Classifications

• • B—PERFORMING OPERATIONS; TRANSPORTING
  • B61—RAILWAYS
  • B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
  • B61L23/00—Control, warning or like safety means along the route or between vehicles or trains
  • B61L23/04—Control, warning or like safety means along the route or between vehicles or trains for monitoring the mechanical state of the route
  • B61L23/041—Obstacle detection
• • B—PERFORMING OPERATIONS; TRANSPORTING
  • B61—RAILWAYS
  • B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
  • B61L25/00—Recording or indicating positions or identities of vehicles or trains or setting of track apparatus
  • B61L25/02—Indicating or recording positions or identities of vehicles or trains
  • B61L25/025—Absolute localisation, e.g. providing geodetic coordinates

Definitions

• the present invention relates to a weeding apparatus arranged to be installed on a railway vehicle for weeding and a method for weeding railway tracks which avoid the growth of weed species near the railway tracks.
• the invention relates to an apparatus for weeding which uses software implementing artificial intelligence logic to optimize the weeding procedure, so that it identifies the weeds species and the position thereof.
• the invention relates to a method to perform the weeding of said weed species with an apparatus which can be installed on railway vehicles, which optimizes the weeding modes, trying to avoid waste and errors.
• the weeding apparatuses arranged to be installed on railway vehicles can avail themselves of software based on artificial intelligence logic (AI) which provide the processing of data arrays, which suitably re-processed provide as output a probability function of presence of weed species.
• AI artificial intelligence logic
• a control unit actuates a weeding unit by optimizing the operation thereof thereby using the weed-killing agent in the required amount and in the necessary points, defined by the presence of weed species.
• the data arrays processed by the AI software are generally extracted from a digital input provided by sensors comprised in the apparatus, for example video cameras.
• the types of sensors can vary depending upon the apparatuses, apart from video cameras which detect the visible spectrum, even infrared video cameras, tachometers, accelerometers, and so on, may be present.
• the arrays are re-processed, preferably through convolution procedures, without using different multiplicative factors for the different arrays, based upon considerations regarding the provenance of data and the data quality depending upon the external conditions which could affect said quality.
• the technical problem underlying the present invention is to provide a weeding apparatus arranged to be installed on a railway vehicle for weeding and a method for weeding railway tracks allowing to obviate the drawbacks mentioned with reference to the known art.
• a weeding apparatus arranged to be installed on a railway vehicle for weeding as defined in the enclosed claim 1.
• This weeding apparatus is specifically arranged to be installed on a railway vehicle for weeding.
• It comprises a first camera which is configured to detect at least the visible spectrum, and it is apt to capture a first digital image of a railway track portion and said first image is expressed digitally through a first array of pixel values.
• a second camera is provided, which is configured to detect at least the infrared spectrum, and it is then configured to capture a second digital image of a railway track portion, and said second image, analogously to the first one, is expressed digitally through a respective second matrix of pixel values.
• the apparatus then comprises a LIDAR type remote-sensing device, which operates with a laser emitter and it is configured to capture a digital scan of a railway track portion, and said digital scan is expressed digitally through a respective third matrix of pixel values.
• a LIDAR type remote-sensing device which operates with a laser emitter and it is configured to capture a digital scan of a railway track portion, and said digital scan is expressed digitally through a respective third matrix of pixel values.
• the apparatus comprises a weeding unit, provided for weeding weed species, and a control module implementing a first software which in turn is capable of receiving a weed species detection signal and triggering the spraying of chemical agent from said supply module through at least a nozzle, based upon the weed species detection signal.
• a unit for the identification of the weed species comprises a communication module arranged to receive the first digital image, the second digital image and the digital scan and arranged to send a weed species detection signal to said control module of the weeding apparatus. It further comprises a memory module, configured to store said first and second image and said scan, and a processing module having a second software arranged to carry out at least a convolution operation between a pixel array of each digital image and of the digital scan and a respective predefined kernel stored in the memory module to obtain an array representing the features of each digital image and of the digital scan.
• the processing module through said second software, can calculate at least a first, a second and a third presence probability and position of a weed species, in a database of weed species, said first, second and third presence probability and position being respectively associated to said first digital image, to said second digital image and to said scan, so that said processing module detects the presence and position of said weed species.
• the processing module generates a weed species detection signal based upon a resulting presence probability and position, calculated as the sum of the first, second and third presence probability and position, respectively multiplied by a first, a second and a third multiplicative factor defined based upon the presence of precipitations and brightness; moreover, the processing module sends said detection signal to the control module which is arranged to activate said weeding unit, so that it acts only in areas in which weed species have been detected.
• the main advantage of the weeding apparatus lies in the fact of multiplying each array representing the features corresponding to a different source of data, in particular to the first, to the second digital image and to the digital scan, by a multiplicative factor which is customized based upon the weather conditions and time of the day (data/night).
• a multiplicative factor which is customized based upon the weather conditions and time of the day (data/night).
• the first camera is to be considered very reliable, possibly more reliable than the second camera and the remote-sensing device; differently, at night and in presence of atmospheric precipitations or heavy fog, the second camera is more reliable than the first camera and the remote sensing device; or at night and under serene conditions, the remote-sensing device is considered the most reliable one.
• the method for weeding railway tracks provides to use a weeding apparatus arranged to be installed on a railway vehicle as it is defined in said first aspect.
• the weeding method provides the steps of capturing a first digital image in the visible of a railway track portion, a second digital image in the infrared of a railway track portion and a laser scan of a railway track portion, each one of said images and said scan being expressed with a respective pixel array.
• the captured images and the scan are sent to a processing and storing module and, through said second software, a convolution is performed between a pixel array of each digital image and of the digital scan and a respective kernel stored in the memory module to obtain an array representing the features of each digital image and of the digital scan.
• a presence probability and position of at least a weed species in a database of weed species from an array representing the features of the image, by detecting the presence and position of said weed species.
• a first, a second and a third multiplicative factor defined based upon the presence of precipitations and brightness are then calculated.
• the first multiplicative factor is then attributed to a first presence probability and position of the first digital image, said second multiplicative factor to a second presence probability and position of the second digital image, and said third multiplicative factor to a third presence probability and position of the digital scan.
• a resulting presence probability and position is then calculated, through said software, as the sum of the first, second and third presence probability and position, respectively multiplied by the first, second and third multiplicative factor, and then, through said processing module, a weed species detection signal is generated, based upon the above-mentioned resulting probability, which is sent to the control module of the weeding apparatus for triggering the weeding procedures through said weeding unit.
• a weeding apparatus arranged to be installed on a railway vehicle for weeding, is designated as a whole with 1.
• the apparatus 1 comprises a first camera 3 configured to detect at least the visible spectrum and being apt to capture a first digital image of a railway track portion 4, said first image comprising a first array of pixel values.
• the apparatus 1 then comprises a second camera 5 configured to detect at least the infrared spectrum and being apt to capture a second digital image of a railway track portion 4, said second image comprising a second array of pixel values.
• the apparatus 1 further comprises a remote-sensing device 6, of the LIDAR type, comprising a laser emitter, the remote-sensing device being apt to capture a digital scan of a railway track portion 4, said digital scan comprising an array of pixel values.
• a remote-sensing device 6, of the LIDAR type comprising a laser emitter, the remote-sensing device being apt to capture a digital scan of a railway track portion 4, said digital scan comprising an array of pixel values.
• the apparatus 1 even comprises a weeding unit arranged for weeding weed species.
• the apparatus 1 comprises a control module 12, implementing a first software arranged to receive a weed species detection signal and to trigger weeding through said weeding unit based upon said weed species detection signal and a unit 13 for the identification of the weed species.
• This identification unit 13 comprises, a communication module 14 which is arranged to receive, the first digital image, the second digital image and the digital scan and to send a weed species detection signal to said control module 12 of the weeding apparatus 1.
• a processing module 16 comprising a second software which is arranged to carry out at least a convolution operation between a pixel array of each digital image and of the digital scan and a respective predefined kernel stored in the memory module 15, with the purpose of obtaining an array representing the features of each digital image and of the digital scan.
• the processing module 16 calculates at least a first, a second and a third presence probability and position of a weed species, in a database of weed species.
• the first, second and third presence probability and position are respectively associated to said first digital image, to said second digital image and to said scan, so that said processing module 16 detects the presence and position of said weed species.
• the processing module 16 generates a weed species detection signal based upon a resulting presence probability and position, calculated as the sum of the first, second and third presence probability and position, respectively multiplied by a first multiplicative factor F 1 , a second multiplicative factor F 2 and a third multiplicative factor F 3 .
• the multiplicative factors are defined based upon the presence of precipitations and the brightness conditions.
• the processing module 16 sends the detection signal to the control module 12 which, in turn, is arranged to activate the weeding unit, so that it acts only in areas in which weed species have been detected.
• the processing module 16 can comprise a plurality of parallel processing cores, and each parallel processing core is arranged to carry out, through said second software, at least a convolution operation between a sub-array constituted by near pixels of each digital image and of the digital scan and a respective predefined kernel, which is stored in the memory module 15, to obtain a sub-array representing the features of each digital image and of the digital scan by assigning a value to each pixel of the image.
• the weeding apparatus comprises an external storage space 100, in case even in cloud, on which the data collected when said weeding apparatus 1 is in use are saved and stored for future uses.
• the processing module 16 can calculate at least a presence probability and position of a weed species in a database of weed species from each array representing the features of the image constituted by the sub-arrays for representing the features, in turn constituted by the parallel processing cores, by detecting the presence and position of said weed species, and it can generate a weed species detection signal based upon a resulting presence probability and position, calculated as the sum of the first, second and third presence probability and position, respectively associated to said first digital image, to said second digital image and to said scan, respectively multiplied by a first, a second and a third multiplicative factor defined based upon the presence of precipitations and brightness.
• This detection signal is then transmitted to the control module which is arranged to activate the spraying unit, so that it acts only in areas in which weed species have been detected.
• the weeding apparatus 1 comprises a first device for detecting brightness arranged to identify a brightness parameter ⁇ , wherein, if ⁇ > ⁇ min the presence of light, that is a brightness sufficient to take images, is considered and otherwise it is dark.
• a second device for detecting precipitations in form of rain and/or hail and/or snow is provided, which is arranged to identify an atmospheric parameter ⁇ , wherein if ⁇ > ⁇ min one establishes that there are precipitations so as to influence the weeding process, or otherwise it is clear.
• the communication module can be arranged to receive the brightness parameter ⁇ and the atmospheric parameter ⁇ and wherein said processing module 16, through said software, establishes said first, second and third multiplicative factors based upon the brightness parameter ⁇ and the atmospheric parameter ⁇ , wherein
• the scan obtained with the remote-sensing device 6 is to be considered less reliable than the first and second digital image which, in turn, could be considered with different multiplicative factors depending on whether they are detected during the day or at night.
• the weeding unit comprises a spraying unit 7 having a supply module 8 with a tank 9 of chemical agent and a dispensing valve 10, and at least a nozzle 11, to spray a chemical agent from said supply module 8.
• the control module 10 is arranged to receive a weed species detection signal and to command the spraying of chemical agent from the supply module 8 through the nozzle 11 based on the weed species detection signal.
• the processing module 16 sends the detection signal to the control module 12 which is arranged to activate the spraying unit 4, so that it acts only in areas in which weed species have been detected.
• the processing module 16 calculates at least a resulting probability which, apart from the presence and position, considers the type of at least one weed species, by detecting, indeed, the presence, position and type of the weed species.
• the processing module 16 then generates a weed species detection signal based upon the resulting presence probability, position and type, and sends said detection signal to said control module 12 arranged to activate, through the second software, the weeding unit, so that it acts only in areas in which weed species have been detected and preferably with a dosage of chemical agent suitable to the type of weed species.
• the supply module 8 can comprise at least two tanks, each one with a chemical agent different from the other ones, and the processing module, through said second software, can generate a signal for detecting the different weed species based upon said resulting presence probability, position and type and sending said detection signal to said control module 12 arranged to activate the spraying unit 7, thereby different chemical agents are sprayed based upon the weed species type.
• the weeding unit comprises a weeding device arranged to emit an electric discharge and/or to emit a laser beam.
• control module 10 When the weeding device is present, the control module 10 is arranged to receive a weed species detection signal and to command the activation of said weeding device, based upon said weed species detection signal and wherein said processing module 16 sends said detection signal to said control module 12 which is arranged to activate said weeding device, so that it acts only in areas in which weed species have been detected.
• the processing module 16 calculates at least a resulting presence probability, position, type of at least one weed species, by detecting the presence, position and type of said at least one weed species and generates a signal for detecting the different weed species based upon said resulting presence probability, position and type and sends said detection signal to said control module 12 arranged to activate selectively, through said software, the spraying unit 7 and/or the weeding device based upon which one is considered to be most suitable for weeding a weed species type, in a determined position, and so that they act only in areas wherein in which the weed species have been detected.
• the weeding device is positioned below the railway vehicle 2.
• This preferential positioning could make the weeding device to be arranged to act below the railway vehicle 2, then on the tracks 4 and in proximity thereof, without reaching areas very far from the railway vehicle 2.
• this limitation could involve mainly the possible implementation of the weeding device which acts through electric discharge.
• the weeding apparatus comprises an anemometer arranged to detect a wind intensity parameter W, and/or a tachymeter arranged to detect a speed parameter V of the vehicle on which the apparatus travels.
• the communication module 14 can receive said wind intensity parameter W and/or said speed parameter V and said memory module can store them and the processing module 16, through said software, verifies that the conditions W min ⁇ W ⁇ W max and V ⁇ V min are fulfilled, W min and W max being threshold values of the wind intensity parameter stored in said memory module 15, and V min being a threshold value of the speed parameter stored in said memory module 15.
• control module receives said detection signal and triggers the weeding of the weed species through said weeding unit, based upon said weed species detection signal.
• FIG. 4 An example of convolution procedures is schematically shown in figure 4 , wherein one obtains: a parameter y ⁇ (0,1) designating the activation or not of the weeding apparatus 1, a parameter P1 and a parameter P2 designating the activation of the spraying unit 7 and of the weeding device, respectively, and a parameter l j designating the intensity to be applied to several nozzles.
• the first and the second software can avail of artificial intelligence logic.
• a preferred method to perform weeding of the railway tracks 4 provides to activate the weeding apparatus, capturing a first digital image in the visible of a railway track portion 4, a second digital image in the infrared of a railway track portion 4 and a laser scan of a railway track portion 4, provides that each one of said images and said scan is expressed as a respective array of pixel.
• the processing module 16 receives through said communication module 14 the captured images and the scan in turn stored in the memory module 14.
• the processing module 16 performs a convolution, through the second software, between a pixel array of each digital image and of the digital scan and a respective kernel stored in the memory module 15, to obtain an array representing the features of each digital image and of the digital scan.
• the method then provides to calculate, through the processing module 16 implementing the second software, at least a presence probability and position of at least one weed species in a database of weed species, from an array representing the features of the image, by detecting the presence and position of said weed species.
• the processing module 16 can calculate a first, a second and a third multiplicative factor defined based upon the presence of precipitations and brightness and can multiplicate them, respectively, with a first presence probability and position of the first digital image, with a second presence probability and position of the second digital image and with a third presence probability and position of the digital scan in order to calculate a resulting presence probability and position.
• the processing module 16 generates a weed species detection signal based upon said resulting presence probability and position of a weed species and sends, through said communication module 14, said weed species detection signal to the control module 12 which can trigger the weeding of the weed species, through said weeding unit, based upon the weed species detection signal.
• the detection signal can comprise even information about the amount of chemical agent to be dispensed based upon the weed species type.
• the detection signal is based upon a presence probability position and type and it can comprise information about different week-killers to be used based upon the weed species type and it triggers said spraying unit 7 thereby different chemical agents are sprayed based upon the weed species type.
• the processing module can make the selection between which is better to use or whether to use both of them and sends the detection signal, comprising the selection, to said control module which can trigger selectively, through said first software, said spraying unit 7 and/or said weeding device.
• the triggering of the weeding apparatus 1 provides to measure the wind intensity at a certain time instant t with the anemometer and storing a wind intensity parameter W(t), measuring the speed of the railway vehicle at a certain time instant t and storing a speed parameter V(t) in the memory module 15 and communicating them, through said communication module 14, to said processing module 16.
• the triggering of the weeding apparatus provides to verify, through said second software implemented on said processing module 16 that the conditions W min ⁇ W(t) ⁇ W max and V(t) ⁇ V min are fulfilled, if these conditions are fulfilled, the weeding apparatus 1 proceeds with subsequent actions, otherwise it does not proceed.
• the weeding method can provide to measure the speed of the railway vehicle 2 and to store a speed parameter V in the memory module 15 and to communicate it through said communication module 14 to said processing module 16.
• the memory module 15 can even communicate a time t e for processing the digital images and the scan and a time t a for activating the weeding unit, both being saved in the memory module, to said processing module 16.
• the fact of identifying the detection area 200 allows to process images and scans of the surrounding reality present at a distance from the installation point of the weeding unit on the railway vehicle 2, and this allows the weeding apparatus to act effectively for weeding the weed species.
• the weeding apparatus 1 allows to identify a detection area 200 and neighbouring areas 201, which correspond to different distances from the installation point of the weeding unit on the railway vehicle 2.

Landscapes

• Engineering & Computer Science (AREA)
• Mechanical Engineering (AREA)
• Soil Working Implements (AREA)

Applications Claiming Priority (1)

Publications (1)

Family

ID=92883524

Family Applications (1)

Country Status (1)

Citations (3)

• 2025
  • 2025-07-09 EP EP25188441.7A patent/EP4678505A1/de active Pending

Patent Citations (3)

Similar Documents

Legal Events