Harvester cutting quality detection and reporting system

Abstract

A harvesting machine is provided that includes an inlet configured to receive a crop including stalks, a knife configured to cut the crop into sections, a sensor configured to detect a three-dimensional appearance of at least a portion of a section and generate a signal associated with the three-dimensional appearance of the at least a portion of the section, and a control system having a processor, a memory, and a human-machine interface. The control system is configured to receive the signal from the sensor and programmed to 1) analyze the three-dimensional appearance of the at least a portion of the section, 2) classify the three-dimensional appearance using a cut quality indicator, and 3) index the cut quality indicator to the memory.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to a harvester having a chopper for cutting a crop such as sugarcane. BACKGROUND

[0002] The chopper includes one or more blades that wear over time due to use. The one or more blades must be periodically replaced. SUMMARY

[0003] The present disclosure provides a chopper cutting quality system that detects and reports cutting quality indicative of maintenance needs (e.g., blade wear and / or need to replace blades) and / or impact on ability to efficiently clean a crop.

[0004] In one aspect, the present disclosure provides a harvester including: an inlet configured to receive a crop including stalks; a blade configured to cut the crop into billets; a sensor configured to detect a three-dimensional appearance of at least a portion of a billet and generate a signal associated with the three-dimensional appearance of the at least a portion of the billet; and a control system having a processor, a memory, and a human-machine interface. The control system is configured to receive the signal from the sensor and programmed to: 1) analyze the three-dimensional appearance of the at least a portion of the billet, 2) classify the three-dimensional appearance using a cutting quality indicator, and 3) index the cutting quality indicator to the memory.

[0005] In another aspect, the present disclosure provides a harvester including: an inlet configured to receive a crop including stalks; a blade configured to cut the crop into billets and thereby form a cut area of a billet; a sensor configured to detect an appearance of the cut area of the billet and generate a signal corresponding to the appearance of the cut area of the billet; and a control system including a processor, a memory, and a human-machine interface. The control system is configured to receive the signal from the sensor and programmed to: 1) analyze the three-dimensional appearance of the cut area of the billet, and 2) communicate a message through the human-machine interface providing information of blade wear and / or cutting quality inferred based on the appearance of the cut area of the billet.

[0006] In yet another aspect, the present disclosure provides a harvester comprising: an inlet configured to receive a crop comprising stalks; a knife configured to cut the crop into pieces; a sensor configured to detect an appearance of at least a portion of a piece and generate a signal corresponding to the appearance of the at least a portion of the piece; and a control system comprising a processor, a memory, and a human-machine interface. The control system is configured to receive the signal from the sensor and programmed to: 1) classify a cutting quality of the piece based on the signal, wherein classifying the cutting quality comprises assigning a cutting quality indicator to the piece from a range of cutting quality indicators, wherein the range of cutting quality indicators comprises at least one relatively high cutting quality indicator and at least one relatively low cutting quality indicator; and 2) index the cutting quality indicator in the memory.

[0007] Other aspects of the present disclosure will become apparent by consideration of the detailed description and accompanying drawings. BRIEF DESCRIPTION OF DRAWINGS

[0008] Figure 1 is a side view of a harvester, such as a sugar cane harvester, in accordance with an implementation of the present disclosure.

[0009] Figure 2 is Figure 1 is a magnified cross-sectional view of a portion of the harvester of

[0010] Figure 3 is Figure 1 is a perspective view of another portion of the harvester of

[0011] Figure 4 is a schematic diagram illustrating a control system of the harvester of Figure 1

[0012] Figure 5 is a schematic diagram illustrating an image analyzed in the control system of Figure 4

[0013] Figure 6 is a table illustrating images classified and indexed in the control system of Figure 4 DETAILED DESCRIPTION

[0014] Before any implementations of the present disclosure are explained in detail, it is to be understood that the present disclosure is not limited in its application to the details of construction and the arrangement of components set forth in the following description or illustrated in the following drawings. The present disclosure is capable of supporting other implementations and is capable of being practiced or being carried out in various ways.

[0015] Figure 1 ​​​A harvester 10, such as a sugarcane segmenter harvester, is illustrated that includes a prime mover (not shown) (such as an internal combustion engine) for providing motive power, and a throttle 11 for controlling the speed of the prime mover, and thus the ground speed of the harvester 10 Figure 3 The harvester includes a main frame 12 that is supported on wheels 14 of other traction devices having continuous tracks 15, tires, or engaging support surfaces 16 (e.g., ground or field). The tracks 15 directly interact with the support surfaces 16 and are responsible for the movement and traction of the harvester 10, but in other implementations the harvester 10 is provided with wheels only (rather than tracks as illustrated). An operator cab 18 is mounted on the frame 12 and contains a seat 20 for an operator Figure 3 A pair of crop lifters 22 having side-by-side augers or spools are mounted on the front of the frame 12 and operate on opposite sides of a row of crop to be harvested. The pair of crop lifters 22 generally define an entrance 23 for receiving the crop. The crop lifters 22 cooperate with a base cutter (not shown) including counter-rotating discs that sever the crop stalks near the support surfaces 16. A topper 24 extends on a boom 25 relative to the frame 12. The topper 24 has one or more topper blades 26 for cutting off the top of the crop. In other implementations, the harvester 10 can be configured for other crops, such as corn and other plants.

[0016] Figure 2 A cross-section through the segmenter 28 and the separator 55 is illustrated. The segmenter 28 cuts the crop, the separator 55 receives the cut crop from the segmenter 28, and the cut crop is generally separated by the crop cleaner 40. A motor 50 drives the segmenter 28, such as a hydraulic motor, a pneumatic motor, an electric motor, an engine, or other suitable prime mover. The crop cleaner 40 can include any suitable mechanism for cleaning the cut crop (such as a fan (as in the illustrated implementation), a source of compressed air, a rake, a shaker, or any other mechanism that differentiates various types of crop parts (by weight, size, shape, etc.) in order to separate foreign plant matter from the segments. The separator 55 can include any combination of one or more of the following: the cleaning chamber 32, the cleaning chamber housing 34, the crop cleaner 40, the fan housing 36, the shroud 38 having the opening 54, and the centrifugal blower impeller 46.

[0017] A separator 55 is coupled to the frame 12 and disposed downstream of the crop elevator 22 for receiving cut crop from the segmenter 28. The segmenter 28 includes a knife 30 for cutting the crop stalks of such a crop as sugarcane C into pieces B (the pieces being segmented stalks). In the illustrated implementation, the knife 30 can include a counter-rotating drum cutter with overlapping knives. In other implementations, the segmenter 28 can include any suitable knife or knives for cutting the crop stalks. The crop also includes dirt, leaves, roots, and other plant matter, which is collectively referred to herein as extraneous plant matter, that is also cut with the sugarcane C in the segmenter 28. The segmenter 28 directs the flow of cut crop (the pieces B and the cut extraneous plant matter) to a cleaning chamber 32, which is generally defined by a cleaning chamber housing 34, a fan housing 36, and / or a shroud 38, all of which are coupled to the frame 12 and positioned just downstream of the segmenter 28 for receiving the cut crop from the segmenter 28. The fan housing 36 is coupled to the cleaning chamber housing 34 and can include deflector vanes 31.

[0018] The shroud 38 is coupled to the fan housing 36 and has a dome shape or other suitable shape, and includes an opening 54 that angles outwardly from the harvester 10 and slightly downwardly to the field 16. In some implementations, the opening 54 can be generally perpendicular to the drive shaft 52. The shroud 38 directs the cut crop through the opening 54 to the outside of the harvester 10, e.g., for discharging a portion of the cut crop removed from the flow of cut crop back onto the field.

[0019] A motor 50, such as a hydraulic motor, includes a drive shaft 52 operatively coupled to drive the segmenter 28. For example, the drive shaft 52 can be keyed or otherwise operatively coupled to drive the segmenter 28.

[0020] Referring again to Figure 1 A conveyor 56 is coupled to the frame 12 for receiving cleaned crop from the separator 55. The conveyor 56 terminates at a discharge outlet 58 (or outlet) that is elevated to a height suitable for discharging the cleaned crop into a collection receptacle of a vehicle (not shown), such as a truck, wagon, or the like, that follows alongside the harvester 10. A secondary cleaner 60 can be positioned adjacent the discharge outlet 58 for cleaning the crop a second time before discharging the crop to the vehicle. For example, the secondary cleaner 60 can include a fan, compressed air, a rake, a shaker, or other suitable device for cleaning the crop.

[0021] As the fan 40 draws the generally lighter foreign plant matter into the shroud 38 and out the opening 54, the swath B is generally separated from the foreign plant matter in the cleaning chamber 32. All of the cut crop that is directed through the opening 54 and ejected back onto the field is referred to herein as residue. The residue generally includes primarily foreign plant matter (which has generally been cut) and can include some swath B.

[0022] The cleaning chamber housing 34 directs the cleaned crop to a conveyor 56. Although some foreign plant matter can still be present in the cleaned crop, the cleaned crop generally includes primarily swath B. Accordingly, some foreign plant matter can be expelled from the discharge outlet 58 along with the swath B. Foreign plant matter expelled from the discharge outlet 58 to a vehicle is referred to herein as trash.

[0023] Figure 3 Illustratively shown in FIG. 2, a hydraulic circuit 62 powering the motor 50 is operatively coupled to the motor 50. In other implementations, the circuit 62 can be electrically powered, pneumatically powered, can include mechanical linkages, etc. A detailed description of one example of a hydraulic circuit for a harvester fan can be found in U.S. Patent Publication No. 2015 / 0342118, which is commonly owned with the present application, the entire contents of which are incorporated herein by reference.

[0024] For example, the hydraulic circuit 62 is a closed loop hydraulic circuit powered by a pump 64. The pump 64 can be driven by a prime mover (not shown) of the harvester 10 or other power source.

[0025] The harvester 10 includes a sensor 70 configured to detect a three-dimensional appearance of a portion of the swath B and / or the entire swath B passing through the harvester 10. The sensor 70 can be configured to detect any wavelength or frequency in the spectrum. For example, the sensor 70 can include a three-dimensional vision camera, a light detection and ranging (LIDAR) device, and / or a structured light three-dimensional scanner. The sensor 70 can detect each swath B or only some of the swath B.

[0026] The sensor 70 can be positioned at any suitable location downstream of the sectioner 28 for viewing the swath B. More specifically, the sensor 70 can be positioned proximate to the conveyor 56 (e.g., above the conveyor 56) for viewing the swath B being conveyed thereon, as shown in FIG. 2. Additionally or alternatively, the sensor 70 can be positioned in the cleaning chamber 32, as shown in FIG. 3. Figure 3 Additionally or alternatively, the sensor 70 can be positioned in the cleaning chamber 32, as shown in FIG. 3. Figure 3The sensor 70 may also be located outside the harvester 10 to observe the sections B being collected in a collection vehicle (not shown) or even at a mill or other destination.

[0027] Sensor 70 is configured to generate a signal associated with the three-dimensional appearance of at least a portion of log B. For example, blade 30 cuts a stalk into logs B, thereby forming a cut region A on each log B. Cut region A can be defined as the end portion of log B that has been severed by blade 30, and can include the end surface and / or some of the side surface. Sensor 70 can be configured to generate a signal associated with at least the appearance of cut region A of log B and / or other regions of log B. In other implementations, sensor 70 can include a two-dimensional vision sensor, such as a camera, configured to detect any wavelength or frequency in a spectrum and generate a signal associated with at least the two-dimensional appearance of cut region A of log B and / or other regions of log B.

[0028] like Figures 3 to 6 And especially Figure 4 As illustrated in FIG, control system 100 includes a controller 102 having a programmable processor 104 (e.g., a microprocessor, a microcontroller, or another suitable programmable device), a memory 106, and a human-machine interface 108. Memory 106 may include, for example, a program storage area 110 and a data storage area 112. Program storage area 110 and data storage area 112 may include one type of memory or a combination of different types of memory, such as read-only memory ("ROM"), random access memory ("RAM") (e.g., dynamic RAM ["DRAM"], synchronous DRAM ["SDRAM"], etc.), electrically erasable programmable read-only memory ("EEPROM"), flash memory, a hard drive, an SD card, or other suitable magnetic, optical, physical, or electronic memory device, or other data structures. The control system may include programming, such as algorithms and / or neural networks. Control system 100 may also or alternatively include integrated circuits and / or analog devices, such as transistors, comparators, operational amplifiers, etc., to implement the logic, algorithms, and control signals described herein.

[0029] The human-machine interface 108 may include a display panel 114 and a control panel 116. The display panel 114 may convey visual and / or audio information to the operator, such as conveying a message to the operator. The message ( Figure 4The message (which is illustratively exemplified in FIG. 1 1 1 ) can include: an icon, an image, a symbol, a color, a gauge, text, audio, etc., or even a change in operation of one of the components of the harvester 10, such as changing the speed or operation of the harvester 10 (e.g., by the throttle 1 1 ) or the speed or operation of any of the components described herein (e.g., stopping the harvester 10, increasing or decreasing the speed of the sectioner 28, etc.). The message can have other forms, such as sending a signal to another device, which can be used to notify other parties concerned with cutting quality / blade wear, such as another operator, a field manager, a mechanic, an owner, a grinder operator, etc. The display panel 1 14 can include a screen, a touch screen, one or more speakers, etc. The control panel 1 16 is configured to receive input from an operator. For example, the control panel 1 16 can include buttons, dials, a touch screen (which can be the same touch screen that provides the display panel or a different touch screen), etc., with which an operator can input settings, preferences, commands, etc. to control the harvester 10.

[0030] The control system 100 includes a plurality of inputs 1 18 and outputs 120 to and from various components, as Figure 3 and Figure 4 illustrated. The controller 102 is configured to provide control signals to the outputs 120 and to receive signals (e.g., sensor data signals, user input signals, etc.) from the inputs 1 18. As used herein, a signal can include an electronic signal (e.g., through an electrical circuit or wire), a wireless signal (e.g., through satellite, the Internet, mobile telecommunication technology, frequency, wavelength, etc.), etc. The inputs can include, but are not limited to, the control panel 1 16, or more generally the human-machine interface 108, the sensors 70, and the sectioner pressure sensor 72 (which will be described in more detail below), and can include other components described herein and other components not described herein. The outputs can include, but are not limited to, the throttle 1 1, the topper 24, the crop cleaner 40, the motor 50, the conveyor 56, and the pump 64, and can include other components described herein and other components not described herein.

[0031] High cutting quality at the cutter 28 is important for improving cleaning at the crop cleaner 40 and for improving sugar recovery at the mill from the cut crop. Higher quality cutting means better cleaning results and recovery of more sugar (i.e., less juice lost due to bad cutting, crushing, etc.). The knives 30 are high wear items and are replaced frequently (e.g., weekly) depending on the number of tons of crop harvested and the incidence of metal or other non-crop items passing through the cutter 28. For a typical cleaning house, it is important for the knives 30 to remain sharp in order to cut not only the stalks into pieces B, but also to cut attached foreign plant matter. As the knives 30 wear, the ability to clean decreases. "Wear" herein refers to dulling of the knives due to the amount of crop processed and / or damage to the knives (e.g., chips, nicks, warping, bending, breaking, cracking, gouges, notches, deformation, misalignment from desired position, etc.) from crop or other non-crop items passing through the cutter 28 and / or from other sources that decrease cutting quality over time. The cutting quality of the pieces B is inversely proportional to knife wear, e.g., as knife wear increases, cutting quality decreases. Thus, by observing cutting quality, it can be inferred that as cutting quality decreases, knife wear is increasing. The level of knife wear, knife sharpness, knife damage, etc. can be inferred from cutting quality observations and communicated to the operator through the human-machine interface 108 (e.g., as one of the above-mentioned messages). Cutting quality can also be communicated to the operator through the human-machine interface 108 in the form of a message. The present disclosure is directed to analyzing the appearance of the pieces B (which can include a portion of the pieces B, such as the cutting region A), classifying cutting quality indicators associated with the pieces B, indexing the classifications into the memory 106, and communicating messages through the human-machine interface 108 that provide information about knife wear and / or cutting quality.

[0032] The control system 100 receives signals from the sensor 70 indicative of the appearance of the pieces B. The control system 100 can continuously or periodically analyze the appearance of the pieces B downstream of the cutter 28, e.g., measure cutting parameters. It should be understood that a different piece B is analyzed each time, but the process of analyzing each new piece B can be the same. Thus, only the process of analyzing a single piece B need be described herein.

[0033] In particular, the cutting region A of the pieces B can be analyzed. In other implementations, any other suitable portion of the pieces B or the entire pieces B can be analyzed. The cutting region A is particularly indicative of the cutting quality of the cutter 28 because damage to the pieces B caused by the worn knives 30 is visible in the cutting region A. Thus, by observing the cutting region A, the level of damage to the pieces B can be estimated.

[0034] For example, roundness, degree of crushing, number of cut surfaces, appearance of severed fibers, or deviation from an optimal appearance are parameters in determining a level of damage. As a more specific example, severed fibers in the cutting area A can have a progressively increasing jagged and / or loose appearance as the blade 30 wears. The control system 100 can measure the length of severed fibers based on signals from the sensor 70 to assess a level of damage and thus a cutting quality. This length can be saved in the memory 106, but need not be in some implementations. Such an algorithm can be hard-coded or can employ a neural network trained with pre-classified images to identify images with severed fibers of various lengths. For example, the neural network can include a convolutional neural network.

[0035] As Figure 5 As a further specific example, the degree of crushing can be assessed by measuring the roundness of end views (e.g., cross-sections) of the cutting area A. Figure 5 A representation of signals received by the control system 100 from the sensor 70 is illustrated, including images of the cutting area A of different lengths B (labeled cutting areas A1-A3 and lengths B1-B3 in Figure 5 The eccentricity of the cutting area A increases from A1 to A3. The control system 100 can be hard-coded to calculate the eccentricity of each cross-section of the cutting areas A1-A3, for example, using observed measurements taken from the images or any other suitable method. The eccentricity of a circle is known to be zero, and the eccentricity of an ellipse is greater than zero and less than one. Increasing crushing can result in increasing eccentricity. Thus, the level of damage to the length B is greater as the eccentricity increases. Thus, the calculated eccentricity values can be used to assess a level of damage and thus a cutting quality. This eccentricity can be saved in the memory 106, but need not be in some implementations. In other implementations, a neural network can be trained with pre-classified images to identify images with various degrees of crushing or any other parameter.

[0036] In some implementations, a zero eccentricity (or another low eccentricity value) can be programmed as an optimal appearance (in this example, the optimal appearance is an optimal eccentricity). Deviation from the optimal appearance (e.g., a difference between the optimal eccentricity and a measured eccentricity) can be used to classify a level of damage and thus a cutting quality.

[0037] Other surface features can be used as parameters to classify a cutting quality. The control system 100 can use multiple length B measurements to classify a cutting quality. Advantageously, three-dimensional data enables multiple measurements from a single three-dimensional image.

[0038] The control system 100 classifies the appearance of the length B by selecting from a range of cut quality indicators. Each cut quality indicator can comprise a unitless label such as LOW, MEDIUM and HIGH, or POOR, GOOD and BEST, or other first, second and third indicators that indicate increasing or decreasing cut quality relative to one another, or other equivalent indicators. For example, indicators such as eccentricity, fibre length, damage extent, or any other parameter that is linked to cut quality and can therefore be used to classify cut quality, that are labelled to indicate the measurements taken (as described above) are considered equivalent. Any number of cut quality indicators can be employed. For example, two cut quality indicators such as LOW and HIGH can be employed. In other examples, four or more cut quality indicators can be employed.

[0039] In this example, LOW indicates a relatively low cut quality such as a relatively large eccentricity (e.g. relative to a predetermined scale of eccentricity and / or compared to previously recorded eccentricities and / or as ascertained from deviation from an optimal eccentricity (as discussed above) etc.). MEDIUM indicates a relatively medium cut quality such as a relatively medium eccentricity (e.g. relative to a predetermined scale of eccentricity and / or compared to previously recorded eccentricities and / or as ascertained from deviation from an optimal eccentricity (as discussed above) etc.). HIGH indicates a relatively high cut quality such as a relatively small eccentricity (e.g. relative to a predetermined scale of eccentricity and / or compared to previously recorded eccentricities and / or as ascertained from deviation from an optimal eccentricity (as discussed above) etc.).

[0040] In some implementations, the neural network is trained to classify the appearance of the length B using the cut quality indicators based on its training. For example, the neural network is trained using images pre-classified as LOW, MEDIUM and HIGH (or other indicators as described above).

[0041] The control system 100 indexes the indicators into the memory 106 as shown in one example of a table 122 illustrated as Figure 6 The indicators HIGH, MEDIUM and LOW are classified and indexed into the table 122 using the processed / analysed images (comprising cut regions Al to A3 of lengths Bl to B3 respectively) in Figure 5 The table is saved in the memory 106. Other methods of indexing the indicators can be employed.

[0042] As discussed above, the relationship between cut quality and blade wear can be used to infer blade wear from indexed cut quality. The control system 100 is configured to transmit a message through the human-machine interface 108 that provides blade wear information based on the indexed cut quality Figure 4 As illustratively shown and described above, the message provides blade wear information based on the indexed cut quality. For example, the message can be triggered when the cut quality decreases to a predetermined level, or decreases to a predetermined level for a predetermined amount of time, or in other suitable manners.

[0043] The message that provides blade wear information can include information about the level of blade wear, the sharpness of the blade, the damage to the blade, and so forth, as well as the cut quality itself from which the operator can infer blade wear. For example, the message can include a gauge that displays the above information on a scale with a level indicator, such as a visual image of a gauge or actual gauge, as a numerical value, as a percentage, as an estimated fraction of life, as an estimated condition, as a maintenance recommendation, such as a recommendation to replace the blade 30, and so forth.

[0044] Ultimately, the control system 100 as described above is used to infer blade wear and / or cut quality information from the appearance of the piece B. In particular, in some implementations, the blade wear and / or cut quality information is inferred from the appearance of the cut region A of the piece B. Moreover, more particularly, in some implementations, the blade wear and / or cut quality information is inferred from the three-dimensional appearance.

[0045] The control system 100 can be configured to detect when the blade 30 is replaced (e.g., using cut quality information, using cutter pressure from the cutter pressure sensor 72, or other suitable methods), and record the blade replacement in the memory 106. In other implementations, the operator can enter the blade replacement into the control system 100. The message can be reset in response to the blade replacement.

[0046] In operation, crop stalks are delivered from a base cutter (not shown) to the cutter 28. The cutter 28 cuts the crop into pieces B by the blade 30, and delivers a stream of pieces B and foreign plant matter to the cleaning chamber 32. The foreign plant matter and pieces B are at least partially separated by the separator 55. The sensor 70 captures an image of the pieces B, in particular the cut region A of the pieces B, and sends the image signal to the control system 100. The control system 100 analyzes the image, classifies the image according to cut quality, and indexes the cut quality indicator into the memory 106. The control system 100 can transmit a message through the human-machine interface 108 that provides information about blade wear and / or cut quality to the operator or other interested party. The operator can replace the blade 30 in response to the message. The message can be reset when the blade 30 is replaced.

[0047] Accordingly, the present disclosure provides, among other things, a harvester having a cutting quality detection and reporting system. Various features and advantages of the present disclosure are set forth in the claims.

Claims

1. A harvester (10), comprising: an inlet (23), the inlet (23) being configured to receive crops including stalks; a blade (26), wherein the blade (26) is configured to cut the crop into sections; a sensor (70) configured to detect a three-dimensional appearance of at least a portion of the section and to generate a signal associated with the three-dimensional appearance of the at least a portion of the section; as well as A control system (100) comprising a processor (104), a memory (106), and a human-machine interface (108), wherein the control system (100) is configured to: receiving a signal from said sensor (70), analyzing the three-dimensional appearance of the at least a portion of the segment, classifying said three-dimensional appearance using a cut quality indicator, indexing the cut quality indicator into the memory (106), and A message is transmitted via the human-machine interface (108), wherein the message indicates a blade life and / or a blade sharpness level inferred from the three-dimensional appearance of the at least a portion of the log.

2. The harvester according to claim 1, wherein: The message indicates blade wear and / or cut quality inferred from the three-dimensional appearance of the at least a portion of the log.

3. The harvester according to claim 1, wherein: The message indicates a level of blade damage as inferred from the appearance of the cut area of ​​the log.

4. The harvester according to claim 1, wherein: The sensor (70) includes at least one of a three-dimensional vision camera, a LIDAR device, and a structured light three-dimensional scanner.

5. The harvester according to claim 1, wherein: The sensor (70) is configured to detect a three-dimensional image of a cut region of the log, wherein the cut region is defined as an end portion of the log that has been severed by the blade (26).

6. The harvester according to claim 5, wherein: A cut quality indicator is indexed into the memory (106) based on a level of damage detected in a cut region of the log.

7. The harvester according to claim 1, wherein: At least one of the roundness, the degree of crushing, the number of cut surfaces, the appearance of the cut fibers and the deviation from the optimal three-dimensional appearance are parameters when analyzing the three-dimensional appearance.

8. The harvester according to claim 1, wherein: The control system is configured to employ a neural network to analyze and / or classify the three-dimensional appearance of the at least a portion of the log.

9. The harvester according to claim 1, wherein: The cut quality indicator is selected from a range of cut quality indicators, wherein the range of cut quality indicators includes at least one relatively high cut quality indicator and at least one relatively low cut quality indicator.

10. A harvester (10), comprising: an inlet (23), the inlet (23) being configured to receive crops including stalks; a blade (26), wherein the blade (26) is configured to cut the crop into sections; a sensor (70) coupled to the harvester downstream of the blade (26), the sensor (70) being configured to detect a three-dimensional appearance of at least a portion of the log and to generate a signal corresponding to the three-dimensional appearance of the at least a portion of the log; as well as A control system (100) comprising a processor (104), a memory (106), and a human-machine interface (108), wherein the control system (100) is configured to: receiving a signal from said sensor (70), Compare the detected 3D appearance with the optimal 3D appearance, determining a degree of deviation between the detected three-dimensional appearance and the optimal three-dimensional appearance, classifying a cut quality of the log based on the degree of deviation, wherein classifying the cut quality comprises assigning a cut quality indicator from a range of cut quality indicators to the log, wherein the range of cut quality indicators comprises at least one relatively high cut quality indicator and at least one relatively low cut quality indicator, indexing the cut quality indicator into the memory (106), and A message is transmitted via the human-machine interface (108), the message indicating a blade life and / or blade sharpness level inferred from the degree of deviation between the detected three-dimensional appearance of the at least a portion of the log and the optimal three-dimensional appearance.

11. The harvester according to claim 10, wherein: The cut quality indicator is assigned based on a level of visible damage to the log caused by the blade (26).

12. The harvester according to claim 10, wherein: One or more of roundness, degree of crushing, number of cut surfaces, appearance of the cut fibers, and deviation from an optimal appearance are parameters in classifying the cut quality.

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