to-be-detected object at a preset distance from the transceiving antenna is received.

[0050] In some embodiments, the to-be-detected object is placed directly above the transceiving antenna by a preset fixing assembly, and the sensing distance between the transceiving antenna and the to-be-detected object is set to 9-11 cm, i.e., the preset distance is set to 9-11 cm. Preferably, the preset distance is 10 cm.

[0051] In step S102, as mentioned above, the terahertz wave is a wave with a frequency between 300 GHz, which is the high-frequency edge of the millimeter wave waveband of electromagnetic radiation, and 3000 GHz, which is the low-frequency edge of the far-infrared spectral band, because the frequency of the terahertz wave is between the vibration and rotation energy levels of biological macromolecules, the absorption spectrum obtained after the terahertz wave penetrates a substance can accurately reflect the molecular structure of the substance, and the fingerprint spectrum is obtained. Therefore, after step S101, different taste molecules in the to-be-detected object will absorb terahertz signals of different frequencies, but the received terahertz reflection signal cannot be directly used, so the terahertz reflection signal in the time domain is converted to the frequency domain for subsequent analysis.

[0052] In some embodiments, the terahertz reflection signal is subjected to Fourier transform to generate a corresponding frequency domain signal.

[0053] In some embodiments, the terahertz reflection signal is subjected to data preprocessing before Fourier transform. Exemplarily, the data preprocessing includes band-pass filtering and signal amplification. Based on the band-pass filtering, only signals of specific frequencies are allowed to pass, and signals of the rest frequencies are shielded to remove environmental noise and interference caused by resonance, and based on the signal amplification, the intensity of the signal is improved, so that a pure time domain signal is finally obtained. The Fourier transform of the pure time domain signal obtains a frequency domain signal, ensuring the accuracy of the data to ensure the accuracy of the subsequent taste molecule feature extraction.

[0054] In step S103, due to the three-dimensional arrangement of atoms in the taste molecule, low-frequency motion and the influence of non-covalent chemical bonds, the terahertz absorption spectrum of the object to be measured will have an absorption peak at a specific frequency. The absorption peak feature is caused by the internal structure of the taste molecule and is the inherent property of the object, so it is used as an important feature for taste recognition in the present application. At the same time, considering the limitation of the preset terahertz source frequency band range, and the fact that the absorption peak of some taste components is not in the terahertz band, exemplarily, the absorption peak of the salty object sodium chloride is not in the terahertz band, it cannot be achieved by extracting the absorption peak to determine the specific frequency region. In the present application, based on the preset neural network, the absorption peak and the spectral feature in the frequency domain signal are extracted simultaneously. When the absorption peak corresponding to the taste component of the object to be measured belongs to the preset terahertz source frequency band, the taste component of the object to be measured is determined according to the specific frequency region where the absorption peak extracted by the preset neural network is located; when the absorption peak corresponding to the taste component of the object to be measured does not belong to the preset terahertz source frequency band, the taste component of the object to be measured is determined according to the spectral feature extracted by the preset neural network.

[0055] Further, considering that as the frequency increases, the characteristic information of some taste molecules is gradually buried in the noise, it is difficult to observe intuitively, the preset neural network of the present application can extract the required features in high-frequency noise to ensure the integrity and accuracy of the data. Exemplarily, the sensing frequency band of the preset terahertz time domain spectrometer is 0.1THz-4THz, when the frequency is higher, the signal attenuation is more serious, which causes the features in the 2THz-4THz frequency band to be buried in the noise, and the corresponding features can be extracted from the noise by the preset neural network.

[0056] Exemplarily, as shown in Figure 3 Fig. 2 is a fingerprint spectrum of an object to be measured, wherein a relatively obvious absorption peak appears near 0.94THz, indicating that the object to be measured contains sweet molecules glucose.

[0057] In some embodiments, the preset neural network is a convolutional neural network.

[0058] In some embodiments, before executing the terahertz wireless sensing-based taste recognition method, if the specific frequency region corresponding to the absorption peak of some taste molecules cannot be determined, the absorption peak features can be extracted using a preset neural network to determine the corresponding specific frequency region. Specifically, this includes the following steps:

[0059] Multiple single-taste test objects are acquired, where a single-taste test object refers to an object containing only one taste component. A transceiver antenna is used to transmit a signal to each single-taste test object, and the single-taste reflection signal reflected back from the single-taste test object is received.

[0060] A single taste response signal is subjected to Fourier transform to generate a corresponding single taste frequency domain signal.

[0061] A single taste frequency domain signal is input into a preset neural network to extract the absorption peak of the single taste frequency domain signal and generate a corresponding fingerprint spectrum to determine the specific frequency region corresponding to the absorption peak of each taste component.

[0062] In step S104, the spectral amplitude of the absorption peak of each taste component in the corresponding specific frequency region is obtained, and the concentration of each taste component is calculated.

[0063] For example, such as Figure 3 As shown, in step S103, it has been determined that the taste components include the sweet molecule glucose. When further determining the concentration of glucose, the range around 0.94THz is first taken as a specific frequency region, the spectral amplitude characteristics of the specific frequency region are extracted, and then the concentration of the corresponding taste components is calculated according to the preset algorithm.

[0064] Based on steps S101 to S104, the taste components in the test object are determined, thereby enabling taste recognition. Simultaneously, the concentration of these taste components is also identified with high sensitivity. Experimental data shows that the concentration recognition of taste components in this invention can reach the highest level (D8) in the taste sensitivity analysis method (ISO3972-2011).

[0065] The terahertz wireless sensing-based taste recognition method provided by this invention achieves non-contact, high-sensitivity taste recognition and has a wide range of applications, such as food composition analysis, bionic machines, virtual reality, and smart healthcare.

[0066] Based on the terahertz wireless sensing-based taste recognition method, this invention also provides a terahertz wireless sensing-based taste recognition device, which includes:

[0067] Terahertz source, used to provide terahertz signals.

[0068] A transceiving antenna is configured to emit a terahertz signal to the object to be measured and receive a reflected signal reflected back.

[0069] A signal conversion module is configured to perform Fourier transform on the reflected signal to generate a corresponding frequency domain signal.

[0070] A taste component extraction module is configured to extract an absorption peak and a spectral feature of the frequency domain signal by using a preset neural network, generate a fingerprint spectrum, and determine the taste components of the object to be measured according to a specific frequency region where each absorption peak in the fingerprint spectrum is located and the spectral feature.

[0071] A taste concentration extraction module is configured to extract a spectral amplitude of the absorption peak of each taste component in the corresponding specific frequency region to calculate the concentration of each taste component.

[0072] In some embodiments, a support tube with a preset length is arranged between the transceiving antenna and the object to be measured, so that the transceiving antenna and the object to be measured are kept at a set distance.

[0073] In some embodiments, the length of the support tube is determined according to the focal length of the convex lens in the transceiving antenna. For example, the length of the support tube is set to 9-11 cm. Preferably, the length of the support tube is set to 10 cm.

[0074] In some embodiments, a carrier sheet is arranged on the top of the support tube to hold the object to be measured. The carrier sheet is preferably a non-polar carrier sheet without obvious absorption peaks in the terahertz wave band.

[0075] In some embodiments, the taste recognition device based on terahertz wireless sensing further comprises a band-pass filter and a signal amplifier, which are configured to perform band-pass filtering and signal amplification processing on the reflected signal in the signal conversion module, remove the interference caused by environmental noise and resonance, and improve the strength of the signal.

[0076] The taste recognition device based on terahertz wireless sensing provided by the present application can be used to perform the taste recognition method based on terahertz wireless sensing to achieve high-sensitivity taste recognition, and also has a wide range of application scenarios, such as food component analysis, bionic machines, virtual reality, and smart medical treatment, etc. At the same time, with the development of miniaturization of terahertz sources, the device of the present application can also be deployed in most portable mobile computing devices, such as smart phones, smart watches, etc.

[0077] The present application also provides a computer readable storage medium having a computer program stored thereon, wherein the program is executed by a processor to implement the steps of the taste recognition method based on terahertz wireless sensing.

[0078] Corresponding to the above method, the application further provides a device, which comprises a computer device including a processor and a memory, and the memory stores computer instructions, and the processor is configured to execute the computer instructions stored in the memory, and the device implements the steps of the method as described above when the computer instructions are executed by the processor.

[0079] The application also provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the steps of the edge computing server deployment method. The computer readable storage medium can be a tangible storage medium, such as a random access memory (RAM), a memory, a read-only memory (ROM), an electrically programmable ROM, an electrically erasable programmable ROM, a register, a floppy disk, a hard disk, a removable storage disk, a CD-ROM, or any other form of storage medium known in the art.

[0080] To sum up, the application provides a taste recognition method and device based on terahertz wireless sensing. The method comprises the following steps: transmitting a signal to a to-be-tested object by using a transceiving antenna of a preset terahertz source, and receiving a reflected terahertz reflection signal; performing Fourier transform on the terahertz reflection signal after preprocessing, to generate a corresponding frequency domain signal; extracting an absorption peak and a spectrum feature of the frequency domain signal by using a preset neural network, to generate a fingerprint spectrum; determining a taste component of the to-be-tested object according to a specific frequency region and the spectrum feature of each absorption peak in the fingerprint spectrum; and obtaining a spectrum amplitude of the absorption peak of each taste component in the corresponding specific frequency region, and calculating a concentration of each taste component. The taste recognition method and device based on terahertz wireless sensing provided by the application realize non-contact high-sensitivity taste component and taste concentration recognition, have high recognition speed and high accuracy, and can be widely applied to food component analysis, bionic machines, virtual reality, and intelligent medical treatment, etc.

[0081] Those of ordinary skill in the art should understand that the example components, systems and methods described in conjunction with the embodiments disclosed herein can be implemented in hardware, software, or a combination of the two. Whether the implementation is in hardware or software depends on the specific application and design constraints imposed on the solution. Those of skill can use various approaches to implement the described functionality depending on the specific application and design constraints. Such implementation should not be interpreted as causing a departure from the scope of the application. When implemented in hardware, the hardware can be, for example, an electronic circuit, an application specific integrated circuit (ASIC), appropriate firmware, a plug-in, a functional card, and the like. When implemented in software, the elements of the application are the program or code segments to perform a desired task. The program or code segments can be stored in a machine readable medium, or carried by a data signal in a carrier wave over a transmission medium or communication link.

[0082] It is to be expressly understood that the invention is not limited to the specific configurations and process described above and illustrated in the accompanying drawings. For the sake of clarity, detailed descriptions of known methods are omitted. In the above-described embodiments, several specific steps are described and illustrated as examples. However, the method processes of the present invention are not limited to the specific steps described and illustrated, and various changes, modifications and additions can be made thereto by one of ordinary skill in the art without departing from the spirit of the present invention, and the order of the steps can be changed.

[0083] In the present invention, features described and / or illustrated with respect to one embodiment can be used in the same or a similar way in one or more other embodiments, and / or in combination with or instead of features of other embodiments.

[0084] The above description is merely illustrative of the application, and is not intended to limit the scope of the application. Various modifications and changes can be made by one of ordinary skill in the art without departing from the spirit and scope of the application. Any modification, equivalent replacement, improvement, and the like made within the spirit and principle of the application should be included in the scope of the application.

Claims

1. A taste recognition method based on terahertz wireless sensing, characterized in that, The method includes the following steps: The transceiver antenna of the preset terahertz source transmits a signal to the object under test and receives the terahertz reflected signal from the object under test; the object under test is fixed at a preset distance from the transceiver antenna. The terahertz reflected signal is subjected to Fourier transform to generate the corresponding frequency domain signal; The absorption peaks and spectral features of the frequency domain signal are extracted using a preset neural network to generate a fingerprint spectrum. Based on the frequency regions of each absorption peak in the fingerprint spectrum and the spectral features, the taste components of the object under test are determined, including: when the absorption peak corresponding to the taste component of the object under test belongs to the preset terahertz source frequency band, the taste component of the object under test is determined based on the frequency region of the absorption peak extracted by the preset neural network; when the absorption peak corresponding to the taste component of the object under test does not belong to the preset terahertz source frequency band, the taste component of the object under test is determined based on the spectral features extracted by the preset neural network; wherein, each frequency region corresponds to one taste component. The spectral amplitude of the absorption peak of each taste component in the corresponding frequency region is obtained in order to calculate the concentration of each taste component.

2. The taste recognition method based on terahertz wireless sensing according to claim 1, characterized in that, The sensing distance between the transceiver antenna and the object under test is set to 9-11 cm.

3. The taste recognition method based on terahertz wireless sensing according to claim 1, characterized in that, Before performing a Fourier transform on the terahertz reflected signal to generate the corresponding frequency domain signal, the process further includes: The terahertz reflected signal is subjected to data preprocessing, which includes at least bandpass filtering and signal amplification.

4. The taste recognition method based on terahertz wireless sensing according to claim 1, characterized in that, Before executing the terahertz wireless sensing-based taste recognition method, the method further includes: Multiple single-taste test objects are acquired, each containing only one taste component; a signal is transmitted to the single-taste test object using the transceiver antenna, and a single taste reflection signal reflected back from the single-taste test object is received; The single taste reflection signal is subjected to Fourier transform to generate the corresponding single taste frequency domain signal; The single taste frequency domain signal is input into the preset neural network, the absorption peak of the single taste frequency domain signal is extracted, and the corresponding fingerprint spectrum is generated to determine the frequency region corresponding to the absorption peak of each taste component.

5. A taste recognition device based on terahertz wireless sensing, characterized in that, The device is used to perform the steps of the terahertz wireless sensing-based taste recognition method as described in any one of claims 1 to 4, the device comprising: Terahertz source, used to provide terahertz signals; A transceiver antenna is used to transmit terahertz signals to the object under test and to receive the reflected signals. The signal conversion module is used to perform Fourier transform on the reflected signal to generate a corresponding frequency domain signal; The taste component extraction module is used to extract the absorption peaks and spectral features of the frequency domain signal using a preset neural network to generate a fingerprint spectrum; and to determine the taste components of the object to be tested based on the frequency region where each absorption peak in the fingerprint spectrum is located and the spectral features. The taste concentration extraction module is used to extract the spectral amplitude of the absorption peak of each taste component in the corresponding frequency region in order to calculate the concentration of each taste component.

6. The terahertz wireless sensing-based taste recognition device according to claim 5, characterized in that, A support tube of a preset length is provided between the transceiver antenna and the object under test to maintain a set distance between them.

7. The terahertz wireless sensing-based taste recognition device according to claim 6, characterized in that, A sample plate is provided at the top of the support tube to hold the object to be tested; the sample plate is a non-polar sample plate that has no obvious absorption peak in the terahertz band.

8. The terahertz wireless sensing-based taste recognition device according to claim 5, characterized in that, The device also includes a bandpass filter and a signal amplifier, used to perform bandpass filtering and signal amplification on the reflected signal in the signal conversion module.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps of the method as described in any one of claims 1 to 4.

Images