Six-dimensional force sensor measurement method and apparatus

Abstract

The application relates to the technical field of force sensor measurement, and discloses a six-dimensional force sensor measurement method and device, which comprises the following steps: acquiring multi-channel digital signals of strain bridge circuits of a six-dimensional force sensor at the same time; extracting feature parameters of the multi-channel digital signals, judging the current working state of the six-dimensional force sensor according to the feature parameters; performing multi-channel fusion on the multi-channel digital signals to obtain comprehensive force information; establishing a basic decoupling matrix according to the current temperature and current load information of the six-dimensional force sensor, and correcting the basic decoupling matrix through the current working state to obtain a corrected decoupling matrix; and performing decoupling calculation on the comprehensive force information through the corrected decoupling matrix to obtain six-dimensional force information. Through working condition sensing, the decoupling matrix is dynamically corrected in combination with temperature-load joint compensation, so that the measurement precision and dynamic response capability of the six-dimensional force sensor under complex dynamic working conditions are improved.

Description

Technical Field

[0001] This invention relates to the field of sensor measurement technology, specifically to a six-dimensional force sensor measurement method and apparatus. Background Technology

[0002] Six-dimensional force sensors are widely used in fields such as robotics, collaborative robots, automated assembly, precision machining, medical equipment, and scientific research testing. They are used to measure forces and torques in three directions in real time, providing key feedback information for robot force control, compliance control, collision detection, and precision operation.

[0003] Currently, six-dimensional force sensors typically employ multiple strain gauge circuits to measure force information in each direction, and then calculate the six-dimensional force and torque data through amplification circuits, analog-to-digital converters, and decoupling algorithms. Most existing systems use a fixed decoupling matrix to decouple the acquired signals from the six-dimensional force sensor, resulting in insufficient dynamic response capability of the force sensor under complex dynamic conditions. Summary of the Invention

[0004] This invention provides a six-dimensional force sensor measurement method and device to solve the problem of insufficient dynamic response capability of force sensors under complex dynamic working conditions.

[0005] In a first aspect, the present invention provides a six-dimensional force sensor measurement method, comprising: Acquire multi-channel analog signals from the strain bridge circuit of a six-dimensional force sensor at the same time, and convert the multi-channel analog signals into multi-channel digital signals; Extract the characteristic parameters of the multi-channel digital signal and determine the current working state of the six-dimensional force sensor based on the characteristic parameters; Multi-channel digital signals are fused to obtain comprehensive force information; A basic decoupling matrix is ​​established based on the current temperature and current load information of the six-dimensional force sensor, and the basic decoupling matrix is ​​corrected by the current working state to obtain the corrected decoupling matrix; By modifying the decoupling matrix, the comprehensive force information is decoupled and calculated to obtain six-dimensional force information.

[0006] In one optional implementation, feature parameters of the multi-channel digital signal are extracted, and the current operating state of the six-dimensional force sensor is determined based on these feature parameters, including: Calculate the total resultant force and total resultant torque of the multi-channel digital signals, and use the total resultant force and total resultant torque as comprehensive state variables; Extract the first time-domain feature parameter and the first frequency-domain feature parameter of the comprehensive state quantity, perform first-level working condition identification based on the first time-domain feature parameter and the first frequency-domain feature parameter, and determine whether the current working state is an abnormal state based on the result of the first-level working condition identification. When the condition is determined to be normal, the current working status is determined based on the result of the first-level working condition identification. When an abnormal state is determined, the second time-domain feature parameter and the second frequency-domain feature parameter of the multi-channel digital signal are extracted. The second-level working condition is identified based on the second time-domain feature parameter and the second frequency-domain feature parameter. The current working state is determined based on the second-level working condition identification result.

[0007] In one optional implementation, secondary operating condition identification is performed based on second time-domain feature parameters and second frequency-domain feature parameters, and the current operating state is determined based on the secondary operating condition identification result, including: The second time-domain feature parameter and the second frequency-domain feature parameter are compared with the state threshold of the corresponding working state, and the current working state is determined based on the comparison result. The current working states include static loading state, low-speed motion state, high-speed motion state, periodic vibration state, impact collision state, and abnormal disturbance state.

[0008] In one optional implementation, after extracting the characteristic parameters of the multi-channel digital signal and determining the current operating state of the six-dimensional force sensor based on the characteristic parameters, the method further includes: Generate analog and digital filter control parameters based on the current operating status; The cutoff frequency of the analog filter is adjusted by the analog filter control parameters, and the adjusted analog filter is used to filter the multi-channel analog signal. The filtering coefficients of the digital filter are adjusted by the digital filter control parameters, and the adjusted digital filter is used to filter multi-channel digital signals.

[0009] In one optional implementation, multi-channel digital signals are fused to obtain comprehensive force information, including: Sensitivity matrix for force and moment directions of strain gauge circuit; A comprehensive contribution evaluation index is established based on the sensitivity coefficients of the sensitivity matrix, the signal noise level, and the output stability. The fusion weights of the multi-channel digital signals are then calculated based on the comprehensive contribution evaluation index. The multi-channel digital signals are weighted and fused according to the fusion weights to obtain the comprehensive force information.

[0010] In one alternative implementation, the formula for calculating the basic decoupling matrix is:

[0011] in, Based on the decoupling matrix, This is the initial decoupling matrix. This is the temperature influence coefficient matrix. The current temperature. To calibrate the temperature, This is the load influence coefficient matrix. For current load information, To calibrate load information.

[0012] In one optional implementation, the basic decoupling matrix is ​​modified based on the current operating state to obtain a modified decoupling matrix, including: When the current working state is static loading state and low-speed motion state, the corrected decoupling matrix is ​​calculated using a first preset formula, where the first preset formula is:

[0013] in, This is the final decoupling matrix. The basic decoupling matrix; When the current operating state is high-speed motion, the corrected decoupling matrix is ​​calculated using a second preset formula, where the second preset formula is:

[0014] in, For dynamic enhancement coefficients; When the current operating state is a periodic vibration state, the corrected decoupling matrix is ​​calculated using the third preset formula, where the third preset formula is:

[0015] in, This is the frequency correction factor. The vibration frequency, This is the frequency correction matrix; When the current working state is an impact collision state, the corrected decoupling matrix is ​​calculated using the fourth preset formula, where the fourth preset formula is:

[0016] in, For impact enhancement coefficient, This is the dynamic response correction matrix; When the current operating state is an abnormal high temperature state, the corrected decoupling matrix is ​​calculated using the fifth preset formula, where the fifth preset formula is:

[0017] in, This is the temperature compensation coefficient. The current temperature. To calibrate the temperature, This is the temperature correction matrix.

[0018] In one optional implementation, the formula for calculating the six-dimensional force information is:

[0019] in, For six-dimensional force information, To correct the decoupling matrix, For comprehensive power information, This is the zero-point bias function; Before performing decoupling calculations on the comprehensive force information based on the modified decoupling matrix to obtain the six-dimensional force information, the following steps are also included: A zero-point bias function is established based on the current temperature, where the zero-point bias function is:

[0020] in, For zero-point bias function, To calibrate the zero point, This is the zero-point temperature drift coefficient. The current temperature. For calibration temperature.

[0021] Secondly, the present invention provides a six-dimensional force sensor measuring device, comprising: a multi-channel synchronous acquisition module and a digital processing module. The multi-channel synchronous acquisition module is used to acquire multi-channel analog signals output by the strain bridge circuit of the six-dimensional force sensor at the same time and output multi-channel digital signals. The digital processing module is used to execute a six-dimensional force sensor measuring method as described in the first aspect above or any corresponding embodiment.

[0022] In one optional implementation, the multi-channel synchronous acquisition module includes: A multi-channel synchronous acquisition unit includes multiple strain bridges disposed on the six-dimensional force sensor, used to synchronously acquire analog signals output by multiple strain bridges in the six-dimensional force sensor, wherein the multi-channel analog signals include analog signals output by multiple strain bridges; The signal conditioning unit includes an analog filter for low-noise instrumentation amplification and programmable gain adjustment of analog signals to improve the amplitude and signal-to-noise ratio of the analog signals. The digital signal unit includes a digital filter, which is used to convert the analog signal processed by the signal conditioning unit into a digital signal, filter the digital signal through the digital filter, and output a multi-channel digital signal.

[0023] The present invention has at least the following beneficial effects: This invention provides a six-dimensional force sensor measurement method and device. By acquiring multi-channel digital signals and extracting feature parameters to identify the current working state, subsequent processing can be adaptively adjusted for different working conditions. A basic decoupling matrix is ​​established based on the current temperature and load and corrected in combination with the current working state, so that the decoupling matrix can be dynamically updated with changes in environment and working conditions. Finally, the decoupling matrix is ​​corrected to perform decoupling calculation on the fused comprehensive force information, thereby improving the measurement accuracy, dynamic response capability and long-term stability of the six-dimensional force sensor under complex dynamic working conditions. Attached Figure Description

[0024] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0025] Figure 1 This is a flowchart illustrating a six-dimensional force sensor measurement method according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the current working state determination process of the six-dimensional force sensor measurement method according to an embodiment of the present invention; Figure 3 This is a schematic diagram of a six-dimensional force sensor measuring device according to an embodiment of the present invention; Figure 4 This is a schematic diagram of the specific structure of the digital processing module of the six-dimensional force sensor measuring device according to an embodiment of the present invention; Figure 5 This is another structural schematic diagram of a six-dimensional force sensor measuring device according to an embodiment of the present invention. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0027] It is understood that before using the technical solutions disclosed in the various embodiments of the present invention, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in the present invention and their authorization should be obtained in accordance with relevant laws and regulations through appropriate means.

[0028] Six-dimensional force sensors are widely used in fields such as robotics, collaborative robots, automated assembly, precision machining, medical equipment, and scientific research testing. They are used to measure forces and torques in three directions in real time, providing key feedback information for robot force control, compliance control, collision detection, and precision operation.

[0029] Currently, six-dimensional force sensors typically employ multiple strain gauge circuits to measure force information in each direction, and then calculate the six-dimensional force and torque data through amplification circuits, analog-to-digital converters, and decoupling algorithms. Most existing systems use a fixed decoupling matrix to decouple the acquired signals from the six-dimensional force sensor, resulting in insufficient dynamic response capability of the sensor under complex dynamic conditions. Most systems use digital filters with fixed parameters for data processing, and these filter parameters remain constant throughout the measurement process. However, when the robot performs different tasks such as static grasping, high-speed motion, and collision detection, fixed filter parameters are difficult to balance noise immunity and dynamic response speed, which can easily lead to measurement delays, signal distortion, or noise amplification. Existing six-dimensional force sensors typically filter and process the signals of each bridge circuit separately, lacking joint analysis between the channels. Due to the mechanical coupling and dynamic correlation between the components of the six-dimensional force, relying solely on single-channel data can easily lead to misinterpreting abnormal disturbances as real loads, thus limiting measurement stability and anti-interference capabilities.

[0030] To at least address one of the aforementioned problems, this embodiment provides a six-dimensional force sensor measurement method, such as... Figure 1 As shown, it includes: Step S101: Obtain the multi-channel analog signal of the strain bridge circuit of the six-dimensional force sensor at the same time, and convert the multi-channel analog signal into a multi-channel digital signal.

[0031] Specifically, the multi-channel digital signals from the six-dimensional force sensor are acquired by the multi-channel synchronous acquisition module. These multi-channel digital signals include digital signals output from multiple bridge circuits simultaneously. Strain gauge bridges are mounted on the elastic body of the six-dimensional force sensor. Each strain gauge bridge consists of multiple strain gauges bonded to the surface of the elastic body, connected in a Wheatstone bridge structure. The resistance changes of each strain gauge correspond to the output of differential voltage signals reflecting the magnitude of the load in each direction, thus achieving synchronous sensing of loads in different directions on the six-dimensional force sensor. The weak differential voltage signals from the multiple strain gauge bridges, i.e., multi-channel analog signals, are acquired by the multi-channel synchronous acquisition module 201 and converted into multi-channel digital signals.

[0032] Step S102: Extract the feature parameters of the multi-channel digital signal and determine the current working state of the six-dimensional force sensor based on the feature parameters.

[0033] Specifically, a time-sliding window is established for the multi-channel digital signal, and time-domain and frequency-domain characteristic parameters of the multi-channel digital signal are extracted within the window. These characteristic parameters include force change rate, peak value, root mean square value, spectral energy, and dominant frequency. The robot's static, dynamic, vibration, and collision states are determined by analyzing these characteristic parameters.

[0034] Step S103: Multi-channel fusion of multi-channel digital signals to obtain comprehensive force information.

[0035] Specifically, the multi-channel digital signal includes digital information from multiple strain bridge channels. The digital information from multiple strain bridge channels is combined into a comprehensive force information, which contains the force and torque information of multiple bridge channels in the multi-channel digital signal.

[0036] Step S104: Establish a basic decoupling matrix based on the current temperature and current load information of the six-dimensional force sensor, and correct the basic decoupling matrix through the current working state to obtain the corrected decoupling matrix.

[0037] Specifically, in practical use, changes in ambient temperature and load magnitude both affect the output characteristics of the six-dimensional force sensor. Temperature changes cause variations in strain gauge resistance and elastic modulus, leading to zero-point drift and sensitivity drift. Increased load may cause nonlinear deformation of the elastic body, altering the coupling relationship between channels. Therefore, the decoupling matrix needs to be corrected based on the current temperature and load. In this step, a basic decoupling matrix is ​​constructed by adding current temperature and load information variables to the original fixed decoupling matrix. This basic decoupling matrix is ​​dynamically updated as the current temperature and load change, adapting the original fixed decoupling matrix to the current environmental conditions and load state. The basic decoupling matrix is ​​then corrected and updated according to different operating states of the six-dimensional force sensor, resulting in a corrected decoupling matrix. Finally, the corrected decoupling matrix is ​​used to decouple and calculate the comprehensive force information to obtain the six-dimensional force information, reducing the coupling error between the six-dimensional force and torque.

[0038] Step S105: Decouple the comprehensive force information by correcting the decoupling matrix to obtain six-dimensional force information.

[0039] Specifically, decoupling calculation is a mathematical process that separates the multiple coupled components in the composite force information into independent directional components. Mechanical coupling is prevalent between the strain bridges of a six-dimensional force sensor; that is, a load in a single direction will generate output responses on multiple bridges. Therefore, the outputs of each bridge cannot be directly used as the force and torque values ​​in the corresponding direction. Decoupling calculation is needed to eliminate crosstalk between directions. In this step, by modifying the decoupling matrix to perform decoupling calculation on the composite force information, the force and torque components in each independent direction can be separated from the multi-channel fused signal, ultimately obtaining the six-dimensional force information.

[0040] This embodiment acquires multi-channel digital signals from multiple strain bridge circuits at the same time and extracts feature parameters to identify the current working state, enabling subsequent processing to adaptively adjust to different working conditions. A basic decoupling matrix is ​​established based on the current temperature and load and corrected in combination with the current working state, allowing the decoupling matrix to be dynamically updated with changes in environment and working conditions. Finally, the decoupling matrix is ​​corrected to perform decoupling calculations on the fused comprehensive force information, improving the measurement accuracy, dynamic response capability, and long-term stability of the six-dimensional force sensor under complex dynamic working conditions.

[0041] In one embodiment, step S102, extracting feature parameters of the multi-channel digital signal and determining the current working state of the six-dimensional force sensor based on the feature parameters, includes: Step S1021: Calculate the total resultant force and total resultant torque of the multi-channel digital signals, and use the total resultant force and total resultant torque as comprehensive state variables.

[0042] Specifically, the multi-channel digital signal of the six-dimensional force sensor contains signals in three force directions and three torque directions. In this step, the signal values ​​in the three force directions are combined to calculate a total resultant force value, and the signal values ​​in the three torque directions are combined to calculate a total resultant torque value. These total resultant force and total resultant torque values ​​are then used as comprehensive state variables. The six-dimensional data of the multi-channel digital signal is converted into two-dimensional data of the comprehensive state variables, and the preliminary identification of the six-dimensional sensor's operating state is performed using these comprehensive state variables.

[0043] For example, the multi-channel digital signal values ​​of the six-dimensional force sensor are divided into a total resultant force value and a total torque value. These values ​​are then used to make a preliminary judgment on the working condition. The formula for calculating the total resultant force value is: ,in, This is the total resultant force value of the multi-channel digital signals. , , The digital signal values ​​for the X, Y, and Z axial force directions of the multi-channel digital signal; the formula for calculating the total resultant torque is: ,in This represents the total resultant torque value of the multi-channel digital signals. , , These are the digital signal values ​​for the X, Y, and Z axis torque direction channels of the multi-channel digital signal. The comprehensive state variables are: .

[0044] Step S1022: Extract the first time-domain feature parameter and the first frequency-domain feature parameter of the comprehensive state quantity, perform first-level working condition identification based on the first time-domain feature parameter and the first frequency-domain feature parameter, and determine whether the current working state is an abnormal state based on the result of the first-level working condition identification.

[0045] Specifically, a sliding time window is used to extract time-series data of the comprehensive state variables, and the first time-domain feature parameters and the first frequency-domain feature parameters are extracted within the window. The window length can be set according to the system's computing power and response speed requirements. Based on the first time-domain feature parameters and the first frequency-domain feature parameters, a first-level operating condition is identified based on a preset first-level judgment threshold to determine whether there is an abnormal state in the current operating state. The first-level judgment threshold includes the rate of change threshold, the peak-to-peak value threshold, and the high-frequency energy ratio threshold, etc.

[0046] Step S1023: When the condition is determined to be normal, the current working status is determined based on the result of the first-level working condition identification.

[0047] Step S1024: When an abnormal state is determined, the second time-domain feature parameters and the second frequency-domain feature parameters of each channel are extracted from the multi-channel digital signal. Second-level working condition identification is performed based on the second time-domain feature parameters and the second frequency-domain feature parameters. The current working state is determined based on the second-level working condition identification results.

[0048] Specifically, when the result of the first-level operating condition identification is normal, the current operating status is output based on the result of the first-level operating condition identification. When the result of the first-level operating condition identification is abnormal, the second-level operating condition identification is further performed.

[0049] The second time-domain feature parameters include: The root mean square (RMS) value represents the overall energy level of the force signal within a certain time window, reflecting the current load intensity. It is used to determine the overall intensity of the force signal. The calculation formula is:

[0050] in, The root mean square value, For window length, For the first in the window The signal values ​​at each sampling point; The maximum rate of change, representing the change in force signal per unit sampling time, is used to determine the collision state of the sensor. The calculation formula is:

[0051] in, For the maximum rate of change, This represents the signal change between two adjacent sampling points; Peak-to-peak value represents the maximum range of force signal variation within a time window. It is used to determine vibration amplitude and dynamic load magnitude, and helps distinguish between stable loading and periodic disturbances. The calculation formula is:

[0052] in, Peak-to-peak value These represent the maximum and minimum values ​​of the signal within the window, respectively.

[0053] The second frequency domain feature parameters are obtained by extracting the signal within the window through a fast Fourier transform. These include the frequency domain features of the force phase and the frequency domain features of the torque direction. The formula for calculating the frequency domain features is as follows:

[0054] in, The frequency number indicates the number of frequencies in the spectrum. Discrete frequency points, The time sampling point index indicates the number of sampling points within the window. Data points at each sampling time, For window length, Indicates the first Collected at each sampling time The value of directional force, for Similarly, the frequency domain result after the fast Fourier transform of the directional force signal can be obtained. Frequency domain results of the directional force signal after Fast Fourier Transform and Frequency domain results of the directional torque signal after Fast Fourier Transform.

[0055] The second frequency domain characteristic parameters include: Clock speed, calculated using the following formula:

[0056]

[0057] in, The formula for calculating the spectral energy is: , For maximum energy frequency index, Main frequency, Sampling frequency, For Fast Fourier Points; The high-frequency energy ratio is calculated using the following formula:

[0058] in, The total energy is calculated using the following formula: , For high frequency, the calculation formula is: , This is the discrete frequency index corresponding to the high-frequency cutoff frequency.

[0059] The spectral centroid is calculated using the following formula:

[0060] in, For the spectral centroid, For the first Each frequency point, and .

[0061] This embodiment employs a primary operating condition identification and a secondary operating condition identification. In the primary operating condition identification, the total resultant force value and the total resultant torque value are calculated as comprehensive state variables, reducing the six-dimensional data to two dimensions for analysis, which significantly reduces the computational load of feature extraction. When an anomaly is identified in the primary operating condition identification, the secondary operating condition fine identification is initiated, extracting time-domain and frequency-domain features from each channel for accurate identification, ensuring efficient utilization of computing resources and ensuring the accuracy of identification under abnormal operating conditions.

[0062] In one embodiment, step S1024, which involves identifying a secondary operating condition based on the second time-domain feature parameters and the second frequency-domain feature parameters, and determining the current operating state based on the secondary operating condition identification result, includes: The second time-domain feature parameter and the second frequency-domain feature parameter are compared with the state threshold of the corresponding working state, and the current working state is determined according to the comparison result. The current working state includes static loading state, low-speed motion state, high-speed motion state, periodic vibration state, impact collision state and abnormal disturbance state.

[0063] Specifically, the second time-domain feature parameter and the second frequency-domain feature parameter are the data feature parameters of each strain bridge channel in the multi-channel digital signal, and the state threshold of the working state is the value range of each data when the six-dimensional force sensor is in this working state. By comparing the second time-domain feature parameter and the second frequency-domain feature parameter with the state threshold of the corresponding working state, it is possible to determine whether the feature parameters of the current multi-channel digital signal fall within the state threshold range of the corresponding working state, and thus determine the current working state of the six-dimensional force sensor.

[0064] For example, such as Figure 2 As shown, the time-domain characteristics, frequency-domain characteristics, and judgment rules corresponding to each operating condition are as follows: Static loading state: Its time-domain characteristics are characterized by a stable, low root mean square value, a small maximum rate of change, and a small peak-to-peak value; its frequency-domain characteristics are characterized by a low proportion of high-frequency energy and a low spectral centroid. The determination rule is: maximum rate of change. Less than the first rate of change threshold And peak-to-peak value Less than the first peak value threshold And the high-frequency energy ratio Less than the first high-frequency energy ratio threshold If so, it is determined to be in a static loading state.

[0065] Low-speed motion: Its time-domain characteristics are characterized by slow changes in the root mean square value, a moderate maximum rate of change, and a moderate peak-to-peak value; its frequency-domain characteristics are characterized by predominantly low-frequency energy and a low spectral centroid. The criterion is: maximum rate of change. Between the first rate of change threshold Second rate of change threshold Between, and the spectral centroid Less than the first spectral centroid threshold And the high-frequency energy ratio Less than the second high-frequency energy ratio threshold If so, it is determined to be a low-speed motion state.

[0066] High-speed motion: Its time-domain characteristics are characterized by a large root mean square value, an increased maximum rate of change, and continuous change; its frequency-domain characteristics are characterized by increased mid-to-high frequency energy and a higher spectral centroid. The determination rule is: maximum rate of change. Greater than the second rate of change threshold D2, and the spectral centroid Greater than the first spectral centroid threshold If the spectral peak is unstable, it is determined to be a high-speed motion state.

[0067] Periodic vibration state: Its time-domain characteristics are characterized by a relatively obvious peak-to-peak value, and the signal changes are periodic; its frequency-domain characteristics are characterized by a significant dominant frequency peak and concentrated spectral energy. The determination rule is: peak-to-peak value... Greater than the first peak value threshold Furthermore, the ratio of energy at the dominant frequency to the total energy... Greater than the first energy ratio threshold And main frequency If it is stable, it is determined to be in a periodic oscillation state.

[0068] Impact collision state: Its time-domain characteristics are characterized by an extremely large maximum rate of change, a sudden change in peak value, and a large peak-to-peak value; its frequency-domain characteristics are characterized by a rapid increase in the proportion of high-frequency energy and a broadened spectrum. The determination rule is: maximum rate of change. Greater than the third rate of change threshold And the high-frequency energy ratio Greater than the third high-frequency energy ratio threshold And the duration of the abnormality is less than the first time threshold. If so, it is determined to be an impact collision state.

[0069] Abnormal disturbance state: Its time-domain characteristics are characterized by an abnormally high root-mean-square value without a clear pattern; its frequency-domain characteristics are characterized by increased high-frequency energy, dispersed spectrum, and no stable dominant frequency. The judgment rule is: the proportion of high-frequency energy. Greater than the fourth high-frequency energy ratio threshold Furthermore, the ratio of energy at the dominant frequency to the total energy... Less than the second energy ratio threshold And the spectral centroid If the fluctuation is abnormal, it is determined to be an abnormal disturbance state.

[0070] This embodiment compares the second time-domain feature parameter and the second frequency-domain feature parameter with the state threshold corresponding to each working condition, thereby accurately classifying the current working state and achieving fine classification of the working state of the six-dimensional force sensor.

[0071] In one embodiment, step S102, after extracting the feature parameters of the multi-channel digital signal and determining the current working state of the six-dimensional force sensor based on the feature parameters, further includes: Step S1025: Generate analog filter control parameters and digital filter control parameters based on the current working state.

[0072] Specifically, based on the characteristics of the working state of the six-dimensional force sensor, corresponding analog and digital filter control parameters are generated. By adjusting the corresponding filters through the analog and digital filter control parameters, the multi-channel analog and multi-channel digital signals are filtered, so that the filtering process can work in coordination with the working state.

[0073] For analog filters, the digital processing module controls the analog filter to change its cutoff frequency, achieving adaptive optimization between measurement accuracy and dynamic response. The formula for calculating the cutoff frequency of the analog filter is:

[0074] in, To simulate the filter cutoff frequency, This is the internal scaling factor of the chip. This refers to the filter clock frequency; For digital filters, an infinite impulse response adaptive low-pass filter is used as the basic filtering method, and a finite impulse response notch filter based on fast Fourier transform spectral analysis is introduced to address periodic interference, achieving broadband noise suppression and specific frequency interference suppression. Under normal conditions, the infinite impulse response adaptive low-pass filter is used as the basic filtering method, and the calculation formula is:

[0075] in, This is the current output. The output from the previous moment. For the current input, The input from the previous moment, The current time number. Forward coefficients, For the feedback coefficient, by changing and To change the cutoff frequency.

[0076] During vibration, a finite impulse response notch filter based on fast Fourier transform spectral analysis is added, and the calculation formula is as follows:

[0077] in, This is the current output. These are the filter coefficients. For historical input values, by changing To achieve different filtering characteristics.

[0078] Step S1026: Adjust the cutoff frequency of the analog filter by the analog filter control parameters, and then filter the multi-channel analog signal using the adjusted analog filter. Step S1027: Adjust the filter coefficient of the digital filter through the digital filter control parameters, and then use the adjusted digital filter to filter the multi-channel digital signal.

[0079] Specifically, in the static loading state, the cutoff frequency of the analog filter is reduced, and the digital filter adopts an infinite impulse response adaptive low-pass filter to reduce the cutoff frequency of the digital filter and increase the smoothness of the filter coefficients. In low-speed motion, the cutoff frequency of the analog filter is set to medium, and the digital filter adopts an infinite impulse response adaptive low-pass filter with the cutoff frequency set to medium. In high-speed motion, the cutoff frequency of the analog filter is increased, and the digital filter adopts an infinite impulse response high-speed response filter, which increases the cutoff frequency of the digital filter. During periodic vibration, the analog filter maintains the analog bandwidth to cover the effective signal, while the digital filter uses finite impulse response notch filtering based on fast Fourier transform spectrum analysis. The vibration dominant frequency is calculated through fast Fourier transform, and the center frequency of the finite impulse response notch filter is set as the vibration dominant frequency to suppress the periodic vibration frequency at a fixed point. During impact collision, the analog filter raises the cutoff frequency to the maximum allowable bandwidth, while the digital filter uses an infinite impulse response low-order high-speed filter to increase the digital cutoff frequency. In the event of abnormal disturbances, the analog filter lowers its cutoff frequency, and the digital filter uses a strong infinite impulse response low-pass filter to lower the digital cutoff frequency. If necessary, a notch filter is added to suppress abnormal frequency bands.

[0080] This invention generates analog and digital filter control parameters based on the current operating state, and adjusts the cutoff frequency of the analog filter and the filter coefficient of the digital filter respectively, thereby achieving coordinated filtering in the analog and digital domains and enhancing the adaptive optimization of noise suppression and dynamic response capabilities under different operating states.

[0081] In one embodiment, step S103 involves multi-channel fusion of the multi-channel digital signals to obtain comprehensive force information, including: Step S1031: Calibrate the sensitivity matrix of the force and moment directions of the strain bridge circuit.

[0082] Specifically, standard loads of known magnitude in each direction were applied to the six-dimensional force sensor, and the output response of each strain gauge circuit was recorded. Using multiple sets of calibration data, a sensitivity coefficient matrix for each strain gauge circuit to different force and torque directions was established. The sensitivity matrix reflects the mapping relationship between the output signal of each circuit and the load in each direction.

[0083] Step S1032: Establish a comprehensive contribution evaluation index based on the sensitivity coefficient of the sensitivity matrix, the signal noise level, and the output stability; calculate the fusion weight of the multi-channel digital signals based on the comprehensive contribution evaluation index.

[0084] Specifically, the sensitivity coefficient is the output data calibrated by the sensitivity matrix, the signal noise level is the fluctuation degree of the multi-channel digital signal under static conditions, and the output stability is the signal drift degree of the multi-channel digital signal under long-term static monitoring. A comprehensive contribution evaluation index is established by using the sensitivity coefficient, signal noise level, and output stability. Based on the comprehensive contribution evaluation index of each channel, the fusion weight of each channel is calculated by normalization. After normalization, the fusion weight of each channel is 1.

[0085] For example, the sensitivity coefficient is obtained by fitting the output data calibrated by the sensitivity matrix using the least squares method; the signal noise level can be characterized by the variance or standard deviation of the statically acquired data; and the output stability can be evaluated by the drift of the statically monitored data over a long period of time.

[0086] Step S1033: The multi-channel digital signals are weighted and fused according to the fusion weights to obtain the comprehensive force information.

[0087] Specifically, the digital signal value of each channel is multiplied by its corresponding fusion weight to obtain the weighted signal value of each channel. At each sampling time, the weighted signal values ​​of all channels are fused to obtain the fused comprehensive force information at that time. Through this weighted fusion process, channels with high sensitivity, low noise, and good stability contribute more to the fusion result, while channels with lower sensitivity or higher noise contribute less, thus giving the fused comprehensive force information a higher signal-to-noise ratio and better stability.

[0088] This embodiment establishes a comprehensive contribution evaluation index by calibrating the sensitivity matrix of the strain bridge circuit and comprehensively considering the sensitivity coefficient, signal noise level and output stability of each channel. Based on the comprehensive contribution evaluation index, the fusion weight of each channel is calculated, thereby realizing the weighted fusion of multi-channel digital signals and improving the signal-to-noise ratio and measurement reliability of the fused comprehensive force information.

[0089] In one embodiment, step S104, the formula for calculating the basic decoupling matrix is:

[0090] in, Based on the decoupling matrix, This is the initial decoupling matrix. This is the temperature influence coefficient matrix. The current temperature. To calibrate the temperature, This is the load influence coefficient matrix. For current load information, To calibrate load information.

[0091] Specifically, the initial decoupling matrix The sensitivity matrix was obtained using the least squares method; the temperature influence coefficient matrix... This is used to characterize the degree of influence of temperature changes on each element of the decoupling matrix. During the sensor calibration phase, calibration experiments are conducted at multiple different temperature points to obtain the decoupling matrix corresponding to each temperature point. Then, the calibration temperature is used as the reference temperature. Using this as a baseline, a linear fit is performed on the decoupling matrix as a function of temperature to obtain the temperature influence coefficient matrix. Load influence coefficient matrix This is used to characterize the degree of influence of load changes on each element of the decoupling matrix. During the sensor calibration phase, calibration experiments are conducted at multiple different load points to obtain the decoupling matrix corresponding to each load point, and then the calibration load is used... Using this as a baseline, a linear fit is performed on the decoupling matrix as a function of load to obtain the load influence coefficient matrix. This matrix reflects the rate of change of each element of the decoupling matrix for each unit change in load.

[0092] This embodiment establishes a basic decoupling matrix based on temperature and load, and combines the initial decoupling matrix with the temperature influence coefficient matrix and the load influence coefficient matrix. This enables the basic decoupling matrix to be dynamically adjusted in real time according to the current temperature and load, overcoming the shortcomings of traditional fixed decoupling matrices that cannot adapt to changes in ambient temperature and load. It effectively compensates for the influence of temperature-induced sensitivity drift and load-induced nonlinear deformation on decoupling accuracy.

[0093] In one embodiment, step S104, which modifies the basic decoupling matrix based on the current working state to obtain a modified decoupling matrix, includes: Step S1041: When the current working state is static loading state and low-speed motion state, calculate the corrected decoupling matrix using the first preset formula, wherein the first preset formula is:

[0094] in, This is the final decoupling matrix. It is the basic decoupling matrix.

[0095] Specifically, when the current working state is static loading, only temperature compensation and static load compensation are needed, and the basic decoupling matrix can meet the accuracy requirements. When the current working state is low-speed motion, the basic compensation can meet the accuracy requirements without external correction, and the basic decoupling matrix can meet the accuracy requirements.

[0096] Step S1042: When the current working state is high-speed motion, calculate the corrected decoupling matrix using the second preset formula, where the second preset formula is:

[0097] in, This is the dynamic enhancement coefficient.

[0098] Specifically, when operating in a high-speed motion state, in order to enhance the dynamic response capability to rapidly changing signals, a dynamic enhancement correction term is added to the basic decoupling matrix: , It reflects the deviation of the current state from the initial state.

[0099] Step S1043: When the current working state is a periodic vibration state, calculate the corrected decoupling matrix using the third preset formula, where the third preset formula is:

[0100] in, This is the frequency correction factor. The vibration frequency, This is the frequency correction matrix.

[0101] Specifically, when the current operating state is a periodic vibration state, considering the influence of the vibration frequency on the coupling characteristics, a frequency correction term is added to the basic decoupling matrix: Frequency correction matrix It reflects the influence characteristics of vibration frequency on the decoupling matrix, which can be obtained through calibration experiments under vibration at different frequencies.

[0102] Step S1044: When the current working state is an impact collision state, calculate the corrected decoupling matrix using the fourth preset formula, where the fourth preset formula is:

[0103] in, For impact enhancement coefficient, This is the dynamic response correction matrix.

[0104] Specifically, when the current operating state is an impact collision state, in order to respond quickly to the impact load, a high dynamic response matrix is ​​added to the basic decoupling matrix: , The dynamic response correction matrix is ​​obtained in advance through impact load calibration experiments.

[0105] Step S1045: When the current working state is a high-temperature abnormal state, calculate the corrected decoupling matrix using the fifth preset formula, where the fifth preset formula is:

[0106] in, This is the temperature compensation coefficient. The current temperature. To calibrate the temperature, This is the temperature correction matrix.

[0107] Specifically, when the current operating state is a high-temperature abnormal state within an abnormal disturbance state, the temperature compensation of the basic decoupling matrix is ​​enhanced by adding a temperature compensation correction term to the basic decoupling matrix: .

[0108] This embodiment modifies the basic decoupling matrix according to the current working state, enabling the decoupling matrix to be further adjusted with changes in working conditions. Different correction strategies are adopted for different working conditions, so that the decoupling matrix can optimally adapt to various actual working scenarios. This significantly improves the six-dimensional force decoupling accuracy and dynamic response capability across the entire working condition range, overcoming the technical defect that a single fixed decoupling matrix cannot meet the needs of different working conditions.

[0109] In one embodiment, step S105, the formula for calculating the six-dimensional force information is:

[0110] in, For six-dimensional force information, To correct the decoupling matrix, For comprehensive power information, This is the zero-point bias function.

[0111] Specifically, the temperature sensor in the measuring device detects the current operating temperature in real time. The data is then transmitted to the digital processing module, which calculates the zero-point offset value at the current temperature in real time based on the aforementioned zero-point offset function. Then, decoupling calculations are performed to separate the multidimensional coupled signal into independent force and torque components. The entire compensation and solution process can be executed in real time during each sampling period, ensuring that the six-dimensional force information output at each moment has eliminated zero-point drift caused by temperature.

[0112] Before performing decoupling calculations on the comprehensive force information based on the modified decoupling matrix to obtain the six-dimensional force information, the following steps are also included: A zero-point bias function is established based on the current temperature, where the zero-point bias function is:

[0113] in, For zero-point bias function, To calibrate the zero point, This is the zero-point temperature drift coefficient. The current temperature. For calibration temperature.

[0114] Specifically, temperature changes not only cause drift in the sensitivity coefficients of the decoupling matrix but also lead to a shift in the zero-point output of the strain gauge circuits. Even without any applied load, temperature changes will cause each strain gauge circuit to produce non-zero output values. This zero-point drift is superimposed on the actual force signal, causing measurement errors. Therefore, zero-point temperature drift compensation is necessary before decoupling calculations. Zero-point temperature drift coefficient. The zero-point calibration was obtained through zero-point calibration experiments at different temperatures.

[0115] The zero-point bias function of the six-dimensional force information calculation formula in this embodiment can eliminate zero-point drift caused by temperature changes, ensuring zero-point stability. The integrated force information fuses the contributions of multiple channels, exhibiting higher stability than single-channel signals. The corrected decoupling matrix eliminates coupling errors between forces and torques in various directions, enabling the calculation results to accurately reflect the force and torque components in each independent direction. By establishing the zero-point bias function and constructing the six-dimensional force information calculation formula using the zero-point bias function, the corrected decoupling matrix, and the integrated force information, the three components work together to complete the conversion from fused signals to high-precision six-dimensional force information. This ensures high-precision output of six-dimensional force information across all operating conditions and temperature ranges, effectively improving the sensor's measurement accuracy, environmental adaptability, and long-term stability.

[0116] This embodiment provides a six-dimensional force sensor measurement device, such as... Figure 3 As shown, it includes: a multi-channel synchronous acquisition module 201 and a digital processing module 202. The multi-channel synchronous acquisition module 201 is used to acquire the multi-channel analog signals output by the strain bridge of the six-dimensional force sensor at the same time and output the multi-channel digital signals. The digital processing module 202 is used to execute a six-dimensional force sensor measurement method as described in the above embodiment. Optional, such as Figure 4 As shown, the digital processing module 202 includes: The signal receiving unit 2021 is used to acquire multi-channel digital signals from the strain bridge circuit of the six-dimensional force sensor at the same time. The signal receiving unit 2021 is connected to the six-dimensional force sensor and receives the analog signals output from the multiple strain bridge circuits of the six-dimensional force sensor, i.e., multi-channel analog signals, and preprocesses the multi-channel analog signals to convert them into multi-channel digital signals. The signal receiving unit 2021 is also connected to the multi-channel synchronous acquisition module 201 and receives the multi-channel digital signals output by the multi-channel synchronous acquisition module 201.

[0117] The operating condition identification unit 2022 is used to extract feature parameters of the multi-channel digital signals and determine the current operating state of the six-dimensional force sensor based on these feature parameters. The operating condition identification unit 2022 extracts time-domain and frequency-domain feature parameters of the multi-channel digital signals, including force change rate, peak value, root mean square value, spectral energy, and dominant frequency, and determines the current operating state of the six-dimensional force sensor based on these feature parameters.

[0118] The dynamic filtering unit 2023, connected to the working condition identification unit 2022, is used to adjust the analog and digital filtering parameters according to the current working state of the six-dimensional force sensor identified by the working condition identification unit 2022; adjust the cutoff frequency of the analog filter in the signal conditioning unit of the multi-channel synchronous acquisition module 201 according to the analog filter, and filter the multi-channel analog signals acquired by the multi-channel synchronous acquisition module 201 through the adjusted analog filter; and adjust the filtering coefficients, cutoff frequency, and filtering structure of the digital filter in the digital signal unit of the multi-channel synchronous acquisition module 201 according to the digital filtering parameters, and filter the multi-channel digital signals through the adjusted digital filter.

[0119] The multi-channel fusion unit 2024 is used to fuse multi-channel digital signals to obtain comprehensive force information. The multi-channel fusion unit 2024 is connected to the dynamic filtering unit 2023. It assigns fusion weights based on the contribution of each channel of the filtered multi-channel digital signal, and performs fusion calculations on the signals of each channel of the multi-channel digital signal according to the fusion weights to obtain stable comprehensive force information.

[0120] The adaptive decoupling unit 2025 is used to establish a basic decoupling matrix based on the current temperature and load information of the six-dimensional force sensor, and to correct the basic decoupling matrix according to the current operating state to obtain a corrected decoupling matrix. Specifically, the adaptive decoupling unit 2025 is connected to the multi-channel fusion unit 2024. The adaptive decoupling unit 2025 is used to acquire the temperature and load change information of the six-dimensional force sensor, and to construct a basic decoupling matrix by adding the current temperature and load information variables to the original fixed decoupling matrix. It then corrects and updates the basic decoupling matrix according to different operating states of the six-dimensional force sensor to obtain the corrected decoupling matrix, which can reduce... The coupling error between them, where, This refers to the translational force exerted by the six-dimensional force sensor in three axial directions. This refers to the torque in the three axial directions of a six-dimensional force sensor.

[0121] The six-dimensional force information calculation unit 2026 is used to decouple and calculate the comprehensive force information using a modified decoupling matrix to obtain six-dimensional force information. The six-dimensional force information calculation unit 2026 is connected to the adaptive decoupling unit 2025. The six-dimensional force information calculation unit 2026 also includes a zero-point bias sub-unit, which is used to establish a zero-point bias function. The six-dimensional force information calculation unit 2026 performs decoupling and calculation on the comprehensive force information based on the modified matrix and the zero-point bias function to obtain the six-dimensional force information. .

[0122] The device also includes a temperature sensor for detecting the ambient temperature of the six-dimensional force sensor.

[0123] In one optional implementation, the multi-channel synchronous acquisition module 201 includes: A multi-channel synchronous acquisition unit is used to synchronously acquire analog signals output by multiple strain bridge circuits in a six-dimensional force sensor. The multi-channel analog signals include analog signals output by multiple strain bridge circuits. Specifically, the multi-channel synchronous acquisition unit includes multiple strain gauge bridges mounted on the elastic body of the six-dimensional force sensor. Each strain gauge bridge consists of multiple strain gauges bonded to the surface of the elastic body, connected to form a Wheatstone bridge structure. The differential voltage signal reflecting the magnitude of the load in each direction is output based on the resistance change of each strain gauge, thus achieving synchronous sensing of loads in different directions on the six-dimensional force sensor. The multi-channel synchronous acquisition unit is used to acquire the weak differential voltage signals, i.e., analog signals, from the multiple strain gauge bridges.

[0124] The signal conditioning unit includes an analog filter for low-noise instrumentation amplification and programmable gain adjustment of the analog signal, thereby improving the amplitude and signal-to-noise ratio of the analog signal.

[0125] Specifically, the signal conditioning unit includes an input protection circuit, a low-noise instrumentation amplifier circuit, a programmable gain adjustment circuit, and an analog filter. The weak differential voltage signal output from the strain gauge bridge first undergoes common-mode interference suppression and transient protection through the input protection circuit, and then enters the instrumentation amplifier circuit for high-precision differential amplification to improve the signal amplitude and signal-to-noise ratio. Based on the different load ranges of the force sensor, the signal gain is adjusted by the programmable gain adjustment circuit to match the output amplitude to the range of the subsequent analog-to-digital conversion stage. Finally, the analog filter limits the signal bandwidth, reduces the impact of high-frequency noise, and improves the accuracy of multi-channel synchronous sampling.

[0126] Optionally, the analog filter employs a programmable anti-aliasing filter to perform low-pass filtering on multi-channel analog signals; the cutoff frequency can be adjusted by issuing commands or specific frequencies through the digital processing module.

[0127] The digital signal unit includes a digital filter, which is used to convert the analog signal processed by the signal conditioning unit into a digital signal, filter the digital signal through the digital filter, and output a multi-channel digital signal.

[0128] Specifically, the digital signal unit includes a multi-channel synchronous conversion subunit, a clock control subunit, and a multi-channel data alignment subunit. The multi-channel synchronous conversion subunit is a parallel structure of a multi-channel synchronous analog-to-digital converter. It uses the clock control subunit to allocate a unified clock, synchronously triggering the conversion and outputting multiple bridge-side digital sampling data simultaneously. The multi-channel data alignment subunit synchronizes and organizes the data output from the multi-channel synchronous conversion subunit, maintaining the time correspondence between different channels and adding a time number to each group of data. Each group of data ultimately forms a unified data frame.

[0129] The multi-channel synchronous acquisition module 201 provided in this embodiment can acquire load data from the six-dimensional force sensor in all directions, and process the acquired data through a signal conditioning unit and a digital signal unit, thereby improving the data quality and accuracy and forming a data frame with a unified timestamp, providing a reliable synchronous data foundation for the subsequent high-precision calculation of six-dimensional force information.

[0130] In one specific embodiment, such as Figure 5 As shown, the analog front-end conditioning circuit acquires multi-channel analog signals from the multi-strain bridge circuit, and processes the multi-channel analog signals through an instrumentation amplifier, a programmable gain amplifier, and an anti-aliasing filter. The processed multi-channel analog signals are then input into a multi-channel synchronous acquisition circuit. The synchronous clock circuit and the multi-channel synchronous analog-to-digital converter in the multi-channel synchronous acquisition circuit synchronously convert the multi-channel analog signals into multi-channel digital signals. The digital processing core circuit receives the multi-channel digital signals, implements the six-dimensional force sensor measurement method described in the above embodiment, and finally outputs six-dimensional force information.

[0131] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for measuring six-dimensional force using a force sensor, characterized in that, include: Acquire the multi-channel analog signal of the strain bridge circuit of the six-dimensional force sensor at the same time, and convert the multi-channel analog signal into a multi-channel digital signal; Extract the feature parameters of the multi-channel digital signal, and determine the current working state of the six-dimensional force sensor based on the feature parameters; The multi-channel digital signals are fused to obtain comprehensive force information; A basic decoupling matrix is ​​established based on the current temperature and current load information of the six-dimensional force sensor, and the basic decoupling matrix is ​​corrected by the current working state to obtain the corrected decoupling matrix; The comprehensive force information is decoupled and calculated using the modified decoupling matrix to obtain six-dimensional force information.

2. The method according to claim 1, characterized in that, The step of extracting feature parameters from the multi-channel digital signal and determining the current operating state of the six-dimensional force sensor based on the feature parameters includes: Calculate the total resultant force and total resultant torque of the multi-channel digital signals, and use the total resultant force and total resultant torque as comprehensive state variables; Extract the first time-domain feature parameter and the first frequency-domain feature parameter of the comprehensive state quantity, perform first-level working condition identification based on the first time-domain feature parameter and the first frequency-domain feature parameter, and determine whether the current working state is an abnormal state based on the result of the first-level working condition identification. When the condition is determined to be normal, the current working state is determined based on the result of the first-level working condition identification. When an abnormal state is determined, the second time-domain feature parameter and the second frequency-domain feature parameter of the multi-channel digital signal are extracted. Second-level operating condition identification is performed based on the second time-domain feature parameter and the second frequency-domain feature parameter. The current operating state is determined based on the second-level operating condition identification result.

3. The method according to claim 2, characterized in that, The step of identifying a secondary operating condition based on the second time-domain feature parameters and the second frequency-domain feature parameters, and determining the current operating state based on the secondary operating condition identification result, includes: The second time-domain feature parameter and the second frequency-domain feature parameter are compared with the state threshold of the corresponding working state, and the current working state is determined based on the comparison result. The current working state includes static loading state, low-speed motion state, high-speed motion state, periodic vibration state, impact collision state, and abnormal disturbance state.

4. The method according to claim 1, characterized in that, After extracting the feature parameters of the multi-channel digital signal and determining the current working state of the six-dimensional force sensor based on the feature parameters, the method further includes: Generate analog filter control parameters and digital filter control parameters based on the current operating state; The cutoff frequency of the analog filter is adjusted by the analog filter control parameters, and the adjusted analog filter is used to filter the multi-channel analog signal. The filtering coefficients of the digital filter are adjusted by the digital filter control parameters, and the adjusted digital filter is used to filter the multi-channel digital signal.

5. The method according to claim 1, characterized in that, The process of multi-channel fusion of the multi-channel digital signals to obtain comprehensive force information includes: The sensitivity matrix for the force and moment directions of the strain gauge circuit is calibrated. A comprehensive contribution evaluation index is established based on the sensitivity coefficients of the sensitivity matrix, the signal noise level, and the output stability. The fusion weights of the multi-channel digital signals are then calculated based on the comprehensive contribution evaluation index. The multi-channel digital signals are weighted and fused according to the fusion weights to obtain the comprehensive force information.

6. The method according to claim 3, characterized in that, The formula for calculating the basic decoupling matrix is ​​as follows: in, Based on the decoupling matrix, This is the initial decoupling matrix. This is the temperature influence coefficient matrix. The current temperature, To calibrate the temperature, This is the load influence coefficient matrix. The current load information, To calibrate load information.

7. The method according to claim 6, characterized in that, The step of correcting the basic decoupling matrix based on the current working state to obtain the corrected decoupling matrix includes: When the current working state is the static loading state and the low-speed motion state, the corrected decoupling matrix is ​​calculated using a first preset formula, wherein the first preset formula is: in, The modified decoupling matrix is... The basic decoupling matrix; When the current working state is the high-speed motion state, the corrected decoupling matrix is ​​calculated using a second preset formula, wherein the second preset formula is: in, For dynamic enhancement coefficients; When the current operating state is the periodic vibration state, the corrected decoupling matrix is ​​calculated using a third preset formula, wherein the third preset formula is: in, This is the frequency correction factor. The vibration frequency, This is the frequency correction matrix; When the current working state is the impact collision state, the corrected decoupling matrix is ​​calculated using a fourth preset formula, wherein the fourth preset formula is: in, For impact enhancement coefficient, This is the dynamic response correction matrix; When the current operating state is the high-temperature abnormal state among the abnormal disturbance states, the corrected decoupling matrix is ​​calculated using the fifth preset formula, wherein the fifth preset formula is: in, This is the temperature compensation coefficient. The current temperature. To calibrate the temperature, This is the temperature correction matrix.

8. The method according to claim 1, characterized in that, The formula for calculating the six-dimensional force information is as follows: in, For the six-dimensional force information, The modified decoupling matrix is... For the comprehensive force information, This is the zero-point bias function; Before performing decoupling calculations on the comprehensive force information based on the modified decoupling matrix to obtain the six-dimensional force information, the method further includes: A zero-point bias function is established based on the current temperature, wherein the zero-point bias function is: in, For zero-point bias function, To calibrate the zero point, This is the zero-point temperature drift coefficient. The current temperature. For calibration temperature.

9. A six-dimensional force sensor measuring device, characterized in that, include: The system includes a multi-channel synchronous acquisition module and a digital processing module. The multi-channel synchronous acquisition module is used to acquire multi-channel analog signals output by the strain bridge circuit of the six-dimensional force sensor at the same time and output multi-channel digital signals. The digital processing module is used to execute the six-dimensional force sensor measurement method as described in any one of claims 1-8.

10. The apparatus according to claim 9, characterized in that, The multi-channel synchronous acquisition module includes: A multi-channel synchronous acquisition unit includes multiple strain bridges disposed on the six-dimensional force sensor, used to synchronously acquire analog signals output by multiple strain bridges in the six-dimensional force sensor, wherein the multi-channel analog signals include the analog signals output by multiple strain bridges; The signal conditioning unit includes an analog filter for performing low-noise instrumentation amplification and programmable gain adjustment on the analog signal to improve the amplitude and signal-to-noise ratio of the analog signal. The digital signal unit includes a digital filter, which is used to convert the analog signal processed by the signal conditioning unit into a digital signal, filter the digital signal through the digital filter, and output the multi-channel digital signal.

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