1943 results about "Dynamic range" patented technology

The invention relates to the technical field of organic display data processing, in particular to an organic display interface multichannel signal modulation method, which comprises the following steps of: generating a standardized data set through gamma correction and gamut mapping, and inputting the standardized data set into time sequence, amplitude and frequency sub-models deployed in a federal learning framework; and respectively analyzing the pulse width-refresh rate relevance, the driving voltage-brightness nonlinear relationship and the conduction period-mobility dynamic response, generating an optimized weight coefficient, and fusing the optimized weight coefficient into a boundary constraint condition of a cross-sub-model. A migration rate parameter index, amplitude gradient calculation and duty ratio correction service of chain calling is constructed based on a service grid, a reinforcement learning dynamic routing strategy is combined to avoid resource competition nodes, and brightness error characteristics are periodically fed back to reversely optimize gradient updating. According to the method, the conflict between time sequence deviation accumulation and local optimum is effectively suppressed, the color gradation continuity, the dynamic range and the edge sharpness are improved, and efficient cooperative modulation of multi-channel signals is realized.

The invention discloses a three-dimensional panoramic intelligent monitoring method and device for a coal conveying gallery, and relates to the technical field of industrial automation and intelligent monitoring, and the method comprises the steps: obtaining initial point cloud data and an initial multispectral image of the coal conveying gallery through a rotary laser radar, a high-dynamic-range camera and an infrared thermal imager; inertial measurement units are arranged in the devices to collect vibration data, and the vibration data are used for carrying out vibration compensation on point cloud and images to generate target point cloud data and target multispectral images; thirdly, performing three-dimensional modeling and multispectral texture mapping on the coal conveying gallery based on the data to obtain a target three-dimensional model; and finally, mapping equipment, personnel and environment data into the three-dimensional model in real time, displaying each piece of state information, and realizing comprehensive monitoring. According to the application, high-precision three-dimensional panoramic monitoring can be realized in a complex vibration environment of the coal conveying gallery, and the safety management level and the operation and maintenance efficiency of the coal conveying gallery are effectively improved.

The invention provides a multi-band radio frequency power amplifier dynamic range adaptive test method and a system thereof. The method comprises the following steps: acquiring an output signal frequency spectrum of a tested radio frequency power amplifier, extracting characteristic frequency points including a center frequency and a bandwidth, matching the characteristic frequency points with a preset frequency band database, and automatically loading a test scheme of a corresponding frequency band. According to the method, the frequency bands are automatically matched through spectrum sensing, the test scheme is loaded, the multi-frequency-band characteristics can be rapidly adapted without manual parameter configuration, index missing test is avoided, and the switching efficiency is improved; dynamically optimizing test parameters by using a genetic algorithm, and accurately capturing a nonlinear distortion critical point while balancing coverage and efficiency; by combining multi-dimensional signal analysis and a deep learning model, the problem of missing detection of traditional single-domain analysis is solved, and the abnormal signal recognition capability is remarkably enhanced; through linear model correction, impedance dynamic matching and index threshold iteration, full automation and high precision of the test are realized, the environmental interference influence is effectively reduced, and a self-adaptive test system is constructed.

The invention discloses a document layout analysis method based on a hybrid method, and belongs to the technical field of digital image processing. Named body recognition and relation extraction are carried out on each text node. The invention provides a novel channel shuffling dynamic range convolution algorithm to ensure that global channel features can learn features of similar pixels rather than adjacent pixels, and an adapter is used to learn text features with less parameter quantity. And finally, taking the predicted text block category and relationship as a result. Finally, a challenging document data set is used as a verification index (FUNSD), and the result shows that the performance of the method can be obviously improved.

The invention provides a roof leakage point intelligent positioning method and system based on machine vision, and relates to the technical field of constructional engineering detection.The method comprises the steps that 1, roof image data and surface texture, temperature field and environment illumination parameters are collected through a visible light and infrared thermal imaging two-channel sensing device, a multi-dimensional data set is constructed, and a multi-dimensional data set is established; generating visual data through dynamic range correction based on the multi-dimensional data set; step 2, based on visual data, performing detection area division on the acquired image, extracting a local temperature difference gradient, a surface texture abrupt change rate and a liquid flow track parameter, and establishing a multi-index characteristic matrix; according to the method, the features of the roof image are extracted through machine vision, intelligent positioning, risk grade division and dynamic evolution tracking of roof leakage points are realized, and the leakage positioning accuracy is improved.

The invention provides a low-light large dynamic image enhancement method based on dynamic weight and pyramid fusion. The low-light large dynamic image enhancement method is suitable for complex illumination imaging in security monitoring. According to the method, the global weight and the detail weight of an image are obtained according to the global average brightness, the local brightness and the gradient of an image sequence, and the total weight is obtained through weighting. And the halo phenomenon easily occurring in the fusion process is reduced through guide filtering. And combining Gaussian pyramid and ratio pyramid decomposition and weighting to obtain a final fusion image. According to the method, the problems of detail loss and limited dynamic range in the low-light scene are effectively solved. Experiments show that the method is superior to the prior art in information entropy, average gradient, edge strength, spatial frequency and other key indexes. The technology has an all-time adaptive capability, is suitable for the fields of intelligent transportation, urban security and protection, low-illumination monitoring and the like, and has a wide market prospect.

The invention discloses a roadway deformation monitoring device based on a millimeter wave radar. The roadway deformation monitoring device comprises a main shell, the millimeter wave radar, a laser sensor, a PCBA (Printed Circuit Board Assembly) and a bubble level, and an integrated multi-modal data fusion analysis module, a dynamic measurement range intelligent adjustment module, a real-time deformation prediction and control module and a self-calibration and fault diagnosis module. The multi-modal fusion system fuses radar and laser data through a Kalman filtering algorithm, and full-scale high-precision monitoring is realized by using median filtering, Gaussian fitting preprocessing and dynamic weight distribution; the dynamic range measurement module intelligently switches measurement and frequency sweeping ranges based on a decision tree algorithm according to mining progress, geological conditions and distance fluctuation coefficients; the real-time prediction module adopts an ARIMA model to predict the deformation in advance, and automatically adjusts the scanning angle and the acquisition frequency; the self-calibration module uses a high-precision reflecting plate to correct errors everyday; the system supports 5G communication and remote control, has the advantages of high precision, self-adaption and high reliability, and is suitable for long-term deformation monitoring of mine roadways.

The invention relates to the technical field of robot control, and discloses a heterogeneous robot control system with intelligent and multi-modal perceptual driving, comprising: a quantum clock reference module used for generating a globally synchronized picosecond-level time reference signal and synchronizing a multi-modal sensor clock through a microwave pulse; the multi-mode sensing module comprises an event camera of which the dynamic range is greater than or equal to 120dB, a six-dimensional force sensor of which the noise density is less than or equal to 0.01 N / Hz and an inertial measurement unit of which the zero-bias stability is less than or equal to 0.8 degree / h; and the random differential manifold module adopts a four-layer full-connection neural network, and an input layer receives multi-modal data. According to the invention, a diamond NV color center system of the quantum clock reference module and a microwave pulse coupling technical scheme are adopted, so that a picosecond-level global signal synchronization effect is achieved. Compared with a scheme depending on a traditional crystal oscillator or a GPS clock in the prior art, the defects that electromagnetic interference is prone to occurring and signal jitter is large are overcome, and high-precision time sequence alignment of multi-module cooperation is ensured.

The invention discloses a laser radar test method based on a long-distance target distance measurement result, and the method comprises the following steps: obtaining a laser radar echo signal, and extracting the frequency spectrum information of the echo signal; doppler frequency shift characteristic parameters are extracted according to the frequency spectrum information, and the relative speed of the target is calculated based on a preset frequency shift calculation model; acquiring multi-source sensor data associated with the laser radar test platform, and fusing to construct a dynamic ranging reference coordinate system; performing dynamic motion compensation on a laser ranging result according to the relative speed of the target to obtain a target initial measurement distance after Doppler correction; mapping the target initial measurement distance after Doppler correction to the dynamic distance measurement reference coordinate system to obtain a remote target final distance measurement result aligned with a test platform coordinate system; and outputting the accurate position and moving state information of the target in the three-dimensional space according to the final distance measurement result. According to the invention, the ranging precision and stability can be improved.

An electronic interface device is configured for use with associated optics for employing coded light for illuminating a liquid, gaseous, or other analyte or target, such as for measuring or determining a composition or other property of the analyte or target. The arrangement can help enable a far higher level of performance, such as for spectral analysis, imaging, or both. A shared common clock on both the illumination and receive sides of the system can be included, such as together with one or more of reference detection, per-channel wavelength-dependent modulation, multiple concurrent feedback loops at different levels, orthogonal and circulant codes, phase-scrambling to better utilize ADC dynamic range, oversampling, and other signal processing can be provided.

The invention discloses a wavefront reconstruction method for improving the dynamic range of a Shack-Hartmann wavefront sensor. Belongs to the technical field of wavefront detection. According to the method, a new Shack-Hartmann wavefront detection method is needed, the effective dynamic range of a Shack-Hartmann sensor can be expanded on the premise that the hardware complexity is not remarkably increased, local mismatching accumulation can be avoided through a reasonable matching strategy, and the detection accuracy is improved. Therefore, high-precision and high-reliability wavefront reconstruction can be realized in a large-amplitude wavefront distortion scene. Comprising the following steps: S1, detecting by a Shack-Hartmann wavefront sensor to obtain a light spot distribution diagram H (x, y); s2, extracting a light spot centroid pixel-level position through a matched filtering algorithm; s3, calculating the sub-pixel-level position of the mass center of the light spot through Gaussian interpolation; s4, a mass center-subaperture matching relation is established through a Kuhn-Munkres algorithm; and S5, calculating the wavefront slope according to the corresponding relationship between the centroid and the sub-aperture, and then recovering the wavefront according to the wavefront slope.

A display device includes: a first sub-pixel configured to receive a first data voltage and drive a first light emitting element included in the first sub-pixel; a second sub-pixel configured to receive a second data voltage and drive a second light emitting element included in the second sub-pixel; a third sub-pixel configured to receive a third data voltage and drive a third light emitting element included in the third sub-pixel. At least one of dynamic ranges, maximum voltages, and minimum voltages of the first data voltage, the second data voltage, and the third data voltage are different from each other. An emission time of the first light emitting element, an emission time of the second light emitting element, and an emission time of the third light emitting element are different from each other.

The present disclosure relates to an active graded magnetic compensation system and method for an unshielded SERF magnetometer. The system comprises: a detection laser, a half-wave plate, a magnetic field compensation coil, a magnetic field modulation coil, a non-magnetic heating assembly, an alkali-metal atomic vapor cell, a polarizing beam splitter prism, a balanced photodetector, a graded feedback control module, a pump laser, a quarter-wave plate, a focusing lens and a photodetector. By means of the present disclosure, a graded compensation system is used to realize high-precision compensation for a magnetic field within a large dynamic range in a geomagnetic environment, thereby ensuring that an instrument carries out high-sensitivity magnetic field measurement under geomagnetic conditions.

The invention relates to a partial discharge detection system based on Rydberg atoms in the field of partial discharge detection of electrical equipment, the system comprises an optical path frequency stabilization module, an atom probe, a photoelectric detection module, a controller module and a power frequency synchronous trigger signal circuit, the optical path frequency stabilization module locks 852.35 nm probe light and pump light frequency less than 509.53 nm through SAS and EIT technologies, and the atomic probe is used for detecting the frequency of the probe light. Inducing transition from a cesium atom ground state to a first excited state to a Rydberg state; under the effect of partial discharge pulse, the atomic probe outputs a modulated EIT transmission spectrum signal, after photoelectric conversion and filtering, the controller module analyzes the amplitude and phase information of the pulse in combination with a power frequency synchronizing signal, the upper computer generates a PRPD diagram to analyze the discharge correlation, the detection sensitivity of the system reaches-50dBm, the frequency band of 300MHz-2GHz is covered, the dynamic range is greater than or equal to 50dB, the equivalent height is greater than or equal to 20mm, and the discharge correlation is greater than or equal to 20mm. Broadband and high-resolution detection is achieved, the problem of phase synchronization is solved, and the device is suitable for high-voltage environment on-line monitoring.

The invention discloses a global enhancement method for a wide-area astronomical image. The method comprises the following steps: carrying out high-frame-frequency image acquisition on a starry sky area; converting the reference star from a star catalogue position to an observation position, and resolving a linear negative film model; geometric distortion correction is carried out based on the resolving result; based on the image after geometric distortion correction, matching and identifying a reference star in a full view field, and obtaining celestial coordinate information of all fixed star images in the view field; on the basis of celestial coordinate information, correcting a poorer astronomical effect of the astronomical image, establishing an ideal coordinate system taking the center of a view field as a tangency point, and projecting a time sequence observation image to the ideal coordinate system; translating the processed graph, accumulating all translated images, and averaging all accumulated pixel positions to realize image superposition enhancement, thereby effectively improving the dynamic range of a detector and the detection capability of a wide-area astronomical observation system; and meanwhile, the signal-to-noise ratio of the astronomical image can be effectively improved, and the astronomical image centering and light measuring precision can be further improved.

The invention relates to the technical field of camera control, and discloses a megapixel camera control method based on multifunctional fusion. The method comprises the following steps: acquiring original image data of an image sensor, and preprocessing to generate an initial brightness distribution diagram; and calculating a scene dynamic range to determine a target exposure parameter set containing exposure time, a gain coefficient and an aperture value, synchronously analyzing color temperature information, matching a preset white balance model to output a correction coefficient, and combining the two to generate a first control instruction to be sent to the image sensor. Receiving a touch screen focusing signal, and extracting a focus area coordinate to adjust a stroke parameter of a focusing motor; ambient light intensity is monitored in real time, and when the ambient light intensity is lower than a preset threshold, a flash lamp compensation module is activated and a compensation light quantity value is calculated. In the photographing mode, the output power of the flash lamp is adjusted according to the compensation light quantity value, the target exposure parameter set is recalibrated based on the focus area coordinates, and the camera complex scene adaptation and imaging quality are improved.

The invention relates to an optical cable monitoring and data analysis method and device, equipment and a medium. The method comprises the following steps: acquiring current state data of an optical fiber link, and dynamically generating adaptive pulse coding parameters and matched filter parameters based on the data by using a deep reinforcement learning agent, so as to generate and inject coded pulses into the optical fiber link; and then receiving an echo signal, performing matched filtering processing on the signal by using the generated matched filter parameter to obtain a filtering output signal, further calculating a performance index vector and a reward signal, and finally updating a strategy network of the intelligent agent by using the reward signal, thereby realizing continuous optimization of pulse coding and matched filtering parameters. Therefore, the system can automatically adapt to the dynamic change of an optical fiber link, the spatial resolution, the dynamic range and the signal-to-noise ratio are effectively improved, and the adaptive capability and the robustness of the system are enhanced at the same time.

A control method of a high gain image sensor is provided. A column bias current source and a column PMOS amplifier transistor are provided in a column signal readout unit, the column bias current source is connected to a column-common current output connecting line, a drain of the column PMOS amplifier transistor is connected to a column-common current input connecting line, and a gate of the column PMOS amplifier transistor is connected to the column-common current output connecting line, to acquire an amplified signal of a floating diffusion region of a readout row pixel unit on the column-common current input connecting line. An SHCG is achieved, and a dynamic range in a dark light scene is expanded. A device structure size in the column signal readout unit can be much larger than the transistor in the pixel, which results in better process consistency and more flexible adjustment of the conversion gain.

The invention discloses a self-energy-supply multi-mode sensing electronic skin based on ionic gel heterojunction array integration and a preparation method and application of the self-energy-supply multi-mode sensing electronic skin. The electronic skin adopts a multi-layer composite structure design and comprises an electrode array layer, a silver paste connecting layer, a nano material doped ionic gel array layer and a pure ionic gel continuous layer, and passive self-energized work is realized through a space ion migration effect at a heterogeneous gel interface. The method is characterized in that the design of a multi-layer flexible composite structure is adopted, space-time coded light, temperature, pressure and humidity four-mode stimulation can be synchronously converted into electroneurographic signals, and a collaborative identification strategy of response intensity dynamic range and synaptic learning / delay time difference is utilized; and high-precision decoupling of the multi-source signals is realized in combination with a classification decision tree algorithm. The electronic skin has the characteristics of flexibility, deformation, environment self-repairing and bionic synapse, and geometrical characteristics of a reconfigurable target source are fused through time-space domain multi-modal data.

The invention relates to the technical field of optical fiber monitoring and maintenance, and discloses an optical fiber monitoring method, device and equipment, a storage medium and a computer program product, and the method comprises the steps: enabling pulse light of a preset period to be coupled into a to-be-detected low-loss optical fiber based on an optical fiber amplifier and a variable optical attenuator, and generating a backward scattering light signal; converting the backward scattering light signal into an electric pulse signal by using a single-photon detector, and counting the electric pulse signal by using a preset period as a period through a synchronous clock to obtain a counting result; adjusting the power of the variable optical attenuator according to a counting result, and drawing a target signal curve of the to-be-measured low-loss optical fiber based on an adjustment result; and analyzing the target signal curve to obtain a monitoring result of the to-be-measured low-loss optical fiber. The power is dynamically adjusted in different measurement sections, and the multi-section measurement results are superposed, so that the dynamic range of the single-photon optical time domain reflectometer is remarkably expanded, and the loss and dead pixels of the low-loss optical fiber can be reflected more comprehensively and accurately.

In order to solve the problem that quick response and distortionless recording of ultrahigh-frequency partial discharge signals are difficult to realize when accidental pulses are generated in the prior art, the invention relates to a dual-channel parallel processing architecture for ultrahigh-frequency partial discharge signals, which comprises a signal cloning circuit and a signal processing circuit, the ultrahigh-frequency partial discharge module is used for receiving ultrahigh-frequency partial discharge signals and synchronously outputting the ultrahigh-frequency partial discharge signals as first target signals and second target signals after lossless copying; the low-gain channel circuit is used for performing buffer transmission for maintaining an original bandwidth and a dynamic range on the first target signal to generate a first gain signal; the high-gain channel circuit is used for performing gain amplification on the second target signal to generate a second gain signal; the digital signal processing unit is used for performing synchronous clock control on the low-gain channel circuit and the high-gain channel circuit; and the FPGA chip is integrated in the digital signal processing unit and is used for performing fusion splicing processing on the first gain signal and the second gain signal based on a waveform fusion splicing algorithm and generating a fusion signal.

A lidar system uses a detector chip have a first column of light sensors and a second column of light sensors, arranged to detect light from pulses of laser light reflected by one or more objects in the environment. The second column of light sensors is arranged to scan a field of view before the first column of light sensor. A processor can adjust power of the emitter, or adjust detector gain of the first column of light sensors, in response to data from the second column of light sensors scanning the field of view, so that light in a dynamic range of the first column of sensors can be used to generate data for a three-dimensional point cloud.

The invention discloses an acoustic Doppler flow velocity measurement method and system, and the method comprises the steps: generating an emission parameter combination adaptive to a current hydrological environment according to the depth characteristics and precision requirements of a target water area; original echo signals are collected based on the emission parameter combination, and a three-dimensional flow velocity vector of temperature compensation is output; inputting the three-dimensional flow velocity vector into the dynamic segmentation network to generate a layered flow velocity distribution model; calling a layered flow velocity distribution model, fusing fluxgate compass azimuth data to carry out flow direction compensation, triggering a deviation correction algorithm when equipment inclination exceeds a limit, and outputting absolute flow velocity distribution of pose calibration; and according to absolute flow velocity distribution and echo intensity dynamic range constraint, calculating an error interval of each depth unit, and outputting a final flow velocity profile with confidence identification. According to the embodiment of the invention, the environmental adaptability and data reliability of flow velocity measurement can be improved.

The invention relates to the technical field of laser ranging, in particular to an unmanned aerial vehicle dynamic laser ranging method based on multi-source fusion and adaptive compensation, and the method comprises the following steps: obtaining a ranging pulse of a laser ranging module, and carrying out three-axis rotation and coordinate translation in combination with an IMU angle to generate a geographic registration coordinate set; radar and ultrasonic ranging are fused to construct redundant distance compensation data, particle filtering is executed based on IMU acceleration angular velocity to generate an attitude constraint distance, SLAM weight is adjusted according to illumination and meteorological parameters, and an unmanned aerial vehicle dynamic ranging coordinate result set is generated. Spatial registration is executed by combining longitude and latitude height data, by establishing dynamic association between the ranging data and IMU attitude data, smoothness and continuity of the ranging data can be kept when attitude disturbance is severe, the weight proportion of the vision ranging data in multi-source fusion is dynamically adjusted, and the high-precision estimation capacity of the target distance in the dynamic flight state is improved.

The invention provides a plastic packaging barrel online defect detection method and system based on machine vision and deep learning. According to the method, visible light and thermal image data, aligned in time, of the surface of the plastic packaging barrel are collected, the dynamic range of a thermal image is expanded to enhance the identification degree, then highlight interference is compensated through the mapping relation between a thermal image stable area and a visible light reflection area, and surface reflection suppression is achieved; superposing the processed dual-mode data to generate a multi-mode fusion image, dynamically adjusting the temperature reference value of the fusion image based on the thermal conductivity of the material and the environment temperature of the production line, and positioning an abnormal temperature region; and finally, extracting topological contours and temperature diffusion characteristics of the regions, and inputting a deep learning model to judge material structure attributes and spatial positions of the defects so as to finish online detection. According to the method, thermal and visual data are fused to enhance the perception capability on fine structure defects, and the precision and robustness of online detection of the plastic packaging barrel in a complex illumination environment are remarkably improved.

The invention relates to the technical field of water level online measurement, and discloses a water level measurement method and system based on ultrasonic waves. According to the invention, a variable time-sharing amplification circuit with a dynamic range is adopted, and the amplification times of echoes with different distances are automatically changed, so that the amplitude of an echo signal is kept to be more than five times of that of noise, and the influence of the noise on the measurement precision is effectively avoided; the method comprises the following steps of: receiving an echo signal, carrying out digital shaping on the echo signal according to a standard echo waveform near an echo peak value, and taking time corresponding to a waveform vertex after shaping as echo time, so that the influence of the measurement accuracy of echo waveform distortion is eliminated through the technology; meanwhile, the method that optimization is carried out after continuous three times of measurement is adopted, and the accidental phenomena of no echo and measurement value jumping can be effectively eliminated.

A system, method, and computer program product are provided for high-dynamic range images. In use, a first pixel attribute of a first pixel is received and a second pixel attribute of a second pixel is received. Next, a scalar based on the first pixel attribute and the second pixel attribute is identified. Finally, the first pixel and the second pixel are blended, based on the scalar, wherein the first pixel is brighter than the second pixel. Additional systems, methods, and computer program products are also presented.

The invention relates to the technical field of vacuum measurement, in particular to a device for expanding the linear range of mass spectrometry measurement, which comprises a gas transmission pipeline, an electromagnetic valve, a small hole and a mass spectrometer, and is characterized in that the front end of the gas transmission pipeline is used for allowing a sample to be measured to enter, and the rear end of the gas transmission pipeline is connected with the mass spectrometer; the middle part of the gas transmission pipeline is divided into three channels, namely a first gas transmission pipeline, a second gas transmission pipeline and a third gas transmission pipeline; the first electromagnetic valve and the first small hole are sequentially arranged on the first gas transmission pipeline, the second electromagnetic valve and the second small hole are sequentially arranged on the second gas transmission pipeline, and the third electromagnetic valve and the third small hole are sequentially arranged on the third gas transmission pipeline. According to the method, manual dilution or segmented sample injection is not needed, a wide concentration range can be covered by single analysis, more than 60% of time cost is saved, and measurement in a dynamic range of 106 is realized.

A method of double-contrast magnetic resonance fingerprinting including: optimizing, using Cramér-Rao lower bound (CRLB) via a computer system, radiofrequency (RF) pulse parameters in an MRF sequence; loading, via the computer system, the RF pulse parameters optimized into an MRI scanner; and capturing raw k-space data by selecting different signal contrast modules for dual-contrast encoding at varying repetition times (TR); reconstructing, via the computer system, at least one image including a plurality of pixels; defining, via the computer system, a dynamic range and step size for tissue parameters; and creating, via the computer system, a dictionary based on Bloch equations, the dynamic range, and the step size; and comparing, via the computer system, signal evolution for each of the plurality of pixels in the at least one image to the dictionary to determine quantitative parameters for each of the plurality of pixels, and generating a quantitative parameter map.

The invention relates to the technical field of optical fiber communication, and discloses a non-intrusive optical fiber optical power measuring system. According to the method, leakage light is generated through micro bending of an optical fiber, high-sensitivity amplification is performed on leakage light current by adopting an AD8304 logarithmic amplifier, and the measurement range of micro current is expanded in combination with an intercept adjustment technology; leakage optical signals in two directions at the micro-bend position are collected through a left-right dual-channel analog-to-digital converter (ADC), and accurate real-time monitoring of optical power is achieved through a digital processing module and a remote control module. The system comprises an optical fiber clamp module, a photoelectric conversion module, a logarithmic amplification circuit, a dual-channel ADC module and a remote control unit, and measurement is completed on the premise that normal communication of optical fibers is not affected at all. The problem that a communication link is interfered by traditional intrusive measurement is solved, the dynamic range of the measured actual optical power reaches 50dB, the measurement error is low, and a high-reliability solution is provided for performance monitoring and maintenance of an optical communication system.