33results about How to "Strong precision" patented technology

The invention discloses a fusion method based on Internet map congestion data. The fusion method comprises the following steps: acquiring congestion data according to different Internet map companies; performing parameter data cleaning on the acquired congestion data to obtain cleaned data; respectively inputting one piece of congestion data and one piece of corresponding cleaned data into a fusion algorithm according to a sequence, and judging until a repeatedly congested road section is obtained; and fusing the repeatedly congested road sections to obtain a fusion result. According to the invention, multi-party navigation map congestion data can be fused, false information is eliminated, and a standardized congestion road condition result is identified and output in real time.

The invention discloses a power line loss calculation and prediction method based on deep learning and error correction, and relates to the technical field of power line loss calculation, and the method specifically comprises the steps of power data information collection, data cleaning and preprocessing, data feature extraction, model building, error correction and precision improvement, and hyper-parameter optimization. According to the method, the advantages of support vector regression and a bidirectional long short-term memory network are fused, and a CNN-BiLSTM-SVR calculation model with high robustness is constructed through deep mining and effective utilization of related data in a power system; the problems of complexity and low efficiency of the traditional line loss calculation method in processing large-scale data are solved by introducing a deep learning technology, especially BiLSTM; error correction is carried out on the preliminary calculation result of the model through SVR, the accuracy of line loss calculation is further improved, the efficiency of line loss calculation is improved, the accuracy of the calculation result is ensured, and powerful technical support is provided for optimization management of a power system.

The invention relates to the technical field of aerial image detection and the technical field of small target detection, in particular to a small target detection model in an unmanned aerial vehicle aerial scene, which is characterized in that an aerial image data set is acquired, an improved YOLOv8s model is trained by adopting the aerial image data set, and the improved YOLOv8s network model comprises a backbone feature network, a detection head and a loss function; an SPD-Conv module is introduced into a P2 layer, a P3 layer, a P4 layer and a P5 layer of the backbone feature network, a Dynamic Head module is introduced into a detection head, a specific small target detection head (SODH) is added, Shape-IoU is used as a loss function, and a to-be-detected aerial image is input into a trained improved YOLOv8s model for detection; the SDSS-YOLOv8 not only can execute a small target detection task in an aerial image shot by an unmanned aerial vehicle, but also has good performance in the aspect of small target detection in an unmanned ship image, the model has strong generalization ability, and although the image environment and target distribution have changes, the SDSS-YOLOv8 can maintain high detection performance in different scenes.

The invention provides an SMP architecture real-time operating system CPU occupancy rate statistical method, electronic equipment and a medium, and the method does not depend on redundant external hardware equipment, does not need to independently create a statistical task occupying CPU running time, and utilizes a timer generating Tick interruption in an operating system to calculate the CPU occupancy rate of the operating system. Through the scheduler-level high-precision statistics of the operation time of the observed task and the calibration of the total operation time of the CPU, the operation time of the observed task and the total operation time of the CPU are displayed in an accurate granularity, and the CPU occupancy rate of the strong real-time task can be accurately measured. By applying the technical scheme provided by the invention, the technical problem of measurement distortion of the CPU occupancy rate of the strong real-time task in the prior art is solved.

The present invention discloses a method for detecting a target on a road using a roadside device, a roadside device, and a computer-readable medium. The roadside device includes a first sensor and at least one second sensor, the first sensor is based on ultra-wideband technology, and the second sensor includes at least one of a camera, a radar, and a laser radar. The method includes: acquiring target detection data from the first sensor and the second sensor; determining a new detection target list based on the target detection data, the new detection target list includes at least one target and its position; performing target matching based on the new detection target list and a historical detection target list to generate a matched detection target list, the historical detection target list includes at least one previously detected target and its position; fusing the positions of the targets in the matched detection target list to generate a fused detection target list; and outputting the fused detection target list and / or the positions of the targets in the fused detection target list.

The application relates to the field of biomedical technology, and discloses a diagnostic agent for identifying melanoma molecular subtype typing and application, wherein the diagnostic agent comprises a first antibody specifically combined with a SOX10 protein and a second antibody specifically combined with an EGR1 protein; the diagnostic agent can be applied to preparation of a diagnostic product for evaluating the prognostic effect of a melanoma patient, preparation of a diagnostic product for predicting the treatment sensitivity of melanoma to a BRAF inhibitor, and preparation of a diagnostic product for guiding an individualized treatment scheme of melanoma. The diagnostic agent for melanoma molecular subtype typing can be directly transformed into clinical practice, and can assist in realizing real individualized treatment.

The utility model discloses an assembling structure of a sub-control valve electric explosion driving firing pin, which comprises a workbench for placing a valve body, a correlation sensing unit arranged on one side, far away from the valve body, of the workbench, and a distance adjusting assembly fixedly arranged on the workbench and used for adjusting the limit distance between the correlation sensing unit and the valve body. According to the assembling structure of the sub-control valve electric explosion driving firing pin, the length, exceeding the valve body, of the firing pin is monitored through the correlation sensing assembly when the firing pin is assembled, press fitting failure of the firing pin and component interference caused by the fact that the firing pin exceeds the limit distance are avoided, and compared with a manual measurement mode, the assembling structure is higher in accuracy, higher in detection efficiency and higher in practicability. And meanwhile, the limiting distance between the correlation sensing unit and the valve body can be adjusted through the distance adjusting assembly, so that the monitoring and alarming range of the penetrating length of the firing pin is widened, and the overall applicability and practicability of the device are higher.

This invention provides a nonlinear time-series estimation method for the state of health (SOH) of lithium batteries, comprising: collecting feature data during the charge-discharge cycle of the lithium battery and generating a multi-channel standardized time-series dataset; extracting features and compressing dimensions of the data through an encoder; reconstructing and denoising the data through a decoder to output sequence features; mining the global correlation between feature sequences to obtain a context vector; further obtaining the SOH estimation result and synchronously updating the parameters. This method effectively suppresses model overfitting while introducing an improved KL divergence to prevent posterior collapse, achieving high-precision and robust estimation of the SOH of lithium batteries.

The present disclosure relates to a liquid flow measurement structure and a measurement system using the same. The measurement structure comprises a flow channel body, an electrode sheet assembly arranged inside the flow channel body, the electrode sheet assembly comprising a plurality of capacitive sensing electrode sheets, and a digital capacitive sensing assembly connected to the electrode sheet assembly through signal lines, configured to collect capacitive signals of the plurality of capacitive sensing electrode sheets and output capacitive data associated with liquid level height. The plurality of capacitive sensing electrode sheets are arranged in a multi-layer grid structure inside the flow channel body, the multi-layer grid structure is distributed along the flow direction of the flow channel body, and a single layer grid structure is configured to arrange a single capacitive sensing electrode sheet. Alternatively, part of the capacitive sensing electrode sheets in the electrode sheet assembly are arranged in the sidewall of the flow channel body. The present disclosure has the advantages of simple structure, low cost, high reliability, and adaptability to various extreme application scenarios.

The embodiment of the invention provides an automatic river curve contradiction detection method, and relates to the technical field of geographic information data processing, and the method comprises the following steps: generating river element data and contour line element data through vector map data, traversing the river element data and the contour line element data, and calculating a river curve contradiction; the intersection points and the elevation values corresponding to the intersection points are stored in the river element data; elevation values of all points corresponding to each river element in the river element data are obtained, and all the points of the river elements are sorted according to the descending order of the elevation values; traversing the intersection point coordinate list, calculating to obtain a first direction angle corresponding to the first vector line segment, and calculating to obtain a second direction angle corresponding to the second vector line segment; and judging whether the river element curve has contradiction or not through the angle of the first direction angle, the angle of the second direction angle and the sensitivity value. According to the scheme, through automatic detection, the river curve contradiction detection efficiency is improved.

The present application relates to a kind of dual optical path nitrogen dioxide measurement system and method based on blue laser, using dual-wavelength laser cavity enhanced absorption spectroscopy technology, carries out NO2 absorption measurement under 405nm and 410nm wavelength, and combined with high reflectivity optical resonator, improve detection precision and sensitivity.Through dual-wavelength comparison method, using dual-wavelength absorption spectroscopy analysis, calculate absorbance difference, to effectively eliminate the influence of environmental factors on measurement accuracy, improve measurement reliability.Using more than 99.9% high reflectivity mirror, to realize high reflectivity optical resonator enhancement technology, laser is reflected in resonator multiple times, optical path is extended hundreds of times, improve NO2 absorption signal intensity, realize ppb grade ultra-low concentration measurement.Compared with traditional optical method, the system has lower cost, higher accuracy and stronger environmental adaptability, provides an efficient, stable solution for atmospheric pollution monitoring.

The utility model relates to the field of corrugated pipe machining, and discloses a corrugated pipe machining positioning and clamping device which comprises a base, a square groove is formed in the base, a support is fixedly connected to the interior of the base, a motor is fixedly connected to the top face of the support, the output end of the motor is fixedly connected with a worm, and the output end of the worm is fixedly connected with a clamping device. The worm is provided with clamping assemblies capable of moving inwards at the same time, one side of the worm is provided with a worm gear, the worm gear is meshed with a worm gear, and the worm gear is provided with a fixing assembly capable of moving inwards at the same time. According to the utility model, a worker starts the motor fixed on the top surface of the support, then the worm connected with the output end of the motor starts to rotate, and the first bevel gear fixedly connected with the outer wall of the worm starts to rotate, so that the working efficiency is improved, convenience and rapidness are realized, the time is saved, and the labor intensity of maintenance workers is greatly reduced; and therefore, the stability in use is improved, and the quality of the corrugated pipe is improved.

The invention relates to a high-precision wide-range displacement sensor based on a grating technology. The device comprises a displacement mechanism; the low-power-consumption induction and self-calibration mechanism comprises a driven gear, a double-meshing gear, a driving gear, an automatic reset component, a driving component and an induction device which are sequentially meshed, the driven gear can receive input torque and sequentially drive the double-meshing gear and the driving gear to rotate, and the double-meshing gear can drive the automatic reset component to move through the driving component. The displacement action of the automatic reset component is sensed through the sensing device; the grating mechanism comprises a grating belt driven shaft, a grating belt driving shaft, a grating belt wheel, a grating belt and a grating decoder, and displacement data are obtained through the grating decoder, or the displacement data on the grating belt are obtained through a distributed optical fiber or a grating demodulator. According to the invention, long-term low-power-consumption or power-consumption-free monitoring and regular self-calibration of equipment are realized, and the device has the advantages of long service life, wide application range, strong stability, strong anti-interference capability and the like.

This invention discloses a method for detecting the alumina content in aluminum-manganese-calcium alloys, mainly solving the technical problem that existing methods cannot accurately and rapidly detect the alumina content in aluminum-manganese-calcium alloys. The technical solution is as follows: a method for detecting the alumina content in aluminum-manganese-calcium alloys, comprising: 1) sample preparation: after removing the oxide layer on the sample surface, the sample is placed in a reagent bottle containing organic solvent for storage; 2) alumina extraction from the sample: first, alumina is extracted from the sample by electrolysis, the sample is placed in an electrolytic cell for electrolysis, the sample is the anode, a platinum electrode is the cathode, and a saturated calomel electrode is the reference electrode; 3) detection of alumina in the sample: the filter membrane and filter material from step 2) are placed in a platinum crucible, and the filter membrane is removed by high-temperature ashing; 4) calculation of the mass percentage of alumina in the aluminum-manganese-calcium alloy. The method of this invention for determining the alumina content in aluminum-manganese-calcium alloys has a relative standard deviation (RSD) of less than 3%, indicating good precision, accuracy, and reliability of the detection data.

The application discloses a generator set vibration trend early warning method based on a deep timing model, comprising the following steps: collecting generator set operation data and performing data preprocessing; constructing an enhanced Neural RDE model; running a conditional rough driving construction unit to generate a logarithmic signature feature set; running a frequency band gate vector field unit to generate a gate coefficient set and a hidden state sequence; running a physical consistency constraint unit to calculate and generate a constraint signal sequence; based on the hidden state sequence, the logarithmic signature feature set and the constraint signal sequence, calculating and generating a trend index set and a risk index set; calculating a joint loss function and updating model parameters; inputting a real-time collected continuous data stream and combining the model parameters and a threshold set to generate a vibration trend early warning result and an early warning lead time. The application significantly improves the vibration trend prediction accuracy, prolongs the early warning lead time and enhances the operation reliability under complex working conditions.

The invention discloses a satellite data traffic measurement method and system, and belongs to the technical field of satellite networks. In order to solve the problems of poor satellite network flow measurement precision and high complexity in the prior art, the invention provides a satellite data flow measurement method, which comprises the following steps: determining a satellite node for data flow measurement, and initializing a configuration probability data structure algorithm and an imitation learning algorithm; sampling network flow in a period of time, judging whether a data flow jitter value in the period of time exceeds a threshold value or not, and if the data flow jitter value exceeds the threshold value, generating a flow value according to a label value and an expert strategy by utilizing an imitation learning algorithm; if not, using a probability data structure algorithm to measure and record a label value, and generating an expert strategy according to the label value; and completing measurement. According to the method, resource utilization is reasonably optimized while the measurement accuracy is improved, high-precision and high-timeliness satellite flow measurement is achieved through mutual complementation of the probability data structure algorithm and the imitation learning algorithm, and the method is low in hardware dependency, high in precision, high in intelligence and high in adaptability.

The application discloses a kind of to judge heliostat fault method using historical heliostat data contrast, comprising the following steps: S1, camera installation and configuration;S2, image acquisition;S3, image pre-processing;S4, image segmentation;S5, shape recognition;S6, feature extraction;S7, historical data contrast;S8, anomaly detection;S9, machine learning detects abnormal heliostat;S10, real-time monitoring and feedback.The application introduces historical data contrast and machine learning technology, significantly improves the accuracy and efficiency of heliostat fault detection, and the specific advantages include: high accuracy, combined with image processing and historical data contrast effectively identify a variety of abnormal types, reduce the misjudgment rate;High degree of automation, through automatic exposure algorithm, region growing algorithm and machine learning model realize full-process automatic detection;Wide adaptability, considering the influence of weather, season and other factors, suitable for complex and changeable operating environment.

The present invention discloses a method for optimal assembly of a high-precision planetary gear reducer, the method comprising: hierarchical optimal planetary gear; hierarchical optimal sun gear; planetary gear mechanism assembly; hierarchical optimal single-stage gear ring housing assembly; assembly and fixing of input shaft and rear flange; assembly and fixing of output shaft and front flange; housing assembly and fixing. In the present invention, after hierarchical optimal planetary gear, sun gear and single-stage gear ring housing are optimally graded, the eccentric direction of the inner hole of the planetary gear is marked in the optimal process, and the eccentric direction of the four planetary gears is directed to the same direction after being installed in the assembly process, and the corresponding sun gear and single-stage gear ring housing are adapted to ensure that the sun gear always has a clearance in one direction and is in a tight fit in the other direction, so as to avoid the problems of jamming and vibration under high-precision meshing conditions, further improve the transmission accuracy and stability of the reducer, and achieve multiple performance indicators such as high precision, low side clearance, low noise, and low starting torque.

This invention discloses a network traffic anomaly detection method based on the fusion of SSM and Transformer, belonging to the field of network traffic monitoring technology. The method includes the following steps: S1, construction of raw traffic observations; S2, construction of joint feature representations; S3, dual-view sample generation: constructing raw view samples and generating corresponding perturbation view samples; S4, multi-scale variable behavior fragment decomposition: performing fragment decomposition on the raw view samples and perturbation view samples at different time scales; S5, hybrid coding feature extraction: extracting intra-session dynamic features using the SSM modeling branch and extracting inter-session correlation features using the Transformer modeling branch; S6, normal behavior representation learning; S7, traffic anomaly determination. This invention captures features at different time granularities through a multi-scale patch hierarchical structure, achieving high-precision and high-stability time-series anomaly detection.

The invention discloses a short-day strawberry breeding target gene sequence screening method, which comprises: S1, RNA extraction: taking leaves of short-day strawberries and four-season strawberries before and after flower bud differentiation, and extracting RNA by using a plant RNA rapid extraction kit; s2, carrying out integrity verification on the extracted RNA, detecting the purity and the concentration, and sequencing the RNA; s3, carrying out reverse transcription on the extracted RNA, designing a qRT-PCR (quantitative reverse transcription-polymerase chain reaction) primer, and carrying out PCR reaction to obtain a FaELF3 gene; and S4, cloning the FaELF3 gene in vitro and verifying the deletion mutant function recovery plasmid. The method effectively overcomes the limitation of traditional phenotype screening, fills up the market blank of the current high-temperature-resistant strawberry variety, has a wide application prospect, and is particularly suitable for the strawberry planting industry in tropical and subtropical regions. According to the method disclosed by the invention, the strawberries can also normally bloom at a relatively high temperature, and other important agronomic characters are not influenced.

The utility model discloses an assembly line manipulator anti-collision visual imaging device which comprises a base, a mechanical arm arranged on the base and a six-axis gripper arranged on the mechanical arm. The six-axis gripper is provided with a data acquisition module used for acquiring the number, colors and relative positions of paper tubes, an image processing module used for preprocessing information acquired by the data acquisition module, and PC platform computer equipment used for analyzing and controlling information sent by the image processing module. The colors, the number and the relative positions of the paper tubes grabbed by the six-axis gripper are acquired through the data acquisition module, are preliminarily processed through the image processing module and then are uploaded to the PC platform computer equipment for comparative analysis, problems are found in time through the PC platform computer equipment, and shutdown processing is conducted in time. The production accuracy is high, the working efficiency is improved, the use range is wide, the operation is simple and convenient, the product grabbing accuracy is high, and the product damage is reduced.

The invention discloses a preparation method of an MEMS hydrogen sensor. The MEMS hydrogen sensor comprises a bottom plate, an MEMS base layer and a hydrogen sensitive material, the hydrogen sensitive material is arranged above the MEMS base layer and comprises three metal oxide nano sensitive film layers and a noble metal deposition layer, and a tin dioxide sensitive film layer, a tin dioxide and zinc oxide composite sensitive film layer and a nickel oxide sensitive film layer are sequentially arranged on the surface of the MEMS base layer to form a three-layer metal oxide nano sensitive film layer semiconductor; the specific beneficial effects are as follows: zinc oxide and stannic oxide have good response to hydrogen; hydrogen sensors with various shapes, specifications and thicknesses can be prepared by an ink-jet printing method; hydrogen sensors with various properties are prepared by adjusting the mass fraction ratio of zinc oxide, stannic oxide and nickel oxide; the sensor has the advantages of high sensitivity, low detection limit, fast response, small size, low power consumption, low cost, large-scale industrial production and the like, and can be applied to monitoring of various environments.

The invention relates to a light-driven automatic centering rotary micro-nano motor on a solid interface, which is in a sheet shape with a center rotationally symmetrical and a non-rotating-shaft radially symmetrical structure, and is formed by laser processing of a metal nano material. Normal capturing force pointing to the center of the structure and tangential force in the parallel cantilever direction are accumulated in the pulse duration time, and then rotating torque is output for automatic centering rotation. And a strong output torque (more than 1nN. M) is generated, and the torque is more than 2 orders of magnitude higher than that of a common electrostatic motor in the MEMS at present. Due to the characteristic of small size, the torque density is up to 0.1 N.m / mm < 3 >, and the torque mass ratio is up to 100N.m / kg. By changing parameters such as laser power, repetition frequency, light spot shape and size and the like, accurate rotation control of the micro-nano motor can be realized. The optical tweezer has the advantages of being simple in structure, suitable for working conditions of a solid interface, free of thermal damage and the like, can achieve automatic centering rotation of the micro-nano motor on the solid interface, is used for driving other nano parts and operating target objects, is highly matched and compatible with existing optical tweezer equipment, and is wide in application range.

The present invention relates to the field of micro-nano manufacturing, and in particular discloses a method for processing hydrogel-based Janus porous films based on femtosecond laser. The present invention utilizes polydimethylsiloxane (PDMS) film spin coating technology and the bio-affinity of hydrogel to achieve the preparation of hydrogel-based Janus films of different thicknesses; utilizes femtosecond laser in-situ etching technology to achieve one-step molding preparation of tapered through holes; and achieves flexible control of tapered hole size by regulating parameters such as laser scanning speed, scanning spacing, and scanning times. The hydrogel-based Janus porous film prepared by the present invention has good biocompatibility, and by combining the hydrophobicity of PDMS and the hydrophilicity of hydrogel, the Janus film has excellent asymmetric wetting properties.

The invention discloses an anti-interference miniature interface circuit for an infrared focal plane detector, which relates to an infrared focal plane detector and comprises a detector interface, a signal input conditioning circuit, a signal differential output conversion circuit and a miniature interface which are connected in sequence, outputting a detector signal to a micro interface through the signal differential output conversion circuit, wherein the detector interface is used for accessing a detector; the bias voltage circuit comprises a fixed bias voltage part and an adjustable bias voltage part, the fixed bias voltage is connected to a working power supply, and the adjustable bias voltage is completed based on a voltage reference circuit chip and an operational amplifier and used for providing low-noise bias voltage for the detector interface; and the time sequence level conversion circuit is connected between the micro interface circuit and the detector and is used for outputting a time sequence signal provided by an external system to an interface circuit of the detector through a level conversion chip. Various interferences such as electromagnetism can be effectively suppressed, back-end signal processing and transmission are facilitated, and universality is achieved.

The application discloses a kind of based on global to local modulation's unsupervised industrial anomaly detection method and system.The method includes extracting global feature using global encoder, extracting local feature using local encoder;The global feature is mapped as modulation parameter, and the local feature is modulated using the modulation parameter, to generate enhanced feature;Further, the enhanced feature is input to decoder for feature reconstruction;Based on the cosine distance between each corresponding hierarchical feature in the local encoder and the decoder, a pixel-level anomaly map is generated;And based on a plurality of preset scoring profiles, determine image-level anomaly score according to the pixel-level anomaly map.The application can realize high-precision, strong robustness detection of various industrial defects, especially unknown small defects, to meet the stringent requirements of complex industrial quality detection.

A three-axis machining head with a replaceable tool comprises a machining head fixing assembly, a drilling and milling mechanism is installed on the machining head fixing assembly, and a lifting assembly used for driving the drilling and milling mechanism to ascend and descend is installed on the machining head fixing assembly. The device has the advantages of reasonable structure, simple operation, high precision, strong adaptability and the like. The multi-shaft combined machining device is mainly composed of a fixing assembly, a lifting assembly, a feeding assembly and a swinging assembly, multi-shaft combined machining of a sectional material can be achieved, the whole machining head does not need to be replaced, only assemblies with different functions need to be replaced, and the maintenance cost of equipment is reduced; meanwhile, due to the flexible design, the device can adapt to different workpiece shapes and sizes, and the production efficiency is improved. In addition, the equipment further has good mobility, accurate control over the machining position can be achieved through the moving assembly, and the machining quality is further improved.

The invention provides a method and a system for adjusting carrier frequency points, carrier bandwidth and the like. Performing multi-stage compression optimization on the original model through deep learning pruning or knowledge distillation to obtain a model after multi-stage compression optimization; and the like. The sensor calibration method and system have the capability of being deployed in the sensor terminal device, the base station and the cloud server respectively, application in multiple types of sensor devices and multiple scenes of the sensor devices is achieved, and simple and efficient inspection of calibration results is achieved through multi-stage cooperative calibration.

The utility model discloses a food processor circuit and a food processor. The circuit comprises a heating unit, a driving unit, an uncovering detection unit, a temperature detection unit and a first coupling unit which are arranged in a cup body, the main control unit and the second coupling unit are arranged in the base; wherein the heating unit and the driving unit are connected with the first coupling unit, and the main control unit is connected with the second coupling unit; when the cup body is placed on the base, the first coupling unit is butted with the second coupling unit; the first coupling unit is provided with a first main needle angle and a second main needle angle, the second coupling unit is provided with a first auxiliary needle angle and a second auxiliary needle angle, and the cover opening detection unit and the temperature detection unit are connected in series between the first main needle angle and the second main needle angle; when the cup body is placed on the base, the first main needle angle is in butt joint with the first auxiliary needle angle, and the second main needle angle is in butt joint with the second auxiliary needle angle. When the driving unit is arranged on the cup body, the universal coupler is still used, and all devices in the cup body are connected with the main control unit.

This invention relates to the field of environmental linkage alarm technology, and discloses a linkage alarm method and system based on environmental monitoring, including: dividing the parking area grid into multiple sub-areas and initializing the wind speed of the sub-areas as the environmental wind speed; correcting the wind speed of the sub-areas based on the building layout; executing an environmental vibration judgment strategy; estimating the equivalent wind speed experienced by the electric vehicle based on triaxial acceleration; and determining whether the environmental wind speed is a vibration trigger source based on the characteristics of the surrounding vibration; executing a single vehicle physical state assessment strategy; calculating the vibration amplitude of the acceleration and the tilt angle of the electric vehicle based on triaxial acceleration; executing an alarm and collaborative suppression strategy based on a threshold assessment of the physical state; setting different alarm levels according to the physical state; executing a theft detection and response strategy according to the alarm level; calculating the direction index of the average acceleration based on triaxial acceleration; calculating the theft confidence based on the kurtosis of the resultant acceleration; and improving the orderliness and intelligence of the alarm.