496 results about "Spectrum analyzer" patented technology

The invention relates to a wireless communication test method and system based on a portable frequency spectrograph and a medium, and belongs to the technical field of radio frequency spectrum analysis, and the wireless communication test method comprises the steps: collecting electromagnetic signal original data of a target area; constructing a dynamic electromagnetic environment baseline model; performing filtering and background subtraction processing on the original data of the electromagnetic signal; carrying out modulation mode identification, protocol analysis and terminal identification extraction on the preprocessed signal matrix, generating a multi-dimensional feature vector, carrying out convolution similarity matching on the multi-dimensional feature vector and a legal signal feature template, and distributing a threat level label; dynamically reconstructing scanning parameters of the portable spectrum analyzer according to the threat level label, generating an equipment parameter adjustment record and updating the electromagnetic fingerprint database; and generating a spectrum optimization control instruction based on the threat level label and the equipment parameter adjustment record, and issuing the spectrum optimization control instruction to the target base station or the terminal equipment. According to the application, the identification precision of the threat signal and the control closed-loop linkage capability in a complex electromagnetic environment are improved.

The invention discloses an SF6 gas leakage detection method and system based on a photoacoustic spectrum analyzer, and the method comprises the steps: arranging a sampling end to collect an SF6 gas sample, and obtaining stable gas input through constant-current sampling and steady-state pretreatment; steady-state gas is guided into the photoacoustic spectrum analyzer, and resonance frequency stabilization and signal amplification output are achieved through the self-tuning unit; executing double-microphone differential detection and digital filtering processing, and outputting a stable SF6 detection signal with a high signal-to-noise ratio; performing time calibration, abnormity elimination and consistency processing on the detection signal to generate standardized detection data; inputting the standardized data to a Transform model, and performing inversion to generate an SF6 leakage source position and a diffusion path; and displaying an inversion result on a monitoring interface, triggering a sound-light alarm when the inversion result exceeds a limit, and uploading the inversion result to a cloud monitoring platform. According to the invention, the intelligent photoacoustic spectrum system combining photoacoustic-fluid steady-state control and self-tuning detection is constructed, so that high-sensitivity detection and accurate positioning of SF6 gas leakage are realized.

The invention provides an LED lamp intelligent energy-saving control method and system, and the method comprises the steps: obtaining environment illumination intensity data, personnel flow density data and current working state parameters of an LED lamp, which are collected by a plurality of sensors, carrying out the preprocessing of the original data of the sensors, and obtaining a standardized environment perception data set; calculating power resources required by the intelligent control system are evaluated according to the LED lamp control parameter optimization scheme, the brightness output of the LED lamp is controlled according to the calculating power resources, and the current proportion of red, green and blue LED chips is adjusted according to the color temperature; whether the light beam angle needs to be adjusted or not is judged through matching analysis of the light beam angle and environmental perception data, if yes, the lens position of the LED lamp is changed, and the output spectral characteristics of the LED lamp are measured and determined through a spectrum analyzer; after sensor calibration parameters are updated, LED lamp power consumption data are collected, and if the deviation between actual power consumption and a theoretical calculation value is smaller than a preset percentage, it is determined that the energy-saving control effect reaches an expected target.

The invention relates to the technical field of boiler combustion control, in particular to a boiler combustion multi-target collaborative optimization control method and system. The method comprises the following steps: firstly, acquiring coal quality parameters in real time through a laser-induced breakdown spectrum analyzer, carrying out qualitative and quantitative analysis on spectral data by utilizing a machine learning algorithm, constructing a boiler combustion digital twinborn model fusing a combustion mechanism model and a data driving model, and predicting combustion characteristics, NOx generation trends and coking risks under different blending schemes; and then, dynamically generating an optimization instruction combination according to a prediction result of the digital twinborn model, establishing a safety interlocking mechanism while executing the optimization instruction, and automatically switching to a manual control mode when detecting that the working condition fluctuates severely or the model prediction deviation exceeds a preset threshold value. According to the method, the problems of coal quality information lag and untimely combustion adjustment caused by traditional manual sampling are effectively solved, and the economical efficiency, the safety and the environmental protection property of boiler operation are improved.

The invention discloses a wireless audio frequency band conflict avoidance method in a high-density and high-intensity electromagnetic environment, and the method comprises the steps: monitoring the signal intensity, the frequency band occupation condition and an interference source in the electromagnetic environment in real time, and carrying out the measurement of the signal intensity through a spectrum analyzer or a radio frequency detector; intelligent prediction and dynamic sensing are performed on the spectrum occupation condition by combining a machine learning algorithm, so that the frequency band of audio signal transmission is adjusted in real time, and the current idle frequency band with less interference is dynamically selected for audio transmission based on a spectrum sensing result, so that the conflict with the frequency bands of other equipment is avoided. Through the intelligent spectrum sensing technology, the spectrum use condition in the electromagnetic environment is monitored in real time, frequency band conflicts and interference sources can be efficiently and accurately found, smooth audio data transmission is ensured, transmission delay caused by the frequency band conflicts can be effectively reduced through dynamic frequency band selection and a rapid switching mechanism, and the low delay requirement of real-time audio transmission is ensured.

The invention provides a microwave superheterodyne frequency sweep measurement system based on Rydberg atoms, and belongs to the technical field of microwave frequency measurement. The laser module excites detection light of 780 nm and coupling light of 480 nm, and the two beams of light are reversely input into the atomic gas chamber through the dichroscope; signal microwaves are generated by a radio frequency signal source and are radiated to the position of the atomic gas chamber through the horn antenna; local oscillation microwaves are generated by the microwave module and are also radiated to the position of the atomic gas chamber through the horn antenna; the atomic gas chamber serves as a mixer to form a difference frequency signal; the spectrum analyzer is used for monitoring low-frequency difference frequency signals generated in the frequency mixing process in real time and recording signal intensity in real time. According to the invention, high-precision and wide-band microwave frequency measurement is realized, continuous and smooth frequency sweeping response can be provided in a frequency range, and absolute frequency detection of microwave signals is realized under the condition that a complex frequency comb technology is not introduced. The hardware architecture is simplified, the automation degree is improved, and integration, popularization and application are facilitated.

The invention discloses a multi-antenna joint precoding Gbit wireless transmission system, which relates to the technical field of wireless communication and comprises a frequency spectrum channel acquisition module, a signal preprocessing module, a precoding joint optimization module, a transmission performance evaluation module and a closed-loop parameter control module. The spectrum channel acquisition module acquires signal data and evaluates a transmission bit error rate and a signal-to-noise ratio by using a spectrum analyzer; the signal preprocessing module performs denoising and normalization and constructs a channel model; the precoding joint optimization module dynamically adjusts precoding and suppresses bit error diffusion; the transmission performance evaluation module calculates a data rate and optimizes protocol design; and the closed-loop parameter control module dynamically configures system parameters to guarantee closed-loop optimization. According to the method, the transmission efficiency and the stability of a Gbit wireless transmission system are remarkably improved, a complex channel environment is effectively dealt with, the bit error rate is reduced, the data rate is improved, a transmission protocol is optimized, intelligent dynamic adjustment of system parameters is realized, and the optimal performance of a multi-antenna joint precoding technology is ensured to be exerted.

A multi-channel analog-digital converter (ADC) subsystem for test device such as a spectrum analyzer may include multiple multi-channel ADCs to receive down-converted signals and convert the received signals to digital output signals, a field programmable gate array (FPGA) to select one or more ADCs based on a frequency, a bandwidth, and / or a signal type of each received signal and a characteristic of each ADC, and an ADC sample clock to provide a clock signal to the selected ADCs. Characteristics of the ADCs may include a resolution, a signal-to-noise-and-distortion ratio (SINAD), an effective number of bits (ENOB), a signal-to-noise ratio (SNR), a total harmonic distortion (THD), a total harmonic distortion plus noise (THD+N), and / or a spurious free dynamic range (SFDR).

The invention discloses a vernier effect and Sagnac ring-based dual-parameter optical fiber sensor, which belongs to the technical field of optical fiber sensors and comprises a broadband light source SLED (1), a coupler (2), a sensing structure A (3), a circulator (4), a sensing structure B (5) and a spectrum analyzer (6). The device comprises a first single-mode fiber (301), a polarization-maintaining photonic crystal fiber (302), a few-mode fiber (303), a fiber Bragg grating (304), a second single-mode fiber (501), a first hollow-core fiber (502) and a second hollow-core fiber (503). Parasitic interference is avoided by grinding the end face of the hollow-core optical fiber, and the reliability of the sensor is improved; two transmission peaks appear on the fiber bragg grating inscribed on the few-mode fiber through different mode numbers in the few-mode fiber, and gas concentration and temperature sensitivity of two signals can be calculated by observing drifting of the transmission peaks; an optical vernier effect can be formed through superposition of a Sagnac interferometer formed by polarization-maintaining photonic crystal fibers and an F-P interferometer formed by hollow core dislocation, and the gas concentration and the temperature sensitivity of the sensor are improved. The sensor has the characteristics of high sensitivity, wide measurement range, simple structure, small size and the like.

The invention discloses a VOCs emission dynamic prediction and energy-saving control system for catalytic combustion equipment in a casting workshop and a medium, the system comprises a high-frequency VOCs concentration monitoring unit which adopts TDLAS and FTIR spectrum analyzers and obtains high-precision concentration data through a data fusion algorithm, and a secondary differential signal of the TDLAS analyzer is independently extracted as a key feature; the data preprocessing and feature engineering module is used for processing multi-source data; the dynamic emission prediction module is internally provided with an attention mechanism time sequence convolutional network ATCN model, and realizes the ultra-early prediction of the emission concentration by fusing the secondary differential signal and historical data; the multi-objective optimization control module adopts a model predictive control MPC framework, the lowest comprehensive operation cost is taken as an objective, a dynamic virtual carbon penalty coefficient beta can be dynamically adjusted according to a workshop production plan, an advanced control instruction is generated through rolling optimization, and the equipment power and the fan frequency are adjusted; according to the method, ultra-early prediction, prospective control, energy conservation and consumption reduction of VOCs treatment are realized.

The invention provides a detection method of an end face integrated reflection type SPR optical fiber biosensor manufactured based on a 2PP technology. An experiment system mainly comprises a single-mode optical fiber, an optical fiber coupler, an SPR probe, a tungsten lamp light source, a sample pool, a spectrum analyzer and a computer. The method is characterized in that a volcanic three-dimensional microstructure is directly constructed on the end face of a single-mode fiber through a 2PP technology, a metal film with the thickness of about 50nm is deposited on the inner wall of the volcanic three-dimensional microstructure, and a stable and efficient SPR excitation structure is formed; the structural parameters are subjected to FDTD simulation optimization design, and have the characteristics of high quality factor and high sensitivity. The sensor can be used for AFP detection, the sensitivity reaches 0.684 nm / (ng / mL) within the linear range of 0-10 ng / mL, the normal and risk early warning concentration interval of human serum AFP is covered, and the sensor has good biological suitability and early hepatocellular carcinoma screening capacity; in addition, the probe structure is small in size, detection can be completed only by a few microliters of liquid to be detected, and the probe is suitable for a microfluidic platform with an extremely low sample size or a clinical sampling scene. Compared with the prior art, the device has the advantages of high structural integration, high sensitivity, low sample consumption, convenience in manufacturing, stability, reliability and the like.

The invention discloses an intelligent monitoring device for chest drainage components, which comprises a spectrum analyzer and a drainage bin, a main control chip; an output unit; a power supply unit; a detection area is arranged on one side of the spectrum analyzer, a detection end capable of stretching into the detection area is arranged on one side of the drainage bin, a detection cavity allowing drainage liquid to enter is formed in the detection end, the optical detection module comprises a light source module capable of emitting light beams to the detection cavity and a detector used for receiving reflected light beams, and the detector is connected with the main control chip. A reflective optical detection technology is adopted, monitoring of key components such as hemoglobin, chylomicroparticles and inflammatory factors is realized at the same time, a characteristic absorption spectrum of a specific biomarker can be covered by a multi-wavelength light source module, and concentration change trends of various components are synchronously obtained by combining absorbance dynamic analysis of a main control chip; the limitation of single parameter detection of a traditional device is broken through.

The invention provides a device and method for manipulating and regulating the bandwidth of a quantum compression state light field, and belongs to the technical field of optics. The problems that an experiment system is complex and high in cost due to the fact that existing bandwidth compression manipulation experiments depend on additional optical devices are solved. The device comprises an optical module, a data acquisition module and a data processing module, two BHDs are used for detecting noise variances of an upper sideband mode and a lower sideband mode based on compression carrier symmetry respectively, then an oscilloscope and a spectrum analyzer are used for detecting time domain signals and frequency domain signals of the BHDs respectively, and broadband compression state light field noise distribution is obtained. A collected time domain signal is post-processed by using an LPSD algorithm, and frequency-dependent differential phase shift is introduced into an upper sideband mode, so that bandwidth compression control of low-pass filtering, high-pass filtering and band-pass filtering effects can be realized.

The invention discloses an automatic medicament preparation and dosage control system based on an artificial intelligence technology and a method thereof, relates to the technical field of industrial medicament preparation, and solves the problems that although the flow of medicaments can be controlled to a certain extent in the prior art, most medicaments lack intelligent prediction capability and cannot effectively process complex nonlinear working conditions. Comprising a sensor module, an intelligent controller and an actuator module, the sensor module comprises a spectrum analyzer and a weighing module and is used for monitoring components and weight of a medicament in real time, the intelligent controller processes data of the sensor module and predicts medicament dispensing parameters, the actuator module executes medicament metering, water adding and stirring operations, the sensor module monitors a medicament dispensing result in real time and feeds back the medicament dispensing result, and the intelligent controller corrects errors. Through an integrated high-precision sensor, an advanced intelligent control algorithm and a highly-automatic execution mechanism, comprehensive automatic, precise and intelligent management of the medicament preparation process is realized.

The invention relates to the technical field of quality safety control of traditional Chinese medicinal materials, and discloses a traceability management system and method for a traditional Chinese medicinal material planting base, and the system comprises an environment monitoring layer, a data collection layer, a block chain evidence storage layer, an intelligent analysis layer, and a user interaction layer. The environment monitoring layer comprises a soil temperature and humidity sensor, an illumination intensity sensor, a meteorological station and a multispectral unmanned aerial vehicle, the environment monitoring layer is used for collecting environment data in real time, and the data collection layer comprises a farming operation recording terminal, a medicinal material growth image collection device and a near infrared spectrum analyzer. By integrating an environment monitoring layer, a data acquisition layer, a block chain evidence storage layer, an intelligent analysis layer and a user interaction layer, full-chain traceability management from planting to circulation of a traditional Chinese medicinal material planting base is realized, the problem of data islands is effectively solved, the credibility and integration of data are improved, the quality safety level of traditional Chinese medicinal materials is improved, and the safety of the traditional Chinese medicinal materials is improved. And a solid foundation is laid for sustainable development of the traditional Chinese medicinal material industry.

The invention relates to the technical field of spacecraft structure micro stress detection, in particular to a spacecraft structure micro stress detection device and a use method thereof, and the spacecraft structure micro stress detection device comprises a displacement amplification structure, a single mode fiber, a reflector, a broadband light source and a spectrum analyzer. An optical resonant cavity formed by an optical fiber end face and a lens is combined with a displacement amplification structure, when stress acts on a spacecraft structure, the cavity length of the Fabry-Perot resonant cavity changes, so that phase movement of light is caused, and accurate measurement of the stress can be achieved by detecting the phase movement. The antenna has extremely high anti-electromagnetic interference capability, and can work stably in a complex space environment. Even under the condition of violent temperature change, high measurement accuracy can be kept, and detection of tiny stress can be achieved through the amplification effect of the displacement amplification structure. And the stress characteristic signal and the background noise can be effectively separated, so that the detection reliability is remarkably improved.

The invention discloses a CO2-water-rock reaction process in-situ measurement system and a CO2-water-rock reaction process in-situ measurement method, and relates to the technical field of geochemical water-rock reaction. The system comprises a reaction kettle unit, a CO2 injection unit, a pure water / salt water injection unit and a data acquisition unit, the reaction kettle unit comprises a reaction kettle, a vacuum pump and a temperature control device, the reaction kettle is provided with a containing cavity, the vacuum pump is communicated with the containing cavity of the reaction kettle, the temperature control device is located outside the reaction kettle, the CO2 injection unit is communicated with the reaction kettle, the pure water / saline water injection unit is communicated with the reaction kettle, and the temperature control device is located outside the reaction kettle. The data acquisition unit comprises a light source, an optical fiber, a spectrum analyzer and a data acquisition and analysis device; the CO2-water-rock reaction monitoring system has the beneficial effects that real-time monitoring of the whole CO2-water-rock reaction process is realized, and the problem that the reaction process cannot be monitored in real time in the previous CO2-water-rock reaction is solved.

The invention discloses a multispectral intelligent identification system for protein post-translational modification sites, comprising: a spectral data acquisition module for controlling different spectrum analyzers to perform spectrum scanning and analog-to-digital conversion and formatting on protein samples in parallel to obtain multiple protein multispectral original data; the intelligent analysis module is used for carrying out preprocessing and feature extraction on the multi-spectral original data of each protein to obtain a plurality of standardized spectral feature vectors; fusing each standardized spectral feature vector to obtain a multi-dimensional feature vector, inputting the multi-dimensional feature vector into a pre-trained modification site recognition deep learning model, and outputting a recognition result list, the recognition result list comprises the positions of the recognized protein post-translation modification sites in the protein sequence and modification types corresponding to the protein post-translation modification sites; and the result output module is used for visually displaying and exporting the identification result list. According to the method, the accuracy and flux of protein post-translational modification site recognition are remarkably improved.

The invention discloses a system for simultaneously measuring temperature and pressure based on forward Brillouin scattering in a multi-core optical fiber, which relates to the technical field of optical fiber temperature and pressure double-parameter sensors, and is characterized in that light emitted by a pump light source enters a polarization controller after being modulated by a pump light modulation system, and then enters an erbium-doped optical fiber amplifier; one part is injected into a Sagnac ring, and the other part excites a high-order torsion-radial mode through a multi-core optical fiber; light emitted by the detection light source is divided into light beams transmitted in the clockwise direction and the anticlockwise direction through the coupler, and the light beams are injected into the Sagnac ring; the spectrum analyzer captures the frequency shift of the Brillouin scattering signal; the signal processing unit processes the frequency shift of the Brillouin scattering signal and inverts temperature and strain data; and the data analysis and feedback system is combined with machine learning to optimize temperature and strain data. According to the invention, high-sensitivity temperature and strain sensing is realized.

The invention discloses a liquid rocket engine combustion tail flame detection device and method, the device comprises an air inlet pipe, an exhaust pipe, a gas chamber packaging pipe and an intelligent controller, a plurality of detection devices such as a temperature sensor and a spectrum analyzer are arranged in the gas chamber packaging pipe along the airflow direction, and the detection devices are connected with the intelligent controller to form a data transmission channel; the detection method comprises the steps that the device is initialized, and all devices are calibrated and debugged; after the engine is started, tail flame parameters are detected in real time and transmitted to the intelligent controller; the controller performs preprocessing and deep analysis on the data; comparing an analysis result with a preset normal parameter range to judge the working state of the tail flame; and if normal, the data are backed up periodically, and the long-term trend of the performance of the tail flame can also be predicted. According to the method, the tail flame parameters can be comprehensively and accurately detected in real time, intelligent analysis and abnormal early warning are achieved, and the safety and reliability of an engine are improved.

The invention discloses a circuit board testing and quality screening automation method and system, and aims to solve the problems of low efficiency, insufficient precision and imperfect quality control of traditional circuit board testing. Precise positioning of the circuit board is achieved through the high-precision X / Y / Z three-dimensional positioning mechanical arm, parallel testing is conducted in combination with equipment such as a multi-channel oscilloscope, a signal source and a spectrum analyzer, and the testing efficiency is improved. Temperature and humidity control testing is carried out through the environment simulation bin, the thermal imager scans temperature distribution of the circuit board, a high-precision instrument is used for detecting signal integrity and analyzing electromagnetic compatibility, and the performance of the high-speed circuit board is ensured. A machine learning algorithm predicts potential faults, a test process is optimized, an automatic sorting system is adopted to separate qualified and unqualified circuit boards, and high consistency and high reliability of product quality are ensured. Through the automatic and intelligent testing process, the production efficiency, the quality control capability and the testing precision are greatly improved, and the labor cost and the production risk are reduced.

The invention relates to the technical field of illuminating lamps, and discloses a nature-imitating intelligent LED illuminating system, which comprises an outdoor data acquisition module used for collecting illumination related data in an outdoor natural environment and recording the real state of outdoor natural light at any moment through a high-precision sensor; and the outdoor data processing module is connected with the outdoor data acquisition module, and the outdoor data processing module is used for removing abnormal values of original data acquired outdoors, unifying data formats and then applying a data analysis and modeling technology. High-precision sensor equipment is used for accurately collecting outdoor light intensity, spectrum, position and trajectory data in real time, a light intensity sensor is wide in measurement range and rapid in response, a spectrum analyzer can accurately analyze the spectrum, the sun position and trajectory tracker is accurate in positioning, and the collected key data can be immediately synchronized to an indoor lamp or a screen.

The present invention relates to the technical field of optical fiber sensing. Disclosed are a multi-core grating sensor and a manufacturing method therefor, and a permafrost monitoring method. The multi-core grating sensor comprises a multi-core optical fiber grating, a strain gauge structure, and a demodulator, and the multi-core optical fiber grating comprises four uniformly and symmetrically distributed single-mode optical fibers, a cladding layer wrapping the four single-mode optical fibers, and a coating layer located between the single-mode optical fibers and the cladding layer; the strain gauge structure is attached to the outside of the multi-core optical fiber grating by means of glue bonding; and the demodulator is used for monitoring the dynamic change of the wavelength of the multi-core optical fiber grating, the demodulator comprises a broadband light source and a spectrum analyzer, an incident end of the multi-core optical fiber grating is connected to the broadband light source by means of the single-mode optical fibers, and an exit end thereof is connected to the spectrum analyzer by means of the single-mode optical fibers. Also disclosed in the present invention is a permafrost monitoring method. By means of comprehensive analysis and demodulation of fiber core wavelength variation amounts of a plurality of single-mode optical fibers on a single multi-core optical fiber grating, simultaneous measurement of multiple parameters is achieved, and the permafrost monitoring accuracy is improved.

The invention relates to a boiler operation parameter optimization method and system for multi-fuel combustion of multiple solid wastes, and the method comprises the following steps: (1) multi-source data collection: obtaining the heat value, the water content, the chlorine-sulfur ratio and the heavy metal content of the solid wastes in real time through a spectrum analyzer, a visual recognition system and an online sensor; (2) intelligent compatibility optimization: calculating a solid waste mixing ratio by adopting a genetic algorithm based on calorific value balance and pollutant inhibition targets, and controlling a Cl / S molar ratio to be 1.2-1.8 and the alkali metal content to be 1t; 50%; (3) pretreatment and drying: the water content gt; and carrying out microwave-steam combined drying on 25% of solid waste, and dynamically adjusting microwave power, steam injection time and the like. The method has the advantages that through the technical integration of multi-source data fusion, intelligent algorithm optimization and digital twinborn verification, a solid waste co-combustion full-process optimization system is constructed, and ultralow emission of pollutants and safe and economical operation are achieved while the energy utilization rate is increased.

A semiconductor etching process end-point detection system includes a sensor configured to measure in real-time electrical properties associated with a semiconductor etching process and to generate raw sensor data, and a computing device configured to receive the raw sensor data. The computing device includes spectrum analyzer circuitry and a memory configured to execute instructions of the spectrum analyzer circuitry via at least one processor. The instructions include obtaining, via the sensor, the raw sensor data; receiving, at the computing device, the raw sensor data; preprocessing the raw sensor data to normalize the raw sensor data to a standard range or distribution; selecting at least one best scoring signal of the normalized sensor data; converting the at least one best scoring signal to a pixel space; and performing an end-point prediction algorithm on the pixel space to predict the end-point of the semiconductor etching process.

The invention relates to an intelligent stair life prediction and maintenance method and system based on multi-sensor fusion, computer equipment and a storage medium. The method comprises the steps that a laser sensor is adopted to scan a stair to obtain a wear data set of the stair; based on at least one pressure sensor preset in each designated area of the stairway, a pressure data set of each designated area of the stairway is obtained; identifying the type of the stair material by adopting a spectrum analyzer to obtain a wear-resistant coefficient and a maximum wear depth corresponding to the type of the stair material; and constructing a life prediction operator, calculating the life of each specified region of the staircase through the life prediction operator, predicting the overall life of the staircase according to a calculation result, and calculating maintenance data of the staircase through a K-means clustering algorithm. By adopting the method, the wear depth, the pressure distribution and the material fatigue condition of the stairs can be monitored and evaluated in real time, and the service life prediction and maintenance analysis are carried out by combining an algorithm.

The invention discloses an environmental physical security detection method, which relates to the technical field of information security, realizes multi-dimensional data acquisition by comprehensively using a thermal imager, a spectrum analyzer and an X-ray machine through the steps S1 to S5, overcomes the blind area of traditional manual detection, and ensures comprehensive identification of hidden secret stealing equipment. And secondly, through de-noising and standardization processing, the accuracy and reliability of the data are enhanced, and the risk of false alarm and missing alarm is reduced. In the feature extraction stage, key parameters such as a mean value Tm, a standard deviation Ts, a maximum frequency Fmax, a maximum intensity Imax and an edge feature Es are utilized to construct a scientific anomaly detection formula, so that the calculation of an anomaly detection index Da is more accurate, and potential safety hazards can be effectively identified. In addition, through matching of a secondary verification mechanism and historical data, the credibility of the detection result is further improved, so that a solid technical support is provided for security protection of a secret-related environment.

The invention provides an anti-interference detection method and system for a methane gas sensor in a complex environment, a storage medium and a program product, and relates to the technical field of gas detection. A methane gas sensor is used for acquiring an original value of methane concentration, and a multi-wavelength spectrum analyzer is used for acquiring a mixed spectrum containing methane and interference gas information. An interference coefficient library is utilized, the interference coefficient library comprises the interference coefficient of each interference gas to the methane sensor and a standard multi-wavelength spectrum, and the interference gas with the maximum contribution can be matched and recognized according to spectral characteristics. After the concentration is determined, the interference value is obtained by multiplying the interference coefficient, the interference value is accumulated, the corresponding scaled standard multi-wavelength spectrum is subtracted from the residual spectrum to update the residual spectrum, and the interference gas influence is stripped circularly. The method does not need to depend on easily-lost filtering or adsorbing materials, the problems of cost and workload increase caused by regular replacement due to material performance reduction are avoided, meanwhile, complex environment interference gas can be effectively dealt with, and high-precision and reliable methane concentration detection is achieved.

The application discloses a handheld spectrum analyzer real-time spectrum signal processing system and processing method, the system comprises a pre-processing unit, an ADC unit, an FPGA and an ARM which are connected in sequence, the FPGA comprises a digital down conversion unit, a multi-rate decimation filter unit, a real-time FFT operation unit and a real-time detection unit which are connected in sequence, and a grid mapping unit, a vector connection unit and a fluorescence statistical unit which are connected with the real-time FFT operation unit in sequence, the ARM comprises a real-time spectrum diagram and waterfall diagram unit which is connected with the real-time detection unit, and a fluorescence display unit which is connected with the fluorescence statistical unit. The application adopts parallel frame real-time detection and vector connection-based digital fluorescence statistical method to compress multiple spectrum data, reduces the requirement of a large number of spectrum data on screen refreshing, adopts vector connection to make fluorescence statistics, so that the measured signal is easier to distinguish, and the application meets the test requirement of a handheld instrument.

The invention discloses a laser device mode hopping detection method, and relates to the technical field of laser detection. Comprising the following steps: a to-be-tested laser emits an optical signal, and the optical signal of the laser is converted into an electric signal; and analyzing the frequency spectrum of the electric signal, and determining whether the laser generates mode hopping or not by judging whether a cross relaxation signal caused by double longitudinal modes exists in the frequency spectrum or not. The laser mode hopping detection method provided by the invention is simple in structure, can realize mode hopping real-time monitoring only through the photoelectric detector and the spectrum analyzer, and is low in cost and convenient to deploy; an interferometer or a delay fiber is not needed in the detection process, the anti-interference capability is high, and mode hopping is visually judged through frequency spectrum changes.