22462 results about "Electric signal" patented technology

The invention provides a defect detection method and system for integrated circuit manufacturing. Wherein in the integrated circuit packaging stage, packaged chips are divided into a first type of chips meeting a preset physical characteristic threshold value and a second type of chips exceeding the physical characteristic threshold value through a pneumatic sorting device; performing scanning electron microscope imaging on the surface of the second type of chip, generating a three-dimensional topological structure by using an image reconstruction technology, and positioning a micron-sized particle defect area by comparing reference type differences; synchronously applying high-frequency electric signal excitation in the sorting process, detecting impedance response of the second type of chips, and recording an abnormal signal sequence exceeding a preset frequency domain range; performing space-time correlation matching on the micron-sized particle defect area and the abnormal signal sequence, and judging that the defect is a multi-layer composite defect when a preset coupling condition is met; and dynamically adjusting the mesh diameter and vibration frequency parameters of the pneumatic sorting device. According to the technical scheme provided by the invention, accurate identification of the multi-layer composite defect of the chip is realized, and the defect interception efficiency is remarkably improved.

The invention provides a power cable joint insulation state intelligent monitoring method based on a complex environment. The method belongs to the technical field of power system monitoring, and comprises the steps that related data are collected through multiple means, and the related data comprise environment temperature data, partial discharge signals and temperature distribution images; collected environment parameters and partial discharge signals are input to an intelligent analysis system, preprocessing and feature extraction are carried out, an insulation state prediction model is established based on a machine learning algorithm, and the aging degree and potential fault points of a cable joint insulation layer are predicted according to historical data and real-time monitoring data. Environment temperature data, partial discharge signals and temperature distribution images are collected through multiple means, and an intelligent analysis system and a machine learning algorithm are combined, so that the aging degree and potential fault points of the cable joint insulating layer can be predicted more accurately.

The invention discloses a visual inspection system for appearance defects of a pressure sensor, and relates to the technical field of visual inspection of defects. Comprising a light source control module, an image acquisition module, an image preprocessing module, a feature extraction module, a defect identification module, an evaluation grading module, a result display module and a man-machine interaction module which are integrated on the appearance defect AOI equipment, and all the modules are connected through electric signals. According to the visual inspection system for the appearance defects of the pressure sensor, through the high-precision industrial camera and the advanced image processing technology, precise recognition of tiny defects on the surface of a product is achieved, compared with a traditional manual inspection mode, higher inspection precision is achieved, tiny scratches and sunken defects which are difficult to perceive by human eyes can be found, and meanwhile, the visual inspection system is convenient to use. The automatic detection process greatly shortens the detection time and improves the production efficiency, and the system can detect a large number of products in a short time.

The invention relates to the technical field of probe testing, and discloses a probe testing device and method, and the method comprises the steps: carrying out the synchronous collection of the electric signal response characteristics of a plurality of chip testing probes in a chip contact process, analyzing the signal transmission interference relation between the probes, and obtaining a multi-probe signal coupling feature pattern; identifying a target signal transmission channel to obtain a first test probe configuration scheme; performing test signal input and response acquisition on the chip to obtain electrical characteristic time-frequency data of the chip; and performing multi-probe collaborative analysis and feature extraction on the time-frequency data of the electrical characteristics of the chip to obtain abnormal indication information of the electrical performance of the chip, and adjusting test parameters and contact positions of a plurality of chip test probes to obtain a configuration scheme of a second test probe. Therefore, the test system can intelligently adjust the subsequent test strategy according to the preliminary test result, and the intelligence and automation of the test process are realized.

A cart system includes a plurality of carts, each cart having a battery, a processor and at least one switching and conditioning circuit, the plurality of carts physically coupled in a mutual and external charging configuration, wherein, under the control of a plurality of processors, the plurality of switching and conditioning circuits condition, switch and route the electrical signal within and between each cart among the plurality of carts. The electrical signal may be switched, routed or conditioned based on semantic analysis. A first cart includes a socket connector which may include an electrical or latching component, and which may be physically connected or latched to secure it with a pairing socket connector of a second cart.

A method for circumscribing an insulating barrier region around a singular conductive microneedle structure or plurality of conductive microneedle structures adhered to a fixed substrate for the purpose of spatially defining a conduit for the routing of an electrical signal from the surface of said microneedle or microneedles to the posterior surface of the substrate is disclosed herein. A microneedle-based electrochemical biosensors structure comprises a substrate, a microneedle biosensor, a primary electrically conductive element, a secondary electrically conductive element and an electrically insulative annular barrier.

The invention relates to the technical field of discharge detection, in particular to a high-precision detection method and device for partial discharge of totally-enclosed GIS equipment. The method comprises the following steps: carrying out metal shell three-dimensional structure modeling on the GIS equipment, and carrying out electromagnetic shielding evaluation so as to obtain a multi-point electromagnetic shielding evaluation value; acquiring an original discharge signal of each sampling point based on the electromagnetic wave sensor, and performing interference suppression processing and back propagation attenuation compensation according to a multi-point electromagnetic shielding evaluation value, so as to obtain an attenuation compensation discharge signal waveform; micro-vibration response parameters are collected based on an MEMS micro-vibration sensor, actual influence waveform point detection marking and physical vibration interference filtering are carried out on attenuation compensation discharge signal waveforms, and therefore pure optimized discharge signal waveforms are obtained. According to the invention, through efficient and accurate partial discharge detection, real-time early warning of the state of the GIS equipment is realized, and the stability and safety of the equipment are improved.

The invention discloses an on-line detection method for gas in transformer oil based on photoacoustic spectrum self-correction, and relates to the technical field of spectrum detection and power equipment state monitoring, and the method comprises the following steps: S1, emitting modulation laser with a specific wavelength to a gas sample released by the transformer oil through a laser, and exciting gas molecules to generate photoacoustic signals; and S2, detecting the photoacoustic signal by using a photoacoustic sensor, converting the signal into an electric signal, and outputting the electric signal. According to the online detection method for the gas in the transformer oil, the correction coefficient is adjusted in real time through a self-correction algorithm, errors caused by light path changes and sensor aging are effectively compensated, the precision and stability of long-term detection are remarkably improved, and the detection accuracy is improved by combining a gas spectrum database and a mode recognition algorithm. According to the method, accurate qualitative and quantitative analysis of various gases is realized, the problem of cross sensitivity of multiple components is solved, and the method also has temperature and pressure compensation functions and can automatically adapt to environmental changes.

The invention discloses a high and low voltage power distribution cabinet operation monitoring system based on data analysis, and relates to the technical field of power distribution cabinet operation monitoring, the system comprises an operation monitoring platform, the operation monitoring platform is in communication connection with a data acquisition module, a fault risk analysis module, a fault risk diagnosis module, a fault positioning module and a monitoring early warning module, the modules are in electric signal connection; the data acquisition module is used for collecting and preprocessing power distribution equipment data of the high-low voltage power distribution cabinet. According to the invention, through integration of the data acquisition module, the fault risk analysis module, the diagnosis module and the positioning module, comprehensive monitoring of the operation state of the high-low voltage power distribution cabinet is realized, a fault risk diagnosis model is established by using a deep learning algorithm, and potential fault risks are accurately identified in combination with real-time data and historical cases, so that the accuracy and timeliness of early warning are significantly improved, and the working efficiency of the high-low voltage power distribution cabinet is improved. And operation and maintenance personnel can intervene in advance according to the early warning information and take preventive measures, thereby effectively avoiding faults and ensuring stable operation of the power system.

The invention discloses a self-adaptive filtering and intelligent separation method for a multi-mode partial discharge signal, and relates to the technical field of insulation state monitoring and signal processing of power equipment, and the method comprises the following steps: S1, collecting the partial discharge signal of the power equipment in real time, and synchronously obtaining an equipment operation parameter and an environment noise signal; according to the adaptive filtering and intelligent separation method for the multi-modal partial discharge signal, the problems of modal aliasing and feature distortion caused by signal and noise time-frequency coupling in a dynamic noise environment in a traditional method are effectively solved through a cooperative mechanism of dynamic coupling degree modeling and dual-channel adversarial decoupling. The dynamic coupling path sensing module quantifies interaction characteristics of noise and signals in real time, and realizes accurate suppression of high-frequency transient interference and low-frequency periodic noise in combination with a double-channel architecture of complex field phase sensitive filtering and vibration trajectory matched filtering.

A system includes a housing and a first circuit board positioned inside the housing. The housing has a top panel, a bottom panel, a left side panel, a right side panel, a front panel, and a rear panel. The front panel is at an angle relative to the bottom panel in which the angle is in a range from 30 to 150°. The first circuit board has a length, a width, and a thickness, in which the length is at least twice the thickness, the width is at least twice the thickness, and the first circuit board has a first surface defined by the length and the width. The first surface of the first circuit board is at a first angle relative to the bottom panel in which the first angle is in a range from 30 to 150°. The first surface of the first circuit board is substantially parallel to the front panel or at a second angle relative to the front panel in which the second angle is less than 60°. The system includes a first data processing module and a first optical interconnect module both electrically coupled to the first circuit board. The optical interconnect module is configured to receive first optical signals from a first optical link, convert the first optical signals to first electrical signals, and transmit the first electrical signals to the first data processing module.

A game controller for a mobile device, the game controller including a first handle, a second handle, a bridge, and a flat, flexible cable. The first handle is configured to contact and support a mobile device. The first handle includes a user-accessible, first hardware interface on a main body portion of the first handle that is configured to accept touch inputs. The second handle is configured to contact and support the mobile device. The second handle includes a user-accessible, second hardware interface on a main body portion of the second handle that is configured to accept touch inputs. The bridge couples the first handle to the second handle. The bridge is in sliding engagement with the first handle and the second handle. The flat, flexible cable is configured to conduct an electrical signal between the first handle and the second handle.

The invention relates to the technical field of high-voltage connectors, and discloses a high-voltage connector fault prediction method and system based on thermal management, and the method comprises the steps: collecting the temperature distribution data and electric signal transmission characteristic data of a high-voltage connector, and building a thermal-electric coupling network model comprising a temperature node and a signal transmission node; separating and optimizing the transmission characteristic function to obtain a temperature-transmission characteristic mapping relation; gaussian process regression calculation is carried out on the temperature time sequence data to obtain temperature dynamic characteristic statistical characteristics; inputting the statistical characteristics of the dynamic temperature characteristics into a specified time delay thermal management neural network for signal transmission delay prediction to obtain delay prediction characteristic parameters; according to the method, the weighted error value in the transmission feature space is calculated, and the signal transmission delay is dynamically adjusted to obtain the compensated signal transmission delay parameter, so that the accurate prediction of the signal transmission delay is realized, and the accuracy and robustness of the compensation effect are improved.

The invention relates to the technical field of unmanned aerial vehicle detection, in particular to a monitoring and early warning system and method for countering unmanned aerial vehicle detection interference, and in the monitoring and early warning system, a signal receiving module independently receives electric signals of multiple unmanned aerial vehicles through array space stations; the abnormal signal detection module performs feature extraction, and detects abnormal signals by using frequency feature change and a spectrum analysis technology; the time difference of arrival detection module calculates the time difference of arrival of each space station to the abnormal signal, and the angle of arrival detection module analyzes and determines the angle of arrival through a space covariance matrix; the cross positioning module synthesizes the time difference and the angle information to determine the position of the abnormal unmanned aerial vehicle; and the adaptive interference suppression module identifies the type of an abnormal unmanned aerial vehicle by using a feature extraction result and a machine learning model, selects a suppression strategy, controls an array space station to align to the position of the abnormal unmanned aerial vehicle, realizes efficient suppression, and protects normal operation of a legal unmanned aerial vehicle and other aerial equipment at the same time.

The invention provides an LNG ship containment system monitoring system and method based on a fiber bragg grating sensor, and belongs to the crossing field of fiber sensing technology and ship safety engineering, the system comprises a fiber bragg grating sensor and a demodulation device, the fiber bragg grating sensor is used for collecting optical signals, and the demodulation device converts the optical signals into electric signals and processes the electric signals. The fiber bragg grating sensor adopts a double-grating structure and is respectively used for stress monitoring and temperature compensation so as to realize omnibearing real-time monitoring. The fiber grating sensor comprises a tail fiber, a protective tube, a base, and a strain grating, a spring and a temperature grating which are located in the protective tube. According to the invention, the monitoring precision and safety of the LNG ship containment system can be improved; through a double-grating temperature compensation technology, the influence of temperature change on stress measurement is eliminated, and the accuracy and reliability of data are ensured; in addition, stress information in different directions can be obtained in real time through the three-dimensional stress monitoring scheme, the stress condition of the structure is comprehensively reflected, and the flexibility and adaptability of monitoring are improved.

An outside handle device for a vehicle door comprises a handle main body provided at the outside of the vehicle door, a handle frame fixed to the vehicle door, a first connector provided at a vehicle body side and electrically connected with an electric signal cable at the vehicle body side, and a second connector provided at the handle main body and electrically connected with the electric component accommodated in the handle main body. The first connector and the second connector are placed with a predetermined distance when the handle main body is assembled in the handle.

The present application relates to a virtual synchronous control method and apparatus for an energy storage system, a device, and a storage medium. The method comprises: controlling an output voltage of a direct-current energy storage valve on the basis of an output electrical signal measurement value of a direct-current side of a voltage source converter and an output voltage reference value of the direct-current energy storage valve; further, controlling an output signal of an alternating-current side of the voltage source converter on the basis of a grid connection point electrical signal measurement value and a grid connection point electrical signal reference value of the voltage source converter. It can thus be seen that the embodiments of the present application implement a virtual synchronous control method independently controlling a voltage source converter and a direct-current energy storage valve in an energy storage system, so that the method can be applied to virtual synchronous control of a high-voltage direct-current direct-mounted energy storage system. In addition, by means of independently controlling the voltage source converter and the direct-current energy storage valve in the energy storage system, the voltage source converter does not need to be configured to take into account both direct-current side control and alternating-current side control, so that the complexity of a control loop of the voltage source converter can be simplified.

The invention relates to the technical field of electrical fault detection, in particular to a photovoltaic inverter fault detection system based on an electric signal, and the system comprises a signal collection module which continuously collects the output electric signal of an inverter, records the amplitude, frequency and phase of the electric signal, and generates an original signal record; and based on the original signal record, screening the electric signal, eliminating noise and non-characteristic data, and generating screened signal data. According to the method, the time frequency characteristics of the signals are extracted in real time through continuous wavelet transform, and the sensitivity and accuracy of fault detection are improved. According to the detailed feature recognition method, even tiny abnormal waveforms or frequency deviations can be captured, and therefore early warning of potential faults is achieved. Meanwhile, the fault detection threshold value is dynamically adjusted through the environmental parameters, flexible response is allowed according to the actual operation environment change, the false alarm and missing alarm conditions are reduced, and the adaptability and the reliability are improved.

The invention discloses a multi-parameter measurement system and method for a power frequency non-partial discharge test transformer, and relates to the technical field of state monitoring of high-voltage test equipment and power equipment, and the system comprises a synchronous trigger unit which is connected to a power frequency voltage signal collection end and is used for detecting a zero crossing point of a power frequency voltage signal and generating a synchronous trigger signal, a power frequency period is divided into a plurality of sub-windows with equal phase angles. According to the multi-parameter measurement system and method for the power frequency non-partial discharge test transformer, the problem of phase mismatch of a power frequency signal and a high-frequency partial discharge signal in traditional multi-parameter measurement is effectively solved through a power frequency phase locked synchronous trigger mechanism and a dynamic noise suppression technology; and the positioning precision of the partial discharge source and the insulation defect diagnosis reliability are improved. The nanosecond-level time sequence error control is realized, and the power frequency coupling interference is inhibited while the details of the high-frequency pulse are kept by combining a phase correlation dynamic filtering strategy, so that the signal-to-noise ratio of the weak discharge signal is improved.

The invention discloses a multi-modal data fusion power equipment health state diagnosis method and system, and belongs to the field of power equipment state monitoring, and the method comprises the steps: S100, collecting infrared thermal imaging data, vibration signals, current harmonic data and partial discharge signals of power equipment, and carrying out the time synchronization and space registration; and S200, acquiring infrared thermal imaging data, vibration signals, current harmonic data and partial discharge signals, and inputting the infrared thermal imaging data, the vibration signals, the current harmonic data and the partial discharge signals into the dynamic weight fusion model to obtain an equipment health state score and a fault type. And S300, according to the equipment health state score and the fault type, triggering grading alarm. According to the invention, timely early warning can be carried out on potential fault hidden dangers of power equipment.

A wide-band oscillation wide-area monitoring system and a wide-band oscillation source localization method, which relate to the technical field of power system stability. The wide-band oscillation wide-area monitoring system comprises: a plurality of signal sensing modules, configured to acquire electrical signals from measured points; a plurality of wide-band measurement devices connected to the signal sensing modules, each wide-band measurement device being configured to perform spectrum analysis on the basis of electrical signals acquired by each signal sensing module, and generate oscillation alarm information on the basis of the spectrum analysis result, and the wide-band measurement devices being further configured to: in response to a waveform recording instruction, start to carry out waveform recording to generate waveform recording files for a same time section, and upload the waveform recording files and the spectrum analysis results; and a wide-band measurement master station in communication connection with each wide-band measurement device, the wide-band measurement master station being configured to: on the basis of the oscillation alarm information uploaded by each wide-band measurement device, determine whether a wide-band oscillation risk is present for a power system, and if so, send the waveform recording instruction to all of the wide-band measurement devices, and on the basis of the spectrum analysis result fed back by each wide-band measurement device, perform oscillation source localization.

The invention discloses an AI intelligent collaborative monitoring management system for a multi-index water volume system, and relates to the technical field of monitoring management, the collaborative monitoring management system comprises a data acquisition module, a water volume system analysis module, a collaborative monitoring module, an emergency early warning module, an early warning scheme module and a data visualization module, all the modules are connected through electric signals. According to the AI intelligent collaborative monitoring management system for the multi-index water volume system, abnormal changes in water quality, water volume and water ecological indexes are identified through anomaly detection, an early warning mechanism is triggered according to the detected anomaly, early warning information is sent to management personnel through various modes such as a visual interface, a short message and an email, and the management personnel can carry out early warning on the water quality, the water volume and the water ecological indexes. According to the invention, the time interval from the occurrence of the abnormity to the discovery of the abnormity is greatly shortened, and valuable response time is provided for managers, so that further deterioration of the abnormity is effectively restrained, and the safety and sustainable utilization of water resources are guaranteed.

A floating thermometer with a disinfection device includes a shell, a temperature sensing device and a display device. An upper part of the shell is provided with a sealed first accommodating chamber, first accommodating chamber is arranged with a control device. A lower part of the shell is provided with a second accommodating chamber and a first through hole connected to the second accommodating chamber. The temperature sensing device is located on surface of the shell and electrically connected to the control device. The temperature sensing device is configured to be immersed in water to detect water temperature, generate an electrical signal, and transmit the electrical signal to the control device. The display device is located on upper surface of the shell and electrically connected to the control device. The control device receives the electrical signal and controls the display device to show temperature.

The invention relates to the technical field of new energy battery testing, and discloses a new energy battery safety testing system and method, and the system comprises a multi-physical field synchronous collection and analysis module which is used for synchronously collecting electric signals, temperature field distribution and stress-strain data in a battery testing process, and carrying out the multi-field coupling analysis; a self-adaptive test parameter regulation and control module; the thermal runaway risk prediction module is used for analyzing and predicting the risk probability and residual safety time of thermal runaway of the battery based on multi-parameter fusion; the microstructure-macroscopic performance correlation analysis module is used for acquiring microstructure information of the battery through nondestructive testing and establishing a correlation model with macroscopic safety performance, and the new energy battery safety test system realizes collaborative analysis of multiple parameters of electricity, heat and force through the multi-physics field synchronous acquisition and analysis module; the safety state of the battery can be reflected more comprehensively, and the defect that a traditional testing method is single in dimension is overcome.

The invention relates to the technical field of GIS equipment, and discloses a partial discharge detection method and device for totally-enclosed vacuum environment-friendly GIS equipment, and the method comprises the steps: constructing a dual detection circuit system of the GIS equipment, and building an equipment impedance characteristic model which comprises housing distribution inductance and internal conductor distribution inductance; acquiring a first multi-mode discharge signal in a vacuum insulation environment, performing empirical mode decomposition to obtain a plurality of eigenmode function components, and synchronously recording environment characteristic parameters; constructing a discharge signal identification model; and identifying the second multi-mode discharge signal of the GIS equipment through the discharge signal identification model, and determining the internal defect three-dimensional coordinate and the hazard level of the GIS equipment, so that intelligent identification of discharge characteristics is realized, the calculation efficiency is improved, the anti-interference capability is enhanced, the three-dimensional coordinate of the internal defect of the GIS equipment can be accurately calculated, and the reliability of the GIS equipment is improved. And comprehensive evaluation of defect types and hazard levels is realized.

Disclosed herein is a system, apparatus and method directed to automated adjustment of a positioning of a drainage bag based on at least an amount of tension within a tubing extending from the drainage bag. The system, apparatus and method pertain to an automated drainage bag actuation system that includes at least a first railing, a control box coupled to the first railing and configured to receive mounting fasteners that couple a drainage bag to the control box, the control box including a tension load cell sensor, a first motor, and circuitry electrically coupled to the first motor and the tension load cell sensor. The circuitry is configured to receive data from the tension load cell sensor indicating an amount of tension in tubing extending from the drainage bag and transmit one or more electrical signals to activate the first motor causing adjustment of a positioning of the drainage bag.

A medical device operating as a stylet is described. The medical device can include an insulating layer (or sheath) encapsulating both a multi-core optical fiber and a conductive medium. The optical fiber can include a cladding and a plurality of core fibers spatially arranged within the cladding. Each of the core fibers can include a plurality of sensors distributed along a longitudinal length of that corresponding core fiber and each of these sensors can be configured to: (i) reflect a light signal of a different spectral width based on received incident light, and (ii) change a characteristic of the reflected light signal for use in determining a physical state of the multi-core optical fiber. The conductive medium can provide a pathway for electrical signals detected at a distal portion of the conductive medium. The conductive medium may be concentric to the cladding, but separate and adjust thereto.

The invention discloses an electrical fire real-time monitoring system based on a wireless sensor network, and relates to the technical field of electrical fire monitoring. The cloud monitoring platform is in communication connection with an electrical data acquisition module, an electrical fire abnormity analysis module, an abnormity early warning module, a node management configuration module and a visual monitoring module, and all the modules are in electric signal connection; the electrical data acquisition module is used for acquiring monitoring data of electrical nodes by using a deployed wireless sensor and transmitting the monitoring data to the cloud monitoring platform through a wireless communication technology, and the monitoring data comprises current, voltage, temperature, humidity and leakage current. Multi-parameter fusion monitoring is carried out through the wireless sensors deployed at the key nodes of the electrical equipment, compared with a traditional wired sensor, the wireless sensors do not need wiring, installation is flexible, early signals of an electrical fire can be captured more comprehensively, and the accuracy of fire early warning is remarkably improved.

The invention discloses a course learning planning system based on a computer, and relates to the technical field of course learning planning, and the course learning planning system comprises a learning data acquisition module, a knowledge graph construction module, a learning index scoring module, a multi-index comprehensive evaluation module, a learning plan making module and a real-time progress feedback module. Wherein the modules are connected through electric signals; the learning data acquisition module is used for collecting learning data of students and determining evaluation indexes of the learning data. According to the course learning planning system based on the computer, by monitoring the learning progress and achievement of students, instant learning feedback is provided for the students, so that the students can quickly know the learning state of themselves, related learning resources and exercises are intelligently recommended according to the learning conditions of the students, the students are helped to consolidate knowledge and make up for deficiencies, and the learning efficiency is improved. Students can achieve a higher learning effect in a shorter time, and the learning efficiency is improved.

The invention discloses an absolute type planar two-dimensional time grating displacement sensor based on an alternating electric field and a measuring method. Excitation signals are applied to X excitation pairs in sequence, when an induction electrode generates an induction signal, the excitation signals are stopped from being applied to the remaining X excitation pairs, and four paths of electric signals generated by an induction group are processed, so that the absolute type planar two-dimensional time grating displacement sensor based on the alternating electric field is obtained. Obtaining the X excitation antipode of the movable ruler base body and the displacement position of the movable ruler base body in the X excitation antipode so as to obtain the two-dimensional time grating absolute displacement value of the movable ruler base body relative to the fixed ruler base body in the X direction; similarly, a two-dimensional time grating absolute displacement value of the movable ruler base body in the Y direction is obtained; and then taking the two-dimensional time grating absolute displacement values in the XY direction as the coordinates of the movable ruler base body in the XY direction to obtain the absolute displacement of the movable ruler base body. The absolute positions in the X direction and the Y direction are obtained in a scanning mode so as to achieve planar two-dimensional absolute displacement measurement, accumulated errors and random errors can be reduced, the measurement precision can be improved, and wide-range high-precision measurement can be achieved.