CN109425446B - Real-time measuring and evaluating system for handle operation manipulation and force - Google Patents
Real-time measuring and evaluating system for handle operation manipulation and force Download PDFInfo
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- CN109425446B CN109425446B CN201710785063.6A CN201710785063A CN109425446B CN 109425446 B CN109425446 B CN 109425446B CN 201710785063 A CN201710785063 A CN 201710785063A CN 109425446 B CN109425446 B CN 109425446B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01L—MEASURING FORCE, STRESS, TORQUE, WORK, MECHANICAL POWER, MECHANICAL EFFICIENCY, OR FLUID PRESSURE
- G01L1/00—Measuring force or stress, in general
- G01L1/04—Measuring force or stress, in general by measuring elastic deformation of gauges, e.g. of springs
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01L—MEASURING FORCE, STRESS, TORQUE, WORK, MECHANICAL POWER, MECHANICAL EFFICIENCY, OR FLUID PRESSURE
- G01L5/00—Apparatus for, or methods of, measuring force, work, mechanical power, or torque, specially adapted for specific purposes
- G01L5/0028—Force sensors associated with force applying means
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Abstract
According to the handle operation method and the real-time measuring and evaluating system for the strength, the sensing module acquires the state changes of the handle rod piece when the handle rod piece is pulled, pressed, bent and twisted in real time, the signal acquisition and conditioning module is used for processing the acquired signals and then transmitting the data to the PC end through the wireless communication module, and the skill level evaluation, the strength quantitative evaluation and the proficiency evaluation are carried out; a machine learning algorithm is used in the evaluation of the skill level, and the difference quantification of the skill of an operator on the skill is automatically extracted; performing quantitative evaluation, namely comparing the time frequency spectrum with the time frequency spectrum of an experienced operator to obtain quantitative difference of strength; finally, the complexity index in the signal is used to evaluate the proficiency of the operator in the operation and the difference of experienced operators. The invention gives out the similarity degree and the specific difference of the manipulation and the strength in the fine operation of the operator and an experienced operator, provides a quantitative evaluation index and provides a guidance basis for the manipulation and the strength training of the operator.
Description
Technical Field
The invention belongs to the combination of measurement and evaluation methods of empirical operation, and particularly relates to a real-time measurement and evaluation system of a handle operation method and force.
Background
Many operations in daily life, such as operations and scraping, require tools based on handle structures, such as spoons, handles and toothbrushes, and control manipulations and strength during use according to previous experience. The manipulations are generally applied by pulling, pressing, bending and twisting; "force path" generally refers to the combination of force application patterns and the magnitude of the applied force over a period of time. However, for some tasks requiring fine manipulation, a beginner to obtain sufficient experience usually requires a long period of time, often takes a lot of time and exercises to accumulate experience, and sometimes even after the instruction of an experienced person, it is still too much to get. It is relatively much easier if it can be trained by an experienced person, the hand grip; but in many cases it is difficult to have such an opportunity.
Disclosure of Invention
In order to solve the problem that a beginner cannot accurately master the correct operation method and force based on a handle structure tool at present, the invention provides a real-time measurement and evaluation system for the operation method and force of handles. Through comparing with a typical pulling, pressing and bending-twisting mode when an experienced operator completes the same task, the similarity degree and specific difference between the current operator and the experienced operator in the manipulation and the strength are given, quantitative evaluation indexes are provided, and guiding bases are provided for the manipulation and the strength training of the operator.
The technical scheme of the invention is as follows:
the invention relates to a real-time measuring and evaluating system for a handle operation manipulation and force, which consists of a sensing module, a signal conditioning and collecting module, a wireless communication module, a manipulation level evaluating module, a force quantitative evaluating module and a proficiency evaluating module.
In the tension and compression stress measuring strain gauge group arranged in the sensing module, the strain direction of half of the strain gauges is parallel to the axial direction of the rod piece, and the sensing module has the beneficial effects that the sensitivity of the sensing module to the tension and compression stress of the rod piece is improved; the strain direction of the other half of the strain gauge is perpendicular to the axis direction of the rod piece, and the beneficial effects are that temperature compensation can be realized after the strain gauge is connected into a circuit, so that the tension and compression stress strain gauge set is not easily influenced by temperature change. The strain directions of the bending moment measuring strain gauge groups arranged in the sensing module are all parallel to the axis direction of the rod piece, and the strain directions are arranged side by side and uniformly distributed on the upper surface and the lower surface of the rod piece in a manner of being perpendicular to the axis direction. The torque measuring strain gauge group arranged in the sensing module has the beneficial effects that the strain directions of the torque measuring strain gauge group arranged on the same surface of the rod piece are respectively 45 degrees and 135 degrees with the axis of the rod piece, and the strain directions are uniformly distributed on two opposite side surfaces of the rod piece, so that the torque of the rod piece under the twisting action can be accurately measured.
The signal conditioning and collecting module comprises a multi-path measuring change-over switch, and has the advantages that the multi-path sensing module can be measured only by using a group of signal amplifying circuits and an analog-to-digital converter, so that the system volume is greatly reduced, and the system is smaller. The signal conditioning and collecting module comprises a group of signal amplifying circuits and an analog-to-digital converter, and has the advantages of effectively reducing the influence of external noise on a measuring result and improving the accuracy and stability of measurement.
Wireless communication module comprises bluetooth transmission module and wiFi transmission module, and its beneficial effect is, can be to the host computer of data transmission that will gather under the condition of not connecing the data line for entire system is lighter and more handy, portable, can transmit data more far away simultaneously, makes the measuring part and the host computer display portion of system can long-range separation, service distance greatly increased.
The technical scheme for evaluating the manipulation level comprises the following specific steps:
(1) collecting equipment operation data: acquiring a time sequence of three signals of tension, compression, bending and torsion to form a 3 x N matrix in each operation process of a current operator, wherein N is the number of sampling points corresponding to one operation; reforming the 3 × N time series into 3N × 1 column vectors; and the same step selects q persons and w operations per person, and the total number of the operations is M-q-w, so that the M-3N dimensional training data matrix of the self-coding neural network is constructed. Preferably, N is 1000.
(2) Normalization: normalizing each component value of the training data matrix to be between [0 and 1], and normalizing all elements in the training data matrix as a whole, wherein the normalization processing process comprises the following steps:
wherein: x is the number ofiFor plant operating data, normalized data, max (x) is the maximum value in the matrix, min (x) is the matrixMinimum value of (1);
(3) parameter learning to obtain a self-coding neural network model: the self-coding neural network is composed of an input layer, a hidden layer and an output layer, and a parameter learning process, namely a training process for the self-coding neural network, wherein the self-coding neural network specifies that the expected output of the network is equal to the input of the network, namely the goal of parameter learning of the self-coding neural network is to enable the output of the network to be equal to the input of the network. Preferably, the number of nodes of the input layer is 3000+1, wherein +1 is a set bias node, preferably, the number of nodes of the output layer is 3000, preferably, the number of nodes of the middle hidden layer is three, the number of nodes is 300+1, 15+1 and 300+1, wherein +1 is the set bias node, preferably, a sigmoid function is selected by a node function, and preferably, an activation function is the sigmoid function.
(4) Selecting characteristics and weights: taking K hidden layer nodes as K abstract features, wherein the activation values of the K hidden layer nodes respectively correspond to the weight of each feature to form a K-dimensional manipulation feature vector; thus, each operation process of the operator corresponds to one point P in the K-dimensional abstract feature spaceiI is 1,2, …, M. Preferably, the hidden layer node is extracted from the hidden layer with the smallest number of nodes as the abstract feature.
(5) Measuring operation similarity: the similarity degree of any two operation processes of any two operators can be measured by the Euclidean distance between two corresponding points in the K-dimensional abstract feature space, namely, the closer the similarity degree omega is, the closer the similarity degree isijThe higher; omegaij＝‖Pi-Pj‖.
(6) Horizontal grading: taking the typical operation technique characteristic vector of an experienced operator as a reference, and taking the operation similarity omega of the current operator as the referenceijAs the horizontal basis of the current manipulation, the multiple manipulations are averaged, and the horizontal level of the manipulation is divided into 5-10 levels according to the similarity.
The technical scheme of the force quantitative evaluation module is as follows: the force channel refers to the magnitude and instantaneous frequency of the force of an operator in each operation process, and has definite time dependence. Therefore, the invention is embodied by respective time-frequency spectrums of the tension-compression, bending and torsion signals acquired by the current operator in each operation process. The specific method comprises the following steps: the collected time sequence of three stress signals of pulling, pressing, bending and twisting of an operator in each operation process is subjected to short-time Fourier transform or Hilbert-Huang transform to obtain respective frequency spectrum distribution along with time, and the frequency spectrum distribution is used as quantitative representation of the operator on a stress path in the operation process; further, the frequency spectrums of experienced operators in three stress states of tension, compression, bending and torsion in the typical operation process are used as reference standards, and the difference between the corresponding frequency spectrums of the current operators and the experienced operators is the quantitative difference evaluation result of the force channel.
Furthermore, the operator's proficiency is also critical to the task of operation. The proficiency degree, the skill level evaluation and the strength quantitative evaluation are different from the evaluation methods related to time, and are independent of the change of the stress of the rod piece along with the time. In actual practice, there are cases where the manipulation and the strength are controlled well but not skilled, and where the manipulation and the strength are not accurate, and it is therefore necessary to consider the skill level of the manipulation. The invention provides a method for quantitatively reflecting the adaptability and flexibility of an operator to an operation task by using the complexity index of the internal fluctuation of a signal, and finally reflecting the proficiency. The specific technical scheme is as follows: time series Z generated under the states of tension, compression, bending and torsion stress respectivelyi(i 1,2,3) performing multi-scale entropy analysis to obtain 3 multi-scale entropies Ai(i is 1,2,3), and further arithmetically averaging the three multi-scale entropies to obtain a complexity index a, that is, the complexity index a
The same method is used to calculate the complexity index A of a typical skilled operator0A and A0The smaller the absolute value of the difference, the higher the current operator proficiency level is, according to the formula
Calculation, the proficiency level is classified, wherein 0-0.2 is extremely unskilled, 0.2-0.4 is unskilled, 0.4-0.6 is moderate, 0.6-0.8 is skilled, and 0.8-1.0 is very skilled.
The invention has the following advantages:
the real-time measurement and evaluation system for the handle operation methods and force paths can quantitatively measure the change of tension and compression stress, bending moment and torque along with time when a user applies force to the handle tools in real time; the evaluation of the manipulation level mainly utilizes an unsupervised learning self-encoder neural network to automatically extract the abstract characteristics and the activation degree of the current operator and the skilled operator, and further quantifies the difference of the manipulation levels of the current operator and the skilled operator; meanwhile, the short-time Fourier transform or Hilbert-Huang transform is utilized to obtain the frequency spectrum distribution of the tension, compression, bending and torsion stress signals, so that the difference of an operator and an experienced operator on a force path is quantitatively represented more accurately; and finally, obtaining a specific quantitative proficiency evaluation difference value of the current operator and an experienced operator in the aspects of the manipulation and the strength by utilizing multi-scale entropy analysis, thereby comprehensively helping a beginner to improve the accuracy and the proficiency of the manipulation and the strength in the fine operation.
Drawings
FIG. 1 is a strain gage layout of the overall structure and sense module of the present invention;
FIG. 2 is a strain gage connection diagram of a sensing module of the present invention;
FIG. 3 is a diagram of a signal conditioning acquisition module and a wireless communication module according to the present invention;
FIG. 4 is a flow chart of the skill level evaluation technique of the present invention;
FIG. 5 is a block diagram of a self-encoding network for unsupervised learning to extract features and weights
FIG. 6 is a flow chart of a technical solution of the force quantitative evaluation module of the present invention;
FIG. 7 is a time-frequency spectrum diagram of time series generated by different operator operations
Detailed Description
The invention will be further illustrated by the following specific examples in order to better understand the invention, without however being limited thereto.
As shown in fig. 1, the real-time measurement and evaluation system for the manipulation techniques and forces of the handles of the invention comprises a handle rod 1, a sensing module 2, a signal conditioning and collecting module 3, a wireless communication module 4 and a PC. In one embodiment, the handle-like bar 1 may be a modified electric toothbrush bar body; the sensing module 2 is internally provided with a plurality of strain gauges 8 which are composed of a tension and compression stress measuring strain gauge group 5, a bending moment measuring strain gauge group 6 and a torque measuring strain gauge group 7, wherein the strain gauges are tightly attached to the periphery of a solid rod piece at the middle section of the toothbrush rod main body; the sensing module 2 is connected with the signal conditioning and collecting module 3 through a plurality of output wires 9; after the signals are processed by the signal conditioning and collecting module 3, the data are transmitted to the PC by the wireless communication module 4, and then real-time measurement and evaluation of the manipulation and the strength are obtained through analysis.
The sensing module 2 described in this embodiment is composed of a strain gauge set for measuring tensile and compressive stress, bending moment and torque. The tension and compression strain gauge group uses 2 BB type double-gate strain gauges, and is symmetrically adhered to the outer surface of the middle section of the toothbrush rod 1 by AB glue, wherein the axial strain direction of the strain gauge group is parallel to the axial direction of the connecting rod 1, so that the sensitivity of the strain gauge group to tension and compression deformation is improved, the strain gauge group is not easily interfered by temperature change, and the tension and compression strain gauge group is suitable for measuring the tension and compression stress of a handle; the bending moment measuring strain gauge group uses 2 FB type double-grid strain gauge groups, AB glue is symmetrically pasted on the upper surface and the lower surface of the toothbrush rod, and the strain directions of the strain gauges are all parallel to the axial direction of the electric toothbrush rod main body, so that temperature compensation is realized, the sensitivity to the bending condition of an external handle can be improved, and the bending moment can be measured more accurately; the torque measuring strain gauge group uses 2 HA type double-grid strain gauge groups, AB glue is symmetrically pasted on two side faces of the middle section of the toothbrush rod, two strain directions respectively form 45 degrees and 135 degrees with the axial direction of the connecting rod 1, and the torque can be accurately measured. The specific connection mode of the strain gage set for measuring tensile stress, bending moment and torque is shown in fig. 2.
As shown in fig. 3, the signal acquisition and conditioning module of the present embodiment is composed of a multi-channel measurement switch, a group of signal amplification circuits, and an analog-to-digital converter, wherein the measurement switch is composed of a relay, each channel of sensing module is connected to the input end of the same group of signal amplifiers through one channel of switch, and the analog-to-digital converter is connected to the microcontroller unit, so that the system size is reduced, the influence of external noise on the measurement result can be effectively reduced, and the measurement accuracy and stability are improved. The signal sampling frequency of the analog-to-digital converter in this embodiment is 300Hz, the acquisition frequency of the sensing module is 100Hz, each acquisition of the data of the sensing module includes 3 signal samplings, the sampling is performed by adopting a time-sharing method, and in a data acquisition period of the sensing module, a tension and compression signal is acquired first, a bending moment signal is acquired again, and a torque signal is acquired finally. The wireless communication module of this embodiment is composed of a bluetooth transmission module and a WiFi transmission module, wherein the bluetooth transmission module and the WiFi transmission module are respectively connected to the MCU. The Micro Control Unit (MCU) described in this embodiment uses the STM32F103RBT6 chip, which has low power consumption and high processing speed, can stably collect and process the digital signals obtained by the signal conversion module, is connected to the PC terminal through the wireless communication module, and transmits the collected data to the PC terminal in real time to complete the evaluation of manipulation level, quantitative evaluation of force channel, and proficiency evaluation.
As shown in FIG. 4, the technique for evaluation of the manipulation level is as follows: firstly, collecting time sequences of three signals of pulling, pressing, bending and twisting when different users use the electric toothbrush for brushing teeth for multiple times, selecting q persons and w operations (total M is q x w operations) for each person for the same step, operating N sampling points for each time, and constructing an M x 3N dimensional training data matrix from a coding neural network; normalizing all elements of the training data matrix, and then performing unsupervised learning and training of the self-coding neural network, as shown in fig. 5, taking K output nodes as K abstract features, and forming K-dimensional manipulation feature vectors by the activation values of the K output nodes, so that each tooth brushing process of a user corresponds to a point P in the K-dimensional abstract feature spaceiI-1, 2, …, M, whereby the degree of similarity between any two electric toothbrush users' two brushing sessions can be determined by applying the K-dimensional abstract featureThe Euclidean distance between two corresponding points in the middle is measured, namely the closer the distance is, the similarity omega isijThe higher; omegaij＝‖Pi-Pj|. Finally, taking the typical operation method of the tooth brushing expert as a reference, and taking the current operation similarity omega of the operator as a referenceijAs the horizontal basis of the current manipulation, the multiple manipulations are averaged, and the horizontal level of the manipulation is divided into 5-10 levels according to the similarity. For example, the similarity ω between the current operator's approach and the experienced operator's approachijThe horizontal level is 10 levels, representing that the two maneuvers are "identical".
As shown in fig. 6, the quantitative evaluation module of the force path obtains a time sequence of the collected three stress signals of the operator in the pulling, bending and twisting processes in each operation process, as shown in fig. 7, obtains the frequency spectrum distribution of each of the three stress signals of the operator along with time during the operation process through short-time fourier transform, and obtains the quantitative difference evaluation result of the current operator force path by comparing the frequency spectrum with the frequency spectrum of the experienced operator in the pulling, pressing, bending and twisting processes in the typical operation process.
For time series Z generated by each operation of using the toothbrush during tooth brushingi(i is 1,2,3, …, n) carrying out multi-scale entropy analysis to obtain n multi-scale entropies Ai(i is 1,2,3, …, n), and then the complexity index a, i.e. the arithmetic mean of the n multi-scale entropies
The same method is used to calculate the complexity index A of the standard brushing method0A and A0The smaller the absolute value of the difference, the higher the proficiency level of the current toothbrushing person, according to the formula
Calculation, the level of proficiency is graded with 0-0.2 being extremely unskilled, 0.2-0.4 being unskilled, 0.4-0.6 being moderate, 0.6-0.8 being proficient, 0.8-1.0 being very proficient. When the operation proficiency level of the operator is 0.9, the operator represents the current operation of the current operatorIs very skilled.
The similarity and specific difference values of the current toothbrushing person and the correct toothbrushing method in the aspects of the manipulation and the force obtained by the manipulation and force evaluation module can be directly displayed on a PC (personal computer) end display screen, so that a user can conveniently know and timely adjust the tooth brushing force and the tooth brushing mode, and the tooth brushing operation accuracy is improved.
Although the present invention has been described with reference to the preferred embodiments, it is not intended to be limited thereto. Those skilled in the art can make numerous possible variations and modifications to the present invention, or modify equivalent embodiments, using the methods and techniques disclosed above, without departing from the scope of the present invention. Therefore, any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present invention are still within the scope of the protection of the technical solution of the present invention, unless the contents of the technical solution of the present invention are departed.
Claims (7)
1. A real-time measuring and evaluating system for the operation technique and force of handle-type rod is composed of a sensing module (1); a signal conditioning and collecting module (2); a wireless communication module (3); a manipulation level evaluation module (4); a force quantitative evaluation module (5); a proficiency level evaluation module (6); the device is characterized in that a plurality of groups of strain gauges are arranged on the surface of a rod piece and used as a sensing module (1), and the state changes of tension, compression and torsion stresses sensed by the rod piece in the operation process are used as data bases of an operator's operation method, force evaluation and proficiency; obtaining the similarity degree of the current operator and an experienced operator in the aspect of operation skills and the skill level of the operator through a self-encoder neural network in a skill level evaluation module (4); the force channel of an operator is reflected by the time frequency spectrum of the tension, compression, bending and torsion signals in the force channel quantitative evaluation module (5), and corresponding force channel difference is obtained by comparing the time frequency spectrum with the time frequency spectrum of an experienced operator; and the proficiency level of the operator in the operation process is quantitatively reflected through the complexity index of the signal in the proficiency level evaluation module (6), and the proficiency level of the operator is obtained through comparison with the complexity index of an experienced operator.
2. The real-time measurement and evaluation system for the operation technique and force path of the handle-like rod piece according to claim 1, wherein the sensing module (1) is provided with three groups of strain gauges for measuring tensile stress, bending moment and torque on the surface of the rod piece; the strain direction of the strain gauge group for measuring the tensile stress and the compressive stress on the same surface of the rod piece is half parallel to the axial direction of the rod piece, the other half is vertical to the axial direction of the rod piece, and the strain gauges are uniformly distributed on the upper surface and the lower surface of the rod piece; the strain directions of the bending moment measuring strain gauge groups are all parallel to the axial direction of the rod piece, are arranged side by side in a manner of being vertical to the axial direction of the rod piece and are uniformly distributed on the upper surface and the lower surface of the rod piece; the torque measuring strain sheet sets are arranged in the strain directions of the same surface of the rod piece, one half of the strain sheet sets are 45 degrees with the axial direction of the rod piece, the other half of the strain sheet sets form 135 degrees with the axial direction of the rod piece, and the strain sheet sets are uniformly distributed on the left surface and the right surface of the rod piece.
3. The real-time measurement and evaluation system for the manipulation and force of the lever-like member of claim 1, wherein the signal conditioning and collecting module (2) comprises a plurality of measuring switches, a plurality of signal amplifying circuits and an analog-to-digital converter, wherein the measuring switches comprise relays, each sensing module is connected to the input end of the same signal amplifier group through a switch, and the analog-to-digital converter is connected to the Micro Controller Unit (MCU).
4. The system for real-time measurement and evaluation of manipulation techniques and forces of a handle-like bar according to claim 1, wherein the wireless communication module (3) is composed of a bluetooth transmission module and a WiFi transmission module, wherein the bluetooth transmission module and the WiFi transmission module are respectively connected to the MCU.
5. The real-time measurement and evaluation system for manipulation and force of handle-like rod members as claimed in claim 1, wherein the horizontal evaluation of the manipulation in the manipulation horizontal evaluation module (4) is obtained by obtaining K abstract features and their manipulation feature vectors through unsupervised learning from the encoder neural network, and then performing similarity estimation with an experienced operator; the specific method comprises the following steps: firstly, a 3 x N matrix is formed by a time sequence of three signals of tension, compression, bending and torsion acquired in each operation process of a current operator, wherein N is the number of sampling points corresponding to one operation; the method comprises the following steps that (1) q operators operate for w times per person, wherein the total M is q x w times, K output nodes serve as K abstract features through unsupervised learning and training of a self-encoder neural network, and the activation values of the K output nodes form a K-dimensional manual feature vector, so that each operation process of the operators corresponds to one point in a K-dimensional abstract feature space; correspondingly, w times of operation of the current operator correspond to w points in the K-dimensional abstract feature space; the similarity of any two operators in any two operation processes can be measured through the Euclidean distance between two corresponding points in the K-dimensional abstract feature space, namely, the closer the distance is, the higher the similarity is; the typical operation method of an experienced operator is used as a reference, the similarity is used as the horizontal basis of the current operator method, and the horizontal level of the operator method is divided into 5-10 levels according to the size of the similarity.
6. The real-time measurement and evaluation system of the manipulation technique and the force path of the handle-like rod according to claim 1, wherein the quantitative evaluation of the force path in the force path quantitative evaluation module (5) is embodied by respective time-frequency spectrums of three signals of tension, compression, bending and torsion acquired in each operation process of the current operator; the specific method comprises the following steps: performing short-time Fourier transform or Hilbert-Huang transform on a time sequence of three signals of tension, compression and torsion acquired in each operation process of a current operator to obtain frequency spectrum distribution of tension, compression and torsion stress states along with time as quantitative representation of corresponding stress paths of the operator in the operation process; and then taking the spectrum in three stress states of tension, compression, bending and torsion of a typical operation process of an experienced operator as reference, and taking the difference of the corresponding time frequency spectrums of the current operator and the experienced operator as a quantitative difference evaluation result of the force channel.
7. The real-time measurement and evaluation system of the manipulation and force path of the handle-like rod according to claim 1, wherein the proficiency evaluation module (6) performs multi-scale entropy analysis on three signals of pulling, pressing, bending and twisting during the manipulation process of the current operator, and further averages three multi-scale entropy analysis results to obtain a complexity index; the multiple operation processes of the same person are that the significance level is tested through the statistical hypothesis of the complexity index to serve as the quantitative evaluation result of the proficiency level; taking multiple operation processes of an experienced operator as reference, and taking the difference of the complexity indexes as the proficiency of the current operator, namely the smaller the difference is, the higher the proficiency is, and the larger the difference is, the lower the proficiency is; the proficiency level of the operator is classified into 5-10 levels as the proficiency level according to the magnitude of the difference of the complexity index.
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