Method for determining torque and driveshaft angle

Abstract

The invention relates to a method for determining a torque (T) and a driveshaft angle (A) of a gear mechanism (1). The method may comprise determining a first measurement signal by means of a torque sensor (2) incorporated in the gear mechanism (1). The method may further comprise determining a second measurement signal by means of a Hall sensor (3) incorporated in the gear mechanism (1). The method may in another step include determining a torque (T) from the first measurement signal. The method may comprise, in another step, determining the driveshaft angle (A) from the second measurement signal. The method may further comprise transmitting a data set (D) comprising the torque (T) and the driveshaft angle (A) to a component (5) arranged outside the gear mechanism (1) by means of a single communication line (4). The invention also relates to a gear mechanism (1) comprising a torque sensor (2) incorporated in the gear mechanism (1), a Hall sensor (3) incorporated in the gear mechanism (1), and a communication line (4).

Description

Technical Field

[0001] The present invention generally relates to the technical field of methods for determining the torque and the drive shaft angle of a gear mechanism. Background Art

[0002] Methods for determining torque and drive shaft angle have many uses in the field of gear mechanism technology. For example, torque and drive shaft angle are measured or mathematically determined to improve gear mechanisms in the field of robotics. In particular, industrial robots and multi-jointed robot joint systems often require high torques and instantaneous drive shaft angles of the gear mechanism to ensure optimal movement of the multi-jointed robot joint system for specific applications. In addition to the field of robotics, torque and drive shaft angle are also important parameters in automotive engineering.

[0003] The gear mechanism typically includes a drive shaft leading to the gear mechanism.

[0004] In order to determine the torque, a torque sensor is usually connected to the robot joint controller. Such a torque sensor is usually formed by attaching a strain gauge to a component of the gear mechanism of the robot joint system and determining the torque based on input data, wherein the input data is measured by the strain gauge. Such a method is described, for example, in the following scientific publication:

[0005] Hashimoto, Minoru, Yoshihide Kiyosawa, and Richard P. Paul. "Atorque sensing technique for robots with harmonic drives." IEEE Transactions on Robotics and Automation 9.1 (1993): 108-116.

[0006] Hashimoto, Minoru, and Yoshihide Kiyosawa. "Experimental study on torque control using Harmonic Drive built-in torque sensors." Journal of Robotic Systems 15.8 (1998): 435-445.

[0007] In order to determine the drive shaft angle, a Hall sensor is usually connected to the robot joint controller. The Hall sensor is positioned close to the drive shaft, wherein a magnet is arranged on the drive shaft. Due to the rotation of the drive shaft and the magnet, the magnetic flux density can be measured using the Hall sensor. From the magnetic flux density, the drive shaft angle, i.e. the instantaneous rotation angle of the drive shaft, can be calculated.

[0008] For a robot joint controller that communicates with both a Hall sensor and a torque sensor, different communication protocols, electrical connections, and wiring must be used for the two sensors. The specifications for guaranteed operating temperature, certified safety level, sampling frequency, and IP (waterproof) level between the two sensors may also be different, resulting in more development work to ensure that both sensors operate properly and maintain high product quality.

[0009] Therefore, it is an object of the present invention to provide an improved method for determining the torque and drive shaft angle of a gear mechanism, thereby at least partially overcoming the above-mentioned disadvantages of the prior art. Another object of the present invention is to provide an improved gear mechanism. Summary of the invention

[0010] These objects are achieved by the features of the independent claims. In its most general form, the invention relates to a method for determining a torque and a drive shaft angle of a gear mechanism. The method may comprise determining a first measurement signal by means of a torque sensor incorporated in the gear mechanism. Furthermore, the method may comprise determining a second measurement signal by means of a Hall sensor incorporated in the gear mechanism. The method may comprise, in a further step, determining the torque based on the first measurement signal. In a further step, the method may comprise determining the drive shaft angle based on the second measurement signal. The method may further comprise transmitting a data set comprising the torque and the drive shaft angle to a component arranged outside the gear mechanism by means of a single communication line.

[0011] The gear mechanism is preferably part of a vehicle or robot. The gear mechanism may be connected to a motor. The motor may be an internal combustion engine, an electric motor, a fuel cell, a hybrid drive or other type of energy converter.

[0012] Torque can be understood as torque that can be used to drive a vehicle, a robot, or a manipulator link of a robot. Torque can be understood as torque applied to a drive shaft of a gear mechanism. For example, the torque of a gear mechanism can be the output torque of the gear mechanism. The torque of a gear mechanism can be directly transmitted to the wheels of a vehicle.

[0013] The drive shaft angle generally refers to the rotation angle of the drive shaft leading to the gear mechanism. For example, the drive shaft may initially have a drive shaft angle of about 0°. After the drive shaft rotates half a turn, the drive shaft angle is approximately 180°. The rotation direction refers to the direction of rotation of the drive shaft. The rotation direction can be clockwise or counterclockwise.

[0014] "Determining the torque and / or determining the drive shaft angle" is generally understood by a person skilled in the art to mean any type of determination and / or calculation in a mathematical sense. Any type of mathematical operation, in particular an iterative method, can be used for this purpose. Reading from a table can also be used to determine the torque and / or determine the drive shaft angle. Mathematical models can also be used to determine the torque and / or the drive shaft angle.

[0015] The determination of the torque and / or the determination of the drive shaft angle can be implemented on a microcontroller integrated in the gear mechanism. This implementation has the advantage that the method steps can be completely performed on the microcontroller and no additional components are required.

[0016] The torque sensor may include a strain gauge. The strain gauge may include a semiconductor and measure a voltage applied to a resistor based on a piezoresistive effect.

[0017] The Hall sensor can be designed as a single-axis or dual-axis Hall sensor. The Hall sensor can have a typical design. The typical design can be rectangular, butterfly or cross.

[0018] The first measurement signal may be a voltage detected by a torque sensor. In addition, the second measurement signal may be a magnetic flux density detected by a Hall sensor.

[0019] The communication line can be a standard communication system or a component of a communication system. The communication system can be, for example, an EtherCAT, RS485 or SPI bus system. The communication between the two sensors, namely the torque sensor and the Hall sensor, and the component arranged outside the gear mechanism can advantageously take place via a bus or line. In addition, no complicated wiring is required between the two sensors and the component. In addition, the torque and the drive shaft angle can be sent simultaneously via the communication line.

[0020] The components arranged outside the gear mechanism can be, for example, a motor controller or a robot joint controller. The motor controller or the robot joint controller can also be designed to control motors and / or other components. The motor controller or the robot joint controller can, for example, adjust the speed of the manipulator link of the robot or the speed of the vehicle. Here, this type of closed-loop control can be implemented using a control loop implemented in an algorithm.

[0021] Gear types that can be used are spur gears, bevel gears, helical gears, planetary gears or strain wave gears.

[0022] Some or all of the method steps may be performed by (or using) a hardware device, such as a microcontroller. The hardware device may also include a processor, a microprocessor, a programmable computer, or an electronic circuit. In some exemplary embodiments, one or more of the key method steps may be performed by such a device.

[0023] Naturally, the method can be fully automatic. The method can also be performed continuously in real time, as is common in the technical field of robots or motors.

[0024] The method according to the invention advantageously leads to an improved communication between a torque sensor or Hall sensor integrated in a gear mechanism and a component arranged outside the gear mechanism. The method leads to an improved, simpler construction and lower production costs of the gear mechanism.

[0025] In another aspect of the invention, the data set is transmitted using a single communication protocol. The communication protocol may be, for example, EtherCAT, RS485 or SPI protocol.

[0026] In another aspect of the invention, the drive shaft angle is determined by means of a Hall sensor incorporated in the gear mechanism and by means of a ring magnet incorporated in the gear mechanism. The ring magnet can be designed as a permanent magnet. Half of the ring magnet can be designed as a positive pole and the other half of the ring magnet as a negative pole.

[0027] In another aspect of the invention, the second measurement signal comprises a magnetic flux density. The drive shaft angle can be determined from the magnetic flux density by means of a mathematical model, preferably a regression model, particularly preferably a nonlinear regression model. The mathematical model can also be a radial basis function (RBF).

[0028] In another aspect of the invention, a sensor system is provided, the sensor system comprising means for performing one of the methods described herein.

[0029] The sensor system may include a torque sensor and a Hall sensor. In addition, the sensor system may include a microcontroller and / or a storage medium (or a data carrier or a computer-readable medium), the storage medium including a computer program stored thereon, the computer program being used to perform one of the methods described herein when executed by a processor. The data carrier, digital storage medium or recording medium is typically tangible and / or non-transient. Another exemplary embodiment of the present invention is a sensor system as described herein, the sensor system comprising a processor and a storage medium.

[0030] In another aspect of the invention, there is provided a computer program comprising instructions which, when the program is executed by a computer, cause the computer to perform one of the methods described herein.

[0031] According to the present invention, a gear mechanism is also provided. The gear mechanism may include a torque sensor incorporated in the gear mechanism, a Hall sensor incorporated in the gear mechanism, and a communication line. In addition, the gear mechanism may be designed so that data sets from the torque sensor incorporated in the gear mechanism and the Hall sensor incorporated in the gear mechanism can be transmitted to a component arranged outside the gear mechanism by means of a single communication line.

[0032] The gear mechanism according to the invention can advantageously have a particularly space-saving and compact design. The gear mechanism can also advantageously have a small number of components.

[0033] In another aspect of the invention, the gear mechanism includes an annular magnet incorporated into the gear mechanism.

[0034] In another aspect of the invention, the gear mechanism includes an analog-to-digital converter incorporated in the gear mechanism. The gear mechanism may also include a microcontroller incorporated in the gear mechanism. The gear mechanism may also include a circuit board incorporated in the gear mechanism.

[0035] Artificial neural networks can be used as mathematical models for the methods described herein.

[0036] Artificial neural network (ANN) is a system inspired by biological neural network, such as biological neural network found in retina or brain. ANN includes multiple interconnected nodes and multiple connections between nodes, so-called edges. There are usually three types of nodes: input nodes that receive input values, hidden nodes that are (only) connected to other nodes, and output nodes that provide output values. Each node can represent an artificial neuron. Each edge can send information from one node to another node. The output of a node can be defined as a (non-linear) function of the input (e.g., the sum of the inputs of the node). The input of the node can be used in the function based on the "weight" of the edge or the node providing the input. The weight of the node and / or the edge can be adjusted as part of the learning process. In other words, training an artificial neural network can include adjusting the weight of the nodes and / or the edges of the artificial neural network, that is, in order to achieve the desired output for a specific input.

[0037] Alternatively, the mathematical model can be a support vector machine, a random forest model or a gradient enhancement model.Support vector machine (i.e., support vector network) is a supervised learning model with a related learning algorithm, which can be used for analyzing data (e.g., in classification or regression analysis).Support vector machine can be trained by providing multiple training input values ​​belonging to one of two categories for input.Support vector machine can be trained so that new input values ​​are assigned to one of two categories.Alternatively, the mathematical model can be a Bayesian network, which is a probabilistic directed acyclic graph model.The Bayesian network can use a directed acyclic graph to represent a set of random variables and their conditional dependencies.Alternatively, the mathematical model can be based on a genetic algorithm, which is a search algorithm and a heuristic technique that imitates a natural selection process.

[0038] The mathematical model can be trained using a training data set, or it can be pre-trained. For example, a training data set can be created on a test bench. Torque sensors and Hall sensors can be used on the test bench to measure the signals required for the training data set.

[0039] For example, "supervised learning" can be used as a training method for a mathematical model. In supervised learning, a mathematical model is trained using multiple training sample values, wherein each sample value may include multiple input data values ​​and multiple expected output values, i.e., each training sample value is associated with an expected output value. By specifying both the training sample values ​​and the expected output values, the machine learning model can "learn" which output value to provide based on input sample values ​​similar to the sample values ​​provided as part of the training. In addition to supervised learning, semi-supervised learning can also be used. In semi-supervised learning, some of the training sample values ​​lack the expected output value. Supervised learning can be based on supervised learning algorithms (e.g., classification algorithms, regression algorithms, or similarity learning algorithms). When the output is limited to a finite set of values ​​(classification variables), i.e., the input is classified as one of a finite set of values, a classification algorithm can be used. If the output exhibits an arbitrary value (within a certain range), a regression algorithm can be used. A similarity learning algorithm can be similar to both a classification algorithm and a regression algorithm, but is based on learning from examples using a similarity function, which measures the similarity or correlation between two objects. In addition to supervised learning or semi-supervised learning, unsupervised learning can be used to train a machine learning model. In unsupervised learning, (only) input data may be provided, and an unsupervised learning algorithm may be used to find structure in the input data (e.g., find commonalities in the data by grouping or clustering the input data). Clustering is the assignment of input data comprising multiple input values ​​into subsets (clusters) such that input values ​​within the same cluster are similar according to one or more (predefined) similarity criteria, while input values ​​within the same cluster are dissimilar to input values ​​comprised in other clusters. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The preferred embodiments of the present disclosure will be described below with reference to the accompanying drawings:

[0041] Figure 1 : shows a gear mechanism 1 according to an embodiment of the present invention.

[0042] Figure 2 : The method according to an embodiment of the present invention is shown in an overview diagram.

[0043] Figure 3A : A cross-sectional view of a gear mechanism 1 with an annular magnet 11 according to an embodiment of the present invention is shown.

[0044] Figure 3B : shows a ring magnet 11 according to an embodiment of the present invention.

[0045] Figure 4 : A gear mechanism 1 according to an embodiment of the present invention is shown in a side view.

[0046] Figure 5 : shows the signals detected by means of the Hall sensor 3 and a method for determining the drive shaft angle A according to an embodiment of the present invention. DETAILED DESCRIPTION

[0047] In the following an embodiment of the invention is described in which a method for determining the torque and the drive shaft angle of a gear mechanism is used in order to make the gear mechanism particularly efficient and compact.

[0048] Figure 1 A gear mechanism 1 according to an embodiment of the present invention is shown. In the example shown, the gear mechanism 1 is used in an industrial robot and comprises a torque sensor 2 incorporated in the gear mechanism 1 and a Hall sensor 3 incorporated in the gear mechanism 1 .

[0049] The gear mechanism 1 is a strain wave gear (SWG) with an elastic gear mechanism element, which is characterized by a high gear mechanism ratio and stiffness. The elastic gear mechanism element is also called a flexspline. The gear mechanism 1 also has a drive shaft and an output shaft. The torque of the output shaft is transmitted to the manipulator of the industrial robot.

[0050] The torque sensor 2 includes a strain gauge, wherein the strain gauge includes a semiconductor and measures the voltage applied to a resistor based on the piezoresistive effect. Here, the change in resistance and voltage is caused by the deformation of the strain gauge. The advantage of the strain gauge used is its high sensitivity compared to conventional metal strain gauges. The strain gauge of the torque sensor 2 is arranged on an elastic gear mechanism element of the gear mechanism 1. Therefore, the torque sensor 2 is embedded in the gear mechanism 1.

[0051] The first measurement signal detected by the torque sensor 2 is transmitted in the form of an analog signal via an analog line 8 to the analog-to-digital converter 6. In the analog-to-digital converter 6, the first measurement signal is converted from an analog signal to a digital signal.

[0052] The first measurement signal detected by the torque sensor 2 is transmitted in the form of a digital signal from the analog-to-digital converter 6 via a first line 9 to the microcontroller 7 . In addition, the second measurement signal detected by the Hall sensor 3 is transmitted to the microcontroller 7 via a second line 10 .

[0053] The first line 9 is a serial peripheral interface (SPI) system. The second line 10 is an inter-integrated circuit (I2C) system.

[0054] A microcontroller 7 is incorporated in the gear mechanism 1. Computer-aided calculations are performed using the microcontroller 7. The torque is calculated from the first measurement signal detected by the torque sensor 2. Furthermore, the drive shaft angle is calculated from the second measurement signal detected by the Hall sensor 3. Finally, the torque and the drive shaft angle are combined into one data set using the microcontroller 7.

[0055] The gear mechanism 1 is connected to a motor controller 5 arranged outside the gear mechanism by means of a single communication line 4. The communication line 4 is an EtherCAT system. Thus, a data set including torque and drive shaft angle is transmitted from the gear mechanism 1 to the motor controller 5.

[0056] In the motor controller 5 , the torque and the drive shaft angle can be used for further calculations.

[0057] All calculation times are within the typical range for robotic applications. All calculation and signal gear mechanisms meet the real-time requirements of industrial robots.

[0058] Figure 2 The method according to an embodiment of the present invention is schematically shown. The method according to this embodiment comprises the following steps:

[0059] First step S1 : determining a first measurement signal by means of the torque sensor 2 integrated in the gear mechanism 1 .

[0060] Second step S2 : determining a second measurement signal by means of the Hall sensor 3 integrated in the gear mechanism 1 .

[0061] Third step S3: Determine the torque T from the first measurement signal and determine the drive shaft angle A from the second measurement signal.

[0062] Fourth step S4 : transmitting the data set D comprising the torque T and the drive shaft angle A to a component 5 arranged outside the gear mechanism 1 by means of the single communication line 4 .

[0063] It should be understood that the order of the mentioned steps S1, S2, S3 and S4 may vary depending on the application. For example, the second measurement signal may be determined first by means of the Hall sensor 3 incorporated in the gear mechanism 1, and then the first measurement signal may be determined by means of the torque sensor 2 incorporated in the gear mechanism 1. The first step S1 and the second step S2 may also be performed simultaneously.

[0064] After the data set D has been transmitted, the torque T and the drive shaft angle A can be used for further calculations in the component 5 in a further step not shown in the embodiment.

[0065] Figure 3A A cutaway view of a gear mechanism 1 with an annular magnet 11 according to an embodiment of the present invention is shown. The gear mechanism 1 comprises a bearing 12, a seal 13 and a drive shaft 14. The annular magnet 11, the bearing 12 and the seal 13 are arranged on the drive shaft 14. The annular magnet 11 is arranged close to the bearing 12. The annular magnet 11 is designed as a permanent magnet.

[0066] Figure 3B An annular magnet 11 according to an embodiment of the present invention is shown. The annular magnet 11 is designed as a permanent magnet and has a negative pole 15 and a positive pole 16. When the annular magnet 11 rotates with the drive shaft 14, the magnetic field around the gear mechanism shaft 14 changes. Radially spaced fixed sensors such as Hall sensors can detect the magnetic flux density.

[0067] Figure 4 The gear mechanism 1 according to an embodiment of the present invention is shown in a side view. The gear mechanism 1 includes a circuit board 17. The analog-to-digital converter 6 and the microcontroller 7 are arranged on the circuit board 17. In addition, a communication unit 18 is arranged on the circuit board 17. A component of an EtherCAT, RS485 or SPI system can be used as the communication unit 18. The Hall sensor 3 is connected to the circuit board 17.

[0068] The ring magnet 11 generates a changing magnetic field as the gear mechanism shaft 14 rotates. The Hall sensor 3 detects the magnetic flux density having coordinates Bx and By.

[0069] The data set D may be stored in a buffer on the circuit board 17. The microcontroller 7 first receives the first measurement signal from the torque sensor 2 and the second measurement signal from the Hall sensor 3 and calculates the drive shaft angle A and the torque T. The microcontroller 7 stores the calculation results in the buffer in each calculation cycle (e.g., at a frequency of 5 kHz).

[0070] The data set D can be transmitted to the component 5 in a further step and further processed using the component 5. Advantageously, no additional decoder or encoder is required in the component 5 for further processing of the data set D. The torque T and the drive shaft angle A can be transmitted to a control loop, for example. In this regard, a control loop can be provided to control the motor and / or the speed. The control loop can also be designed to control the torque. Advantageously, a closed-loop control based on the control loop can thus be improved.

[0071] Figure 5 The measurement signals detected by the Hall sensor 3 and a method according to an embodiment of the invention for determining the drive shaft angle A are shown. The drive shaft angle A is determined by the magnetic flux density having the coordinates Bx and By.

[0072] The second measurement signal is recorded in the form of a magnetic flux density with coordinates Bx and By using the Hall sensor 3. The signal Y is then calculated using the coordinates Bx and By of the magnetic flux density:

[0073] Y = arctan2(Bx / By),

[0074] Among them, arctan2() is the square inverse tangent function.

[0075] In a further step, the drive shaft angle A is determined from the signal Y using a mathematical model f():

[0076] A=f(Y),

[0077] The mathematical model f() is a nonlinear regression model. The mathematical model f() is pre-trained using a training data set and conventional machine learning methods. The determination of the drive shaft angle A occurs on the microcontroller 7 .

[0078] In addition to its use in robots and passenger cars, the principles disclosed here can also be implemented in other fields of application, for example in drives for trucks, vans, motorcycles, axle drives and flight simulators.

[0079] The algorithms or computer programs required for the above functions can be advantageously implemented in whole or in part in the microcontroller 7, the torque sensor 2, the Hall sensor 3 and / or in another computer system connected to these devices. The computer system can be a local computer device (e.g., a personal computer, a notebook computer, a tablet computer or a mobile phone) having one or more processors and one or more storage devices, or can be a distributed computer system (e.g., a cloud computing system having one or more processors or one or more storage devices distributed at different locations, such as distributed at a local client and / or one or more remote server farms and / or data centers).

[0080] Depending on specific implementation requirements, exemplary embodiments of the present invention can be implemented using hardware or software.Some or all of the method steps can be performed by (or using) a hardware device such as a processor, a microprocessor, a programmable computer or an electronic circuit.

[0081] Although some aspects have been described in the context of an apparatus, it is apparent that these aspects also constitute a description of a corresponding method, wherein a block or apparatus corresponds to a method step or a function of a method step. Similarly, the various aspects described in the context of a method step also represent a description of a corresponding block or element or a property of a corresponding apparatus.

Claims

1. A method for determining a torque (T) and a drive shaft angle (A) of a gear mechanism (1), wherein: The method comprises the following method steps: determining a first measurement signal by means of a torque sensor (2) integrated in the gear mechanism (1); determining a second measurement signal by means of a Hall sensor (3) integrated in the gear mechanism (1); determining the torque (T) from the first measurement signal and determining the drive shaft angle (A) from the second measurement signal; and A data set (D) comprising the torque (T) and the drive shaft angle (A) is transmitted to a component (5) arranged outside the gear mechanism (1) by means of a single communication line (4).

2. The method according to claim 1, wherein: The data sets (D) are transmitted by means of a single communication protocol.

3. The method according to any one of claims 1 or 2, wherein: The drive shaft angle (A) is determined by means of the Hall sensor (3) integrated in the gear mechanism (1) and by means of a ring magnet integrated in the gear mechanism (1).

4. The method according to any one of claims 1 to 3, wherein: The second measurement signal comprises a magnetic flux density, and the drive shaft angle (A) is determined from the magnetic flux density by means of a mathematical model, preferably by means of a regression model, particularly preferably by means of a nonlinear regression model.

5. A sensor system comprising means for performing the method according to any one of claims 1 to 4.

6. A computer program comprising instructions which, when the program is executed by a computer, cause the computer to perform the method according to any one of claims 1 to 4.

7. A gear mechanism (1), comprising a torque sensor (2) incorporated in the gear mechanism (1), a Hall sensor (3) incorporated in the gear mechanism (1), and a communication line, wherein: The gear mechanism (1) is designed so that a data set (D) from the torque sensor (2) integrated in the gear mechanism (1) and the Hall sensor (3) integrated in the gear mechanism (1) can be transmitted to a component (5) arranged outside the gear mechanism (1) by means of a single communication line (4).

8. The gear mechanism (1) according to claim 7, wherein: The gear mechanism (1) comprises an annular magnet (11) incorporated in the gear mechanism (1).

9. The gear mechanism (1) according to any one of claims 7 or 8, wherein: The gear mechanism (1) comprises an analog-to-digital converter (6) integrated in the gear mechanism (1), a microcontroller (7) integrated in the gear mechanism (1) and / or a printed circuit board (17) integrated in the gear mechanism (1).

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