Multi-sensor smart finger based on triboelectric effect and use method and application thereof

Abstract

This invention discloses a multi-sensor smart finger based on triboelectric effect, its usage method, and applications. It includes a first phalanx covered with a first friction sensing mechanism; a second phalanx internally encapsulating a second friction sensing mechanism; a third phalanx internally encapsulating a microprocessor chip and a third friction sensing mechanism; a connecting joint, shaped like a turntable, connecting the end of the first phalanx to the front end of the second phalanx and connecting the end of the second phalanx to the front end of the third phalanx; a fourth friction sensing mechanism on the contact surfaces of the two connecting joints; a servo motor mounting bracket located at the ends of the first and second phalanxes; and a signal processing circuit connecting the microprocessor chip to the first, second, third, and fourth friction sensing mechanisms via wires. This invention can achieve multi-channel information sensing and has the advantages of small size and high flexibility. Furthermore, this invention can also achieve the effect of human motion or environmental monitoring.

Description

Technical Field

[0001] This invention relates to the field of triboelectric nanogenerator technology, and in particular to a multi-sensor smart finger based on the triboelectric effect, its usage method, and its application. Background Technology

[0002] Robotics science has been thrust back to the forefront in recent years with the development of artificial intelligence, and its importance and application prospects are gradually gaining recognition and attention. Over the past few decades, industrial robots have replaced humans in heavy, repetitive, or unsafe manufacturing tasks. However, with economic development, current manufacturing demands have shifted towards the small-batch assembly of more customized and variable products, requiring robots to possess greater adaptability, flexibility, broader manipulation capabilities, and programmability. Robotics technology is also increasingly permeating ordinary people's home lives. Unlike industrial environments, home environments are typically unstructured, meaning that autonomous perception capabilities need to be added to the robot's control strategies. Traditionally, the control of robot end effectors is achieved by inputting empirical knowledge about the manipulated object and the operating environment into the control algorithm. Therefore, robotic hands can only manipulate known objects and work in structured environments, making them less adaptable to unexpected events.

[0003] To achieve mechanical sensing in complex environments or structures, triboelectric nanogenerators, a technology that converts mechanical signals from the environment into electrical signals, have been researched and applied in the field of sensing. Due to the diversity and stability of the mechanical signals they collect, they can be used to sense various forms of activity or physical quantities, while the electrical signals can also be self-powered. Based on the coupling effect of triboelectric and electrostatic induction, they can harvest many forms of mechanical energy. They offer advantages such as small size, high energy conversion efficiency, low cost, simple manufacturing, light weight, and environmentally friendly processes. Traditional methods for sensing are often limited by operating methods, size constraints, and power supply difficulties. Using triboelectric nanogenerators for sensing effectively solves these problems while maintaining high sensing sensitivity and accuracy.

[0004] Simultaneously, with the development of transportation and medical technologies, and the general increase in global life expectancy, the demand for rehabilitation support equipment such as prosthetics is also growing. Bionic limbs, as a new type of rehabilitation tool, can help people with limb loss regain limb function, improve their quality of life, and enhance their social abilities. Currently, prostheses can mimic many mechanical functions of biological limbs, such as grasping, grabbing, and placing. This can help those with limb loss regain certain physical functions, thereby restoring some social functions, such as shaking hands and greeting. However, most existing prostheses only allow for human control of the bionic limb, lacking appropriate sensory feedback; that is, they only achieve unidirectional control. This can affect the function of the prosthesis and the user's quality of life, making it difficult for patients receiving prosthetic treatment to fully return to normal life, and often leading them to feel that the prosthesis is a foreign object. Therefore, new bionic limb solutions are needed to compensate for the shortcomings of existing bionic limbs, making them more effective and easier for patients to accept. To solve this problem, we can use triboelectricity to convert the mechanical motion generated by human movement or contact with the outside world into electrical signals. These electrical signals can then be transmitted to a computer program as sensing signals for data analysis and pattern recognition using algorithms.

[0005] This sensor, based on a triboelectric nanogenerator, eliminates the need for traditional battery power, thus avoiding the environmental pollution associated with batteries. Furthermore, this sensor can be adaptively optimized and designed according to the structural and activity characteristics of different parts, meaning it can autonomously generate signals in various application scenarios without requiring any battery power.

[0006] Once the sensors capture the mechanical signals from the finger and convert them into electrical signals, the next step is to develop corresponding algorithms and software for data analysis and pattern recognition. These algorithms can recognize different finger movements, gestures, and contact strengths, thereby achieving precise control and perception of the smart finger. Simultaneously, these algorithms can also convert electrical signals into feedback signals that humans can understand, allowing users to feel the touch and movement of the bionic finger.

[0007] In terms of applications, smart fingers based on triboelectric nanogenerator sensing have a wide range of potential applications. Firstly, they can be used in the research and development of bionic limbs and rehabilitation support. Users can achieve more natural and precise movements through smart fingers, while simultaneously sensing the force and texture of contact, thereby improving rehabilitation outcomes and quality of life.

[0008] Furthermore, smart fingers based on triboelectric nanogenerator technology can also play an important role in the fields of virtual reality and augmented reality. Users can interact with virtual environments through smart fingers, feeling the touch and movement of virtual objects, enhancing immersion and interactive experiences. Therefore, based on the goal of bringing breakthroughs to the fields of robotics and bionic limbs, and providing new possibilities for fields such as intelligent interaction and virtual reality, developing a smart finger technology based on triboelectric nanogenerator sensing has become an urgent technical problem to be solved. Summary of the Invention

[0009] The purpose of this invention is to provide a multi-sensor smart finger based on triboelectric effect, along with its usage method and applications. This multi-sensor smart finger can achieve multi-channel information sensing and has the advantages of small size and high flexibility. Furthermore, this invention can also achieve the effect of human motion or environmental monitoring.

[0010] The technical solution of the present invention: a multi-sensor smart finger based on triboelectric effect, including a first phalanx and a surface covered with a first friction sensing mechanism;

[0011] The second phalanx contains a second friction sensing mechanism encapsulated internally.

[0012] The third phalanx contains a microprocessor chip and a third friction sensor mechanism.

[0013] The connecting joint is turntable-shaped, connecting the end of the first phalanx to the front end of the second phalanx and connecting the end of the second phalanx to the front end of the third phalanx; the contact surfaces of the two connecting joints are provided with a fourth friction sensing mechanism.

[0014] The servo mounting bracket is located at the ends of the first and second phalanges;

[0015] The signal processing circuit connects the microprocessor chip to the first friction sensing mechanism, the second friction sensing mechanism, the third friction sensing mechanism, and the fourth friction sensing mechanism via wires.

[0016] The aforementioned multi-sensor smart finger based on triboelectric effect has a centripetal inclined surface and drainage channel on the upper surface of the first phalanx, and a liquid storage cavity inside the first phalanx; the second phalanx has a semi-closed cavity structure and a first cap; the third phalanx has a semi-closed cavity structure and a second cap, and a through hole at the bottom end and a rectangular opening at the top end.

[0017] The aforementioned multi-sensor smart finger based on triboelectric effect has a first friction sensing mechanism with a friction layer and an electrode layer that are the same shape as the first phalanx, and an insulating layer is provided between part of the friction layer and the electrode layer.

[0018] In the aforementioned multi-sensor smart finger based on triboelectric effect, the electrode layer of the second triboelectric sensing mechanism is disposed on the inner wall of the cavity that contacts the lower surface of the movable triboelectric cube, and the surface of the movable triboelectric cube is provided with a triboelectric layer.

[0019] The aforementioned multi-sensor smart finger based on triboelectric effect has a third triboelectric sensing mechanism that is arched in shape, with the electrode layer fixed at both ends and bent into an arched structure in the middle.

[0020] The aforementioned multi-sensor smart finger based on triboelectric effect has a fourth triboelectric sensing mechanism that is disc-shaped, with a fan-shaped triboelectric layer and an interdigitated electrode layer, with an insulating layer between the triboelectric layer and the electrode layer; wherein the interdigitated electrode layer includes a multi-finger-shaped first electrode and a second electrode; the first electrode and the second electrode are arranged in an opposing and intersecting manner.

[0021] The aforementioned multi-sensor smart finger based on triboelectric effect has the following features: the first triboelectric sensing mechanism senses liquids, materials, and pressure; the second triboelectric sensing mechanism senses acceleration; the third triboelectric sensing mechanism senses temperature changes; and the fourth triboelectric sensing mechanism senses angles.

[0022] In the aforementioned method of using a multi-sensor smart finger based on the triboelectric effect, under stable conditions, when the multi-sensor smart finger is stationary, none of the triboelectric sensing mechanisms generate electrical signals; when the multi-sensor smart finger is active and / or the surrounding environment changes, the first, second, third, and / or fourth triboelectric sensing mechanisms generate electrical signals. After being amplified and filtered by the signal processing circuit, the electrical signals are connected to the microprocessor chip through wires. The microprocessor chip analyzes and classifies the signals using a machine learning model to form the sensing of multiple senses.

[0023] The aforementioned application of multi-sensor smart fingers based on triboelectric effect involves human or machine automated operation of the multi-sensor smart fingers. By collecting the electrical signal characteristics generated when the multi-sensor smart fingers move and / or the surrounding environment changes, a machine learning model is established to learn, identify, and classify the electrical signal characteristics, forming a sensing of multiple senses, which is then used for monitoring motion and / or environmental changes.

[0024] Compared with existing technologies, when the multi-sensor smart finger of this invention moves and / or the surrounding environment changes, the first, second, third, and / or fourth friction sensing mechanisms generate electrical signals. These signals are amplified and filtered by a signal processing circuit and then connected to a microprocessor chip via wires. The microprocessor chip analyzes and classifies these signals, thus enabling multi-channel information sensing with high sensitivity. The multi-sensor smart finger of this invention has the advantages of small size and high flexibility. Furthermore, it is self-powered, capable of acquiring high-precision electrical signals, and is cost-effective. Moreover, this invention can sense liquids, pressure, materials, temperature changes, angles, and accelerations, achieving the effect of human movement or environmental monitoring. Attached Figure Description

[0025] Figure 1 This is a side cross-sectional view of the present invention;

[0026] Figure 2 This is a top cross-sectional view of the present invention;

[0027] Figure 3 This is a rear cross-sectional view of the first phalanx of the present invention;

[0028] Figure 4 This is a side cross-sectional view of the first phalanx of the present invention;

[0029] Figure 5 This is a side cross-sectional view of the second phalanx of the present invention;

[0030] Figure 6 This is a side cross-sectional view of the third phalanx of the present invention;

[0031] Figure 7 A simplified schematic diagram of the friction sensing mechanism provided on the surface of the first finger joint of the present invention;

[0032] Figure 8 This is a schematic diagram of the friction sensing mechanism provided in the second phalanx of the present invention;

[0033] Figure 9 A schematic diagram of the fixed interdigital electrode of the friction sensing mechanism provided on the joint contact surface of the present invention.

[0034] Figure 10 A schematic diagram of the movable electrode of the friction sensing mechanism provided on the contact surface of the connecting joint of the present invention;

[0035] Figure 11 This is a schematic diagram illustrating the working principle of the friction sensing mechanism provided on the surface of the first finger joint of the present invention.

[0036] Figure 12This is a schematic diagram illustrating the working principle of the friction sensing mechanism provided in the second phalanx support body of the present invention.

[0037] Figure 13 This is a schematic diagram illustrating the working principle of the friction sensing mechanism provided on the contact surface of the connecting joint of the present invention.

[0038] Figure 14 This is a simplified schematic diagram illustrating the working principle of the friction sensing mechanism provided in the third phalanx of the present invention.

[0039] Figure 15 This is a schematic diagram of the intelligent finger after the addition of a robotic arm bracket and a servo motor in Example 2. Detailed Implementation

[0040] The present invention will be further described below with reference to the accompanying drawings and embodiments, but this should not be construed as limiting the present invention.

[0041] Example 1: A multi-sensor smart finger based on triboelectric effect, such as... Figure 1 As shown, it includes a first phalanx 101, which is a solid support body with a first friction sensing mechanism on its surface.

[0042] The second phalanx 102 has a semi-closed cavity structure, a second friction sensing mechanism 205 is provided in the cavity, and a through hole is provided at the bottom; it is equipped with a first cover 105.

[0043] The third phalanx 103 has a semi-closed cavity structure, is equipped with a second cover 106, has a through hole at the bottom and a rectangular opening at the top, and is internally encapsulated with a microprocessor chip and a third friction sensing mechanism 206.

[0044] The connecting joint 104, in the form of a turntable, is disposed on the end of the first phalanx 101, the front end of the second phalanx 102 and its corresponding cap, and the front end of the third phalanx 103, and rotates with each other. The contact surface of the connecting joint 104 is provided with the fourth friction sensing mechanism 204.

[0045] The first servo mounting bracket 107 and the second servo mounting bracket 108 are located on the opposite side of the connecting joint 104 and are used to mount servos.

[0046] Both the first servo mounting bracket 107 and the second servo mounting bracket 108 have through holes on their sides;

[0047] The friction sensing mechanism in this embodiment consists of friction layers and electrode layers of different shapes and materials;

[0048] like Figure 3 and Figure 7As shown, the first friction sensing mechanism on the surface of the first knuckle 101 includes a first part 201, a second part 202 and a third part 203, all three parts having a friction layer 301 and an electrode layer 302 that are the same shape as the first knuckle 101; wherein an insulating layer is provided between the friction layer 301 and the electrode layer 302 of the first part 201.

[0049] like Figure 5 and Figure 8 As shown, the second friction sensing mechanism 205 of the second phalanx 102 is disposed on the inner wall of the spherical cavity, the friction layer 301 is a cube, and the electrode layer 302 is a group of four independent rectangular electrodes.

[0050] like Figure 5 and Figure 9 , Figure 10 As shown, the fourth friction sensing mechanism 206 provided on the contact surface of the connecting joint 104 is disc-shaped, with a fan-shaped friction layer 301 and an interdigitated electrode layer 302, and an insulating layer is provided between the friction layer 301 and the electrode layer 302.

[0051] like Figure 6 As shown, the third friction sensing mechanism 205 provided on the top of the third phalanx 103 is arched in shape, with the electrode layer fixed at both ends and bent into an arched structure in the middle.

[0052] The signal processing circuit connects the microprocessor chip to the first friction sensing mechanism, the second friction sensing mechanism 205, the third friction sensing mechanism 206, and the fourth friction sensing mechanism 204 via wires.

[0053] In this embodiment, the materials of the first phalanx 101, the second phalanx 102, the third phalanx 103, and the outer shell of the connecting joint 104 should be lightweight and rigid, such as resin, polylactic acid, etc., preferably resin; the through holes provided on the third phalanx 103 and the second cover 106 are used for assembly, and the bearing groove and the rudder mounting groove are used for the installation of bearings and rudder motors; the electrode layer 302 of the friction sensing mechanism should be lightweight, have high conductivity, low cost, and high electropositivity, such as copper, aluminum, etc.; wherein, the friction layer of the first part 201 of the first friction sensing mechanism should have higher electronegativity than common liquids (such as distilled water, physiological saline, etc.); the friction layer of the second part 202 of the first friction sensing mechanism is a sandwich between two electrode layers, and its material should be highly electronegative. The friction layer of the third part 203 of the first friction sensing mechanism is made of two polymers with significantly different electronegativity, such as polyvinylidene fluoride and polyvinylpyrrolidone, to respond to pressure. The fixed electrode layer of the fourth friction sensing mechanism 204 is made of two electrode materials 401 and 402 placed in an opposing interdigitated manner to sense opposite angles, and its free electrode layer 303 should have higher electronegativity. The friction layer of the second friction sensing mechanism 205 is wrapped around the surface of the movable cube, and the selected material should be a highly electronegative insulating polymer compound, such as polytetrafluoropropylene. The friction layer material of the third friction sensing mechanism 206 should be two polymers with different electronegativity, such as polytetrafluoroethylene. In this embodiment, a servo motor mounting bracket is provided to facilitate automated operation.

[0054] In this embodiment, the working process of each friction sensing mechanism is as follows:

[0055] The first part 201, the second part 202, and the third part 203 of the first friction sensing mechanism respectively realize liquid, material, and pressure sensing: For example Figure 11As shown, the initial state is defined as when there is no liquid dripping, the distance between the identification material and the friction layer is relatively far, and no pressure is applied to the third part 203 of the first friction sensing mechanism. At this time, the friction layers of each sensing mechanism are exposed to the air and no electrical signal is generated. The intermediate state is defined as when the liquid drips just into contact with the friction layer of the first part 201 of the first friction sensing mechanism, the distance between the identification material and the friction layer of the second part 202 is very close, and pressure is applied to the third part 203. At this time, the liquid diffuses and flows on the surface of the friction layer of the first part 201, and the friction layer of the first part 201 becomes negatively charged due to the triboelectric effect, while the electrode layer of the first part 201 becomes positively charged due to electrostatic induction, and electrons flow from the reference electrode to the electrode layer of the first part 201. When the identification material approaches the friction layer of the second part 202, the charge balance is broken, and the potential of the electrode layer of the second part 202 changes. When pressure is applied to the third part 203, the friction layer of the third part 203 deforms, and the two submicron fibers come into contact with each other, resulting in the generation of opposite triboelectric charges. The final state is defined as when the liquid droplet spreads out, the identification material comes into contact with the friction layer, and the pressure is released. At this time, the liquid-solid contact area is basically stable, and friction no longer occurs. The number of electrons transferred from the first part 201 electrode layer to the reference electrode decreases, and no current is output. When the identification material comes into complete contact with the second part 202 friction layer, a new charge balance is generated between the material, the second part 202 friction layer, and the second part 202 electrode layer, and there is no more output. When the pressure is released, the two submicron fibers return to their original positions, resulting in the separation of positive and negative charges, thereby inducing opposite charges in the third part 203 electrode layer at both ends and generating an electrical signal.

[0056] The fourth friction sensing mechanism 204, i.e., angle sensing: such as Figure 12 As shown, the movement of the connecting joint causes relative rotation between the rotor and stator. The free electrode layer is installed on the rotor and carries a positive charge through friction on the friction layer of the fourth friction sensing mechanism 206. Taking electrode 401 as an example, the initial state is when the free electrode layer is aligned with the left fixed electrode. At this time, due to electrostatic induction, negative charge accumulates on the left electrode, while the right electrode carries an equal amount of positive charge. The movement of the connecting joint causes the free electrode to move from the left electrode to the right electrode, which is an intermediate state. Free electrons will continuously flow from the left electrode to the right electrode. The final state is when the free electrode is exactly above the right electrode. Due to the overlap difference, the second electrode leads the first electrode, forming a detectable phase difference between the two signals.

[0057] The second friction sensing mechanism 205, i.e., the acceleration sensing mechanism, is as follows: Figure 13As shown, the triboelectric sensing mechanism operates under two different principles when vibrating in different directions. In the initial state, when the movable triboelectric cube 301 remains at the bottom due to its gravity and contact with the electrode layer 302, surface charges are generated between the movable triboelectric cube 301 and the electrode layer 302 due to the triboelectric effect. Based on the triboelectric level, since the electrode material is more positive than the movable triboelectric cube, the movable triboelectric cube 301 and the electrode layer 302 possess negative and positive charges, respectively. Due to the insulating properties of the movable triboelectric cube 301, the generated negative triboelectric charge can remain on its surface for a long time. At this time, the charge is balanced, and there is no electrical output. When the triboelectric sensing mechanism vibrates longitudinally, the movable triboelectric cube 301 rebounds and separates from the electrode layer 302, thereby giving the electrode layer 302 a higher potential, allowing electrons to flow from the reference electrode to the electrode layer 302. As the movable friction cube 301 continues to rise, the flow of induced electrons can continue until a new electrical balance is established. When the friction sensing mechanism vibrates horizontally, the movable friction cube 301 slides away from the electrode layer 302. The friction charge on the mismatched area cannot be compensated, and the resulting potential difference will force electrons to flow from the reference electrode to the electrode layer 302. When the movable friction cube 301 separates from the electrode layer 302, a new electrical balance is generated, and there is no longer any output.

[0058] The third friction sensing mechanism 206, namely the temperature change sensing mechanism: such as Figure 14 As shown, when it is necessary to measure the temperature or its change, the arched structure is pressed to make the friction layer 301 contact the electrode layer 302; when the pressing is stopped, the movable friction layer 301 separates from the electrode layer 302. Due to the difference in electronegativity between the two friction layer 301 materials, the two friction layers 301 carry opposite charges, which are induced in the electrode 302, realizing the charge transfer between the reference electrode and the electrode layer 302.

[0059] Signal processing circuits include preamplifiers, filters, and operational amplifiers. The preamplifier amplifies the small electrical signals generated by the device to a suitable level, the filter removes unnecessary signal interference, and the operational amplifier further amplifies the signal to ensure its accuracy and stability.

[0060] The sensor signal classification algorithm is used for real-time monitoring and classification of environmental physical and motion information of the smart finger. It is programmed into a microprocessor chip. Based on a machine learning model, this algorithm analyzes signals obtained from triboelectric nanogenerators to identify the smart finger's environmental physical and motion information, such as fluid, acceleration, and temperature changes. The algorithm employs a deep learning neural network, which, through training on a large amount of limb motion data, effectively improves the accuracy and robustness of motion state classification.

[0061] In this embodiment, when the smart finger is stationary in a stable environment, none of the friction sensing mechanisms generate electrical signals.

[0062] When the multi-sensor smart finger is active and / or the surrounding environment changes (such as elongation, movement, pressing contact, liquid contact, temperature change), the first friction sensing mechanism, the second friction sensing mechanism, the third friction sensing mechanism and / or the fourth friction sensing mechanism generate electrical signals. After the electrical signals are amplified and filtered by the signal processing circuit, they are connected to the microprocessor chip or load through wires. The microprocessor chip analyzes and classifies the sensor signals through a sensor signal classification algorithm to form the sensing of multiple senses.

[0063] Specifically, the algorithm flow is as follows:

[0064] 1. Raw data collection & data analysis approach:

[0065] The signal from the friction sensing mechanism is a time-domain correlated signal. Multiple actions are performed within one oscilloscope sampling period to collect a set of data, which is used to build a machine learning model and verify the reliability of the model. The original signal is the voltage response relationship with time. In this process, determining when and what kind of environmental change or movement occurred is the difficulty of the analysis, which requires the use of appropriate feature extraction methods and algorithms.

[0066] 2. Data preprocessing workflow:

[0067] First, the first derivative of the original pulse signal sequence is calculated, and then the regional extremum is obtained based on the reciprocal of the first stage. Based on the time point corresponding to the regional extremum, data of equal length around it is extracted as a feature value of an electrode. The feature values ​​of the triboelectric channel and the electromagnetic generation channel are fused together as a common feature value. Multi-channel data fusion is beneficial for including more information and improving the classification results.

[0068] 3. Using conventional methods, the data was divided into 70% training, 15% testing, and 15% validation.

[0069] 4. Classification:

[0070] In the above process, even if the regional extrema are extracted based on the derivative, perfect time alignment cannot be guaranteed. Therefore, an algorithm capable of handling temporal drift, namely the Transformer algorithm, is employed. The Transformer algorithm is a neural network model based on an attention mechanism, which can effectively process sequential data and has been widely used, especially in fields such as natural language processing. The method provided in this invention applies it to pulse signal recognition, which can fully extract the temporal information and correlation features in the signal, thereby improving the accuracy and robustness of the model.

[0071] In the Transformer model, modules such as self-attention mechanism and fully connected layer are used to extract and process features of impulse signals;

[0072] The Transformer divides the data into small segments, then compares their information and sorts them.

[0073] The processed feature vectors are input into the output layer for classification.

[0074] The smart finger based on triboelectric nanogenerator sensing described in this embodiment can realize real-time monitoring and analysis of changes in the physical information of the surrounding environment and finger movements, and has great application prospects. It can be applied to fields such as industrial production and medicine.

[0075] The smart finger in this embodiment may also include a rectifier. The electrical signal generated by the friction sensing mechanism is connected to the input terminal of the rectifier via a wire, and the output terminal of the rectifier is connected to a control motor to realize the autonomous driving of the smart finger.

[0076] Example 2 demonstrates the application of the smart finger based on triboelectric nanogenerator sensing in industrial production, as described in Example 1. This example provides an automated control sensing system. For instance... Figure 15 As shown, the system includes a multi-sensor integrated smart finger based on triboelectric effect, a robotic arm support, a servo motor and its control board.

[0077] The robotic arm support consists of a chassis 501, a turntable 502, and an arm support 503. The turntable 502 and the chassis 501 rotate and cooperate with each other, and the movable angle can reach 360 degrees.

[0078] The automated control system in this embodiment has 5 servo motors, which are respectively located at the joint connecting the first phalanx 101 and the second phalanx 102, the joint connecting the second phalanx 102 and the third phalanx 103, the chassis 501 and the arm support 503.

[0079] The servo motor on the smart finger has a maximum working angle of 180 degrees, the servo motor on the arm support 503 joint has a maximum working angle of 360 degrees, and the servo motor on the chassis 501 can work in 360 degrees.

[0080] By programming the control board, servo motors can be driven to control finger movements, thus achieving automated operation.

[0081] To meet the needs of industrial production, the smart finger can be trained in advance, and even a certain function of the finger can be enhanced. Specifically, it can meet the needs of material testing, product pressure resistance testing, and leakage detection.

Claims

1. A multi-sensor smart finger based on triboelectric effect, characterized in that: Including the first knuckle, the surface of which is covered with a first friction sensing mechanism; The second phalanx contains a second friction sensing mechanism encapsulated internally. The third phalanx contains a microprocessor chip and a third friction sensor mechanism. The connecting joint is turntable-shaped, connecting the end of the first phalanx to the front end of the second phalanx and connecting the end of the second phalanx to the front end of the third phalanx; the contact surfaces of the two connecting joints are provided with a fourth friction sensing mechanism. The servo mounting bracket is located at the ends of the first and second phalanges; The signal processing circuit connects the microprocessor chip to the first friction sensing mechanism, the second friction sensing mechanism, the third friction sensing mechanism, and the fourth friction sensing mechanism via wires. The upper surface of the first phalanx is provided with a centripetal inclined surface and a drainage channel, and the interior of the first phalanx is provided with a liquid storage cavity; the second phalanx has a semi-closed cavity structure and is provided with a first cap; the third phalanx has a semi-closed cavity structure and is equipped with a second cap, and the bottom end of the third phalanx is provided with a through hole and the top end is provided with a rectangular opening; The first friction sensing mechanism has a friction layer and an electrode layer that are the same shape as the first finger joint, and an insulating layer is provided between part of the friction layer and the electrode layer; The electrode layer of the second friction sensing mechanism is disposed on the inner wall of the cavity that contacts the lower surface of the movable friction cube, and the surface of the movable friction cube is provided with a friction layer; The third friction sensing mechanism is arched in shape, with the electrode layer fixed at both ends and bent into an arched structure in the middle. The fourth friction sensing mechanism is disc-shaped, with a fan-shaped friction layer and an interdigitated electrode layer, and an insulating layer between the friction layer and the electrode layer; wherein the interdigitated electrode layer includes a multi-finger first electrode and a second electrode; the first electrode and the second electrode are arranged in an opposing and intersecting manner; The first friction sensing mechanism realizes the sensing of liquid, material and pressure, the second friction sensing mechanism realizes the sensing of acceleration, the third friction sensing mechanism realizes the sensing of temperature change, and the fourth friction sensing mechanism realizes the sensing of angle.

2. The method of using the multi-sensor smart finger based on triboelectric effect according to claim 1, characterized in that: In a stable environment, when the multi-sensor smart finger is stationary, none of the friction sensing mechanisms generate electrical signals. When the multi-sensor smart finger moves and / or the surrounding environment changes, the first, second, third, and / or fourth friction sensing mechanisms generate electrical signals. After being amplified and filtered by the signal processing circuit, the electrical signals are connected to the microprocessor chip through wires. The microprocessor chip analyzes and classifies the signals using a machine learning model to form a sensing of multiple senses.

3. The application of the multi-sensor smart finger based on triboelectric effect according to claim 1, characterized in that: A multi-sensor smart finger, operated automatically by a human or machine, collects electrical signal characteristics generated when the smart finger moves and / or the surrounding environment changes. A machine learning model is then established to learn, identify, and classify these electrical signal characteristics, forming a sensing capability for multiple senses, which can then be used to monitor movement and / or environmental changes.

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