WO1995009698A1 - Dispositif de reconnaissance et/ou de tri de fruits ou legumes, procede et utilisation correspondants - Google Patents
Dispositif de reconnaissance et/ou de tri de fruits ou legumes, procede et utilisation correspondants Download PDFInfo
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- WO1995009698A1 WO1995009698A1 PCT/FR1994/001139 FR9401139W WO9509698A1 WO 1995009698 A1 WO1995009698 A1 WO 1995009698A1 FR 9401139 W FR9401139 W FR 9401139W WO 9509698 A1 WO9509698 A1 WO 9509698A1
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- light
- analysis
- sorting
- channels
- product
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B07—SEPARATING SOLIDS FROM SOLIDS; SORTING
- B07C—POSTAL SORTING; SORTING INDIVIDUAL ARTICLES, OR BULK MATERIAL FIT TO BE SORTED PIECE-MEAL, e.g. BY PICKING
- B07C5/00—Sorting according to a characteristic or feature of the articles or material being sorted, e.g. by control effected by devices which detect or measure such characteristic or feature; Sorting by manually actuated devices, e.g. switches
- B07C5/34—Sorting according to other particular properties
- B07C5/3416—Sorting according to other particular properties according to radiation transmissivity, e.g. for light, x-rays, particle radiation
Definitions
- the field of the invention is that of the recognition and analysis of one or more characteristics of fruits or vegetables, in particular with a view to carrying out a qualitative sorting of these fruits or vegetables. More specifically, the present invention relates to a non-destructive device and method for the recognition and qualitative sorting of fruits and vegetables.
- the invention can in particular be applied to the automatic sorting of whole unpeeled potatoes, whole peeled potatoes, garden tomatoes and greenhouse tomatoes, onions, peppers, peaches, apricots and citrus fruits, whatever their destination.
- These fruits and vegetables can for example be intended for industrial processing, for consumption or for seed (in particular for potatoes).
- Some of these machines analyze the spectral characteristics of the reflected light.
- the products are illuminated and the reflected light captured is measured and analyzed for a number of wavelengths.
- the major drawback of these machines is that the analysis relates only to the external aspect of the product.
- the internal state of the product is not analyzed and the quality is therefore determined solely according to the state of the surface (and possibly a layer of insignificant thickness below it).
- these machines do not provide enough information regarding the quality of the product and are therefore characterized by poor sorting accuracy.
- a weakness common to these devices is their insufficient accuracy in sorting. They also have the drawback of being very sensitive to stray light reflections, due for example to the irregular shape of the product or to other random factors. Another of their weaknesses is that they are specific to a given product or application.
- the known devices are therefore insufficiently precise to allow efficient industrial use. In particular, they do not allow effective detection of a local product defect. In addition, they are generally dedicated to a given type of product and application.
- the invention particularly aims to overcome these various drawbacks of the state of the art.
- an objective of the invention is to provide a device for recognizing and / or sorting fruit or vegetables of high precision, allowing in particular the detection and taking into account of local internal or external faults, even of small size, and possibly determining the location of these faults.
- Another object of the invention is to provide such a device that can be used for a large number of fruits or vegetables and for a large number of applications.
- an object of the invention is to provide such a device which is easily adaptable as required.
- the invention aims to provide such a device which detects the presence or not of internal or external defects due to diseases, insects, rodents, worms or mechanical damage, maturity, color, shape, size and dry matter content of a fruit or vegetable, or at least one of these.
- Another particular objective of the invention is also to provide such a device capable of overcoming the aging of certain components, in particular optical components.
- a device for recognizing and / or sorting fruit or vegetables comprising means for lighting an object. recognizing and / or sorting, emitting at least one beam of incident light, means for recovering at least part of the light scattered by said object and means for analyzing said scattered light, generating recognition information and / or sorting representative of said object, said recovery means comprising at least two independent optical receivers, placed on separate axes and different from the axis of said beam of incident light, so that said optical receivers receive light fluxes distinct scattered corresponding to at least partially distinct portions of said scattered light, said analysis means processing each of said lumi flows independently neux.
- object or, indifferently, product for designate any element capable of being treated by the device of the invention, that is to say, essentially, fruits and vegetables, but also, where appropriate, any foreign body such as stones or clods of Earth...
- An essential characteristic of the invention is therefore to treat two distinct light fluxes independently, corresponding to at least partially different portions of the object. It is a completely new approach for those skilled in the art. Indeed, it has always sought to analyze the light returned by the object so as to obtain as much information as possible in a single beam, either by recovering direct light (in the axis of the incident light ), or by grouping two reflected beams. It was a specifically global approach, simply delivering information of global quality and generally unreliable.
- the invention it is easy to detect local faults, and possibly to locate them in the object, while of course allowing the determination of an indication of overall quality.
- the fact that the light recovered is scattered light means that it carries precise and reliable information on the internal quality of the product.
- said optical receivers are placed symmetrically on either side of the axis of said beam of incident light.
- the axis of each of said optical receivers forms with the axis of said beam of incident light an angle between 120 ° and 150 °.
- said analysis means take into account at least two successive measurements of scattered light corresponding to the projection of said incident light beam on areas at least partially distinct from said object. In this way, the analysis is very precise, and makes it possible to detect small defects.
- said optical receivers comprise at least one of the means belonging to the group comprising objectives and slit diaphragms.
- the slit width of said slit diaphragms is for example chosen so that two consecutive measurement readings correspond to two substantially slices contiguous on said object.
- the device comprises means for dividing and / or filtering at least one of said light fluxes diffused into at least two light channels having distinct frequency bands.
- Said frequency bands are for example chosen in the range from 550 to 900 nm.
- the analysis means process these different channels to perform the sorting, according to a process more precisely described below.
- the device of the invention also comprises a set of means for transforming each of said light fluxes or channels into optoelectronic signals supplying said analysis means, and means for calibrating said transformation means, delivering the same reference. light to each of said transformation means.
- the device of the invention also comprises a complementary optical receiver placed in the axis of said incident light beam and used as a detector for the presence of an object in the field of said incident beam
- This additional receiver ensures synchronization of the device, and in particular of the analysis means and the calibration means.
- the device of the invention comprises means for adding at least two light flows and / or channels coming from separate optical receivers, so as to form a complementary channel.
- Said complementary channel may in particular have a frequency band between 900 and 1500 nm. In this case, it allows, among other things, to determine the dry matter content.
- this device comprises reflecting means placed so as to adapt the ratio between the light scattered by said object and the light reflected by said object in the light received by said optical receivers.
- the existence, positioning and reflection coefficient of these means of reflection are chosen according to needs, and in particular according to the preponderance of the external or internal quality of the product.
- said analysis means comprise means for calculating the logarithm of the ratio of two distinct light channels extracted from the same light flux.
- said analysis means also comprise means for detecting stray light reflections on said object, so as to correct the measurements made.
- the device comprises means for programming at least one recognition and / or sorting threshold value, informing said analysis means.
- the device comprises means for programming at least one recognition and / or sorting threshold value, informing said analysis means.
- the device comprises means for bringing objects to be sorted, directing said objects so that they fall in free fall between said lighting means and said light recovery means broadcast.
- said supply means comprise at least one N-shaped element, each branch of which comprises at least two parallel bands running at different speeds.
- the invention also relates to a method for recognizing and / or sorting fruit or vegetables, comprising the following steps: emission of a beam of light incident on an object to be recognized and / or sorted; recovery of part of the light scattered by said object by at least two independent optical receivers, placed on separate axes and different from the axis of said beam of incident light, so as to obtain distinct scattered light fluxes corresponding to at least partially distinct portions of said scattered light; analysis of said diffused light fluxes, so as to produce recognition and / or sorting information representative of said object.
- said analysis step comprises the following steps: determination of at least two light channels having distinct frequency bands from at least one of said light fluxes; optoelectronic transformation of said light channels into corresponding electrical signals; calculation of the ratio of two electrical signals corresponding to light channels originating from the same light flux; comparison of said report with at least one threshold value, so as to produce recognition and / or sorting information.
- the method advantageously further comprises a step of calculating the logarithm of said ratio.
- said comparison step comprises the steps of: prior determination of a set of reference indices taking into account at least one of the information belonging to the group comprising the length and / or the surface of said object, the ratio of two light channels , the logarithm of said report, the specific characteristics of the fruits or vegetables to be sorted, the sorting criteria set by a user; calculation of a set of indices representative of the object to be sorted, said set of indices comprising at least one index; - comparison of each index representative of the object to be sorted with the corresponding reference indices.
- this method comprises the following steps: bringing said object into free fall opposite said beam of incident light; making at least two successive measurement readings, corresponding to two zones at least partially distinct from said object; calculation of a ratio of two electrical signals corresponding to light channels originating from the same light flux for each of said successive measurement readings; determination of a curve representative of the evolution of said ratio during the free fall of said object; analysis of said curve so as to determine information representative of the overall quality of said object.
- the method of the invention may also include a step of grouping at least two light fluxes on a predetermined frequency band and a step of analyzing the complementary channel produced during said grouping step, delivering information representative of the content in dry matter of said object.
- the method also comprises a step of detecting the presence of an object facing said light beam, producing presence information, and a synchronization step, taking account of said presence information.
- the method comprises a step of estimating the weight of said object.
- This information can in particular enable the overall weight and / or by sorting categories of sorted products to be estimated.
- the device and / or method of the invention can in particular be used for at least one of the applications belonging to the group comprising: analysis of the internal quality of a fruit or vegetable; analysis of the external quality of a fruit or vegetable; - analysis of the internal color of a fruit or vegetable; analysis of the external color of a fruit or vegetable; analysis of the shape and or size of a fruit or vegetable; analysis of the dry matter content of a fruit or vegetable; detection of internal or external defects due to a disease, an insect, a rodent, a worm or mechanical damage; detection of a foreign body such as a stone or a clod of earth.
- the invention can in particular be implemented for at least one of the fruits and / or vegetables belonging to the group comprising: peeled potatoes; - unpeeled potatoes; garden tomatoes and greenhouse tomatoes; onions ; peppers; peaches; - apricots; citrus.
- the fruits and / or vegetables belonging to the group comprising: peeled potatoes; - unpeeled potatoes; garden tomatoes and greenhouse tomatoes; onions ; peppers; peaches; - apricots; citrus.
- FIG. 2 is a diagram illustrating the principle of the reception of the light transmitted through the product by two main channels A and B and their sharing into five beams containing the different sectors of the spectrum analyzed;
- FIG. 3 shows some illustrative embodiments of the ratio of two signals of different wavelengths corresponding to different qualities of the product;
- FIG. 4A to 4F illustrate some embodiments of signals from the channels
- a and B corresponding to different positions of a defect in the product
- FIG. 5 is a diagram showing the operating algorithm of the logic analyzer
- - Figure 6 shows the principle of the simultaneous reception of transmitted light and reflected light from a product
- - Figures 7A and 7B give two examples of the light reflection on the product passing through the inspection area, depending on whether it has a regular or irregular shape
- - Figure 8 is a block diagram of the photometric camera of the device
- - Figure 9 is a block diagram of the analysis means of the device of the invention
- FIG. 10 is a diagram of the synchronization means of Figure 9;
- - Figure 11 is a diagram of the means for recognizing completely defective products and foreign bodies;
- - Figure 12 shows the time diagrams of the main signals generated during the passage of the product in the device of the invention;
- the advantages of the device of the invention are recalled.
- the achievements obtained by scanning the three sides contain information on the internal and external state of it, allowing the recognition of everything type of defect using only two informative sectors of the spectrum ⁇ l and ⁇ 2.
- the use of an additional informative sector ⁇ c in the near infrared region makes it possible to recognize, in combination with ⁇ l and ⁇ 2, the dry matter content (for potatoes, tomatoes etc.), or the presence of cavities, while recognizing the degree of maturity of the product (respectively the internal and external color of tomatoes for example). This information is obtained without rotation of the product or of the optical system as is the case with certain known devices.
- the sorting error is minimized using an iterative procedure according to which, for a number of combinations of indices equal to that of the classes sought, each combination having maximum classification accuracy in a given class, taking final decision on the classification of the product is made using a multi-element logical classifier which takes into account the wishes of the user on the primacy of precision in this or that class.
- the known methods do not offer these possibilities, because they classify objects into two or more classes in a fixed manner and using image recognition where the objects are divided into classes by a single informative combination containing a limited number of clues.
- Another advantage is that it is possible to recognize multiple defects in various products, and also, the overall quality of whole unpeeled potatoes intended for consumption, processing or seed, the overall quality of potatoes whole peeled earth, the overall quality of tomatoes intended for consumption or processing, the overall quality of peaches and whole apricots, the overall quality of citrus fruits, plums, peppers, onions etc.
- Another advantage of the invention consists in the elimination of light reflections during the scanning of the product, thus considerably increasing the sorting precision.
- the product oriented along its length, then projected through the measuring zone of the photometric camera along a path determined by its initial speed and its size, falls, deflected or not laterally by pulses of compressed air controlled by solenoid valves and depending on the chosen category, in channels covered with a specially shaped surface intended to avoid mechanical damage.
- the device gives the possibility of predetermining the correspondence between the three categories and the three product outlet channels, as well as grouping together different categories (for example: first and second or second and third in the same channel), thus allowing to leave fall without deviation the largest fraction quantit ⁇ ment to save compressed air.
- Another advantage lies in the fact that, in addition to the qualitative recognition of the product, the quantity and mass of the product are also determined. each of the categories, by choosing in the computer, for the different products or for the different species of a given product, the corresponding approximation model.
- the simultaneous measurement of the quantity (mass) of the products in each of the categories gives the possibility of stopping the sorting at the appropriate time after reaching a desired quantity in a given category (and this, automatically or by operator intervention) .
- the invention allows sorting according to one or more quality constraints, namely: internal and external defects, maturity, color, shape and dry matter content, without deteriorating the integrity of the product, and to recognize and discriminate between non-standard products in size (too small or too large), soil residue and other foreign bodies.
- This task of recognizing the quality of fruit and vegetables is accomplished according to the principle illustrated in FIGS. 1A and IB by measuring the light transmittance of product 101 (for example a potato) - exposed from one side to a light source white 102 - thanks to the transmitted light perceived by two optical channels A and
- the invention is distinguished in particular by the fact that the transmitted light returns through a region of the surface of the product, namely the side exposed to the incident light, and crosses the entire coplanar edge 104 like the filament of the lamp 102 , to stand out in particular from the two regions overlooking the optical channels A and B, knowing that the sides in question are complementary and of the same area and shape.
- the light perceived by channels A and B is divided into five beams 1A, 2A, IB, 2B and C, as illustrated in FIG. 2.
- These beams contain different sectors of the product spectrum , so that it is possible to use simultaneously up to five different wavelengths ⁇ l A, ⁇ 2A, ⁇ lB, ⁇ 2B and ⁇ C for the identification of the desired quality.
- the scanning of the product along its length L and through the five information channels thus formed gives rise to realizations of the U ⁇ lA (L) type respectively, U ⁇ 2A (L), U ⁇ lB (L), U ⁇ 2B (L) and U ⁇ C (L) where the wavelengths ⁇ l and ⁇ 2 of the visual and near infrared region are chosen in the range of 550 to 900 nm for fault recognition , maturity, color and shape, while ⁇ C, located in the near infrared region from 900 to 1500 nm, together with ⁇ l and ⁇ 2, allows to recognize the dry matter content.
- the informative wavelengths ⁇ l and ⁇ 2 are chosen so that the form of the mathematical embodiment U ⁇ l / U ⁇ 2 (L) has an injective relationship with the quality of the product, as illustrated in FIG. 3.
- FIG. 4A to 4F illustrate some situations that may arise. These figures combine different examples of products with the appearance of the beams A and B, from which it is easy to determine the ratio illustrated in FIG. 3. The following situations are observed:
- a fault 142 is substantially central: the two curves are concave (little light received by the two receivers);
- the presence of faults along the axis of the incident light beam causes analogous changes in the form of embodiments 141A and 141B obtained through the two channels A and B, while the presence of faults in an area offset from this axis affects more the realization obtained from that of the two channels A and B which is closer to the fault.
- the logarithmic realizations lgU ⁇ l (L), lgU ⁇ 2 (L) and lgU ⁇ C (L) also provide information on the quality of the product and, used in combination with the realization
- U ⁇ l / U ⁇ 2 (L) T ⁇ l / T ⁇ 2 (L), allow the recognition and classification of said product.
- the realization U ⁇ l / U ⁇ 2 (L) is approximated by a sinusoid or another model and the two functions - the realization and the mathematical model - are compared through the calculation of a group d '' indices which make it possible to highlight local faults but also to distinguish unacceptable green areas on the surface and inside of the tomato, pepper etc. from that marked by the tail of the product and by the green region around it.
- the realizations collected on the two information channels A and B and their sinusoidal models are compared with each other using a second group of indices which are used for the recognition of defects arranged asymmetrically inside or on the surface of the product and for the recognition of the shape thereof.
- indices For the recognition of the general internal and external quality of the products of which the content of dry matter, mixtures of earth and other foreign bodies is part, a third group of indices is used.
- each index as a function is made up of the ratio of signals, their logarithm and the length of the product:
- n being the number of indices
- a combination of indices ⁇ Xj ⁇ m is composed for each category of the product (j - number of the index, m - number of categories ) so as to ensure, by image recognition, maximum accuracy in attributing the product to a given class.
- the definitive attribution of the product to the class concerned is carried out using a decision-making algorithm which results in a choice among the possible classes.
- a product to be diagnosed is therefore scrutinized by the optical channels giving rise to embodiments which are submitted separately for each optical channel, to the classification as illustrated in FIG. 5.
- channel A (respectively of channel B) is classified (151) by the combination of indices ⁇ Xj ⁇ 3 which is specialized in the recognition of third class products.
- the production concerned undergoes the test (154, 155) of the second combination of indices ⁇ Xj ⁇ 2 which determines whether or not the product belongs to the second class. If so, the diagnosis of the optical channel concerned is final (branch 156A (respectively 156B)). If the object has not been assigned to the second class, the realization of channel A
- indices ⁇ Xj ⁇ l which constitutes the final diagnosis (158) of the channel concerned, by assigning the object to one of the possible classes: branches 159A, 1510A or 1511A (respectively 159B, 1510B or 151 IB) in FIG. 5.
- the final diagnoses of the two channels A and B possibly contradictory, arrive at a decision-making block 1512 which will favor one or the other in based on user preference. It should be noted that the decision-making algorithm can be modified if the user does not give priority to the accuracy of the most qualitative class.
- the information from the two channels A and B is processed separately so as to allow the operator to have the product classified according to its degree of external, internal or global quality (internal and external).
- an irregularly shaped product (as illustrated in Figure 7 A) or deviated from its normal path for any reason ( Figure 7B), may cause light reflection towards one optical channels A and B, the intensity of which can exceed by several times the intensity of the light transmitted through the product and thus cause a diagnostic error.
- This can be avoided according to the invention by detecting the presence of the reflection on the channel concerned and by carrying out the recognition on the basis of the sound scanning of the other channel.
- the invention also makes it possible to determine, in addition to the qualitative recognition of the products, their quantities in each of the categories by choosing in the computer the approximation models corresponding to the different products or to the different species of the same product.
- the device of the invention notably comprises the following elements: system for conveying product at the inlet, light source and photometric camera for lighting the product and acquiring the light transmitted in two directions and two wavelengths, frequency separator - permanent effect - of the useful signal and that of the "compensation”, amplifiers fitted with error corrector, analog-digital converter, computer, power output switches and sorting devices.
- FIG. 13 illustrates one of the elements of the conveying system, intended to properly separate the products to be analyzed, so as to guarantee a minimum space between two consecutive products. It is a "V" conveyor, each branch 1301A and
- 1301B consists of at least two parallel endless belts 1302A, 13O2B and
- the two bands 1302i and 1303i move at different speeds and two springboards (not shown) placed at the bottom of the V destabilize the products.
- the products which are piled up (1304) are progressively separated (1305), those above are driven more slowly than those below.
- the products are in single file, and with a constant speed because they are entrained by the bottom bands 1302 A, 1302B.
- Figure 8 illustrates the essential elements of this device, optically.
- photometric camera composed of the following elements: incandescent light source with linear filament and optical projection system 1, camera body 2 comprising the reflecting elements 4, objectives 5, converging lenses 6,
- slit diaphragms 7, objectives (also called collimators) 8 synchronization photoreceptors 9, dichroic mirrors 10 and 11, reflective mirrors 12, optical filters 13, 14, 15, 16 and 23 for the lengths 12A, 11A, 11B, 12B and 1C respectively, photoreceptors 18, 19, 20, 21 and 27, optical fibers 22, focusing and light adjustment modules 25, light emitting diode 26 and photonic current preamplifiers 28, camera which has 7 outputs: five information outputs 29, 30, 31, 32 and 33, a synchronization output 34 and an output 35 for the system for stabilizing the ratio of two signals.
- the electronic processing means are illustrated in the form of an operating block diagram in FIG. 9.
- the information outputs 29 and 30 of the photometric camera 2 are respectively connected to the inputs of two filters identical high-pass 36 and 39 and two identical low-pass filters 37 and 38.
- the output of filters 36 and 39 is connected respectively to the input of two detectors 40 and 43, the output of which is connected, in turn, at the input of two low-pass filters 44 and 47, the output of which is connected to the first input of the electronic switches 51 and 54, switches the output of which is connected, for their part, to the input of the logarithmic amplifiers 56 and 57.
- the output of the low-pass filters 37 and 38 is connected respectively to the input of two identical amplifiers 41 and 42, the output of which is connected both to the input of the two identical comparators 45 and 46 and to that of the two circuits identical sampling and blocking 48 and 50.
- the second input of comparators 45 and 46 is linked to a reference voltage source Uref, while their output is connected to the inputs of a logic circuit of "OR" type 49 , the output of which is connected, for its part, both to the control input of circuits 48 and 50, to one of the inputs of the logic circuit of "OR” type 64 - forming part of channel C (FIG. 8) - and to one of the logic inputs of computer 80.
- circuits 48 and 50 are connected respectively to the other input of electronic switches 51 and 54 and to the two inputs of analog divider 52, the output of which is connected to one end of resistor 56.
- channel A the outputs of filters 44 and 47 are connected to the two inputs of the analog divider 53.
- channel B the information outputs 32 and 31 of photometric camera 2 ( Figure 8) are connected to the corresponding inputs of this channel which includes modules absolutely identical to those from 36 to 57 linked together in identical fashion to the modules of channel A.
- the information output 33 of the photometric camera 2 is connected both to the inputs of a high-pass filter 58 and of a low-pass filter 59, the output of the filters 58 is 59 is connected respectively to the input of circuits 60 and 61 - respectively amplifier and detector - whose output is connected to the input of circuits 62 and 63 - respectively sampler-blocker and low-pass filter.
- the output of the latter two is, in turn, connected to two of the inputs of the electronic switch 65.
- the output of circuit 49 of channel B, as well as that of channel A, is both connected to a logic input of computer 80 and to the second input of logic circuit of "OR" type 64 whose output is connected to the control input of circuit 62.
- Circuit 65 for its part, is connected by its output to the input of logarithmic amplifier 66.
- the logic output of computer 80 is connected to both control input of the electronic switches 51 and 54 of the two channels A and B, as well as of the electronic switch 65 of the channel C and of the control input of the pulse generator 67 whose output is connected to the input 35 of the photometric camera 2.
- the output of the logarithmic amplifiers 55 and 57 of channel A and their counterparts of channel B is connected to the four inputs of the adder 71 whose output is connected to the first input of the multiplexer 78.
- the output of the logarithmic amplifier 55 of the channel A and that of channel B are respectively connected to both the first two inputs of the adder 72 and to the second and ninth inputs of the multiplexer 78, while the output of the logarithmic amplifier 57 of channel A and of its counterpart of channel B are respectively connected both to the first two inputs of the adder 73 and to the fifth and the eighth input of the multiplexer 78.
- the output of the logarithmic amplifier 66 of channel C is connected simultaneously to the third input of the adders 72 and 73, these being connected by their respective outputs to the fourth and to the seventh input of the multiplexer 78.
- the other end of resistor 56 of channel A and its counterpart of channel B is connected respectively to the fourth input of the comparator block 70, to the third and to the tenth input of the multiplexer 78, as well as to the two contacts of the switch 69.
- the output of the analog divider 53 of channel A and its pendant of channel B is connected respectively to the sixth and to the tenth input of the multiplexer 78.
- the output of the sampling-blocking circuit 48 of channel A and of the corresponding circuit of channel B is connected respectively to the first and to the second input of the comparator block 70 whose outputs are connected to two logic inputs of the computer 80.
- the first end of potentiometers 74, 75, 76 and 77 is connected to the reference voltage Uref, while their second end is connected to ground, their midpoint is connected respectively to the twelfth, thirteenth, fourteenth and fifteenth inputs of multiplexer 78, the output of which is connected to the input of the analog-digital converter 79.
- the digital inputs / outputs thereof are connected to the computer 80 which, for its part, is connected to the control module of the device 81 and to the electronic power switches 82 these these being connected by their output to the sorting members 83.
- FIG. 10 shows the details of the synchronization means 68, the input of which, connected to the output 34 of the photometric camera 2, is connected both to one of the inputs of the comparator 86 and to the input of the detector peak 85, the output of which is connected to one of the inputs of the comparator 88.
- the output of the latter is connected to the control input of the reversible counter 87, while the output of the comparator 86, for its part, is connected simultaneously to a logic input of the computer 80 and to the start input of the pulse generator 84 whose output is connected to the counting input of the reversible counter 87.
- the digital output of the latter is connected to the digital input of the digital-analog converter 90, the analog output of which is connected to the input of the amplifier 91.
- the output of the latter amplifier is connected to both at the other input of the comparator 88 and at the input of the low-pass filter 92, the output of which is connected to one end of the potentiometer 89.
- the other end of the latter is connected to ground, then that its midpoint is connected to the other input of comparator 86.
- FIG. 11 presents a more detailed diagram of the means 70 for recognizing completely defective products and foreign bodies, which have 4 inputs (two groups of two corresponding to the optical channels) and two outputs. One of the inputs corresponds to channel A (respectively channel B) is connected to block 48 and the other is connected to resistor 56.
- these inputs are connected to the first inputs (respectively second inputs) of the comparators 95 and 96.
- the first end of the potentiometers 93 and 94 is connected to the reference voltage source Uref, their second end is connected to ground, while their midpoint is connected respectively to the second input of comparators 95 and 96 of the two channels A and B.
- the output of the comparators 95 and 96 is connected respectively to the first input of the two logic circuits of "OR" type 97 and 98, and in the same way the output of the two corresponding comparators of channel B is connected to the second input of the same circuits 97 and 98, the outputs of which are connected, for their part, to logic inputs of the computer 80.
- the device of the invention operates in the following manner: during its passage through the inspection zone of the photometric camera 2 (FIG. 8), the product 3, lit by the light source 1, is crossed by the light which will be perceived by the two identical optical channels A and B, which in turn will also give rise to a third channel C.
- the optical system of the light source 1 projects the image of the linear filament of the source on the illuminated surface of the product 3 in the form of a rectangular light spot.
- the slices observed from the surface of the product have the same shape and the same width, namely the width of the image of the filament, and with the aid of the objectives 5 they are projected onto the planes of the slit diaphragms 7 and consequently the product is scanned from two sides along its entire length during its passage through the inspection area.
- the light fluxes A and B are each divided into 3 parts, filtered by the filters 13, 14, 15, 16 and 23 and are focused, by the converging objectives 17 and 24, on the photoreceptors 18 , 19, 20, 21 and 27.
- the same photoreceptors also receive the reference light signal from the light-emitting diode 26, routed by optical fiber, focused and adjusted by the modules 25.
- the photoreceptors 18, 19, 20, 21 and 27 have the role of transforming the light signals, in this case the transmitted and reference lights, into electrical signals which are amplified by the amplifiers 28 and routed through the outputs 29, 30, 31, 32 and 33, to the inputs of the two identical electrical channels A and B and channel C ( Figure 9).
- the light beam from the source 1 reaches and excites the photoreceptor 9, passing through the converging optical system 6.
- the light beam in question is cut , which causes at the output of the photoreceptor 9 a series of electrical pulses, the duration and the interval of succession of which are directly related to the length of each product and their interval of succession, as illustrated in FIG. 12, at
- the electrical synchronization signal 34 thus obtained at the outputs of the photometric camera 2 is communicated to the synchronization module 68 (FIG. 9), the operation of which is shown in FIG. 10.
- the absence of product causes said photoreceptor 9, which for its part activates the output 34 of the photometric camera 2, connected to the peak detector 85 (FIG. 10).
- the signal at the input of the detector 85 is maximum, that at its output is also, which causes, passing through a signal monitoring system consisting of the comparator 88, the pulse generator 84, the reversible counter 87 , of the analog-digital converter 90, of the amplifier 91 and of the comparator 86, at the input of the low-pass filter 92 a signal whose value is equal to the maximum value of the output of the peak detector.
- This reference signal is filtered by the low-pass filter 92 and then transmitted to the potentiometer 89 delivering a signal proportional to this maximum value which will allow the comparator 86 to compare it continuously with the current value of the photoreceptor signal.
- the penetration of the product into the measurement area and therefore into the light beam causes the photoreceptor signal to decrease more and more.
- the comparator 86 switches, stops the pulse generator 84 and at the same time sends an active level pulse to computer 80. Conversely, removing the product from the measurement zone increases the signal from the photoreceptor 9 and eventually causes the comparator 86 to switch, thereby causing the pulse generator 84 of the maximum level monitoring system to start, and simultaneously transmits a non-active level signal "0" to the computer 80.
- the computer 80 transmits a start signal to the corresponding input of the pulse generator 67 which consequently turns on the light-emitting diode 26 by activating the input 35 of the photometric camera 2.
- the duration Te of the pulse packet is chosen so as to be always shorter than the pause Tp (the time interval between two products following each other), as is illustrated in FIG. 12, signal c. From outputs 29 and 30 of the photometric camera 2 coming from channel A
- two useful signals U ⁇ lA and U ⁇ 2A are obtained and two compensation signals U ⁇ lEA and U ⁇ 2EA.
- the useful signals are first filtered by the low-pass filters 37 and 38, then amplified by the amplifiers 41 and 42, then transmitted to the sampling-blocking circuits 48 and 50 and finally routed to the first inputs of the comparators 45 and 46.
- the same reference voltage Uref is connected to the second input of the comparators in question.
- the circuits 48 and 50 are in "sampling" operating mode and the signals appear at their outputs. If the illuminated product deviates considerably from its normal trajectory or if it has an irregular shape, it gives rise to reflection ( Figure 7) and causes exceeding Uref by U ⁇ lA or U ⁇ 2A which changes the state at the output of comparators 45 and / or 46, and therefore also the output of logic circuits 49 and 64, and puts circuits 48 in "blocking" state, 50 as well as the sampling-blocking circuit 62 of channel C, and simultaneously transmits an active level signal to the computer 80.
- the signals U ⁇ lA and U ⁇ 2A are memorized and remain unchanged during the time of reflection and the computer recognizes which of the two channels A and B perceived the reflected light and aborts on the disturbed channel the diagnosis which would have given an erroneous result.
- the computer After the product has left the inspection area, the computer receives a signal from the synchronization circuit 68 and starts the pulse generator 67, causing the light-emitting diode 26 which in turn emits light pulses sent out. by the modules 25 and the optical fibers 22 to all the photoreceptors 18, 19, 20, 21 and 27 (FIG. 8).
- these pulses are transmitted by the same outputs 29 and 30 of channel A of the photometric camera to the electronics of channel A ( Figure 9) and are separated by high-pass filters 36 and 39 respectively, rectified by detectors 40 and 43 and filtered by low-pass filters 44 and 47.
- channel A delivers two useful signals corresponding to the wavelengths under observation, U ⁇ lA and U ⁇ 2A , while in the interval which separates two passages of the product, the signals delivered are those of compensation,
- the output of blocks 48 and 50 being connected to the input of the analog divider 52, the digital output of the latter represents the value U ⁇ lA / U ⁇ 2A.
- the same signals from blocks 48 and 50 are also transmitted respectively to the first input of electronic switches 51 and 54.
- the compensation signals available at the output of blocks 44 and 47, are transmitted to the second analog divider 53 which delivers (during the pauses), in turn, the U ⁇ lEA / U ⁇ 2EA ratio.
- the synchronization circuit 68 goes into a passive state, causing the pulse generator to start up by the computer and switching switches 51 and 54 - by their control inputs - so that they appear on their output the compensation signals U ⁇ lEA and U ⁇ 2EA, then taken in logarithm respectively by the same logarithmic amplifiers 55 and 57.
- Channel B is designed and works like channel A, except that the input signals of channel B correspond to the wavelengths ⁇ lB and ⁇ 2B. As for channel A, its output signals (see figure 9) are sent to adders 71, 72 and 73.
- Channel C is distinguished from channels A and B by the fact that it processes a single wavelength ⁇ C and, from the signal 33 of the photometric camera 2 (FIG. 8) passed through the low-pass filters 58 and passes -high 59, generates only two signals U ⁇ C and U ⁇ EC which undergo, through blocks 60, 61, 62, 63, 64, 65 and 66, processing similar to that of their counterpart of channels A and B.
- the presence of the product in the inspection area shows the following signals at the respective output of the adders 71, 72 and 73: l / 2 (lgU ⁇ l A - lgU ⁇ 2A + IgU ⁇ lB - lgU ⁇ 2B), l / 2 (lgU ⁇ lA + IgU ⁇ lB) - IgU ⁇ C and l / 2 (lgU ⁇ 2A + lgU ⁇ 2B) - IgU ⁇ C.
- these same outputs of the adders deliver signals related to the compensation signals U ⁇ lEA, U ⁇ 2EA, U ⁇ lEB, U ⁇ 2EB, U ⁇ EC.
- U ⁇ lEB / U ⁇ 2EB as well as the signals IgU ⁇ lA, lgU ⁇ 2A, IgU ⁇ lB and lgU ⁇ 2B are sent, through the multiplexer 78, to the analog-digital converter 79 where they are converted before reaching the computer 80.
- the latter proceeds to the addition of the logarithmic signals and to the division of the other useful signals by their counterpart to eliminate the effect of the variations in the gain of the optoelectronic circuit of channels A, B and C due to aging, temperature changes, feed fluctuations etc. It then calculates the value of the indices Xj and their combinations ⁇ Xj ⁇ m.
- the algorithm also makes it possible to discriminate foreign bodies.
- the computer 80 sends a signal to the block of power switches 82 which, in turn, activates the corresponding sorting member 83.
- the potentiometers 74, 75 and 76 make it possible to move the border between the categories of products when these are sorted by color or by maturity, while with the potentiometer 77 one determines the limit value of the dry matter content, when that -this represents an additional sorting criterion.
- the block 81 transmits two digital signals to the computer 80, one of which makes it possible to determine the border between the different categories when the sorting is based on the severity of the defects, and this by determining the a priori probabilities of the presence of products of each quality category in the input stream of the device.
- the other digital signal of block 81 allows the adjustment of a parameter in the recognition algorithm as a function of the general qualitative state of the product depending on climatic and soil conditions, conditions and duration of storage. etc.
- the appropriate reflection coefficient of the reflecting elements 4 is chosen (FIG. 8).
- the outputs of the resistors 56 (FIG. 8) are together, leading to the mixing of the signals from channels A and B, to result in two sets of identical signals as follows: l / 2 (U ⁇ l A / U ⁇ 2A + U ⁇ lB / U ⁇ 2B). This allows the product to be sorted according to its overall quality (color, maturity, dry matter content).
- the following adaptations are in particular possible: use of several lighting sources (by ensuring, preferably, that the recovered light is at least partly scattered light, and not direct light, by choosing the positioning appropriately sensors relative to sources); use of more than two independent optical receivers and / or more than two channels per recovered light flux, so as to increase the signals analyzed; - analysis carried out directly on a conveying element, and no longer during a free fall; modification of the processing means, for example by directly digitizing the optoelectronic signals and by carrying out an entirely (or essentially) digital processing; - adaptation of the sorting algorithm, according to needs and products;
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- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Toxicology (AREA)
- Investigating Or Analysing Materials By Optical Means (AREA)
- Investigating Materials By The Use Of Optical Means Adapted For Particular Applications (AREA)
Abstract
Description
Claims
Priority Applications (3)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
AU78161/94A AU7816194A (en) | 1993-10-01 | 1994-09-29 | Device for recognizing and/or sorting fruits or vegetables, and related method and utilization |
JP7510638A JPH09509477A (ja) | 1993-10-01 | 1994-09-29 | 果実や野菜の検査及び/又は等級付け装置、その方法及びその利用 |
EP94928930A EP0723484A1 (fr) | 1993-10-01 | 1994-09-29 | Dispositif de reconnaissance et/ou de tri de fruits ou legumes, procede et utilisation correspondants |
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
FR9311934A FR2710564B1 (fr) | 1993-10-01 | 1993-10-01 | Dispositif de reconnaissance et/ou de tri de fruits ou légumes, procédé et utilisation correspondants. |
FR93/11934 | 1993-10-01 |
Publications (1)
Publication Number | Publication Date |
---|---|
WO1995009698A1 true WO1995009698A1 (fr) | 1995-04-13 |
Family
ID=9451607
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/FR1994/001139 WO1995009698A1 (fr) | 1993-10-01 | 1994-09-29 | Dispositif de reconnaissance et/ou de tri de fruits ou legumes, procede et utilisation correspondants |
Country Status (6)
Country | Link |
---|---|
EP (1) | EP0723484A1 (fr) |
JP (1) | JPH09509477A (fr) |
AU (1) | AU7816194A (fr) |
CA (1) | CA2172844A1 (fr) |
FR (1) | FR2710564B1 (fr) |
WO (1) | WO1995009698A1 (fr) |
Cited By (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
ES2159244A1 (es) * | 1999-07-30 | 2001-09-16 | Miguel Antonio Ortiz | Maquina para clasificacion por calibre de frutos. |
US8722424B2 (en) | 2000-09-25 | 2014-05-13 | Panasonic Corporation | Chromatography quantitative measuring apparatus |
CN104076026A (zh) * | 2013-03-25 | 2014-10-01 | 华中农业大学 | 一种氯化妥龙在检测柑橘果皮机械损伤中的用途 |
WO2015052358A1 (fr) * | 2013-10-07 | 2015-04-16 | Universidad De Sevilla | Système automatique de détection et d'identification de phases de maturité du piment habanero et de fruits similaires |
WO2018226105A1 (fr) | 2017-06-09 | 2018-12-13 | The New Zealand Institute For Plant And Food Research Limited | Procédé et système de détermination d'attribut(s) de qualité interne(s) d'articles de produits agricoles |
Families Citing this family (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
ES2152156B1 (es) * | 1998-06-17 | 2001-07-16 | Espan Food Mach | Sistema electrooptico de clasificacion de frutas y hortalizas. |
JP4797233B2 (ja) * | 2000-09-25 | 2011-10-19 | パナソニック株式会社 | 小型試料濃度測定装置 |
NL1019600C2 (nl) * | 2001-12-18 | 2003-06-19 | Greefs Wagen Carrosserie | Inrichting voor het classificeren van producten. |
CN100429501C (zh) * | 2004-12-14 | 2008-10-29 | 中国农业大学 | 一种快速无损检测鸭梨黑心病的方法 |
KR101226697B1 (ko) * | 2010-12-10 | 2013-01-25 | 주식회사 생명과기술 | 농산물 선별 방법 |
JP5672376B2 (ja) * | 2011-05-13 | 2015-02-18 | コニカミノルタ株式会社 | 反射特性測定装置用光学系および反射特性測定装置 |
JP6282086B2 (ja) * | 2013-08-20 | 2018-02-21 | 三井金属計測機工株式会社 | 鱗茎菜類の評価装置および鱗茎菜類の評価方法 |
JP6662729B2 (ja) * | 2016-07-04 | 2020-03-11 | ヤンマー株式会社 | 内部品質評価システム |
JP6662751B2 (ja) * | 2016-10-20 | 2020-03-11 | ヤンマー株式会社 | 内部品質評価システム |
JP6662752B2 (ja) * | 2016-10-20 | 2020-03-11 | ヤンマー株式会社 | 内部品質評価システム |
Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
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FR2029953A7 (fr) * | 1969-03-18 | 1970-10-23 | Weimar Werk Veb | |
EP0223446A2 (fr) * | 1985-10-29 | 1987-05-27 | Roger Frederick Bailey | Appareil de tri optique |
DE4132472C1 (fr) * | 1991-09-30 | 1993-03-11 | Friederich Justus Gmbh, 2000 Hamburg, De | |
WO1993007468A1 (fr) * | 1991-10-01 | 1993-04-15 | Oseney Limited | Systeme de collecte d'informations par dispersion/emission de lumiere |
-
1993
- 1993-10-01 FR FR9311934A patent/FR2710564B1/fr not_active Expired - Fee Related
-
1994
- 1994-09-29 AU AU78161/94A patent/AU7816194A/en not_active Abandoned
- 1994-09-29 JP JP7510638A patent/JPH09509477A/ja active Pending
- 1994-09-29 EP EP94928930A patent/EP0723484A1/fr not_active Withdrawn
- 1994-09-29 CA CA 2172844 patent/CA2172844A1/fr not_active Abandoned
- 1994-09-29 WO PCT/FR1994/001139 patent/WO1995009698A1/fr not_active Application Discontinuation
Patent Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
FR2029953A7 (fr) * | 1969-03-18 | 1970-10-23 | Weimar Werk Veb | |
EP0223446A2 (fr) * | 1985-10-29 | 1987-05-27 | Roger Frederick Bailey | Appareil de tri optique |
DE4132472C1 (fr) * | 1991-09-30 | 1993-03-11 | Friederich Justus Gmbh, 2000 Hamburg, De | |
WO1993007468A1 (fr) * | 1991-10-01 | 1993-04-15 | Oseney Limited | Systeme de collecte d'informations par dispersion/emission de lumiere |
Cited By (12)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
ES2159244A1 (es) * | 1999-07-30 | 2001-09-16 | Miguel Antonio Ortiz | Maquina para clasificacion por calibre de frutos. |
US8722424B2 (en) | 2000-09-25 | 2014-05-13 | Panasonic Corporation | Chromatography quantitative measuring apparatus |
US8722425B2 (en) | 2000-09-25 | 2014-05-13 | Panasonic Corporation | Chromatography quantitative measuring apparatus |
US8778698B2 (en) | 2000-09-25 | 2014-07-15 | Panasonic Healthcare Co., Ltd. | Chromatography quantitative measuring apparatus |
US8822230B2 (en) | 2000-09-25 | 2014-09-02 | Panasonic Healthcare Co., Ltd. | Chromatography quantitative measuring apparatus |
CN104076026A (zh) * | 2013-03-25 | 2014-10-01 | 华中农业大学 | 一种氯化妥龙在检测柑橘果皮机械损伤中的用途 |
WO2015052358A1 (fr) * | 2013-10-07 | 2015-04-16 | Universidad De Sevilla | Système automatique de détection et d'identification de phases de maturité du piment habanero et de fruits similaires |
ES2537826A1 (es) * | 2013-10-07 | 2015-06-12 | Universidad De Sevilla | Sistema automático de detección e identificación de fases de madurez del Chile Habanero y frutos similares |
WO2018226105A1 (fr) | 2017-06-09 | 2018-12-13 | The New Zealand Institute For Plant And Food Research Limited | Procédé et système de détermination d'attribut(s) de qualité interne(s) d'articles de produits agricoles |
EP3635368A4 (fr) * | 2017-06-09 | 2021-03-03 | The New Zealand Institute for Plant and Food Research Limited | Procédé et système de détermination d'attribut(s) de qualité interne(s) d'articles de produits agricoles |
US11650162B2 (en) | 2017-06-09 | 2023-05-16 | The New Zealand Institute For Plant And Food Research Limited | Method and system for determining internal quality attribute(s) of articles of agricultural produce |
AU2018281696B2 (en) * | 2017-06-09 | 2024-04-11 | The New Zealand Institute For Plant And Food Research Limited | Method and system for determining internal quality attribute(s) of articles of agricultural produce |
Also Published As
Publication number | Publication date |
---|---|
EP0723484A1 (fr) | 1996-07-31 |
JPH09509477A (ja) | 1997-09-22 |
FR2710564A1 (fr) | 1995-04-07 |
FR2710564B1 (fr) | 1995-11-24 |
AU7816194A (en) | 1995-05-01 |
CA2172844A1 (fr) | 1995-04-13 |
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