CN112485202A - Spectrometer for evaluating internal quality of fruit and attenuation slope calculation method - Google Patents
Spectrometer for evaluating internal quality of fruit and attenuation slope calculation method Download PDFInfo
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Abstract
The invention provides a spectrometer for evaluating the internal quality of fruits and an attenuation slope calculation method, wherein the spectrometer for evaluating the internal quality of fruits comprises a computer, a semiconductor laser, a collimating mirror, a multimode optical fiber, a non-contact probe, a single-mode optical fiber, a single-photon detector, a data acquisition card and an optical attenuator; a collimating lens is arranged in front of a light outlet of the semiconductor laser, and laser emitted by the semiconductor laser is led into the light attenuator after being collimated by the collimating lens; the light outlet of the optical attenuator is connected with one end of the multimode fiber by adopting an FC interface; the other end of the multimode fiber is vertically fixed on the non-contact probe through an FC interface; one end of the single mode fiber is vertically fixed on the non-contact probe through an FC interface, and the other end of the single mode fiber is connected with the single photon detector; the single photon detector is electrically connected with the input end of the data acquisition card; the output end of the data acquisition card is electrically connected to the computer. The instrument is little affected by the environment, has good stability and low cost, and can flexibly set parameters.
Description
Technical Field
The invention relates to the technical field of food/agricultural product quality detection, in particular to a spectrometer for evaluating the internal quality of fruits and an attenuation slope calculation method.
Background
The fruit industry is the third industry behind the ranking of grains and vegetables in the planting industry of China, is one of the post industries of the rural economic development of China, and is also an important way for farmers to have employment and increase income. Although China is a big fruit producing country and the export amount is generally increased, the fruit consumption market is still mainly concentrated in China. The fruit yield increase, the good quality and the poor quality of the fruits become typical characteristics of fruit sales in China in recent years, and the main reasons are that fruit growers seek high yield in production, neglect quality, and have low fruit commercialization processing level and poor average quality. Consumers often prefer to buy expensive fruits and also prefer to buy damaged or even rotten fruits, which directly results in huge economic loss of fruit industry and brings about serious food safety hidden dangers, environmental pollution and other problems. Therefore, in each post-harvest link, the quality of the fruits is detected and graded in time, and the method has very important practical significance for improving the quality of the fruits in China, reducing the economic loss of the fruit industry and enhancing the international competitiveness. Developing an accurate, reliable and fast automatic detection technology capable of detecting and grading the quality of fruits has become an important scientific research target of the fruit industry. The fruit quality grading is divided into appearance quality grading and interior quality grading. Optical grading technology combined with machine vision technology is a hot spot and a major development direction for the grading of the appearance quality of fruits. Unfortunately, appearance quality grading can only address the facies demand for fruit, and cannot determine the internal quality. With the increasing concern of consumers on the taste and quality of fruits, the detection of the internal quality of the fruits is particularly important. At present, dielectric property detection technology, nuclear magnetic resonance detection technology, electronic tongue and electronic nose technology, acoustic and ultrasonic detection technology, optical detection technology and the like are tried to be used for detecting the internal quality of fruits. The optical detection technology (especially visible light/near infrared spectrum technology and hyperspectral imaging technology) becomes a main means and method because of the advantages of non-contact, strong stability, high precision, small environmental influence, no damage, automatic industrialization and the like. However, the spectroscopic technique is an empirical technique essentially, and it is an empirical technique that a statistical method is used to establish a correlation between spectral characteristics and chemical or physical properties of a sample, and cannot reflect physical changes such as internal scattering of fruit, evaporation of fruit surface, brownian motion of particles inside fruit, and cannot reflect physiological changes such as movement of organelles, cell mass flow, transport of intracellular substances, cell division and growth, and the propagation of light inside fruit tissues does not completely follow Beer-Lambert law, so that the visible/near infrared spectroscopic technique has problems of unstable analysis model, poor adaptability, difficulty in further improvement of analysis accuracy, and the like. The hyperspectral imaging technology combines the image technology and the spectrum technology to realize the detection of the fruit quality, and reflects the difference of the physical structure and the chemical composition in the sample by relying on the spectrum information, which has the same difficulty as the spectrum technology.
Near infrared diffusion spectroscopy (DCS) is a new method for nondestructive detection of deep physical and physiological processes of biological tissues, and is widely used in the biomedical field at present, and is well applied to cancer imaging, diagnosis and treatment detection, detection and diagnosis of stroke, mitochondrial diseases, epilepsy detection, detection of brain function activity and brain injury, muscle activity detection and the like. The DCS technology carries out quantitative detection on deep physical change and physiological change in the tissue by calculating a time correlation function of the speckle spot light intensity of the surface tissue by means of a rapid single photon detection technology and an optical fiber technology. The internal physical change and physiological state change of the fruit are related to the speckle activity of the fruit. The fruit speckle activity refers to the phenomenon that coherent light is adopted to irradiate fruit tissues, and biological speckles are generated by interaction of the coherent light and the fruit tissues. The biological speckle image is actually a hybrid image of light intensity fluctuation speckles caused by internal changes in the tissue. At present, no method and equipment for detecting the internal quality of the fruit by adopting near infrared diffusion related spectrum exists at home and abroad.
Disclosure of Invention
In order to solve the problems, the invention provides a spectrometer for evaluating the internal quality of fruits and an attenuation slope calculation method; a spectrometer for evaluating the internal quality of fruits comprises a computer, a semiconductor laser, a collimating mirror, a multimode optical fiber, a non-contact probe, a single-mode optical fiber, a single-photon detector, a data acquisition card and an optical attenuator;
the laser emitted by the semiconductor laser is led into the optical attenuator after being collimated by the collimating mirror, and the intensity of the incident laser is adjusted by the optical attenuator;
the light outlet of the optical attenuator is connected with one end of the multimode fiber by adopting an FC interface;
the other end of the multimode fiber is vertically fixed on the non-contact probe through an FC interface;
one end of the single mode fiber is vertically fixed on the non-contact probe through an FC interface, and the other end of the single mode fiber is connected with the single photon detector; intermittent random photon flow collected by the non-contact probe is transmitted to a single photon detector through a single mode fiber and is converted into electric pulse flow by the single photon detector;
the single photon detector is electrically connected with the input end of the data acquisition card; the data acquisition card samples the total number of photons in unit time according to the electric pulse stream;
the output end of the data acquisition card is electrically connected to the computer; and the computer acquires the sampling result of the data acquisition card and stores the sampling result in the memory for carrying out normalization correlation calculation on the light intensity.
Further, the collimating lens is an aspheric lens collimating lens; the non-contact probe includes: the device comprises an imaging lens, a long-pass filter, a light source and a detector optical fiber probe plate; the long-pass filter and the imaging lens are coaxially arranged and are arranged in front of the imaging lens, and the light source and the detector optical fiber probe plate are arranged at the image plane of the imaging lens; the imaging lens, the long-pass filter, the light source and the detector optical fiber probe plate are packaged by an aluminum alloy shell to form the non-contact probe.
Further, the method for calculating the attenuation slope of the internal quality evaluation of the fruit specifically comprises the following steps:
s101: the method comprises the following steps of emitting laser by using a semiconductor laser, wherein the laser enters a multimode optical fiber after being collimated by a collimating mirror, and the laser in the multimode optical fiber is incident to the surface of a fruit to be detected through a non-contact probe;
s102: the laser incident to the fruit to be detected enters the fruit tissue to be scattered, diffused light overflows from the surface of the fruit tissue at different distances from the incident position, the diffused light is collected by a non-contact probe and then enters a single mode fiber, and the discontinuous random photon flow collected by the single mode fiber is converted into electric pulse flow by a single photon detector;
s103: the data acquisition card receives the electric pulse stream, controls the clock end of the counter through the output sampling clock of the data acquisition card, counts photons in the unit sampling clock input to the counter to obtain a counting result, and transmits the counting result to the data acquisition card;
s104: the data acquisition card acquires the counting result and sends the counting result to the computer, and the computer stores the counting result in a local memory; and meanwhile, carrying out normalized autocorrelation calculation on the counting result, and carrying out fitting calculation to obtain a normalized autocorrelation attenuation slope.
Further, in step S104, the normalized autocorrelation function of the light intensity is used to perform normalized autocorrelation calculation on the counting result, and the specific formula is as follows:
wherein g (i, τ) is a normalized autocorrelation function of the light intensity; n (i) represents the number of photons at time i Δ t; n (i + τ) represents the number of photons at time (i + τ) Δ t, < > represents the time average; delta t is the acquisition time; i is the current ith sample; τ represents a delay time; k is the number of data extracted from the memory during calculation; eta is the data number of the translation operation in the autocorrelation calculation; the computer 1 extracts k data from the memory, calculates the photon number in unit time by using difference, carries out eta translation on the photon number array, then multiplies the photon number array, namely realizes the autocorrelation calculation with the delay time of eta delta t, and calculates the normalized autocorrelation attenuation slope by fitting.
The technical scheme provided by the invention has the beneficial effects that: according to the technical scheme provided by the invention, the time correlation function of the speckle spot light intensity of the fruit surface tissue is calculated, so that the optical nondestructive detection of the deep physical change and the physiological change in the fruit tissue with low cost, rapidness, no damage, real time and qualitative and quantitative performance is realized.
Drawings
The invention will be further described with reference to the accompanying drawings and examples, in which:
FIG. 1 is a diagram of a spectrometer for evaluating the internal quality of fruit according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a counter for sampling optical pulses in accordance with an embodiment of the present invention;
fig. 3 is a schematic flow chart of a method for calculating an attenuation slope for evaluating the internal quality of a fruit according to an embodiment of the present invention.
Detailed Description
For a more clear understanding of the technical features, objects and effects of the present invention, embodiments of the present invention will now be described in detail with reference to the accompanying drawings.
The embodiment of the invention provides a spectrometer for evaluating the internal quality of fruits and an attenuation slope calculation method.
Referring to fig. 1, fig. 1 is a diagram of a spectrometer for evaluating internal quality of fruit according to an embodiment of the present invention; the spectrometer provided by the embodiment of the invention comprises: the system comprises a computer 1, a semiconductor laser 2, a collimating mirror 3, a multimode optical fiber 4 (the core diameter is 200 mu m, and NA is 0.17), a non-contact probe 5, a single mode optical fiber 7 (the core diameter is 4.7 mu m, and NA is 0.13), a single photon detector 8, a data acquisition card 9 and an optical attenuator 14; the non-contact probe 5 is arranged at a preset distance from the fruit 11 to be detected; in the embodiment of the invention, the distance between the non-contact probe 5 and the fruit 11 to be detected is 5 cm;
wherein, a collimating lens 3 is arranged in front of a light outlet of the semiconductor laser 2, the laser emitted by the semiconductor laser 2 is led into an optical attenuator 14 after being collimated by the collimating lens 3, and the intensity of the incident laser is adjusted by the optical attenuator;
the light outlet of the optical attenuator 14 is connected with one end of the multimode optical fiber 4 by adopting an FC interface;
the other end of the multimode fiber 4 is vertically fixed on the non-contact probe 5 through an FC interface;
one end of the single mode fiber 7 is vertically fixed on the non-contact probe 5 through an FC interface, and the other end is connected with the single photon detector 8; the intermittent random photon flow collected by the non-contact probe 5 is transmitted to a single photon detector 8 through a single mode fiber 7 and converted into an electric pulse flow by the single photon detector 8;
the single photon detector 8 is electrically connected with the input end of the data acquisition card 9; the data acquisition card 9 samples the total number of photons in unit time according to the electric pulse stream;
the output end of the data acquisition card 9 is electrically connected to the computer 1; the computer 1 acquires the sampling result of the data acquisition card 9 and stores the sampling result in the memory for the normalization correlation calculation of the light intensity.
In the embodiment of the invention, the data acquisition card 9 adopts a PCI6602 acquisition card of NI company; the detected optical signal enters a high-sensitivity single-photon detector 8 through a single-mode optical fiber 7, a PCI6602 sampling clock is input to a clock end of a counter, and the single-photon detector 8 outputs 25ns TTL pulse signals and data are acquired through a PCI6602 of an NI company and then enter a computer 1.
In the embodiment of the present invention, the collimating lens 3 is an aspheric lens collimating lens. The noncontact probe 5 includes: an imaging lens 6, a long-pass filter 12 (below 630 nm), a light source and detector fiber probe plate 13; the long-pass filter 12 is arranged coaxially with the imaging lens 6 and is arranged in front of the imaging lens 6, and the light source and detector optical fiber probe plate 13 is arranged at the image plane of the imaging lens 6; the imaging lens 6, the long-pass filter 12, the light source and the detector optical fiber probe plate 13 are packaged by an aluminum alloy shell to form the non-contact probe 5.
The light source and detector optical fiber probe board 13 is provided with a plurality of light source and detector intervals, the light source part adopts a long coherent semiconductor continuous laser with the wavelength of 785nm, the laser power is 100mW, the coherence length is more than 5m, the laser stability is high, the mode hopping phenomenon does not occur within 3 hours, and the power stability is 1%.
The multimode optical fiber 4 is vertically fixed on the light source and detector optical fiber probe plate 13 through an FC interface, and the single mode optical fiber 7 for detection is vertically fixed on the light source and detector optical fiber probe plate 13 through the FC interface.
Referring to fig. 2, fig. 2 is a schematic diagram illustrating a principle of sampling an optical pulse by a counter according to an embodiment of the present invention; the data acquisition card 9 is provided with an 8-channel counter/timer of a digital I/O line; the counter of the data acquisition card 9 samples the total number of photons per unit time by means of the electrical pulse stream.
The single mode optical fibre 7 may be multiple, with FC fixed perpendicularly to the interface for probing different depths provided by the light source and detector fibre probe plate 13.
The normalized correlation calculation of the light intensity has the following specific formula:
wherein g (i, τ) is a normalized autocorrelation function of the light intensity; n (i) represents the number of photons at time i Δ t; n (i + τ) represents the number of photons at time (i + τ) Δ t, < > represents the time average; delta t is the acquisition time; i is the current ith sample; τ represents a delay time; k is the number of data extracted from the memory during calculation; eta is the data number of the translation operation in the autocorrelation calculation; the computer (1) extracts k data from a memory, calculates the photon number in unit time by using difference, carries out eta translation on the photon number array, then multiplies the photon number array, namely realizes autocorrelation calculation with delay time of eta delta t, and calculates the normalized autocorrelation attenuation slope by fitting.
Referring to fig. 3, fig. 3 is a schematic flowchart of an attenuation slope calculation method for evaluating internal fruit quality according to an embodiment of the present invention, applied to the spectrometer for evaluating internal fruit quality; the attenuation slope calculation method provided by the embodiment of the invention specifically comprises the following steps:
s101: the method comprises the following steps that a semiconductor laser 2 is used for emitting laser, the laser enters a multimode optical fiber 4 after being collimated by a collimating lens 3, and the laser in the multimode optical fiber 4 is incident to the surface of a fruit 11 to be detected through a non-contact probe 5;
s102: the laser incident to the fruit 11 to be detected enters the interior of the tissue of the fruit 11 to be scattered, diffused light overflows from the surface of the tissue of the fruit 11 at different distances from the incident position, the diffused light is collected by the non-contact probe 5 and then enters the single mode fiber 7, and discontinuous random photon flow collected by the single mode fiber 7 is converted into electric pulse flow by the single photon detector 8;
s103: the data acquisition card 9 receives the electrical pulse stream, controls the clock end of the counter through the output sampling clock of the data acquisition card 9, counts photons input into the unit sampling clock of the counter to obtain a counting result, and transmits the counting result to the data acquisition card 9;
s104: the data acquisition card 9 acquires the counting result and sends the counting result to the computer 1, and the computer 1 stores the counting result in a local memory; and meanwhile, carrying out normalized autocorrelation calculation on the counting result, and carrying out fitting calculation to obtain a normalized autocorrelation attenuation slope.
Finally, the computer 1 brings the autocorrelation attenuation slope into a pre-established fruit quality prediction model to predict the internal quality of the fruit 11 to be measured.
In step S104, a normalized autocorrelation function of the light intensity is used to perform normalized autocorrelation calculation on the counting result, wherein the specific formula is as follows:
in the above formula, g (i, τ) is the normalized autocorrelation function of the light intensity; n (i) represents the number of photons at time i Δ t; n (i + τ) represents the number of photons at time (i + τ) Δ t, < > represents the time average; delta t is the acquisition time; i is the current ith sample; τ represents a delay time; k is the number of data extracted from the memory during calculation; eta is the data number of the translation operation in the autocorrelation calculation; the computer 1 extracts k data from the memory, calculates the photon number in unit time by using difference, carries out eta translation on the photon number array, then multiplies the photon number array, namely realizes the autocorrelation calculation with the delay time of eta delta t, and calculates the normalized autocorrelation attenuation slope by fitting;
and establishing a prediction model by using the attenuation slope and the internal quality parameters of the fruit. k Δ t is the measured time resolution, and if the time resolution needs to be adjusted, the value of k is modified. The first eta photon numbers and the last eta photon numbers in the photon number array are deleted, the delay time of eta delta t can be realized, and the light intensity normalization correlation calculation of different delay times can be realized by changing the deleted photon number eta.
The autocorrelation is the cross-correlation of a signal with itself at different points in time, i.e. the similarity between two observations as a function of the time difference between them, where the normalized autocorrelation of the light intensity is calculated, since the light intensity signal appears as a discrete light pulse signal, i.e. the number of photons, < n (i) · n (i + τ) > denotes the average of the similarity between i and i + τ measurements over the time difference between them.
In the disclosed example, the autocorrelation operation and counting are performed simultaneously, the time resolution of the DCS is set by setting the number of data extracted from the memory by the computer, and the delay time of the DCS is set by the number of steps of performing the translation operation on the photon matrix.
The invention has the beneficial effects that: according to the technical scheme provided by the invention, the time correlation function of the speckle spot light intensity of the fruit surface tissue is calculated, so that the optical nondestructive detection of the deep physical change and the physiological change in the fruit tissue with low cost, rapidness, no damage, real time and qualitative and quantitative performance is realized.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (8)
1. The utility model provides a spectrum appearance of inside quality evaluation of fruit which characterized in that: the method comprises the following steps: the device comprises a computer (1), a semiconductor laser (2), a collimating mirror (3), a multimode fiber (4), a non-contact probe (5), a single mode fiber (7), a single photon detector (8), a data acquisition card (9) and an optical attenuator (14);
wherein, a collimating lens (3) is arranged in front of a light outlet of the semiconductor laser (2), laser emitted by the semiconductor laser (2) is led into an optical attenuator (14) after being collimated by the collimating lens (3), and the intensity of the incident laser is adjusted by the optical attenuator;
the light outlet of the optical attenuator (14) is connected with one end of the multimode optical fiber (4) by adopting an FC interface;
the other end of the multimode fiber (4) is vertically fixed on the non-contact probe (5) through an FC interface;
one end of the single-mode optical fiber (7) is vertically fixed on the non-contact probe (5) through an FC interface, and the other end is connected with the single-photon detector (8); intermittent random photon flow collected by the non-contact probe (5) is transmitted to a single-photon detector (8) through a single-mode optical fiber (7) and is converted into electric pulse flow by the single-photon detector (8);
the single photon detector (8) is electrically connected with the input end of the data acquisition card (9); the data acquisition card (9) samples the total number of photons in unit time according to the electric pulse stream;
the output end of the data acquisition card (9) is electrically connected to the computer (1); the computer (1) acquires the sampling result of the data acquisition card (9) and stores the sampling result in the memory for carrying out the normalization calculation of the light intensity.
2. The spectrometer for evaluating the internal quality of fruit according to claim 1, wherein: the collimating lens (3) is an aspheric lens collimating lens.
3. The spectrometer for evaluating the internal quality of fruit according to claim 1, wherein: the non-contact probe (5) comprises: the device comprises an imaging lens (6), a long-pass filter (12), a light source and detector optical fiber probe plate (13); the long-pass filter (12) and the imaging lens (6) are coaxially arranged and are arranged in front of the imaging lens (6), and the light source and detector optical fiber probe plate (13) is arranged at the image plane of the imaging lens (6); the imaging lens (6), the long-pass filter (12), the light source and the detector optical fiber probe plate (13) are packaged by a shell to form the non-contact probe (5).
4. A spectrometer for fruit internal quality assessment according to claim 3, wherein: the shell is made of aluminum alloy.
5. A spectrometer for fruit internal quality assessment according to claim 3, wherein: the multimode optical fiber (4) is vertically fixed on the light source and detector optical fiber probe plate (13) through an FC interface, and the single mode optical fiber (7) for detection is vertically fixed on the light source and detector optical fiber probe plate (13) through the FC interface.
6. The spectrometer for evaluating the internal quality of fruit according to claim 1, wherein: the data acquisition card (9) is provided with a channel counter of a digital I/O line (8); the counter of the data acquisition card (9) samples the total number of photons per unit time by means of the electrical pulse stream.
7. An attenuation slope calculation method for evaluating the internal quality of a fruit is applied to a spectrometer for evaluating the internal quality of the fruit according to any one of claims 1 to 6; the method is characterized in that: the method for calculating the attenuation slope of the fruit internal quality evaluation specifically comprises the following steps:
s101: the semiconductor laser (2) emits laser, the laser enters the multimode optical fiber (4) after being collimated by the collimating lens (3), and the laser in the multimode optical fiber (4) is incident to the surface of the fruit (11) to be detected through the non-contact probe (5);
s102: the laser incident to the fruit (11) to be detected enters the interior of the tissue of the fruit (11) to be scattered, diffused light overflows from the surface of the tissue of the fruit (11) at different distances from the incident position, the diffused light is collected by the non-contact probe (5) and then enters the single mode fiber (7), and the discontinuous random photon flow collected by the single mode fiber (7) is converted into electric pulse flow by the single photon detector (8);
s103: the data acquisition card (9) receives the electric pulse stream, controls the clock end of the counter through the output sampling clock of the data acquisition card (9), counts photons input into the unit sampling clock of the counter to obtain a counting result, and transmits the counting result to the data acquisition card (9);
s104: the data acquisition card (9) acquires the counting result and sends the counting result to the computer (1), and the computer (1) stores the counting result in a local memory; and meanwhile, carrying out normalized autocorrelation calculation on the counting result, and carrying out fitting calculation to obtain a normalized autocorrelation attenuation slope.
8. The method for calculating the attenuation slope of the internal quality evaluation of the fruit according to claim 7, wherein: in step S104, a normalized autocorrelation function of the light intensity is used to perform normalized autocorrelation calculation on the counting result, wherein the specific formula is as follows:
wherein g (i, τ) is a normalized autocorrelation function of the light intensity; n (i) represents the number of photons at time i Δ t; n (i + τ) represents the number of photons at time (i + τ) Δ t, < > represents the time average; delta t is the acquisition time; i is the current ith sample; τ represents a delay time; k is the number of data extracted from the memory during calculation; eta is the data number of the translation operation in the autocorrelation calculation; the computer (1) extracts k data from a memory, calculates the photon number in unit time by using difference, carries out eta translation on the photon number array, then multiplies the photon number array, namely realizes autocorrelation calculation with delay time of eta delta t, and calculates the normalized autocorrelation attenuation slope by fitting.
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| CN202011120187.0A CN112485202A (en) | 2020-10-19 | 2020-10-19 | Spectrometer for evaluating internal quality of fruit and attenuation slope calculation method |
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