1380 results about "Highly sensitive" patented technology

The invention relates to the technical field of unmanned aerial vehicle-mounted nuclear radiation detection, and provides an unmanned aerial vehicle-mounted nuclear radiation detection method and system based on deep learning, and the method comprises the steps: collecting a gamma energy spectrum signal, and carrying out the digitization of the gamma energy spectrum signal, and obtaining original energy spectrum data; preprocessing the original energy spectrum data to obtain preprocessed energy spectrum data; constructing a nuclide identification model based on a deep learning network, and performing nuclide identification on the preprocessed energy spectrum data to obtain an original nuclide identification result; performing post-processing analysis and refinement on the original nuclide identification result to obtain a nuclide identification result; and fusing the nuclide identification result with the geographic position information to obtain a nuclear radiation pollution distribution diagram, and setting a multi-level early warning mechanism based on nuclide types and intensity. According to the invention, the precision of nuclide identification in a complex environment is improved, and high-sensitivity detection of various nuclides under the condition of low signal-to-noise ratio is realized.

The invention belongs to the technical field of computer data security, and discloses an enterprise data encryption storage system based on strategy optimization. The system is composed of a strategy map construction and optimization module, a sensitivity identification and encryption strategy generation module, an encryption execution and ciphertext structure processing module, a strategy-driven storage scheduling module and an audit recording and feedback optimization module. According to the method, a strategy graph containing multiple types of nodes such as users, data, behaviors, risks and resources is constructed, the edge weight and the node confidence coefficient are dynamically adjusted through the behavior frequency, the access relation and historical audit information, a graph structure oriented to behavior contexts is formed, and on the basis, an encryption strategy label is generated in combination with a fuzzy semantic reasoning mechanism; a traditional static recognition mode based on field rules can be broken through, potential high-sensitivity data and abnormal behavior paths are recognized, and the generation accuracy and the self-adaptive capacity of a data encryption strategy are improved.

The invention relates to the technical field of power system monitoring and fault diagnosis, and particularly discloses a fault diagnosis system of an electrical variable measurement insulator detection device. The system comprises a synchronous acquisition module, a multi-physical field feature extraction module, a self-adaptive fault diagnosis engine and a feedback module. By synchronously acquiring voltage harmonic waves, leakage current and temperature data, extracting feature vectors of coupling electric-thermal influence and performing two-stage collaborative diagnosis by using a dynamic threshold value and a mahalanobis distance, high-sensitivity and self-adaptive accurate identification and early warning of an early latent fault of the insulator are realized. According to the system, by constructing a synchronous data acquisition module and a multi-physical field feature extraction module, two key influence factors, namely an operation voltage harmonic component and an environment temperature, are brought into a diagnosis system in a quantifiable feature form for the first time.

The invention discloses a preparation and measurement method of a polymer-based multi-point force flexible sensor for knee joint pose measurement, and relates to the technical field of polymer-based flexible sensors and soft measurement. The structure of the multi-point force polymer-based flexible sensor shaped like a Chinese character'ao 'is designed for knee joint stress and posture state measurement, and the flexible sensor is prepared and packaged through a silk-screen printing method. A flexible sensor strain input-output knee joint stress data mapping set and a flexible sensor strain input-pose angle output data mapping set required by modeling are completed through a flexible sensor, a thin film force sensor corresponding to multi-point force and an inertial sensor corresponding to pose angle measurement of installed multi-point force polymers. And establishing a neural network soft measurement model based on an MLP algorithm, and carrying out training and verification. And the knee joint pose angle with reliable precision and the maximum stress state of the knee joint are obtained. The sensor has the advantages of being flexible, thin, skin-friendly, high in sensitivity and stable in signal output.

The invention discloses a static database self-adaptive fuzzification desensitization implementation method for highly sensitive data in the power industry. The method comprises the following steps: a data preprocessing module, a sensitivity analysis module, a fuzzification algorithm module, a self-adaptive mechanism module and an effect evaluation and verification module. Compared with the prior art, the method has the advantages that 1, self-adaptive dynamic adjustment is performed: a desensitization strategy is automatically optimized according to data characteristics and use scenes, and privacy protection indexes (such as k-anonymity values) are improved by 30%-50%; 2, multi-dimensional balance: the information loss rate is reduced by 10%-20%, the query accuracy is improved by 5%-10%, and safety and service requirements are considered; 3, system expansibility: a plug-in architecture supports dynamic loading of new algorithms and rules, and a configuration management module realizes strategy real-time adjustment; and 4, compliance guarantee: through a law and regulation rule base and a compliance check algorithm, the compliance is ensured to meet the standard.

The invention discloses a high-sensitivity metal micro-strain sensor label and a detection method thereof, which are applied to the field of nondestructive testing and the field of structural health monitoring. The problems that an existing tag antenna is low in strain detection sensitivity and difficult in micro-strain detection are solved. The high-sensitivity metal micro-strain RFID sensing tag is attached to the surface of a component, when the tag deforms, the impedance change of the tag is Zsened, and the radar cross section changes accordingly; the reader can remotely monitor antenna parameters according to the change of the RCS0, the RCS1 and the intensity while communicating with the tag, so that the change of the intensity RSSI of an echo signal is deduced, and the deformation of the tag is indirectly known; when the impedance of the tag antenna changes, the resonant frequency of the tag changes accordingly, and the deformation information of the tag can be indirectly obtained by analyzing the deviation of the resonant frequency.

This invention belongs to the field of biological detection technology, specifically relating to a monoclonal antibody combination for detecting feline NT-proBNP protein and its applications. The monoclonal antibody combination of the present invention comprises monoclonal antibodies 3A6 and 5H5. These two antibodies possess unique heavy and light chain variable region complementarity-determining regions, respectively, and their amino acid sequences have been fully defined (SEQ ID NOs. 1-12). This antibody combination can specifically recognize and efficiently bind to feline NT-proBNP protein, making it suitable for the development of a highly sensitive and specific diagnostic tool for feline cardiomyopathy. By constructing a double-antibody sandwich ELISA assay system, the minimum detection limit can reach 100 pg / mL, and it exhibits excellent specificity and stability.

The invention discloses a cognitive training system and method, electronic equipment and a storage medium, and the system comprises an electroencephalogram signal collection module which uses a high-sensitivity non-invasive electroencephalogram sensor to collect an electroencephalogram signal of a user in real time; the signal processing module is used for preprocessing the collected electroencephalogram signals by using a deep learning algorithm, removing noise and extracting useful features; the training strategy optimization module is used for analyzing the electroencephalogram signals of the user based on a game theory model and formulating a personalized cognitive training strategy; and the feedback control module is used for feeding back the optimized training strategy to the user, and improving the cognitive participation degree and the training effect of the user through multi-sensory stimulation such as visual sense and auditory sense. According to the cognitive training system and method, the electronic equipment and the storage medium, the game theory is applied to the BCI system, and the cognitive training effect can be enhanced through strategy optimization.

The invention discloses a high-sensitivity tactile sensing system based on a magnetic cilia array, a sensor comprises the magnetic cilia array and a sensor array, and the magnetic cilia array is attached to the upper surface of the sensor array; the magnetic cilia array comprises a substrate and cilia structures which are orderly arranged and fixed on the substrate; the cilia structure is made of ecological silicone rubber mixed with magnetic powder, and a plurality of groups of sensors are adopted to form a sensor array to construct a sensing system. By optimizing the magnetization process, uniform distribution of the magnetic particles in each cilium is ensured, and the output stability and sensitivity of the sensor are improved; meanwhile, the multi-sensor array layout is adopted, and high-precision sensing of multi-dimensional tactile information such as pressure, direction and vibration is achieved.

The invention relates to the technical field of cosmetics, and discloses an anti-inflammatory soothing cosmetic composition which comprises the following components in percentage by weight: 0.5%-4% of a barrier repairing component, 0.5%-3% of an immunoregulation component, 0.3%-2.5% of a nerve soothing component, 0.3%-3% of an anti-inflammatory plant compound, 1%-10% of a moisturizing soothing enhancer and the balance of auxiliary materials. According to the components, through a five-dimensional synergistic mechanism of barrier repair, immune tolerance, nerve desensitization, anti-inflammatory itching relieving, moisturizing and stability maintaining, anti-inflammatory relieving and barrier repair are remarkably enhanced; ceramide, rare ginsenoside, phytosterol ester and free fatty acid are introduced to synergistically construct a bionic liposome which is closer to the composition of human cuticle lipid, so that the transdermal absorption and stability are enhanced, and the repair efficiency is remarkably improved; the dipotassium glycyrrhizinate, the tamarix chinensis flower extract, the purslane extract, the dinoflaxanthine and the baicalin cooperate to quickly resist inflammation and relieve itching and strengthen barrier repair, so that the composition is suitable for highly sensitive skin.

The invention discloses a winter wheat LAI inversion method based on scenarized parameter calibration and ensemble learning. The method comprises the following steps: fusing a remote sensing image with auxiliary geographic information such as terrain and soil, and performing typical planting scene division on a research area by adopting a spectral clustering method; then scene optimization is carried out on highly sensitive parameters (such as LAI, Cab, Cm and ALA) in the radiation transfer model PROSAIL based on a Markov chain Monte Carlo (MCMC) algorithm, and parameter posterior distribution more consistent with actual observation is obtained; further utilizing optimization parameters to generate a high-quality and homogenized simulation sample set, and mapping the simulation sample set to a Sentinel-2 waveband to construct a training data set; and finally, performing training by adopting various machine learning models (such as LightGBM, XGBoost, RF and KNN), and constructing a fusion model through a stacking integration strategy to realize high-precision inversion of LAI. Experimental results show that the method has higher fitting precision and stronger generalization ability in a plurality of typical planting scenes.

The invention discloses a digital cultural tourism management system based on multi-source data analysis, and the system comprises a multi-source heterogeneous data collection module which is used for collecting tourist behavior data, environment data, cultural resource data and third-party platform data in real time; the user demand intelligent analysis module is used for constructing a dynamic user portrait through the multi-modal interaction data and identifying dominant and implicit demands; the culture knowledge graph construction module is used for generating a reasonable multi-dimensional knowledge network based on culture resource attributes and historical data; the travel route dynamic generation module is used for generating a personalized touring route in combination with the user portrait, the real-time environment and the resource state; according to the digital cultural tourism management system based on multi-source data analysis disclosed by the invention, the utilization rate of cultural resources is greatly improved, and the decision response speed is increased; the cultural cognition depth of tourists is improved, and the residence time of the tourists is prolonged; the damage rate of high-sensitivity cultural relics is reduced; and the special group culture acquisition efficiency is improved in a breakthrough manner.

The invention provides an orbital angular momentum interferometer based on a double-resonance spiral long-period fiber grating and application, and belongs to the field of optical fiber sensing and optical communication passive devices. According to the invention, the double-resonance spiral long-period fiber grating is used as an OAM mode converter, the wavelength of the laser is secondarily regulated and controlled to match left and right resonance peaks, phase superposition of conjugate OAM beam pairs is realized, and secondary sensitization of the OAM interferometer is realized based on a single mode converter. The OAM interferometer is applied to the field of temperature and strain sensing, high-sensitivity detection of temperature variation and strain variation is achieved by combining a double-phase matrix decoupling algorithm, and the problem of cross sensitivity is effectively solved. The invention provides an all-fiber integrated and environment interference resistant innovative solution for high-sensitivity OAM optical fiber sensing, and is suitable for the fields of industrial monitoring, environment sensing and optical communication.

The invention belongs to the crossing field of medical information technology and privacy calculation, and particularly relates to a medical privacy protection method based on zero-knowledge deep learning, which comprises the following steps: constructing a medical privacy protection system comprising a client and a doctor side, and deploying a zero-knowledge neural network model based on an improved zkReLU activation function at the doctor side; the patient end receives physiological data input by a patient, carries out sensitivity grading on the physiological data, and encrypts the physiological data with different sensitivities by adopting different algorithms to obtain encrypted data; inputting the encrypted data into a zero-knowledge neural network model for forward propagation to obtain a middle-layer zero-knowledge proof; the patient terminal initiates a diagnosis result query request, and the doctor terminal integrates the intermediate layer zero-knowledge proof to generate an aggregate zero-knowledge proof to wait for verification; the verifier verifies the correctness of the aggregated zero-knowledge proof through the verification public key, and confirms that the diagnosis result accords with a preset rule and the irrelevant privacy of the patient is not leaked; local decryption of high-sensitivity data and encryption reasoning of low-sensitivity data are realized, and the leakage risk is eliminated.

The invention provides a flexible fluorescence sensor as well as a preparation method and application thereof. The flexible fluorescence sensor comprises TCTG particles and dual-network hydrogel, the TCTG particles are distributed in network pores of the dual-network hydrogel to form functional gel, the TCTG particles are formed by Ti3C2TxMXene nanosheets and graphene quantum dots, the dual-network hydrogel is formed by acrylamide and sodium carboxymethyl cellulose, and the TCTG particles are distributed in the network pores of the dual-network hydrogel to form functional gel. The functional gel is soaked in a hydrochloric acid glycol solution for treatment. The flexible fluorescence sensor provided by the invention can integrate the structural advantages of all the components, so that a synergistic coupling effect is possibly generated, a fluorescence detection function with excellent mechanical strength, frost resistance and high sensitivity is integrated into a multifunctional system, the food spoilage condition can be reliably monitored in real time under a harsh environmental condition, and the application prospect is wide. And health and economic risks caused by occupational exposure and environmental emission in an aquatic product supply chain are solved.

The invention relates to the technical field of gas detection, in particular to response type aerogel and application thereof. The response type aerogel is prepared according to the following steps: mixing and dissolving a metal organic framework material and lead acetate to obtain an adsorption and response integrated probe; mixing silk fibroin, polyethylene glycol diacrylate and the adsorption-response integrated probe, and performing light curing reaction under the action of a photo-crosslinking agent to obtain the adsorption-response integrated probe. Wherein a double-grid aerogel substrate generated by reaction of silk fibroin and polyethylene glycol diacrylate can adsorb water molecules in environments with different humidity to wet the substrate, and a saturated microscopic water environment is provided for colorimetric reaction on the surface of a pore wall, so that interference of environmental humidity on response is effectively relieved. The quantitative method established by using the response type aerogel can be used for high-sensitivity quantitative detection of hydrogen sulfide in livestock and poultry farms.

An optical arrangement for a LIDAR system includes a laser, scanner, fold mirror, lens, and sensors. Adding a wedge-shaped optical element creates an auxiliary field of view, when positioned to overlie an edge portion of the lens. The wedge-shaped optical element may have a variable transparency preventing reception by the sensors of excessive signals from close targets. The sensors may be: a plurality of sensors with unique lengths / widths, arranged to form a linear array; or sensors with the same length / width, but positioned to form an arcuate shape, compensating for an arcuate scan line; or two columns of sensors, one with a field of view in focus at far field positions, and the other in focus at near field positions, correcting for parallax effect / error; or a column of highly sensitive sensors surrounded by a plurality of guard rail sensors having higher immunity to damage from stray laser light.

The invention belongs to the technical field of digital monitoring, and provides an intelligent monitoring method and system for a digital supervision platform, and the method comprises the steps: carrying out the sensitivity grading of data, the homomorphic encryption of high-sensitivity data, and the secure multi-party calculation, achieving the secret state feature alignment, and generating a zero-knowledge proof; selecting a federal mode according to data sensitivity, injecting adaptive differential privacy noise, and encrypting transmission gradient through two channels; the aggregation gradient of the Byzantine fault-tolerant protocol is improved, abnormal nodes are detected, and reputation punishment is carried out; constructing a collaborative decision tree based on credible data, generating zero-knowledge proof and performing uplink storage, and supporting non-intrusive auditing; establishing a feedback mechanism, and dynamically adjusting privacy budget to balance privacy and monitoring efficiency; according to the method, the problems of cross-mechanism data collaboration privacy protection and efficiency balance are solved, secret state calculation, dynamic privacy adjustment and whole-process credible evidence storage are realized, and the monitoring safety and the supervision efficiency are improved.

The invention discloses an optical fiber dislocation temperature sensor and a preparation method thereof. The optical fiber dislocation temperature sensor comprises a dislocation optical fiber integrated with a photoresist film layer. The staggered optical fiber integrated with the photoresist film layer comprises a staggered optical fiber and a photoresist film layer covering a staggered area of the staggered optical fiber; the dislocation optical fiber is composed of a first multi-mode optical fiber, a second multi-mode optical fiber and a third multi-mode optical fiber which is welded between the first multi-mode optical fiber and the second multi-mode optical fiber in a dislocation mode. The staggered optical fiber is prepared through the optical fiber melting technology, the staggered area of the staggered optical fiber is coated with the SU-8 photoresist with the high thermo-optical coefficient and the high thermal expansion coefficient to form the photoresist film layer, high-sensitivity temperature sensing detection is achieved, the size is small, the preparation process is simple, and the sensor is suitable for biomedical treatment, medical treatment and the like. Wide application prospects are realized in the fields of aerospace, industry and agriculture and the like.

The invention relates to the technical field of artificial intelligence ethical decision, and discloses a self-adaptive ethical decision method and system based on cognitive development stage modeling. The system comprises a multi-modal behavior acquisition module, a cognitive stage modeling module, an ethical reasoning module, an ethical visualization module, an anomaly intervention module and the like. According to the system, behavior data in the user interaction process is collected, a cognitive stage model with self-reflection capacity is constructed, and judgment is carried out on the basis of a graph neural network by fusing ethical concepts, social specifications and context weights. The system further supports causal path visualization backtracking, similar experience migration enhancement, ethical deviation identification and memory blanking intervention, and improves reasoning accuracy and transparency. The method can be widely applied to high-sensitivity interaction scenes such as medical assistance, automatic driving and man-machine cooperation, and personalization, self-adaption and controllability of artificial intelligence ethical decision making are effectively improved.

The invention discloses a microdefect-containing high-temperature structure damage regulation and control method based on a dual-scale modeling method and a related device, and relates to the technical field of structural integrity evaluation and optimization of high-temperature alloy materials, and the method comprises the following steps: obtaining a plurality of alloy experiment samples subjected to standard heat treatment; the method comprises the following steps: establishing a macroscopic-microscopic dual-scale model based on an alloy experimental sample; mapping the macroscopic displacement field to a microscopic model in the macroscopic-microscopic dual-scale model, calculating a local plastic slippage cumulant, and taking a cumulative plastic slippage critical value as a fatigue failure criterion; based on the local plastic slippage cumulant and the cumulative plastic slippage critical value, defect parameter sensitivity evaluation is conducted on the alloy experiment sample, and the influence of the defect shape, the defect size and the defect position on the fatigue life is obtained; and carrying out surface gradient microstructure strengthening on the high-sensitivity area, optimizing a defect form through plastic deformation and transferring a damage accumulation position. The service life of the high-temperature structural part is remarkably prolonged.

The invention relates to the technical field of government affair shared data encryption, and discloses a self-adaptive government affair shared data conformal encryption method and system, and the method comprises the steps: recognizing a data entity containing potential sensitive content in original government affair data after structural analysis through employing an improved entity recognition model, and generating a sensitive tag; carrying out sensitivity evaluation on the data entities, and carrying out sensitive grading processing on the data entities by utilizing an improved clustering algorithm; and carrying out encryption processing and data replacement on the data entity after sensitive grading by adopting a self-adaptive encryption algorithm to obtain government affair shared data. The invention provides a government affair data protection method fusing entity identification, sensitivity evaluation and an adaptive encryption strategy, and the method achieves the conformal encryption protection of a high-sensitivity entity and the desensitization replacement of a low-sensitivity entity through the construction of a multi-dimensional sensitivity matrix, the fine grading of potential sensitive fields, and the matching of an adaptive encryption mode. And the privacy security and the structure availability of government affair data sharing are improved.

The invention discloses an SERS (Surface Enhanced Raman Scattering) detection method for paclitaxel drug concentration in blood of a breast cancer patient, and belongs to the technical field of detection. The method comprises the following steps: performing acetonitrile two-step precipitation centrifugal treatment on a blood sample to obtain a detection sample; the method comprises the following steps: constructing a high-sensitivity SERS substrate (the volume ratio of gold nanoparticles to ethanol is 1: (90-100), and a film is formed on a water-cyclohexane interface) through self-assembly of gold nanoparticles on a liquid-liquid interface; the method comprises the following steps: dropwise adding a sample into a substrate, and detecting characteristic peaks of 1024cm <-1 > and 1053cm <-1 > by using a portable Raman spectrometer (785nm, 30mW, 0.5 s); and calculating the paclitaxel concentration in combination with a pre-established quantitative curve. The method is easy and convenient to operate and suitable for clinical bedside rapid monitoring.

The invention constructs a universal visual virus molecularly imprinted sensor modified with an anti-protein coating, the sensor uses magnetic Fe3O4 as an imprinting carrier, HBV as a template and dopamine as a functional monomer for imprinting to obtain a molecularly imprinted polymer with a polydopamine coating (PDA), and before the template is removed, the molecular imprinting polymer with the polydopamine coating (PDA) is separated from the template, so that the molecular imprinting polymer with the polydopamine coating (PDA) is obtained. The surface of the PDA layer is covered with a slightly cross-linked PMEO2MA layer through a water precipitation polymerization method, and the polymer can effectively reduce non-specific protein adsorption; and finally, exposing an imprinting cavity of the PDA layer by eluting the template molecules. On the other hand, potassium permanganate (KMnO4) is used as a signal output molecule, and when no target object exists, the strong reducibility of PDA can enable KMnO4 entering the imprinting cavity to be subjected to a color fading reaction. Based on the principle, high-specificity colorimetric visual detection on the HBV is realized. The sensor can be combined with a smart phone through naked eyes to carry out visual semi-quantitative analysis and carry out quantitative detection through ultraviolet rays, and the universality of the sensor can be confirmed through a template replacement experiment. And meanwhile, the sensor shows an excellent cost advantage. The diagnosis which is high in sensitivity, low in cost and capable of achieving rapid visualization shows huge potential in practical application, and particularly has important application value in infectious disease screening and monitoring work in areas with limited resources.

This invention is related to the field of biosensors. In particular, devices and methods are described which enable the quantification of biomolecules by virtue of particle speed driven by induced-charge electrophoresis. For example, a range of biomolecules can be simultaneously detected in a highly sensitive manner from a library (e.g., combination) of active particles having different shapes or fluorescent signatures. Such biomolecules are related to conditions including, but not limited to, cancer biomarkers, viral infection biomarkers, toxins, pesticides, and small molecule drugs.

The invention discloses a high-sensitivity flexible tactile sensor, a preparation method thereof and an intelligent robot with a body, and the high-sensitivity flexible tactile sensor comprises a flexible chamber substrate, an anti-corrosion protection ring, a flexible cover film, a sensing material layer and a plurality of projection structures. According to the high-sensitivity flexible tactile sensor, due to the innovative design of the flexible sealing cavity substrate, the flexible cover film and the protruding structure, the flexible tactile sensor shows high sensitivity and low detection limit. Meanwhile, through the arrangement of the convex structure, the close-range sensing performance of the flexible sensor and an interaction object is improved, the micro-deformation capability of the sensor is enhanced through the multi-layer deformation of the convex structure, the flexible cover film and the cavity, and the sensitivity of the sensor is further improved.

The invention relates to the technical field of intelligent control of double-drum washing machines, and discloses an intelligent control system of an energy-saving double-drum washing machine, which comprises a hardware execution unit used for providing multi-mode sensing, accurate liquid management, mechanical execution and energy recovery functions; the control processing unit is used for processing the received data, operating an algorithm and coordinating the operation of each component of the system; the cooperative control software module runs on the main control board and comprises an acoustic fingerprint identification and fault diagnosis module and an intelligent fluid precise counterweight and cooling module; an AI-driven collaborative decision and adaptive optimization module; the invention discloses a micro heat pump energy recovery and precise temperature control linkage module. By means of the high-sensitivity acoustic array sensor and the acoustic fingerprint recognition and fault diagnosis module, clothes imbalance is recognized, point-to-point liquid balance weight is achieved by means of the micro-fluidic spraying valve array, the optimal dehydration cooperative scheduling strategy is generated, water and electricity resources are greatly saved, and the dehydration efficiency is improved.

The invention discloses an AES-GCM multimodal transport electronic waybill targeted encryption method based on a block chain, and the method comprises the following steps: obtaining an original waybill sub-waybill, extracting all fields on the waybill, and recognizing a high-sensitivity field set; performing field privacy coefficient calculation on each high-sensitivity field in the high-sensitivity field set through a privacy risk assessment model; based on a waybill ID, a timestamp and a counter, a first 128-bit key is generated and intercepted through HMAC-SHA3-512, and a session key is dynamically derived; performing GCM encryption on a field by using a session key, generating a ciphertext containing Non, Header, Ciphetext and Tag, increasing a counter, and performing targeted encryption: when the counter reaches an integral multiple of N, generating a new key, hash an old key, storing the old key through a block chain, ensuring that the key cannot be tampered, performing key rotation and storage, performing NIST randomness test and fractal dimension analysis and evaluation on an encryption result, and performing target encryption; and the performance indexes are displayed in real time through a visual interface, so that visual monitoring and performance optimization are realized.

The invention discloses a pressure detection system, and relates to the technical field of intelligent wearing, and the pressure detection system comprises 1) a flexible substrate layer which is used for fitting skin and sensing external tiny pressure changes; the micro-column array layer is composed of a plurality of micro-column structures and used for amplifying and conducting the pressure change sensed by the flexible substrate layer; the flexible gel sensing layer is used for receiving the pressure transmitted by the micro-column array layer and generating an electric signal; 4) a packaging layer; an interdigital electrode layer is arranged in the flexible gel sensing layer, an electric signal of the flexible gel sensing layer changes along with the change of external pressure, and the detection of a pressure electric signal is realized through the interdigital electrode layer. By means of the design, high-sensitivity response to tiny pressure changes can be achieved, micro-pressure signals are remarkably amplified, meanwhile, the problem of hysteresis effect generally existing in traditional silica gel or metal film materials is solved, and therefore the response speed of the sensor is greatly increased.

The invention provides an intelligent wearable high-sensitivity visual mechanical sensor and a preparation method thereof. The preparation method comprises the following steps: firstly, mixing a liquid crystal monomer, a chiral agent, a cross-linking agent, a chain extender, a photoinitiator and a catalyst, and carrying out prepolymerization reaction to obtain a first solution; then coating the first solution on the film-shaped PU adhesive to enable the cholesteric liquid crystal to complete evaporation-induced self-assembly, and then irradiating and curing under an ultraviolet lamp to obtain a color-changing film; and finally hot-pressing the color-changing film on the fabric to obtain the intelligent wearable high-sensitivity visual mechanical sensor. The color-changing film and the textile are combined through the PU adhesive, amino in the PU adhesive reacts with carbon-carbon double bonds in the color-changing layer by controlling the chemical composition of the color-changing layer, the color-changing layer and the PU adhesive are combined more firmly, the PU adhesive can permeate into the textile in the hot pressing process, and the color-changing effect is improved. The color-changing layer, the middle layer and the textile are tightly combined, and the wearable force response visual sensor better fitting the three-dimensional curved surface of the human body is prepared.