WO2002039073A1 - Procede et agencement permettant de determer le poids d'une charge dans un vehicule de mine - Google Patents

Procede et agencement permettant de determer le poids d'une charge dans un vehicule de mine Download PDF

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Publication number
WO2002039073A1
WO2002039073A1 PCT/FI2001/000973 FI0100973W WO0239073A1 WO 2002039073 A1 WO2002039073 A1 WO 2002039073A1 FI 0100973 W FI0100973 W FI 0100973W WO 0239073 A1 WO0239073 A1 WO 0239073A1
Authority
WO
WIPO (PCT)
Prior art keywords
arrangement
linear
load
mining vehicle
weight
Prior art date
Application number
PCT/FI2001/000973
Other languages
English (en)
Inventor
Jarmo Puputti
Mariaana Savia
Heikki Koivo
Pauli Viljamaa
Original Assignee
Sandvik Tamrock Oy
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Sandvik Tamrock Oy filed Critical Sandvik Tamrock Oy
Priority to CA002431584A priority Critical patent/CA2431584C/fr
Priority to AU2369702A priority patent/AU2369702A/xx
Priority to AU2002223697A priority patent/AU2002223697B2/en
Publication of WO2002039073A1 publication Critical patent/WO2002039073A1/fr
Priority to SE0301174A priority patent/SE524212C2/sv

Links

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01G—WEIGHING
    • G01G19/00—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups
    • G01G19/08—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups for incorporation in vehicles
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01G—WEIGHING
    • G01G19/00—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups
    • G01G19/08—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups for incorporation in vehicles
    • G01G19/12—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups for incorporation in vehicles having electrical weight-sensitive devices

Definitions

  • the invention relates to a method of determining the weight of a load in a mining vehicle, in which method the load weight is determined on the basis of measuring signals obtained from separate measuring means.
  • the invention further relates to an arrangement for determining the weight of a load in a mining vehicle, which arrangement comprises means for determining the weight of the load.
  • a known solution weighs a load by measuring the cylinder pressure caused by the load in the lifting cylinder that moves the system made up of lifting arms and a bucket or dump box.
  • the pressure is measured on both sides of the lifting cylinder several times during a certain measuring period, and the load in the bucket is calculated on the basis of the average of the obtained pressure differences.
  • the effect of the tilting of the machine and the po- sition of the lifting arms or dump box on the pressure difference measured in the lifting cylinder is compensated by means of compensation coefficients.
  • the calculation method is linear and load determination is done while the machine is moving. When calibrating the measuring system, pressure is first measured with an empty bucket or dump box and then by using a load having a known weight in the bucket or dump box.
  • the obtained measuring values are relatively correct and the load in the vehicle can be determined at an adequate accuracy.
  • the problem is, however, that due to the quickly driven and short distances, weighing must be done during the drive, in which case the tilting of the vehicle, bumps on the road and several other factors affect the final result of the weighing, and in certain situations, a systematic error towards one direc- tion may easily occur.
  • a problem with the solution is applying a linear method to a non-linear system and that even additional measurings used are not enough to compensate for all errors caused by drive-time measuring in the level of the pressure signal.
  • One drawback is using a fixed measuring time when calculating the average of the pressure differences from measuring signals oscillating at varying period lengths.
  • WO publication WO99/09379 discloses a method that utilises a neural network and fuzzy logic to determine the weight of a mining vehicle load on the basis of measuring signals measured by sensors.
  • Variables to be measured can be for instance the cylinder pressure of the lifting cylinders of a bucket or dump box, the tilting of the vehicle in both longitudinal and lateral direction and the position of the lifting arms of the bucket or the position of the dump box.
  • the weight of the payload in the vehicle can be determined on the basis of the measured variables and the dimensions and geometry of the bucket or dump box mechanics.
  • a signal representing the load weight is defined on the basis of the cylin- der pressure of the lifting cylinders and the position of the lifting arms of the bucket and any random pressure variations in the measurements are removed using curve fitting and averaging.
  • the resulting curve representing the load weight is interpolated or extrapolated in relation to curves defined during the calibration of the apparatus for the purpose of determining the weight of the load in the bucket.
  • FI patent 94,677 discloses a method based on measuring the deformation of structures for measuring loads directed to structures, espe- cially the weight of a load in a vehicle. The method is suitable for calculating the load caused by static loads that are practically stationary in relation to the structures, but it cannot be used to calculate the load in a moving vehicle.
  • the method of the invention is characterized in that a nonlinear Kalman filter is used to determine the weight of the load.
  • the arrangement of the invention is characterized in that the arrangement comprises a calculation unit that is arranged to utilise a non-linear Kalman filter.
  • the essential idea of the invention is that the weight of a load in a mining vehicle is determined by a non-linear Kalman filter that esti- mates the weight of the load in the vehicle, which load weight cannot be directly measured, by means of measuring signals obtained from measuring means located in the vehicle.
  • the invention provides the advantage that by using a nonlinear Kalman filter, a better estimate can be made on the weight of the vehicle load, because to solve a non-linear problem, a non-linear method is used, by means of which it is also possible to minimise the impact of the noise included in the measurements on the estimated load weight.
  • Another advantage is that the calibration of the method is simple and that the method need not be specifically trained to identify different masses. Further, the determination of the load weight is done faster and more accurately than in the prior art methods.
  • Figure 1 is a schematic representation of a dumper used in mines, to which the method of the invention is applied
  • Figure 2 is a schematic representation of a wheel loader used in mines, to which the method of the invention is applied,
  • Figure 3 is by way of example a schematic representation of an application of a non-linear Kalman filter and an apparatus that can be used to determine the weight of the load for instance in the dumper of Figure 1
  • Figure 4 is a schematic representation of the operating principle of the non-linear Kalman filter.
  • Figure 1 is a schematic representation of a dumper having a body 1 on wheels and a dump box 3 fastened at its rear end by joints 2 to the body 1. To empty the dump box 3, lifting cylinders 4 are connected between it and the body 1 , and when the dump box 3 is lowered to its down position, its front end rests on top of supports 5.
  • the dumper has sensors 6 based on gravitational force to measure the inclination of the body 1 in relation to the horizontal both in the longitudinal and lateral direction of the dumper.
  • the inclination of the dump box 3 in relation to the body 1 can be measured for instance by using angular sensors in the joints 2 or by measuring the volume of pressure fluid fed into the lifting cylinders 4 and calculating the inclination of the dump box 3 on the basis of it and by means of the geometry between the cylinder 4 fastening points and the joints 2.
  • FIG 2 is a schematic representation of a wheel loader having a body 1 on wheels and a bucket 9 fastened to it on lifting arms 7 through joints 8, and the bucket turns around joints 10 in relation to the lifting arms 7.
  • a separate tilting cylinder 11 tilts the bucket 9 in relation to the lifting arms 7, and a lifting cylinder 4 between the lifting arms 7 and the body 1 lifts the bucket 9.
  • the wheel loader has in the manner shown in Figure 1 inclination sensors 6 based on gravitational force for measuring the inclination of the wheel loader in relation to the horizontal on the basis of earth's gravity in both longitudinal and lateral direction of the wheel loader.
  • the position of the bucket 9 in the elevation of the body 1 can be defined by using angular sensors in the joints 8, for instance, and calculating on the basis of the measuring information provided by them and using the geometry of the lifting arms 7 the lifting height of the bucket 9 when it is turned in the most upright position by means of its turning cylinder 11.
  • the lifting height can also be defined by measuring the volume of pressure fluid fed into the cylinder 4, whereby it is possible to calculate the lifting height on the basis of said volume and the length of the joints and the cylinder 4.
  • FIG 3 is a schematic representation of an apparatus utilising a non-linear Kalman filter and suitable for determining for instance the weight of a load transported by a dumper according to Figure 1 , with which apparatus it is possible to measure the load in the dumper when the vehicle is either moving or stationary, in which case the method and apparatus of the invention can also be utilised in connection with an automatic filling of the bucket of a wheel loader to make sure that the bucket is full.
  • measuring sensors or measuring means are used, of which two measuring sensors 2a and 2b are strain gauges, for instance, that are mounted in a suitable place with respect to the joints 2 of the dump box 3 on both sides of the dumper body 1.
  • the apparatus comprises sensors 4a and 4b for measuring the pressures of the pressure fluid of the lifting cylinders 4 on both the side of the lifting cylinders 4 where the pressure fluid is fed and the side from which the pressure fluid flows out.
  • the weight of a load can be defined at a sufficient accuracy in a basically static situation on a horizontal base.
  • Measuring signals from the strain gauges 2a and 2b are forwarded through amplifiers 12 to a calculation unit 13 that calculates the position of the dump box 3 that has been defined as described earlier, and from the calculation unit 13, the parameter describing the position of the dump box 3 is forwarded to the input of a block 14 implementing the non-linear Kalman fil- ter.
  • the calculation of the position of the dump box 3 can also be included as part of the actual Kalman algorithm.
  • the block 14 implementing the non-linear Kalman filter also receives measuring signals from the pressure sensors 4a and 4b, the temperature of the pressure fluid from a temperature sensor 4c of the cylinder 4 and the inclination of the vehicle measured by the inclination sensors 6.
  • the block 14 can be a microprocessor, signal processor or another corresponding calculation unit capable of performing pre-programmed functions.
  • Figure 3 also shows a memory unit 15 for storing for instance the estimated weight of the load and other values measured, calculated or esti- mated during the estimation of the load weight.
  • the memory unit 15 also stores the initial values required by the non-linear Kalman filter for beginning the estimation process and described in the description of the operation of the non-linear Kalman filter of Figure 4. When beginning the estimation process, the initial values are read from the memory unit 15 to the block 14 implementing the non-linear Kalman filter.
  • the memory unit 15 can also be arranged as part of the calculation unit 14, but for clarity's sake, the memory unit 15 is shown as a separate component in Figure 3.
  • Figure 4 shows on a general level the operation of the nonlinear Kalman filter used in estimating the weight of a load to be weighed.
  • the model of the weighing system which comprises the dump box 3 or bucket 9 of the mining vehicle, the lifting arms 7 and the lifting cylinders 4 and/or tilting cylinder 11 to move them, and the measuring means described above, is dynamic, non-linear and discretely-timed.
  • the dynamics of the system can be described by the equation
  • x(k + 1 ) is the actual state of the system at the time instant k + 1
  • f() is a non-linear function corresponding to the state transition matrix of the system
  • x(/ ) is the actual state of the system at an earlier time instant k
  • vector v(/r) is white process noise with a zero mean value that describes a modelling error between the actual system and the model made of the system, the modelling error having the expected value of
  • the system model can take into consideration the high and low pressures P y and P a of the lifting cylinder of the dump box, the tilting ⁇ of the machine, the position s of the dump box, and the temperature L of the pressure fluid, e.g. hydraulic oil.
  • a state vector x of the non-linear state model of the weighing system of the vehicle would then comprise six elements
  • the actual weight m of the load are measurable variables.
  • the measurement of the temperature L of the pressure fluid can also be left out of the above-mentioned measurements without any essential change in the accuracy of the estimate of the load weight m.
  • the dependency of the load weight m on said measurements is non-linear, i.e. the function f() describing the dynamics of the weighing system shown in formula (1 ) is non-linear.
  • other factors that are not directly measurable can also be taken into consideration in the function f() describing the model of the load weight m.
  • the measurement function h() is generally a non-linear function, but within the scope of this invention, the measurement function h() can also be linear, and w(/c) is white measuring noise with a zero mean value that describes the error summed to the measurements from the measuring devices and measuring environment.
  • the expected value of the measuring noise w(/ ) is
  • R(/ ) is the covariance matrix of the measuring noise.
  • the estimate 23 of the actual state x(k) at the time instant k is an approximation of the conditional expected value of the actual state
  • n x is the number of states that in this case is six, e,- is an / -th tv dimensional basis vector whose /* component is one and other components are zero, KAT describes higher-order terms that in this case can be excluded and
  • n z is five, i.e. the number of measurements.
  • x ⁇ k + l is the prediction error of the state x ⁇ k + l) 21 based on the information available at the time instant k .
  • the updated estimate of the state, i.e. the filtered value x ⁇ + l ⁇ k + l) 27 of the state at the time instant k + l based on the information available at the time instant k + 1 is
  • x(k + l ⁇ k + 1) x(k + l ⁇ k)+ W(k + l) ⁇ (k + 1) (15)
  • the estimation of the system state i.e. according to this invention, also the estimation of the load weight m, by means of a Kalman filter can, in principle, be divided into three parts: predicting the state, calculating the amplification of the filter, and calculating the residual of the measurement, and on the basis of these, it is possible to calculate an estimate for the system state, and in this case, especially for the load weight m.
  • the uncertainties in the weighing system model and the measuring devices affect through the state covariance the amplification of the filter, with which the residual of the measurement is weighted in such a manner that in updating the state estimate, the information provided by the measurements on the state of the system and the state calculated on the basis of the system model are taken into account to a suitable extent, since neither of them alone is completely reliable, i.e. corresponds to the actual system.
  • the obtained updated values are further used in forming the estimate of the next time instant.
  • These calculation cycles are re- peated until the state provided by the filter as its output, i.e. in this case especially the weight m of the vehicle load, has settled to a certain level that thus corresponds to the estimate of the weight m of the load in the vehicle.
  • the estimation can be ended for instance when the variance of the load weight estimate is below a predefined limit value that can be changed, i.e. it is a parame- ter of the algorithm.
  • a predefined limit value that can be changed, i.e. it is a parame- ter of the algorithm.
  • ⁇ ) corresponding to the initial state, and the uncertainties of the weighing system model and the measuring devices are required, all of these being stored in the memory unit 15, from which they are read to the block 14 implementing the non-linear Kalman filter when weighing is started.
  • Values set at the factory to the vehicle in question can be used as the initial values.
  • the first measurement can also be used as the initial value for the states to be measured, in which case the actual estimate calculation is started from the second measurement.
  • the reason why the estimated value of the load weight m does not immediately at the first Kalman filter calculation cycle give the correct result is due to the fact that the calculation is started from the initial value of the state that is not necessarily correct. In addition, there is interference in the measuring signals especially at the beginning of the measurement that first must be filtered by the Kalman filter.
  • the vehicle is loaded with a test load of known weight.
  • a test load of known weight To perform calibration for an empty dump box or loading vehicle, it is enough to weigh the empty bucket and one known test load, but it is also possible to use several test loads of different weights.
  • the calibration is performed specifically for each machine. Further, the calibration can be performed again during the use of the machine to compensate for the impact of changes caused by aging of the machine or change of components.
  • the non-linear Kalman filter can also be used to estimate the parameters of the non-linear model of the weighing system.
  • the weighing can be done by means of a wheel loader, in which case the position of the bucket and other factors can easily be taken into account.
  • a wheel loader it is in principle possible to use the measuring diagram of Figure 3, in which case the position of the bucket 9 in the elevation of the body 1 and/or the inclination of the lifting arms 7 are taken into account in the weighing system model.
  • the state vector x of the model and the functions rep- resenting the system dynamics change from what is stated above while the principle of load weight m estimation remains the same.

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  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Operation Control Of Excavators (AREA)
  • Control Of Transmission Device (AREA)
  • Feedback Control In General (AREA)
  • Testing Of Balance (AREA)
  • Component Parts Of Construction Machinery (AREA)

Abstract

L'invention concerne un procédé et un agencement permettant de déterminer le poids d'une charge dans un véhicule de mine. Dans ces procédé et agencement, on utilise un filtre non linéaire de Kalman pour déterminer le poids (m) de ladite charge.
PCT/FI2001/000973 2000-11-09 2001-11-08 Procede et agencement permettant de determer le poids d'une charge dans un vehicule de mine WO2002039073A1 (fr)

Priority Applications (4)

Application Number Priority Date Filing Date Title
CA002431584A CA2431584C (fr) 2000-11-09 2001-11-08 Procede et agencement permettant de determiner le poids d'une charge dans un vehicule de mine
AU2369702A AU2369702A (en) 2000-11-09 2001-11-08 Method and arrangement for determining weight of load in mining vehicle
AU2002223697A AU2002223697B2 (en) 2000-11-09 2001-11-08 Method and arrangement for determining weight of load in mining vehicle
SE0301174A SE524212C2 (sv) 2000-11-09 2003-04-23 Förfarande och anordning för bestämning av vikten av last i ett gruvfordon

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
FI20002462A FI113696B (fi) 2000-11-09 2000-11-09 Menetelmä ja sovitelma kaivosajoneuvon kuorman painon määrittämiseksi
FI20002462 2000-11-09

Publications (1)

Publication Number Publication Date
WO2002039073A1 true WO2002039073A1 (fr) 2002-05-16

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PCT/FI2001/000973 WO2002039073A1 (fr) 2000-11-09 2001-11-08 Procede et agencement permettant de determer le poids d'une charge dans un vehicule de mine

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AU (2) AU2369702A (fr)
CA (1) CA2431584C (fr)
FI (1) FI113696B (fr)
SE (1) SE524212C2 (fr)
WO (1) WO2002039073A1 (fr)

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2007121517A1 (fr) * 2006-04-20 2007-11-01 Cmte Development Limited Systeme et procede d'estimation de charge utile
US8463517B2 (en) 2007-09-25 2013-06-11 Renault S.A.S. Method for hill start assistance for motor vehicle
DE102012223806A1 (de) * 2012-12-19 2014-06-26 Trumpf Werkzeugmaschinen Gmbh + Co. Kg Verfahren zum materialabtragenden Bearbeiten eines Werkstücks
US11150627B2 (en) 2017-12-20 2021-10-19 Caterpillar Underground Mining Pty. Ltd. System and method for monitoring conditions associated with operation of an underground machine
DE102022210216A1 (de) 2022-09-27 2024-03-28 Robert Bosch Gesellschaft mit beschränkter Haftung Verfahren zur Schätzung einer von einer Arbeitsmaschine aufgenommenen Last und Arbeitsmaschine

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4893262A (en) * 1986-06-27 1990-01-09 K-Tron International, Inc. Weigh feeding system with self-tuning stochastic control
US4954975A (en) * 1988-08-10 1990-09-04 K-Tron International, Inc. Weigh feeding system with self-tuning stochastic control and weight and actuator measurements

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4893262A (en) * 1986-06-27 1990-01-09 K-Tron International, Inc. Weigh feeding system with self-tuning stochastic control
US4954975A (en) * 1988-08-10 1990-09-04 K-Tron International, Inc. Weigh feeding system with self-tuning stochastic control and weight and actuator measurements

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
M. NIEDZ'WIECKI ET AL.: "Application of adaptive filtering to dynamic weighing of vehicles", CONTROL ENG. PRACTICE, vol. 4, no. 5, 1996, pages 635 - 644, XP002906846 *

Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2007121517A1 (fr) * 2006-04-20 2007-11-01 Cmte Development Limited Systeme et procede d'estimation de charge utile
US20090187527A1 (en) * 2006-04-20 2009-07-23 Cmte Development Limited Payload estimation system and method
US8311970B2 (en) 2006-04-20 2012-11-13 Cmte Development Limited Payload estimation of weight bearing machinery using multiple model adaptive estimator system and method
AU2007242056B2 (en) * 2006-04-20 2012-12-06 Ezymine Pty Limited Payload estimation system and method
US8463517B2 (en) 2007-09-25 2013-06-11 Renault S.A.S. Method for hill start assistance for motor vehicle
DE102012223806A1 (de) * 2012-12-19 2014-06-26 Trumpf Werkzeugmaschinen Gmbh + Co. Kg Verfahren zum materialabtragenden Bearbeiten eines Werkstücks
DE102012223806B4 (de) 2012-12-19 2018-11-29 Trumpf Werkzeugmaschinen Gmbh + Co. Kg Verfahren zum materialabtragenden Bearbeiten eines Werkstücks und zugehöriges Computerprogrammprodukt
US11150627B2 (en) 2017-12-20 2021-10-19 Caterpillar Underground Mining Pty. Ltd. System and method for monitoring conditions associated with operation of an underground machine
DE102022210216A1 (de) 2022-09-27 2024-03-28 Robert Bosch Gesellschaft mit beschränkter Haftung Verfahren zur Schätzung einer von einer Arbeitsmaschine aufgenommenen Last und Arbeitsmaschine

Also Published As

Publication number Publication date
SE524212C2 (sv) 2004-07-13
CA2431584C (fr) 2009-09-15
AU2002223697B2 (en) 2006-03-30
CA2431584A1 (fr) 2002-05-16
FI20002462A (fi) 2002-05-10
FI20002462A0 (fi) 2000-11-09
FI113696B (fi) 2004-05-31
SE0301174L (sv) 2003-06-12
SE0301174D0 (sv) 2003-04-23
AU2369702A (en) 2002-05-21

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