METHOD FOR LOAD DETERMINATION OF AN INSTALLATION CONVEYOR AND INSTALLATION CONVEYOR

Description

[0001] The invention relates to a method for determining the load in a forklift truck, in particular a counterbalance forklift or reach truck, with a load handling device comprising a lifting mast with at least one mast profile, wherein an elastic deformation of the mast profile is detected by means of a sensor device, wherein the elastic deformation of the mast profile is detected by measuring strains and torsions by means of at least one strain gauge as a sensor device.

[0002] The invention further relates to a forklift truck, in particular a counterbalance forklift or reach truck, for carrying out the method with a load handling device comprising a lifting mast with at least one mast profile, wherein at least one sensor device is arranged on the mast profile, which is designed to detect an elastic deformation of the mast profile and to determine deformation data, wherein the elastic deformation of the mast profile is detected by measuring strains and torsions using at least one strain gauge as a sensor device.

[0003] Industrial trucks include, for example, forklifts, especially counterbalance forklifts, and reach trucks. These industrial trucks are equipped with a load handling device for stacking and storing goods. The load handling device typically comprises a lifting mast with at least one mast profile. Usually, two mast profiles arranged parallel to each other and oriented vertically are provided. The lifting mast can also be equipped with a tilting mechanism, allowing the mast profiles to be tilted relative to the vertical. A load carriage, in particular a fork carriage, to which forks are typically mounted, can be moved vertically along the mast profiles, for example, by means of a hydraulic lifting cylinder. A load, such as a pallet, can then be picked up onto the forks.

[0004] Knowing the load weight is crucial for the safety of industrial trucks, particularly with regard to stability. Accordingly, numerous devices and methods exist for determining this weight as accurately and efficiently as possible. Often, attempts are made to utilize existing load-measuring devices already present in the industrial truck.

[0005] One possibility is to calculate the load weight from the pressure, which is usually already recorded, in the part of the hydraulic circuit of the working hydraulics that serves to lift the load.

[0006] For example, continuous load measurement systems are known in which the pressure in the lifting cylinder is measured and the load weight is calculated from this.

[0007] On the other hand, there are also discontinuous load measuring systems that measure the pressure curve in the lifting cylinder at the moment the fork carriage stops lowering and calculate the load weight from this. This method can achieve higher accuracy.

[0008] Load measuring systems based on the principle of pressure measurement in the hydraulic circuit of the working hydraulics are known, for example, from EP 1 953 114 B1.

[0009] German patent DE 10 2015 104 069 A1 describes a method for determining the tipping stability of a forklift truck, which uses pressure measurement in the working hydraulics and additional sensors. The parameters obtained from the additional sensors, such as speeds and accelerations of the load handling device, changes in the cross-sections of valve openings, etc., can improve the tipping stability calculation.

[0010] Regarding the determination of the load weight, the known systems integrated into the working hydraulics have the disadvantage that internal disturbances of the hydraulics, e.g., pressure pulsations and slipstick effects, which only occur in closed hydraulic systems, are also taken into account. This can distort the load determination.

[0011] Another method for load measurement is to indirectly determine the load weight by measuring the ground force of the forklift truck at the rear axle. Rear axle sensors can be used for this purpose, measuring the elastic deformation in the rear axle. Using the ground force determined via Hooke's Law, the stability of the forklift truck can be calculated using a model, with a high ground force corresponding to high stability.

[0012] From DE 10 2005 011 998 A1 and DE 10 2005 012 004 A1, the use of a computational model based on vehicle-specific information for the tipping behavior of a forklift truck is known. The computational model is stored in a control unit of the forklift truck. A number of sensors record physical parameters of the forklift truck relevant to its tipping behavior and compare them with the computational model in the control unit. Depending on the driving and loading conditions thus determined, the control unit performs corrective interventions to maintain or increase tipping stability.

[0013] When handling loads, the operator of a forklift truck is expected to be able to estimate not only the load's mass but also its center of gravity. This is particularly difficult for the operator with loads that are not visible, such as those in a rack, with complex geometric shapes, or in closed transport boxes. Misjudgments can lead to accidents and transport damage.

[0014] The cited publications on the state of the art do not offer a solution for also capturing the lateral offset of the load center of gravity to the vehicle center and taking it into account when determining the rollover stability.

[0015] From DE 10 2008 035 574 A1, a method according to the preamble of claim 1 for determining the center of gravity of a load located on a load-handling device of a forklift truck is known, wherein the lifting pressure of the lifting cylinder is determined by a sensor and the tilting pressure of the tilting cylinder is determined by a sensor. The load weight is determined from the lifting pressure of the lifting cylinder determined by the sensor. In conjunction with the tilting pressure of the tilting cylinder determined by the sensor, the distance of the center of gravity of the load in the longitudinal direction of the vehicle can be determined. The lateral load eccentricity is determined from the lateral deflection of the lifting mast by measuring the corresponding lateral deflection of the lifting mast profiles using strain gauges on the outer sides of the lifting mast profiles.

[0016] The present invention is based on the objective of designing a method of the type mentioned above and a corresponding industrial truck in such a way that the load mass and the load center of gravity can be determined with high accuracy at the same time.

[0017] This problem is solved according to the invention by processing the deformation data obtained from the elastic deformation of the mast profile detected by means of the sensor device with a physical calculation model of the industrial truck stored in a control unit of the industrial truck, based on vehicle-specific information, and determining the load mass and load center of gravity from this.

[0018] The invention is based on the understanding that by recording the elastic deformation of the mast profile and processing the deformation data with a vehicle-specific computational model—i.e., in the case of a counterbalanced forklift or a reach truck, with a computational forklift model—precise load determination is possible. In this way, interference influences, such as those that occur during measurements in the hydraulic circuit, can be prevented.

[0019] The calculation model is based on vehicle-specific information regarding the load-dependent deformation behavior of the mast profile. By comparing the model data with the measured deformation data, the load mass and the load center of gravity can be determined.

[0020] Another advantageous embodiment involves basing the computational model on vehicle-specific information regarding the static, quasi-static, and / or dynamic tipping behavior of the industrial truck. By processing the measured deformation data with the model data, both the operating state of "static and / or quasi-static tipping" (at high lifting height and low travel speed or standstill) and the operating state of "dynamic tipping" (high lateral acceleration when cornering, high longitudinal acceleration when braking) can be covered. This allows the vehicle behavior of the industrial truck to be intervened in such a way as to prevent tipping.

[0021] The elastic deformation of the mast profile is expediently recorded by measuring strains and torsions in three-dimensional space. From this, tensile, compressive, and torsional forces are determined as deformation data, for example using Hooke's Law, and compared with corresponding data stored in the computational model. The load mass and center of gravity can then be determined from this comparison with the computational model.

[0022] According to the invention, the elastic deformation of the mast profile is detected by measuring strains and torsions using at least one strain gauge. The use of strain gauges is a proven method for measuring stress and strain. Strain gauges are used in a wide variety of applications to indirectly determine forces via strain measurement. A strain gauge module with one strain gauge is known, for example, from DE 10 2014 117 334 A1.

[0023] The measurement is preferably carried out continuously, so that the current load mass and the current load center of gravity can be determined at any given time.

[0024] The load center is advantageously determined as a point in a three-dimensional coordinate system with the coordinates x, y and z, where the x-coordinate represents the vertical height of the load center above the road surface, the y-coordinate represents the horizontal lateral offset of the load center to the vehicle center, i.e. to the vehicle longitudinal center axis, and the z-coordinate represents the horizontal distance of the load center from the lifting mast.

[0025] Using Fast Fourier Transform (FFT) signal analysis of the typically digital force signals of the tensile, compressive, and torsional forces detected by the sensor system, the digital force signals can be decomposed into their frequency components, which can then be analyzed. In this way, the natural frequency of the lifting mast can be determined.

[0026] The load mass can be deduced from static deflections during the elastic deformation of the mast profile using the lever principle.

[0027] To further increase measurement accuracy, a preferred embodiment of the invention provides for the acquisition of additional measured values ​​by means of additional sensors, which are also incorporated into the computational model. This allows errors with common causes to be excluded.

[0028] For this purpose, lifting forces acting on the load handling device can be measured, and the lifting force measurements can be additionally taken into account when processing the deformation data with the calculation model.

[0029] Additionally or alternatively, tilting forces acting on the load handling device are advantageously measured and the tilting force measurements are additionally taken into account when processing the deformation data with the calculation model.

[0030] In a further preferred embodiment, the lifting height of the load handling device is additionally or alternatively measured and the lifting height measurements are additionally taken into account when processing the deformation data with the calculation model.

[0031] To inform the forklift operator about the results of the load determination, it is advantageous to display the load mass and the load center of gravity on a display device. This display device thus serves as the interface to the operator, informing them about the load mass and the position of the load center of gravity in the x, y, and z directions of the load being lifted.

[0032] The display can also show a visual warning to inform the operator about the distance to critical system limits. The operator can then take appropriate countermeasures. For example, they can reduce the forklift's travel speed and / or decrease the lifting height of the load to ensure the forklift's full operational safety.

[0033] To reduce the risk of the industrial truck tipping over, a particularly advantageous embodiment of the invention provides that the computational model determines a driving and loading condition of the industrial truck based on physical quantities that are relevant for static and / or quasi-static and / or dynamic tipping behavior of the industrial truck.

[0034] In a simple design, the driving and loading status of the forklift is displayed to the driver. The driver can then manually initiate appropriate measures to prevent the forklift from tipping over.

[0035] In a further developed embodiment, automation is provided in which the control unit independently makes corrective interventions to maintain or increase tipping stability in a drive and / or steering drive of the industrial truck and / or a working drive of the load handling device, depending on the determined driving and loading condition of the industrial truck.

[0036] The driver can also be supported by automated, shutdown interventions to prevent overriding system limits when approaching them at close range. These interventions can affect the working hydraulics control, the drive control, and the steering control. The overall goal of these interventions is to reduce kinetic energy and minimize large changes in kinetic energy.

[0037] The invention further relates to a forklift truck, in particular a counterbalance forklift truck, for carrying out the method according to the invention with a load handling device comprising a lifting mast with at least one mast profile, wherein at least one sensor device is arranged on the mast profile, which is designed to detect an elastic deformation of the mast profile and to determine deformation data.

[0038] In the case of the industrial truck, the task is solved by the sensor device being in operative communication with a control unit of the industrial truck, in which a physical computational model of the industrial truck based on vehicle-specific information is stored, and the control unit is configured to process the deformation data determined by the sensor device in the computational model and to determine the load mass and load center of gravity from it.

[0039] Advantageously, the sensor device includes at least one strain gauge designed for measuring strains and torsions in three-dimensional space.

[0040] The sensor device is preferably integrated into the mast profile in such a way that differences in mast profiles and tonnages are taken into account in the mechanical integration. This integration into the mast profile also protects the sensor device against mechanical damage.

[0041] If the load handling device of the industrial truck is designed such that the lifting mast comprises two parallel mast profiles, a sensor device is preferably arranged on each of the two mast profiles.

[0042] The invention offers a whole range of advantages: Particularly advantageous compared to the prior art is that, according to the invention, the load center of gravity can be detected three-dimensionally in relation to the vehicle.

[0043] In particular, the lateral offset to the center of the vehicle is not taken into account by the systems currently available.

[0044] Another advantage is the scalability of the sensor technology. According to the invention, the same sensor device can always be used in different vehicles, tonnages, and mast systems. This enables the use of standardized sensor devices and cost-effective application in steel construction.

[0045] A further advantage is that the system according to the invention measures outside the hydraulic system. Internal interference pulses, waves, or impermissible operating points, such as those at the end stop of the working hydraulics, are not detected. For this reason, no complex correction calculation is necessary with the new solution.

[0046] The invention makes it possible to combine the advantages of different sensor technologies. This results in more accurate measurements that are also more robust across the various operating points of the industrial truck. Furthermore, this method elegantly eliminates common-cause errors.

[0047] The interface with the forklift truck allows the operator to be informed and supported during load handling. This is particularly important for loads that are not visible, such as those in racks, complex geometric shapes, or enclosed transport boxes. By providing the operator with information about the load weight and the position of the load's center of gravity in the x, y, and z directions, the operator can prevent accidents and transport damage.

[0048] Critical situations can be actively prevented through automated interventions by the control unit.

[0049] Further advantages and details of the invention are explained in more detail with reference to the exemplary embodiments shown in the schematic figures. These show Figure 1 is a perspective view of a forklift truck, Figure 2 is a detailed view of a lifting mast with one sensor device, Figure 3 is a detailed view of a lifting mast with two sensor devices, Figure 4 is a detailed view of the sensor device, Figure 5 is a diagram for data processing in the control unit, and Figure 6 is a diagram of a control structure for increasing the tipping stability of the forklift truck.

[0050] The industrial truck according to the Figure 1For example, it is designed as a front-seat counterbalance forklift. A load handling device 1 arranged at the front of the vehicle consists of an extendable lifting mast 1a with two parallel mast profiles 1d and a load carriage 1b, which is height-adjustable on the mast profiles 1d and has forks 1c attached to it. Various types of loads can be lifted and transported using the forks 1c.

[0051] The lifting mast 1a is tiltable about a horizontal axis arranged transversely in its lower section. Of course, it is also possible to provide a rigid, i.e., non-tiltable, lifting mast 1a and instead design the load carriage 1b to be not only height-adjustable but also tiltable, as is often the case, for example, with so-called warehouse equipment (e.g., reach trucks). Depending on the application, other load-handling devices can also be attached to the load carriage 1b. It goes without saying that additional movements of the load handling device 1 are also possible in principle, provided the necessary equipment, e.g., a side shifter, is available.

[0052] The lifting mast 1a can be tilted by means of hydraulic tilt cylinders 1e. Extending the lifting mast 1a and raising the load carriage 1b is accomplished by means of hydraulic lifting cylinders, optionally with one or more load chains. Lowering the load carriage 1b or retracting the lifting mast 1a is achieved using the dead weight of the load carriage 1b and the upwardly extended components of the lifting mast 1a, as well as, if applicable, the weight of the load. These hydraulic actuators are supplied by a hydraulic pump. Together with the necessary hydraulic valves and a motor driving the pump, this system thus comprises several working drives for the lifting, lowering, and tilting movements of the load handling device 1.

[0053] The industrial truck according to the exemplary embodiment further comprises a drive system in which a front axle 2 is designed as a drive axle, and a steering drive with the aid of which a rear-mounted steering axle 3 is actuated.

[0054] A sensor device 4, designed as a strain gauge 4, is attached to one or both mast profiles 1d. The strain gauge 4 measures the elastic deformation of the respective mast profile 1d by detecting strains and torsions in three-dimensional space. From this, tensile, compressive, and torsional forces in the mast profile 1d are determined as deformation data using Hooke's law. The deformation data is transmitted to a control unit SE of the industrial truck via a data line or wirelessly via a radio connection. The control unit contains a physical computational model of the industrial truck, which is based on vehicle-specific information. This vehicle-specific information includes parameters that influence the tipping stability of the industrial truck, such as the dimensions and masses of the industrial truck and the lifting mast 1a, the tire characteristics, and the maximum possible payload.Furthermore, the computational model also contains data on the load-dependent deformation behavior of the mast profiles. Overall, the computational model represents a comprehensive computational model of the industrial truck, i.e., an electronic forklift model. In the control unit SE, the deformation data recorded by the strain gauges 4 are processed with the computational model, so that the load mass and the center of gravity of a load located on the forks 1c can be determined.

[0055] In the Figure 2 Figure 1 shows a detailed section of the lifting mast 1a. The lifting mast 1a comprises two parallel mast profiles 1d. A sensor device 4, designed as a strain gauge 4, is attached to one of the mast profiles 1d.

[0056] The Figure 3 Figure 1a also shows a detailed section of the lifting mast. This embodiment differs from the one shown in Figure 1. Figure 2represented by the fact that a sensor device 4 designed as a strain gauge 4 is attached to each of the mast profiles 1d.

[0057] In the Figure 4 The sensor device 4, designed as a strain gauge 4, is of the Figure 2 and 3 The process is shown in detail. The strain gauge 4 is integrated into the mast profile 1d in such a way that it is protected from mechanical damage. The strain gauge 4 measures the elastic deformation of the mast profile 1d by detecting strains and torsions in three-dimensional space. From this, tensile, compressive, and torsional forces of the mast profile 1d are determined as deformation data using Hooke's law. The tensile and compressive forces are shown in the Figure 4The forces are represented as force vectors pointing in the three spatial directions x, y, z, where the x-direction corresponds to a vertical direction, the y-direction to a transverse direction of the vehicle, and the z-direction to a longitudinal direction of the vehicle. The torsional forces are the radial forces around the force vectors represented as arrows. Thus, a total of six forces can be determined at this point using the strain gauge 4. If a strain gauge 4 is attached to each of two mast profiles 1d, a total of 12 forces can be determined. The forces are measured continuously using the strain gauges 4.

[0058] The Figure 5This shows a diagram for data processing (DV) in the control unit of the industrial truck. On the left are listed the parameters determined by the sensors, as well as the computational model D, which is a computational, physical model of the forklift. The data determined by the sensors include the forces (DMS I and / or DMS II) detected by one or two strain gauges on one or both mast profiles (six forces per strain gauge). In a design according to the Figure 2 Only the forces DMS I of a strain gauge are present, in a design according to the Figure 3The forces DMS I and DMS II of the two strain gauges are available. Additionally and optionally, the tilting forces NK, the lifting forces HK of the lifting mast, and the lifting height H can be available as parameters. Using data processing DV of the parameters DMS I and / or DMS II recorded by the sensors, as well as the parameters NK, HK, and H recorded by any other sensors, and comparing this data with the physical forklift model D, the load mass L and the load center of gravity LS are calculated. The load center of gravity is determined as a point in a three-dimensional coordinate system with the coordinates x, y, and z, where the x-coordinate represents the vertical height of the load center of gravity above the ground, the y-coordinate represents the horizontal lateral offset of the load center of gravity from the vehicle center, and the z-coordinate represents the horizontal distance of the load center of gravity from the lifting mast.

[0059] In principle, the forces measured by one or both strain gauges 4, DMS I and / or DMS II, would be sufficient for comparison with the forklift model. The optional additional parameters NK, HK, and H serve to further increase measurement accuracy.

[0060] In the Figure 6 A rule structure for increasing the tipping stability of a material handling vehicle, such as a forklift, is shown. The inputs P from the driver of the material handling vehicle at the accelerator pedals, steering wheel, and control levers result in a driving and loading state Z, which is fed back to the driver in the form of a subjective perception W, whereupon the inputs P may be changed.

[0061] The forklift is equipped with sensors S that measure physical quantities from which the driving and loading conditions Z can be objectively determined. These quantities include the load mass L and the load center LS, the lifting height H, the load moment M, the mast tilt angle WM, the steering angle WL, the direction of travel R, the travel speed V, the longitudinal acceleration BL, the lateral acceleration BQ, and the yaw rate G. For example, the tilt cylinder forces or the axle load of the steering axle (rear axle) can be used to determine the load moment M.

[0062] The sensors S also include strain gauges, which detect the elastic deformation of the mast profile by measuring strains and torsions in three-dimensional space. From this, tensile, compressive, and torsional forces are determined as deformation data using Hooke's law, which can then be processed by the computational model.

[0063] Of the aforementioned sensors S, some are designed to detect physical quantities required for determining static and quasi-static tipping hazards. These include sensors for detecting the direction of travel R, the travel speed V, the load mass L and center of gravity LS, the lifting height H, the load moment M, the mast tilt angle WM, and the steering angle WL. Additional physical quantities must be detected to determine dynamic tipping hazards. For this purpose, sensors are provided to detect the longitudinal acceleration BL, the lateral acceleration BQ, and the yaw rate G.

[0064] The measured values ​​recorded by the sensors S are passed on to the control unit SE, in which a computational model D of the forklift is stored based on vehicle-specific data, such as the dimensions and masses of the industrial truck and the lifting mast, the tire characteristics and the maximum possible payload.

[0065] In the control unit SE, the current driving and loading state Z of the industrial truck is determined in a driving condition observer FB from the calculation model D and the measured values ​​of the sensors S, and it is determined whether the working and / or driving movements are tipping-critical and therefore require intervention.

[0066] Here, the driving condition observer FB monitors critical driving maneuvers FM1 and FM2 for a first intervention area E1 and a second intervention area E2, respectively. For the first intervention area E1, in which measures against static and / or quasi-static rollover may be required, these maneuvers are: braking forward when the vehicle is tilted forward, accelerating backward when the vehicle is tilted forward, braking from reverse in a curve when the vehicle is tilted perpendicular to the rollover axis, and accelerating into forward travel in a curve when the vehicle is tilted perpendicular to the rollover axis.

[0067] For the second intervention area E2, in which measures against dynamic rollover are to be implemented, the steering speed, for example, can be monitored as a critical driving maneuver FM2. From this, the necessary interventions E in the drive system, steering system, and working drive can be derived to ensure that the rollover limits are not reached or exceeded. The control unit SE thus increases rollover stability.

[0068] The interventions performed are interventions in intervention area E1 (e.g., reducing driving and working speed) and interventions in intervention area E2 (e.g., reducing driving speed, changing the steering ratio to reduce steering speed), each of which corrects the operator's inputs P (connection K1), for example, by overriding the target values. Furthermore, interventions can influence the inputs P at the moment they are generated (arrow K2), e.g., increasing the steering torque required to turn the steering wheel in the second intervention area E2 or force feedback signals to the operator's control levers of the working hydraulics, so that the operator is informed of decreasing distances to system limits.

Claims

1. Method for load determination in an industrial truck, in particular a counterweight forklift or reach truck, with a load handling device (1) comprising a lift mast (1a) having at least one mast profile (1d), wherein an elastic deformation of the mast profile (1d) is detected by means of a sensor device (4), wherein the elastic deformation of the mast profile (1d) is detected by measuring strains and torsions by means of at least one strain gauge (4) as a sensor device (4), wherein deformation data determined from the elastic deformation of the mast profile (1d) detected by means of the sensor device (4) are processed using a physical computational model (D), stored in a control device (SE) of the industrial truck and based on vehicle-specific information, of the industrial truck, and the load centre of gravity (LS) is determined therefrom, characterized in that the load mass (L) is determined from the deformation data which are provided by the at least one strain gauge (4) of the sensor device (4) and are processed using the physical computational model (D), stored in the control device (SE) and based on vehicle-specific information, of the industrial truck.

2. Method according to Claim 1, characterized in that the computational model (D) is based on vehicle-specific information with respect to the load-dependent deformation behaviour of the mast profile (1d).

3. Method according to Claim 1 or 2, characterized in that the computational model (D) is based on vehicle-specific information with respect to the static and / or quasi-static and / or dynamic tipping behaviour of the industrial truck.

4. Method according to either of Claims 1 to 3, characterized in that the elastic deformation of the mast profile (1d) is detected by measuring strains and torsions in three-dimensional space, and tensile, compressive and torsional forces are determined as deformation data therefrom.

5. Method according to one of Claims 1 to 4, characterized in that the load centre of gravity (LS) is determined as a point in a three-dimensional coordinate system with the coordinates x, y and z, wherein the x-coordinate represents the vertical load centre of gravity height above the driving surface, the y-coordinate represents the horizontal, lateral offset of the load centre of gravity (LS) with respect to the centre of the truck, and the z-coordinate represents the horizontal distance of the load centre of gravity (LS) from the lift mast (1a).

6. Method according to one of Claims 1 to 5, characterized in that lifting forces (HK) acting on the load handling device (1) are measured, and the lifting force measured values are additionally taken into account when processing the deformation data using the computational model (D).

7. Method according to one of Claims 1 to 6, characterized in that tilting forces (NK) acting on the load handling device (1) are measured, and the tilting force measured values are additionally taken into account when processing the deformation data using the computational model (D).

8. Method according to one of Claims 1 to 7, characterized in that the lift height (H) of the load handling device (1) is measured, and the lift height measured values are additionally taken into account when processing the deformation data using the computational model (D).

9. Method according to one of Claims 1 to 8, characterized in that the load mass (L) and the load centre of gravity (LS) are displayed in a display device for a driver.

10. Method according to one of Claims 1 to 9, characterized in that a driving and loading state of the industrial truck is determined using the computational model (D), which driving and loading state is based on physical variables that are relevant for a static and / or quasi-static and / or dynamic tipping behaviour of the industrial truck.

11. Method according to Claim 10, characterized in that the driving and loading state of the industrial truck is displayed in a display device for a driver.

12. Method according to Claim 10 or 11, characterized in that, depending on the determined driving and loading state of the industrial truck, the control device (SE) performs corrective interventions, which maintain or increase tipping stability, in a travel drive and / or steering drive of the industrial truck and / or a working drive of the load handling device (1).

13. Industrial truck, in particular counterweight forklift or reach truck, arranged for carrying out the method according to Claim 1, with a load handling device (1) comprising a lift mast with at least one mast profile, wherein at least one sensor device (4) is arranged on the mast profile (1d), which sensor device is designed to detect an elastic deformation of the mast profile (1d) and to determine deformation data, wherein the elastic deformation of the mast profile (1d) is detected by measuring strains and torsions by means of at least one strain gauge (4) as a sensor device (4), wherein the sensor device (4) is operatively connected to a control device (SE) of the industrial truck, in which a physical computational model (D) of the industrial truck based on vehicle-specific information is stored, and the control device (SE) is configured to process the deformation data determined by the sensor device (4) in the computational model (D) and to determine the load mass (L) and load centre of gravity (LS) therefrom.

14. Industrial truck according to Claim 13, characterized in that the sensor device (4) comprises at least one strain gauge (4) which is designed for measuring strains and torsions in three-dimensional space.

15. Industrial truck according to Claim 13 or 14, characterized in that, in the case of a lift mast (1a) comprising two parallel mast profiles (1d), a sensor device (4) is arranged on each of the two mast profiles (1d).