547 results about "Mems sensors" patented technology

The invention relates to the technical field of medical equipment, in particular to an intelligent dynamic monitoring and evaluation system for altitude sickness and wearable equipment thereof, and the system comprises a physiological parameter monitoring module, an environmental parameter monitoring module, a data processing and analysis module and a user interaction and feedback module; high-precision physiological parameter monitoring is carried out by combining multi-lead ECG and PPG technologies, intelligent data processing and real-time health early warning are realized by utilizing a multi-layer deep learning neural network and a fuzzy logic system, precise environmental parameter monitoring is carried out by integrating an MEMS sensor technology, and personalized health management suggestions are provided for users.

The invention relates to the technical field of engineering mechanical structure health monitoring, and discloses a carry-scraper structural member crack real-time detection system and method based on vibration characteristics, and the carry-scraper structural member crack real-time detection system based on vibration characteristics comprises a sensing acquisition module which is used for acquiring structural member vibration response and obtaining an original signal; the signal processing module is used for carrying out wavelet denoising on the original signal and extracting effective vibration data; the feature extraction and dynamic calibration module is used for extracting multi-domain features and performing dynamic calibration in combination with working conditions; the crack recognition and intelligent diagnosis module is used for inputting an intelligent model to recognize a crack state; and the crack positioning and alarm feedback module is used for positioning cracks and giving an alarm in combination with the diagnosis result. According to the invention, the multi-modal sensor array is constructed, piezoelectric and MEMS sensors are cooperatively arranged, a magnetic snap-in type installation structure is combined, broadband response signals are stably collected under different working conditions, and then front-end signal optimization is completed in cooperation with a multi-scale wavelet denoising and standardization mechanism.

The invention relates to a high-precision data acquisition method and system for an MEMS sensor, and the method comprises the following steps: carrying out the multi-channel parallel sampling of an initial electric signal outputted by the MEMS sensor, and obtaining an original data flow matrix; performing adaptive denoising processing on the original data stream matrix to obtain a denoised data set; performing signal phase reconstruction on the noise reduction data set through a phase unwrapping technology to obtain a continuous phase feature sequence; performing dynamic drift compensation on the continuous phase feature sequence to obtain a calibration signal vector; performing transient characteristic extraction on the calibration signal vector to obtain a sensor response characteristic curve; and performing high-precision data resampling on the sensor response characteristic curve based on an adaptive quantization coding technology to obtain a high-precision data acquisition result, thereby solving the technical problem of how to effectively remove noise interference generated in a multi-channel parallel sampling process.

The invention provides a low-cost and high-integration meteorological detection system for low-altitude meteorological service, and belongs to the technical field of meteorological detection. The low-cost and high-integration-level meteorological detection system for the low-altitude meteorological service comprises a plurality of small meteorological stations and MEMS sensors integrated with temperature, humidity, air pressure, wind speed, wind direction and the like. A plurality of small laser wind finding radars are based on an optical fiber laser and a VCSEL (Vertical Cavity Surface Emitting Laser) technology and adopt a modular design. And the data fusion module is used for fusing multi-source data of a ground station, a laser radar, a satellite and the like by adopting a four-dimensional variation assimilation algorithm to generate a 100-meter-resolution grid meteorological product. The technical bottleneck of traditional low-altitude meteorological detection is broken through, and a meteorological service solution is provided for the fields of urban fine management, navigation safety, intelligent agriculture and the like. The system has the characteristics of high cost performance, high flexibility and high resolution, and promotes low-altitude meteorological observation to be upgraded from sparse monitoring to global sensing.

A MEMS sensor and a preparation method therefor. The method comprises: forming a first oxide layer on a substrate wafer, performing patterned etching on the first oxide layer, and performing deposition and doping on the first oxide layer that has undergone the patterned etching, so as to form a first polycrystalline silicon layer; performing patterned etching on the first polycrystalline silicon layer to form a wiring, and depositing a second oxide layer on the first polycrystalline silicon layer; upon performing patterned etching on the second oxide layer, performing deposition and doping to form a second polycrystalline silicon layer; performing patterned etching on the second polycrystalline silicon layer to form bonding anchor points and a capacitive plate having a lower height than the bonding anchor points; bonding a device wafer with the bonding anchor points, and performing patterned etching on the device wafer to generate a movable structure, so as to obtain a device layer; and bonding the side of the device wafer distant from the substrate wafer with a cover layer.

According to the mobile phone terminal multi-source fusion 3D visual high-precision indoor navigation method, firstly, an improved robust PDR scheme based on a built-in MEMS sensor of an intelligent terminal is constructed, a dynamic optimal filtering measurement model is constructed by taking INS as core optimization and utilizing multilayer constraint data as observation data, sensor errors are estimated and compensated in real time, and robustness and positioning precision are improved; secondly, establishing a shortest path constraint improved magnetic field matching algorithm, adding the magnetic declination as a magnetic field fingerprint of one dimension into the magnetic field matching algorithm, respectively solving a shortest path constraint result by utilizing the magnetic field fingerprints of multiple dimensions, solving an overall matching result, and reducing a mismatching probability; and finally, by utilizing complementary characteristics of different positioning data sources, an algorithm fusing PDR, magnetic field and Bluetooth multi-source data is established, a quality control mechanism is set, the precision and the robustness of the positioning system are improved, the visual indoor positioning system based on the intelligent terminal is realized, and the integrated navigation positioning precision and the robustness are good.

The invention discloses a multi-mode water-air-land cross-medium cooperative sensing system and method based on an MEMS (Micro Electro Mechanical System). The system comprises an underwater robot, a buoy station, an unmanned aerial vehicle and a ground control station, each node is provided with an MEMS sensor integrating acoustics, optics, magnetism, inertia and other modes, and data transmission and relay are achieved through acoustics, optical communication and radio links. And the ground control station carries out fusion processing, target identification and decision control on multi-source data through time synchronization and space registration, and issues a cooperative instruction to each node to realize a perception-decision-re-perception closed loop. The method comprises five steps of node deployment and calibration, multi-modal data acquisition, hierarchical transmission and sharing, adaptive weighted fusion and closed-loop cooperative control. According to the invention, global coverage, high-precision and multi-mode environment and target perception can be provided in a complex water-air-land environment, and the detection reliability and the communication efficiency are significantly improved.

The invention discloses an optical terminal intensity instrument and an earthquake monitoring service system and method, and the optical terminal intensity instrument comprises an optical fiber modem and an MEMS sensor module. The optical fiber modem comprises an MCU (Microprogrammed Control Unit) and an optical communication module electrically connected with the MCU; the optical communication module is used for realizing network access and data uploading; the MEMS sensor module is electrically connected with the MCU; the MEMS sensor module is used for collecting seismic intensity data in real time; and the optical fiber modem is used for providing a dual data transmission channel comprising broadband communication and the seismic intensity data. According to the technical scheme provided by the invention, the MEMS sensor is embedded in the optical fiber modem, and a more dense, more efficient and more economical solution is provided for earthquake early warning and intensity rapid reporting.

Microelectromechanical systems (MEMS) apparatuses and processes are described that can employ a spring pillar or flexible pillar coupled to a sensing membrane to enhance deformation of the sensing membrane while providing robust MEMS sensors or devices. Described MEMS sensors or devices can comprise an exemplary spring pillar or flexible pillar between the sensing membrane structure and the backplate structure. Exemplary spring pillar or flexible pillar can facilitate adjusting stiffness of the sensing membrane to provide MEMS sensors or devices having large sensing area and compact device size.

The invention relates to the technical field of energy storage cabinet safety monitoring, in particular to an energy storage cabinet multi-parameter intelligent monitoring device based on an MEMS sensor array, a sensor array unit in the energy storage cabinet multi-parameter intelligent monitoring device comprises distributed MEMS temperature and vibration sensors, the temperature sensors are installed in a non-vertical mode, detection deviation caused by direct blowing of airflow is avoided, and the energy storage cabinet multi-parameter intelligent monitoring device based on the MEMS sensor array is obtained. The airflow disturbance correction unit corrects temperature original data in real time and eliminates interference of airflow on module body temperature detection by means of a heat dissipation airflow vector field dynamic model and a compensation algorithm, and the multi-parameter coupling analysis unit processes vibration and temperature signals in a double-channel mode, extracts tab loosening high-frequency micro-vibration characteristics and correlates the temperature rising rate. Early fault logic is triggered through two-stage judgment, the fault decision and output unit fuses the correction temperature, the coupling strength coefficient and the speed-up ratio, graded early warning is generated through a fault tree model and transmitted to an external monitoring system, and accurate monitoring of early faults of the energy storage cabinet is achieved.

The invention discloses a deep learning correction system for an MEMS sensor, and relates to the technical field of sensor correction, and the system comprises a multi-source data collection module which collects various data in real time, verifies and caches the data, and transmits the data; the feature extraction and analysis module processes the data and extracts features, and transmits the features to the drift detection modeling and motion impact discrimination module; modeling, calculating, monitoring sudden change and synchronizing information; the event type output result is judged; the correction decision execution module executes correction accordingly, and is internally provided with self-checking and fine tuning functions to guarantee the stability of the system; according to the invention, technologies of multi-source data acquisition, multi-dimensional feature analysis, coupling dynamic regression, deep convolutional neural network and the like are fused, so that comprehensive sensing and accurate drift detection of the sensor are realized; and through collaborative operation of an attention fusion joint discrimination algorithm and the like, event types are accurately distinguished and targeted correction is performed, the system stability is maintained, and the measurement precision and the practical value are improved.

The invention provides an MEMS inertial three-dimensional displacement monitoring method and system, and relates to the technical field of MEMS sensors, and the method comprises the steps: obtaining acceleration and angular velocity signals of an inertial measurement unit, and generating a dynamic acceleration after attitude calculation, error compensation and gravity removal; updating a group of state variables containing position and speed information in real time through integral operation so as to obtain continuous first displacement information with drifting; under a preset condition, measuring the absolute position of the object by using an external acoustic positioning system so as to obtain accurate and drifting-free second displacement information; the state variable is corrected by a fusion process using a deviation between the first and second displacement information, and position information is extracted from the corrected state variable as a final output. The advantages of inertial measurement and external positioning are combined, integral drift is effectively inhibited, and the precision and reliability of long-term monitoring are remarkably improved.

The invention discloses a comprehensive safety monitoring system for a building structure. The comprehensive safety monitoring system comprises an equipment sensing unit, a data processing unit, a system management unit, a terminal monitoring platform and a communication unit. The sensing module is integrated in the equipment main body of the equipment sensing unit, the equipment sensing unit is convenient to install and use, the MEMS sensor technology based on microelectronic elements and micromechanical elements is adopted, the acceleration, angle, temperature and humidity, wall internal stress and settlement change of a building structure are accurately monitored, and the construction quality is improved. According to the method, a plurality of algorithm models in an algorithm processing module of a data processing unit are matched, the health state of a monitoring structure is comprehensively judged, abnormal data are classified and managed according to disaster types, corresponding emergency rescue measures are intelligently recommended, and according to the autocorrelation and seasonality of sensing data and based on historical data, the monitoring structure is monitored. The method is used for predicting the trend of future sensing data, and predicting potential risks possibly occurring in the future in cooperation with a danger data threshold value, set by the system, of a building structure and big data analysis.

The invention provides an orthodontic pressure real-time detection device integrated with MEMS (micro-electromechanical systems) sensors, which comprises a plurality of internal terminal systems packaged on a flexible printed circuit board and an external host system connected through wireless network signals, and the internal terminal systems are integrally mounted in an invisible orthodontic appliance diaphragm or an invisible orthodontic appliance resin accessory. The MEMS flexible diaphragm can also be manufactured into an independent MEMS flexible diaphragm which can be used for orthodontic force measurement; wherein the internal terminal system comprises an ASIC (Application Specific Integrated Circuit) chip assembly and an antenna, and the ASIC chip assembly comprises an ASIC chip and an MEMS (Micro Electro Mechanical System) sensor array connected with the ASIC chip; compared with the prior art, the invention has the following beneficial effects: the MEMS sensor array which is small in size and easy to integrate is utilized to realize multi-point stress measurement on each tooth at the same time, pressure information of the teeth of a user is collected through the MEMS sensor array and then is sent to the ASIC chip, the ASIC chip sends the information to the computer, and the computer is connected with the MEMS sensor array. Therefore, the stress condition of the teeth can be monitored in real time in the correction process.

The invention belongs to the technical field of sensors, and particularly relates to a TSV-based MEMS capacitive accelerometer wafer-level packaging structure and packaging method. A gold-silicon bonding and TSV (Through Silicon Via) combined technology is adopted, and a gold layer is used as a bonding medium and a sensor capacitor polar plate, so that the problem of integration of a polar plate structure and signal lead-out in an MEMS sensor is solved, the design that an independent electrode layer or an additional polar plate is needed in traditional packaging is avoided, and the packaging complexity is reduced. Meanwhile, the gold layer has low resistance and good conductivity, compared with a traditional electrode material, signals can be better transmitted, and the electrical performance of the MEMS sensor is improved. After the TSV technology is combined, short-path signal extraction can be realized in the wafer, signal attenuation and interference are reduced, and signal integrity and precision are improved.

The invention relates to an inertial navigation device based on multiple MEMS sensors. Comprising an MEMS sensor array and a control unit, wherein the MEMS sensor array comprises n MEMS sensors with a set layout, and n is greater than or equal to 2; each MEMS sensor is connected to the control unit through a control switch; the output end of each MEMS sensor is connected to the control unit; the control unit is configured to be used for collecting initial measurement data of each MEMS sensor, selecting a plurality of better target MEMS sensors from the MEMS sensor array, and correcting and fusing the initial measurement data of the target MEMS sensors to obtain inertial measurement data; and outputting a switch control signal to the control switch so as to open or close the MEMS sensor to output initial measurement data. According to the technical scheme, the initial measurement data of the better MEMS sensor is used for obtaining the inertial measurement data, so that the measurement precision is improved, and the use effect of inertial navigation is improved.

The embodiment of the invention provides a Beidou water vapor inversion method and system based on a buoy platform. The method is applied to the technical field of data processing, and comprises the following steps: receiving a Beidou dual-frequency signal through a direct antenna to obtain original observation data; the multi-path effect and the platform shake are inhibited by combining buoy motion characteristics obtained by the MEMS sensor to obtain pre-processed data; calculating a troposphere delay estimated value; establishing a delay-water vapor conversion model; suppressing short message interference to obtain effective observation data; and inputting the data into a model to calculate the amount of precipitable water and the relative humidity. According to the method, the key technical problems of sea surface multi-path effect suppression, platform shake compensation, marine atmosphere modeling, short message interference elimination and the like are solved, so that reliable water vapor parameter inversion on the buoy platform is realized.

The invention belongs to the field of MEMS sensors, and discloses a high-temperature-resistant MEMS pressure sensor chip and a packaging structure thereof. The chip is provided with an SOI substrate, an AlN layer and a SiO2 layer from bottom to top, a plurality of P-type piezoresistors are arranged on the uppermost layer of the SOI substrate and are symmetrically distributed at the stress concentration position of the edge of the elastic diaphragm; a channel which continuously penetrates through the AlN layer and the SiO2 layer is arranged above the P-type piezoresistor; a metal Pad is arranged in the channel; the upper end of the metal Pad is located on the uppermost layer of the high-temperature-resistant MEMS pressure sensor chip, and the lower end of the metal Pad is in contact with the P-type piezoresistor. According to the invention, the relatively thick buried oxide layer can resist a high-temperature severe environment, and an AlN heat dissipation material with a high heat conductivity coefficient is deposited, so that rapid heat dissipation at a high temperature is ensured; and meanwhile, the stability and the reliability of the sensor are improved by adopting leadless packaging, and the packaging density is further optimized.

The utility model discloses an MEMS sensor and an electronic atomization device. The MEMS sensor comprises a substrate, a base plate, a first polar plate, a second polar plate and a conductive contact. The first surface of the substrate is provided with a groove, the second surface of the substrate is provided with a Wheatstone bridge circuit, and a bridge arm of the Wheatstone bridge circuit comprises a piezoresistor; the substrate covers the groove to form a sealed cavity; the first polar plate is arranged on the bottom wall of the groove; the second polar plate is arranged on the substrate and is spaced from the first polar plate; the conductive contact is arranged on the substrate and / or the base plate and is electrically connected with at least one of the first polar plate and the second polar plate; the first pole plate and the second pole plate are configured to be capable of repelling or attracting each other under the power-on condition. Through the mode, the deflection of the strain film is always small, so that the problem that the deformation of the substrate does not have ideal linear change with the pressure is well improved, and the detection precision of the MEMS sensor is improved.

The invention belongs to the technical field of power equipment monitoring, and discloses a quantum sensing and MEMS sensing integrated partial discharge detection device and method. Partial discharge signals are collected through the quantum sensor and the electric field sensor; the data acquisition card transmits data to the microprocessor, the microprocessor judges the discharge type by using a wavelet transform method, extracts characteristic parameters, transmits the data to the computer, analyzes and determines calculation weights of different sensors according to the characteristic parameters to perform data fusion, and calculates and displays the partial discharge electric field intensity. According to the method, data fusion of the quantum sensor and the MEMS sensor is realized, more comprehensive and accurate information is provided, the source and characteristics of partial discharge can be better identified, the diagnosis accuracy and the reliability of a detection system are improved, false alarm and missing alarm are reduced, and reliable data are provided for the operation state, fault diagnosis and maintenance of power equipment.

An assembly is provided which includes a package and a printed circuit board. The package includes a housing bounding a region and an acoustic sensor within the region. The housing includes a base with a first hole. The sensor is configured to generate signals indicative of sound received by the sensor through the first hole. The printed circuit board is in mechanical communication with the base and includes a second hole aligned with the first hole such that sound received by the second hole propagates through the first hole to the sensor. The printed circuit board further includes an electrically conductive layer, at least a portion of which extends across the second hole and is configured to allow the sound to propagate through the second hole and to at least partially shield the region containing the sensor from electromagnetic interference.

The invention discloses an MEMS sensor based on a half cymbal structure and a preparation method thereof. The preparation method comprises the following steps: providing a substrate; a first structure layer is formed on one side of the substrate and comprises an end cover layer, the end cover layer comprises a first horizontal part, an inclined part and a second horizontal part, the two ends of the inclined part are integrally connected with the first horizontal part and the second horizontal part respectively, the first horizontal part is located on the substrate, and the second horizontal part is parallel to the first horizontal part; a first gap is formed between the substrate and the end cover layer; sequentially forming a lower electrode layer, a piezoelectric layer and an upper electrode layer on one side, far away from the substrate, of the first structure layer; a second gap exists between the lower electrode layer and the end cover layer. Through the method, the preparation process of the micron-sized MEMS sensor is simplified, and the production yield and the production efficiency of the MEMS sensor are improved.

The invention discloses a shear stress microsensor based on lens array optical conduction and a packaging method thereof, and belongs to the technical field of MEMS sensors. Comprising an optical fiber, a transmission lens group, an MEMS chip, a reflection lens group and a photoelectric detector which are sequentially arranged along an optical path, an optical signal transmitted by the optical fiber is transmitted to the MEMS chip through the transmission lens group, the optical signal carrying displacement is reflected through a reflection grating of the MEMS chip, and the reflected optical signal is transmitted to an effective working area of the photoelectric detector through the reflection lens group; optical signals are converted into electric signals through a photoelectric detector, so that displacement information used for calculating shear stress is obtained. According to the invention, the problems of optical fiber displacement and angle deviation which are easy to occur when the optical fiber is fixed by adhesive are effectively avoided, the optical loss is reduced, and the transmission efficiency and stability of optical signals are improved, so that the sensitivity of the sensor is enhanced. The problems of large optical path transmission loss, poor stability and the like are solved.

The invention discloses an outdoor static measurement MEMS sensor sensitivity calibration method, and relates to the technical field of sensor calibration, and the method comprises the specific steps: firstly constructing dual references including a factory reference and a field relation; synchronously collecting multi-source data according to a set period, and preprocessing to obtain an effective sequence; then double check chain fitting key indexes are started in parallel; if a collaborative judgment result is conflicted, high-grade diagnosis is triggered; after diagnosis, the acquisition period of sensitivity drift is prolonged, and parameters are recalculated; and finally, if the conditions are met, solidifying calibration parameters, installing a fault output alarm, and uploading whole-process data records to the cloud. According to the method, the sensitivity calibration of the sensor is guaranteed by constructing double references, multi-source data are synchronously acquired, and the performance is evaluated through double check chains. The efficiency is improved through round-robin scheduling of time slices, effective data are reserved through data preprocessing, differential processing is carried out after fault diagnosis, whole-process data recording and uploading are carried out, calibration parameters are solidified, it is guaranteed that the result is effective, and the application range is widened.

The invention belongs to the technical field of MEMS sensor signal processing, and discloses an MEMS sensor signal processing method and system based on an RLS-VMD fusion algorithm, and the method comprises the steps: continuously collecting an original acceleration signal at a preset sampling frequency through an MEMS sensor; offset in the original acceleration signal is eliminated through iterative calculation based on an RLS algorithm, and an offset correction signal and a residual error are obtained; a dynamic energy threshold value is obtained based on residual calculation, and frequency characteristic secondary verification is carried out on each screened modal component; carrying out superposition reconstruction to obtain an acceleration signal; and taking the purified acceleration signal as input, performing two times of integral operation based on the Newton's law of motion to realize displacement calculation, and finally outputting a displacement signal. According to the method, a correlation mechanism of RLS offset correction and VMD screening parameters is established, deep collaboration is achieved, and finally the acceleration signal processing quality and the displacement calculation precision of the MEMS sensor are improved.

A manometric catheter probe includes a flexible printed circuit, one or more pressure sensor assemblies coupled to the flexible printed circuit along a length of the flexible printed circuit, and a first flexible sleeve. Each pressure sensor assembly includes a body. The body includes a central cavity configured to receive the flexible printed circuit and an annular recess of the body. Each pressure sensor assembly further includes a microelectromechanical systems (MEMS) sensor disposed in the annular recess, an electrical connector configured to electrically couple the MEMS sensor and the flexible printed circuit, and a first flexible sleeve disposed over the annular recess of the body. The first flexible sleeve includes a fluid configured to communicate pressure to the MEMS sensor, and a second sleeve is disposed over the pressure sensor assembly.

The invention relates to the technical field of gas parameter extraction, in particular to a gas physical property parameter extraction method based on micro thermal field dynamic characteristics, which comprises the following steps: applying a sweep frequency excitation electric signal to a micro heater of an MEMS sensor, collecting and processing an original dynamic response signal, and generating frequency domain response data; constructing a parameterized extraction model, extracting real-time physical property parameters from the frequency domain response data, substituting the real-time physical property parameters into a signal-to-noise ratio objective function, and calculating and generating optimized excitation parameters; generating an updated sweep frequency excitation electric signal based on the optimized excitation parameter; acquiring and generating reference frequency domain response data; actually measured physical property parameters are extracted from the reference frequency domain response data, a measurement deviation signal is generated through comparison, and online calibration and correction are conducted on internal coefficients of the parameterized extraction model. According to the method, the frequency domain response of the dynamic micro thermal field is subjected to decoupling analysis, and an online self-adaption and self-correction mechanism is combined, so that accurate and reliable online extraction of the physical property parameters of the complex mixed gas is realized.

The invention belongs to the field of deep foundation pit intelligent supporting systems, and particularly relates to a deep foundation pit intelligent supporting system based on oblique beam grid and digital twinning and a collaborative construction method.The deep foundation pit intelligent supporting system based on oblique beam grid and digital twinning comprises an oblique beam grid supporting structure composed of two-way crossed steel oblique beams, and the outer layer of each steel oblique beam is a Q355B steel pipe with the thickness not smaller than 12 mm; the inclined beam is filled with ultra-high performance concrete with the compressive strength not smaller than 150 MPa, the inclination angle of the inclined beam ranges from 25 degrees to 60 degrees, and an MEMS micro-electro-mechanical system sensor is pre-buried at a node; and the digital twin platform integrates the geological BIM model and the LSTM neural network prediction model. The bending rigidity is improved through the oblique beam grid supporting structure and the concrete filled steel tube composite beam, the inclination angle ranges from 25 degrees to 60 degrees, force flow transmission is optimized, and micro-strain-level stress monitoring is achieved through the MEMS sensors embedded in the nodes. A digital twin platform and an LSTM model are fused with 12-dimensional parameters, the 72-hour deformation prediction error is smaller than or equal to 1.5 mm, and compared with a traditional experience algorithm, the precision is improved.

The invention discloses an overlapping structure comb tooth capacitance type Z-axis acceleration sensitive chip and a manufacturing method thereof, and belongs to the technical field of MEMS sensors. The sensitive chip is formed by overlapping a comb tooth capacitor layer and an elastic beam structure layer, and the comb tooth capacitor layer and the elastic beam structure layer are bonded together through an oxide layer. In addition to the advantage of small damping coefficient, the comb capacitor has the following three advantages: 1, the structure of overlapping the comb capacitor and the elastic beam does not need to occupy extra chip area, which is beneficial to microminiaturization and can reduce chip cost at the same time; secondly, the comb capacitor and the elastic beam are overlapped, so that the elastic beam is prevented from occupying the space for distributing the comb teeth around the mass block when the comb capacitor and the elastic beam are placed in a plane, the number of the comb teeth is greatly increased, and the capacitance of the comb structure is effectively increased; and thirdly, the elastic beams can be symmetrically distributed around the mass block due to the overlapping structure, and the cross coupling influence in the X-axis direction and the Y-axis direction is remarkably reduced.

The invention discloses an earphone space audio positioning method integrated with an MEMS sensor and a control system, and relates to the field of earphone space audio positioning. A temperature compensation MEMS sensor group and a microphone array are used for collecting motion data and sound wave signals, and signals are enhanced through orthogonal wavelet denoising and beam forming; the attitude is solved by adopting double-extended Kalman filtering and fusing data, and fuzzy logic is introduced to evaluate the credibility of the sensor; predicting a sound field by using a CNN model, and reconstructing the sound field in combination with an adaptive wave field synthesis technology; and based on auditory masking effect optimization balance, the influence of altitude on sound velocity is compensated. Through an ultra-precision sensor and an advanced algorithm, the positioning precision and reliability of earphone space audio are improved, and delay and power consumption are reduced; accurate sound source positioning, personalized sound field adaptation and cross-modal immersion experience in a complex scene are realized, and the audio experience of a user is improved.