Research On Self-powered Sensors Based On Triboelectric/Piezoelectric Energy Conversion

With the progress of information technology and the rapid development of The Internet of things,many intelligent devices have been widely used in our daily lives,such as intelligent manufacturing,intelligent agriculture,intelligent family,public security,intelligent medical treatment,urban management and so on.Sensors,as a bridge between intelligent devices and the outside,play an important role in these functions.At present,most sensors need to be powered by external power,and the common modes of power supply are battery power and grid power.However,the battery mode needs to replace the battery frequently,and the grid mode increases the complexity of the system,which not only increases maintenance costs,but also hinders the development of Internet of things technology.To solve the above problems,scientists propose the concept of self-powered sensors based on nanogenerator technology.By converting environmental energy into electrical energy,the self-powered sensor can passively convert environmental mechanical disturbances into electrical signals.It could therefore get rid of the dependence on the battery and be an important part of the sensor of the Internet of things.Triboelectric/piezoelectric nanogenerator can not only collect environmental mechanical energy and convert it into electrical energy,but also be used as a self-powered sensor due to its sensitivity to environmental mechanical disturbance.Based on it,this dissertation develops six kinds of self-powered sensors with different structures for various applications.Combined with the analysis of working principle,modeling,simulation,and experimental research in output performance,this dissertation explores its potential application value in terms of mechanical fault diagnosis,voiceprint recognition,infant care,flexible sensing,temperature monitoring,and sewage ion monitoring.The main work of this paper is as follows:（1）Two kinds of triboelectric sensors for fault monitoring and diagnosis of mechanical equipment are developed.The first triboelectric sensor can monitor the bolt looseness and equipment inclination of mechanical equipment.The sensor can convert the mechanical signal generated by the contact and separation of PTFE balls and copper electrode into an electrical signal during equipment vibration.Through the experimental test,it is found that the electrical output performance of the sensor is not only related to the diameter and number of balls,but also varies to the inclination angle and the change of external vibration frequency.The experiments prove that the sensor has a response time of 55 ms,a signal-to-noise ratio is 29.12 dB,and a sensitivity is 14mV/Hz.When the equipment shows signs of bolt looseness or inclination,the output signal of the sensor will change significantly if fix the sensor on the vibrating mechanical equipment,helping to find and eliminate faults in time.This work shows that the developed self-powered sensor has potential application value in the diagnosis of mechanical equipment bolt looseness and equipment inclination,providing important guidance for the intelligent fault diagnosis and monitoring of mechanical equipment in the future.The second triboelectric sensor can monitor the loss of the piston ring and the fracture of electrodes in the closed structure of the piston-cylinder.The working principle of the sensor relies on the periodic distance change between the piston ring and the electrode when the piston moves in the cylinder,which realizes the conversion of the mechanical signal to an electrical signal,solving the problem of integration of sensor and equipment.The sensor has a response time of 15 ms,a signal-to-noise ratio of 24.6 dB,and a sensitivity of 1.6μA/m·s^-1.Experiments show that the output performance of the sensor is sensitive to the change in the moving speed of the piston and the number of piston rings.It has been proved that the sensor can effectively detect the piston ring loss fault and electrode fracture fault,and it is also able to locate its fault location accurately.This work provides a new solution for fault monitoring and diagnosis of closed structures.（2）Two kinds of triboelectric sensors for biomechanical signal monitoring are developed.The first triboelectric sensor can realize accurate recognition of human voices.The PDMS film of the sensor can vibrate regularly under the action of sound,leading to a periodic change of the distance between the PDMS film and the aluminum electrode,realizing a convention from the mechanical signal to an electrical signal.The experiments prove that the sensor has a response time of 60 ms,a signal-to-noise ratio is 18.66 dB,and a sensitivity is 0.041 V/mm.The experiment proves that the sensor is recognizable for different human languages.At the same time,it also proves that the fabricated sensor has a relatively stable recognition ability for the human language for the same person.The sensor is formed by full 3D printing technology at one time,which not only enhances the interchangeability of the sensor,but also effectively avoids the cumbersome manufacturing process and high manufacturing cost.This work provides an important reference for wireless transmission and accurate recognition of human language.The second triboelectric sensor can convert the biological mechanical signal generated by the infant during movement into an electrical signal,which can be used for intelligent infant care.The sensor is made of gelatin,agar,and seaweed,all of which are edible,avoiding the risk of accidental swallowing by infants.After analyzing and studying the electrical output performance of the sensor,it has been proved that the sensor has a response time of 50 ms,a signal-to-noise ratio is 23.1 dB,and a sensitivity is 0.28 V/kPa.Subsequently,two modes of infant care are proposed.For the passive monitoring mode,the sensors are stuck onto the edge of the bed.When the infant touches the sensors,it means the infant enters a dangerous area,and the sensor can send an alarm to the system;for the active monitoring mode,multiple sensors are attached to the different positions of the infant’s body.When the infant moves,the multi-channel data acquisition system can collect the signal characteristics of each sensor in real-time,and recognize the specific movements of the infant with help of a deep learning algorithm,which finally realizes the real-time monitoring for the infant.This self-powered sensor provides a promising paradigm for intelligent monitoring of infants.（3）A flexible and stretchable piezoelectric self-powered sensor is developed to monitor joint motion,vibration frequency,and mechanical collision.Aiming to eliminate the disadvantage of non-stretchability and inflexibility that commonly exist in traditional rigid piezoelectric sensors,a self-powered piezoelectric sensor with a serpentine structure is made by improving the structure of PVDF film,which can not only be stretched,but also induce the piezoelectric charges due to the strain generated on its surface during stretching,realizing the transformation from mechanical signal to an electrical signal.The sensor has a response time of 52 ms,a signal-to-noise ratio of15.45 dB,and a sensitivity of 6.83 mV/mm.In the experiment,it is found that the sensor is very sensitive to the change of stretching rate,and it is also proved that the sensor can sense the change of small motion of human/robot joint.At the same time,sensors also have successful applications in sensing mechanical force.The sensor can not only have a high monitoring ability for the change of vibration frequency in a certain range,but also accurately monitor the location of mechanical collision in the sensor network composed of multiple groups of sensors.This work has played an important role in promoting the development of flexible self-powered sensors.（4）A self-powered water-quality-monitoring sensor with a coupling triboelectric/magnetoelectric generator is designed for water temperature monitoring and sewage ion monitoring.The shape memory alloy wire could drive the belt to rotate due to the deformation stress generated by temperature change,converting the temperature signal to a mechanical signal,and then convert the mechanical signal to an electrical signal based on triboelectric nanogenerator technology and electromagnetic power generation technology.The experiments prove that the sensor has a response time of 12 ms,a signal-to-noise ratio is 27.53 dB,and a sensitivity is 0.12 V/℃.Experiments prove that the sensor has a successful application in monitoring the water temperature of automobile water tank and sewage ion,which has promoted the development of automobile intelligent sensing monitoring and portable sewage ion monitoring.