973 results about "Field detection" patented technology

The invention discloses a network protocol reverse analysis method based on deep learning and a graph neural network, and the method comprises the steps: basic field detection: carrying out the byte-level feature extraction of a binary data stream through sliding window embedding, bidirectional LSTM coding and knowledge enhanced CRF decoding, and outputting a structured field labeling sequence; performing protocol format clustering based on the sequence: calculating a multi-dimensional similarity through an improved Needleman-Wunsch algorithm, realizing automatic classification of unknown protocols in combination with a dynamic density clustering algorithm optimized by LSH, and outputting a protocol cluster; and performing composite structure analysis based on the protocol cluster: constructing a protocol syntax tree based on a graph neural network, performing multiple rounds of message passing through a graph attention network GAT attention mechanism, identifying a nested structure and performing recursive analysis, and generating a multi-level protocol syntax tree. According to the method, the automation degree and accuracy of complex protocol analysis can be remarkably improved.

A real-time quantitative characterization method, equipment and a medium for rock mass evolution are disclosed. The method includes: the multiphase field detection and monitoring data is fused; a deep learning model driven by physical principles is established based on the physical principles of fluid density; the deep learning model is trained using real-time fused data as input and corresponding evolution distribution images as output; a trained deep learning model is used to obtain an evolution distribution image based on multi-phase field detection and monitoring data of different time periods and types; a mathematical model is used to quantitatively characterize of physical and mechanical parameters in the whole process of progressive failure of the dynamic evolution of the rock mass based on the macroscopic mechanical parameters and evolution distribution images synchronized with multiphase field detection and monitoring data.

The invention belongs to the technical field of tunnel safety monitoring, and particularly relates to a rock stratum stress-deformation coupled tunnel safety real-time dynamic modeling method, which comprises the following steps of: embedding a rock mass mechanical relationship into a neural network model as a hard constraint, and establishing explicit mapping of monitoring data and a physical field, a model parameter field is dynamically optimized by adopting ensemble Kalman filtering real-time general field detection data, and a data driving and physical mechanism collaborative deduction mechanism is designed, so that long-term prediction error accumulation is effectively inhibited; a stress field, a deformation field and other physical quantities deduced and output by the model are directly utilized to calculate disaster risk indexes with clear mechanical significance, and a physically interpretable early warning decision is realized by fusing fuzzy reasoning and multi-source risks; the technical problems of physical misalignment, weak long-term generalization and poor early warning interpretability of a data-driven model are solved.

The invention discloses an ARVR resin wafer process which comprises the following steps: preparing a to-be-detected resin wafer and a reference test piece, and carrying out positioning marking on a micro-nano structure area of the to-be-detected resin wafer to obtain a detection sample; performing multi-dimensional spectrum characterization on the detection sample and the reference test piece, determining a material non-uniform distribution area of the detection sample through comparative analysis, and obtaining molecular structure characterization data; carrying out stress field detection and dynamic response analysis on the material non-uniform distribution area to obtain mechanical property characterization data and high-risk defect points; carrying out microstructure and morphology analysis on the high-risk defect points to obtain defect feature data; and performing system evaluation according to the molecular structure characterization data, the mechanical property characterization data and the defect characteristic data to obtain a health degree evaluation result of the resin wafer. According to the technical scheme, multi-scale characteristic characterization can be carried out on the micro-nano structure area in the resin wafer for AR / VR, and systematic detection of the characteristics such as the molecular state, the interface stress and the phase change of the material is achieved.

The invention discloses a virus infection positioning detection method and system based on diffractive optics. The method comprises the following steps: acquiring diffraction fingerprints corresponding to all to-be-detected cells in an imaging area by utilizing a diffraction imaging principle; respectively extracting texture features of each diffraction fingerprint in the imaging area by using a gray level co-occurrence matrix method; the extracted texture features are compared with standard texture features pre-stored in a relation model of cell morphological change and diffraction fingerprints, so that the'cell state 'of each cell to be detected in the imaging area can be obtained, and the virus infection state of each cell in the imaging area can be positioned and identified. The efficient light diffraction spectrum system is used for virus infection detection, and the requirement for professionals and expensive and complex professional field detection equipment is eliminated. The continuous and high-throughput evaluation on the cell condition after virus infection is met, and a foundation is laid for popularization and application of a virus infection instant detection platform.

The invention discloses an intelligent translation calibration method based on an RAG knowledge base, and belongs to the technical field of artificial intelligence and natural language processing. In order to solve the problems that an existing large language model (LLM) is insufficient in professional term translation accuracy in text translation, low in RAG system retrieval efficiency and the like, an intelligent calibration triggering mechanism is constructed, so that the LLM can autonomously judge whether translation content needs knowledge base enhancement or not in the modes of field detection, term density analysis, user-defined triggering and the like; a full-amount retrieval strategy is changed, and the system efficiency is improved; an RAG knowledge base retrieval framework based on function calling is constructed, multiple types of knowledge sources such as a translation memory library, a term table and a professional corpus are integrated, and accurate domain knowledge is provided for translation calibration; flexible multi-knowledge-base configuration and priority management are supported, and a user can select knowledge base types and set retrieval strategies and fusion weights according to needs; through a progressive translation optimization process of initial translation, intelligent judgment, knowledge base retrieval and calibration optimization, accurate calibration of different granularities such as term level, sentence level and paragraph level is realized, and a standardized knowledge base interface specification is provided. According to the method, the defects of LLM in the aspects of translation accuracy and knowledge base utilization efficiency in the professional field are effectively overcome, and the accuracy and efficiency of knowledge-intensive translation tasks are remarkably improved.

The embodiment of the invention provides a steel wire rope tension detection method and a steel wire rope tension detection device.The method comprises the steps that under the condition that a steel wire rope is excited, a detection video of the steel wire rope is collected in real time, and the detection video comprises multiple pieces of image data on the time sequence; processing the detection video based on the tension detection model to obtain tension detection result data of the steel wire rope, acquiring the detection video of the excited steel wire rope in real time, and processing the detection image by using the tension detection model to obtain the tension of the steel wire rope. The problem that tension detection is inaccurate due to the fact that a sensor-based tension detection device is used in the prior art is solved, the field detection efficiency is improved, and the tension detection cost is reduced.

The invention relates to the technical field of soil heavy metal pollution detection, and discloses a soil heavy metal pollution detection method and system, and the method comprises the steps: collecting an original signal containing a target heavy metal characteristic signal and a plurality of auxiliary background signals; preprocessing the original signal to obtain a preprocessed multi-dimensional signal; analyzing the multi-dimensional signal to identify interference characteristics of the target heavy metal characteristic signal and the auxiliary background signal; according to the interference characteristics of the auxiliary background signal, evaluating the composition and intensity of background interference, and according to the composition and intensity of the background interference, separating a pure signal of the target heavy metal from the background by using a nonlinear compensation algorithm; the target heavy metal pure signal is converted into the concentration value of the target heavy metal, chemical digestion is not needed, complex background interference can be effectively recognized and compensated for for soil heavy metal pollution detection, the accuracy and reliability of field detection are remarkably improved, and errors caused by inaccurate reagent degradation and background deduction in a traditional method are overcome.

The invention belongs to the technical field of image processing, and particularly relates to a graphite ore grade detection method based on an improved YOLO11 model, C3k2-CAS and Detect-SEAM modules are introduced, the feature extraction capability is enhanced, the expression of different scales of ore textures is optimized, and the perception capability of the model for grade difference is improved, so that the detection precision is remarkably improved; the attention mechanism of the CAS module is adopted to replace the traditional multiplication operation, the calculation complexity and the model parameter quantity are greatly reduced while the detection performance is maintained, and the improved model is more efficient than a baseline model and is more suitable for edge device deployment; a plurality of data enhancement strategies are combined, so that the model can maintain high robustness and stable detection capability in a complex industrial environment; the trained optimization model can be efficiently deployed to graphite ore grade detection intelligent equipment, real-time and accurate industrial field detection is achieved, the mineral separation efficiency is greatly improved, and an efficient and reliable computer vision solution is provided for the intelligent mining industry.

The invention discloses multifunctional integrated portable special equipment intelligent inspection equipment and method, and relates to the field of special equipment inspection, and the inspection equipment comprises on-site working equipment which is used for collecting on-site actual measurement data; an intelligent inspection system and an inspection result determination module; the intelligent inspection system comprises an inspection report module and an intelligent question and answer module. The inspection report module is used for receiving field actual measurement data; the system is also used for managing personnel, managing contracts and the like; the intelligent question and answer module is used for providing knowledge retrieval and question and answer auxiliary functions for detecting historical data and law and regulation standard judgment rules for field detection personnel and providing detection qualification judgment rules; and the inspection result determination module is used for forming an inspection result or conclusion according to the field actual measurement data and the inspection qualification judgment rule. According to the invention, modular design and integrated and portable improvement can be carried out on inspection instruments and tools, and unified integrated management of the inspection instruments, the tools and measurement data is realized.

The invention relates to the technical field of optical detection, in particular to a bright and dark field detection device and method.First illumination light emitted by a bright field light source is modulated through an illumination modulation assembly, then the first illumination light and second illumination light emitted by a dark field light source are guided to irradiate the surface of a to-be-detected sample, and the first illumination light is reflected by the to-be-detected sample to form bright field signal light; the second illumination light is scattered by the sample to be detected to form dark field signal light, and the bright field signal light and the dark field signal light are transmitted along a common light path and are mutually separated in space; an objective lens matched with the illumination modulation assembly receives and microscopically amplifies the bright field signal light and the dark field signal light; the imaging assembly receives the bright-field signal light and the dark-field signal light and carries out bright-field imaging and dark-field imaging. Through a bright and dark field common-path sub-view-field design, simultaneous imaging detection of bright and dark fields is realized; in addition, by arranging the illumination modulation assembly, the reflection phenomenon of illumination light on the periphery of the exit pupil plane of the objective lens is inhibited, and interference of stray light on imaging is eliminated.

The invention provides an improved YOLOv11 model-based tea plant disease and insect pest detection method in a complex environment, which comprises the following steps of: acquiring an original image through field shooting, performing data amplification by using a data enhancement technology, and realizing bounding box labeling by using a labeling tool label Img to form a training data set; the method comprises the following steps: constructing a network model of tea plant diseases and insect pests, improving an original model structure of YOLOv11n, and improving a Head module by using an MSDAF module; improving a loss function; performing end-to-end training on the network architecture by using the training set and the test set, and adjusting hyper-parameters; and performing field detection on the tea leaf scab area by using the trained network model. The invention provides a novel tea disease and insect pest detection algorithm based on a YOLOv11 target detection algorithm, and the average precision of tea disease and insect pest detection in a complex environment can be effectively improved.

The present invention discloses an integrated biosensor platform based on microneedles and hydrogels and its application in detecting monkeypox virus, wherein the platform comprises a three-electrode microneedle, a hydrogel, a burning needle and a micro-electrochemical workstation. The microneedle electrode of the working electrode is combined with a nanoenzyme and an A29 protein antibody, and the monkeypox virus in the sample is extracted by the specific binding of the antibody with the monkeypox virus; the burning needle is used to connect the three-electrode microneedle and the micro-electrochemical workstation and transmit electrochemical signals. After the three-electrode microneedle is inserted into the hydrogel, the nanoenzyme catalyzes the TMB contained in the hydrogel and generates a blue oxidation product, thereby generating an electrochemical signal, which is collected by the micro-electrochemical workstation through the burning needle, and the electrochemical signal is collected through Bluetooth and a hydrogel colorimetric image is obtained, thereby realizing the detection of monkeypox virus. The integrated biosensor platform of the present invention has a low detection limit and has broad application prospects in the rapid on-site detection of monkeypox virus.

The invention discloses a semiconductor laser light beam collimation quality detection device and detection method, and relates to the technical field of laser detection. The device comprises a loading subassembly, a near-field detection subassembly and a far-field detection subassembly. The object carrying subassembly comprises an object carrying table used for bearing the laser chip to be detected. The near-field detection subassembly comprises a near-field industrial camera located on the light emitting side of the laser chip, and a beam splitter prism is arranged on the side, facing the laser chip, of the near-field industrial camera. The far-field detection subassembly comprises a far-field industrial camera. A near-field industrial camera and a far-field industrial camera are used for receiving a near-field light spot and a far-field light spot of a light beam respectively, centroid coordinates (Xa, Za) and (Xb, Zb) of the near-field light spot and the far-field light spot are calculated, if Xa-Xb is smaller than delta x, slow collimation of the light beam is qualified, and if Za-Zb is smaller than delta z, fast axis collimation of the light beam is qualified. The device and the detection method are simple in operation and high in efficiency, and can ensure the measurement precision of the mass center position of the light spot.

The invention discloses a hydraulic turbine set governor internal oil leakage detection method and system, and the method comprises the steps: S1, obtaining the historical oil leakage state data of a hydraulic turbine set governor oil pressure device, and building the oil leakage risk evaluation data of the oil pressure device; s2, preprocessing the oil leakage risk assessment data of the oil pressure device to obtain an oil leakage risk assessment data set; s3, constructing an oil leakage comprehensive prediction model according to the oil leakage risk assessment data set; and S4, detecting the oil leakage amount of the target hydraulic turbine set speed regulator through the oil leakage comprehensive prediction model, constructing an oil leakage comprehensive prediction model by collecting historical oil leakage state data of the hydraulic turbine set speed regulator oil pressure device, and calculating the oil leakage amount of the target hydraulic turbine set speed regulator by searching the weight and the threshold of the minimum error of the BP neural network real oil leakage amount and the prediction output result. According to the method, the accuracy of predicting the predicted oil leakage amount of the target hydraulic turbine set speed regulator is improved, workers do not need to conduct field detection in the process, and the time and energy of the workers are greatly saved.

The invention relates to the technical field of optical detection, in particular to an optical detection system and optical detection equipment. A first optical element for changing a bright field illumination light beam into first linearly polarized light is arranged in a light path of the bright field illumination light beam; a second optical element for changing the dark field illumination light beam into second linearly polarized light is arranged in a light path of the dark field illumination light beam, the polarization direction of the first linearly polarized light is different from that of the second linearly polarized light, and the first optical element is used for inhibiting the first stray light from being mixed into a transmission path of the first linearly polarized light; the first stray light comprises light which reaches the bright field illumination lens group after the second linearly polarized light is reflected and / or scattered; therefore, in the dark field detection process, the first stray light is prevented from being reflected by the bright field illumination lens group through the first optical element, the adverse effect of the first stray light on dark field imaging is reduced, the imaging quality and the imaging effect of dark field images are improved, and the detection efficiency and the detection accuracy are improved.

The invention provides a lighting device and a dark field detection system and method, and the method comprises the steps: carrying out the pre-detection of the distribution positions of bright defects and dark defects on the surface of a to-be-detected wafer based on a wide-view-field imaging device, and obtaining a defect distribution map of the to-be-detected wafer; classifying the brightness degree of each defect in the defect distribution map, and obtaining light source brightness level distribution corresponding to each position of the wafer to be detected; in the dark field detection device, a light source is provided for a to-be-detected area of a to-be-detected wafer based on linear illumination light, each to-be-detected area on the to-be-detected wafer is scanned, the intensity of a detection light signal is regulated and controlled according to the brightness level of the corresponding light source, and the adjusted detection light signal is collected so as to realize dark field detection. During dark field detection, the detection sensitivity consistency of different pixel positions is good, the light source intensity utilization rate is high, and the image acquisition dynamic range is large.

The invention relates to the technical field of engineering plastic detection, and particularly discloses an aging detection and evaluation method and system suitable for nylon 6 in a marine environment, the system comprises nylon 6 as a core layer, an aging response color-changing material as a surface layer and a middle layer located between the core layer and the surface layer; the thickness of the middle layer is 200-250 [mu] m, and the composite conductive film is transferred to the position 0.2 mm below the surface of the nylon 6 component in a hot pressing mode; the thickness of the surface layer is 0-200 microns and is realized by spraying an aging response color-changing material solution. By integrating the specially designed aging response color-changing material and the conductive film into the nylon 6 matrix, real-time, visual and efficient detection of the aging process is realized. According to the method, the problem that equipment such as a traditional optical fiber spectrometer is complex and expensive is solved, the convenience of field detection is greatly improved through double signal output of color gradient indication and simple electronic reading, and a brand new technical solution is provided for life prediction and preventive maintenance of nylon 6 components in ocean engineering.

An optical detection device, comprising an objective lens, a bright field illumination unit and a dark field illumination unit. The objective lens is provided with a bright field light channel and a dark field light channel. The bright field illumination unit comprises a bright field beam splitting unit and a bright field light source for providing a bright field incident light beam, wherein the bright field incident light beam is reflected by the bright field beam splitting unit and then enters the bright field light channel. The dark field illumination unit comprises a dark field light source for emitting a dark field incident light beam, a prism module and a dark field beam splitting unit; the prism module and the dark field beam splitting unit are sequentially arranged in the transmission direction of the dark field incident light beam; the prism module is used for converting the dark field incident light beam into a circular light beam, wherein the circular light beam is reflected by the dark field beam splitting unit and then enters the dark field light channel; and the dark field beam splitting unit comprises a circular beam splitter and an aperture formed at the center of the circular beam splitter, wherein the aperture is located on the transmission path of the bright field incident light beam. The present invention more conveniently realizes switching between bright field detection and dark field detection, thereby improving the detection efficiency.

The invention relates to the technical field of microelectronics, and discloses a small and special electric machine armature defect detection method based on improved YOLOv11n, which comprises the following steps: S1, acquiring small and special electric machine armature defect image data; s2, constructing an armature defect network model, wherein an original YOLOv11n model structure is improved by constructing a C3K2-MA module; a lightweight feature extraction module is used to replace a convolution module in a trunk feature extraction and down-sampling process, and a down-sampling module is improved; the CIoU of the original YOLOv11n model is improved by using DIOU, so that the model precision is improved, and a loss function is improved; s3, using the training set and the test set obtained in the step S1 to train through the armature defect network model constructed in the step S2; and S4, using the trained armature defect network model to carry out field detection on the armature defects of the small and special electric machine. According to the invention, a partial multi-scale feature aggregation module C3K2-MA is provided, the detection capability of different scale targets is significantly improved, and the detection precision is improved.

A Doppler radar apparatus, including a transmitter, a receiver, and a processor, is provided. The transmitter transmits a radio frequency signal to a field. The receiver is coupled to the transmitter and receives a reflected signal corresponding to the radio frequency signal from the field. The processor is coupled to the receiver and is configured to detect a target in the field according to the reflected signal. In response to the target not being detected in the field, the processor switches to a power saving mode according to workload reduction information, and workload of the radio frequency signal in the power saving mode decreases based on the workload reduction information.

The invention relates to the technical field of detection devices, in particular to a reinforcing steel bar field detection device for constructional engineering acceptance, which comprises a base, an adjusting shell, an oil cylinder, a clamping piece, a driving piece and a drawing instrument. The adjusting shell is installed on the base. The oil cylinder comprises a cylinder body and a telescopic cylinder, the cylinder body is spherically hinged with the adjusting shell, the telescopic cylinder is coaxial with the cylinder body and is in sliding fit with the cylinder body, an oil cavity is defined between the cylinder body and the telescopic cylinder, and the oil cavity is connected with the drawing instrument through a connecting pipe. And the clamping piece can clamp the embedded steel bar. The driving piece is used for driving the barrel to rotate relative to the adjusting shell. According to the steel bar on-site detection device for constructional engineering acceptance, a multiple-detection mode is adopted, the cylinder rotates relative to the adjusting shell, the directions of drawing force applied to embedded steel bars in each detection are different, the accuracy of the detection result can be improved, the detection device does not need to be repeatedly disassembled and assembled in each detection, and the detection efficiency is improved. The operation is convenient.

The utility model belongs to the technical field of transformer insulating oil detection, and particularly relates to a transformer insulating oil breakdown voltage field detection device which comprises a detection box and supporting legs, and a detection device and a filtering device are arranged in the detection box. According to the field detection device for the breakdown voltage of the transformer insulating oil, the oil temperature of the insulating oil is detected through the temperature sensor, and when the oil temperature is too low, the electric heating wire in the electric heating box is started to heat the insulating oil in the oil conveying pipe, so that the situation that the detection result is influenced due to the unstable oil temperature is avoided; a large number of solid impurity particles such as iron particles, copper particles, carbon particles and fiber particles can be generated in transformer oil due to mechanical vibration, partial discharge and the aging effect of oil paper insulation in the operation process of the transformer, so that after detection is completed, the insulating oil is conveyed into the filter box through the oil discharge pipe, and then the transformer oil is filtered. And solid particles in the insulating oil are intercepted and filtered through the filter screen, so that the service life of the insulating oil is prolonged.

The invention provides a chemical fiber cloth defect detection device, and belongs to the field of cloth detection.The chemical fiber cloth defect detection device comprises a bottom plate, two first supporting rods, a placement roller, a fourth motor and a storage roller, a sweeping assembly, a tension adjusting assembly and a detection assembly are installed on the bottom plate, and the detection assembly comprises a detection box fixedly connected to the upper end face of the bottom plate; and a first supporting plate is fixedly mounted on the inner wall of the detection box. The upper and lower irradiation lamps are arranged in the detection box, so that the irradiation effect is better, the device performs bright field detection and dark field detection according to requirements, meanwhile, the angles and heights of the two irradiation lamps can be synchronously adjusted, illumination optimization is realized, distortion and light reflection can be reduced, the comprehensiveness and accuracy of cloth detection are remarkably improved, and the detection efficiency is improved. The light spot interference of a high-reflection area can be avoided, the imaging uniformity is improved, meanwhile, the brush bristles are used for cleaning the surface of the cloth, misjudgment caused by impurities on the cloth during detection is avoided, and the detection accuracy is improved.

The invention relates to the technical field of semiconductor detection, in particular to a wafer bright field illumination and imaging system, a wafer defect detection device and a wafer defect detection method, the system comprises an illumination module, a beam combining module, an objective lens module and an acquisition imaging module; wherein the illumination module generates an illumination light beam adaptive to a wafer detection view field; the beam combining module realizes non-interference separated transmission of an illumination light path and an acquisition light path through a reflection area and a transmission area which work independently; the objective lens module converges the light beams reflected by the reflection area to the surface of the wafer, and controls the light beams to form illumination only at the edge of an entrance pupil so as to realize off-axis illumination; meanwhile, the reflected light beams on the surface of the wafer are collimated and then transmitted to the transmission area; and the acquisition imaging module receives the parallel light beams, converts optical signals into electric signals, and generates a wafer surface image. According to the invention, the problems of high energy loss, high cost, low detection rate and insufficient resolution of a traditional bright field detection system are effectively solved.

The utility model belongs to the technical field of gas leakage detection, and particularly relates to a carbon dioxide on-site detection device and a carbon dioxide pipeline leakage detection system.The carbon dioxide on-site detection device comprises a ventilation duct, an alarm assembly and a controller, a carbon dioxide detection piece is arranged at the other end of the ventilating duct; the controller is electrically connected with the carbon dioxide detection piece and the alarm assembly. A carbon dioxide field detection device is arranged near a carbon dioxide conveying pipeline, the concentration of carbon dioxide around the carbon dioxide pipeline is detected in real time through a carbon dioxide detection piece, an alarm assembly comprises multiple alarm modes used for sending different alarm signals, and each alarm mode corresponds to different concentration threshold values of the carbon dioxide concentration. The controller is used for switching the corresponding alarm mode according to the concentration threshold value of the carbon dioxide concentration, so that the numerical value of the carbon dioxide concentration is visually reflected, and an operator can take corresponding treatment measures.

The invention provides a light source multiplexing diamond NV color center wide field detection system and an illumination detection method. The system comprises a diamond containing an NV color center, an exciting light module, a first double-color sheet, an objective lens, a second double-color sheet, a wide field imaging module, an illumination imaging module and a microwave module, exciting light generated by the exciting light module irradiates the first double-color piece, is guided to the objective lens, and irradiates the diamond after being transmitted by the objective lens so as to excite the NV color center of the diamond to generate fluorescent light; the objective lens is of an infinity type; the exciting light is irradiated to a sample to be detected after being transmitted by the diamond; fluorescent light and exciting light from a sample to be detected are collected by the objective lens, then transmitted to the first double-color piece and guided to the second double-color piece through the first double-color piece, the second double-color piece guides the fluorescent light to the wide-field imaging module for imaging, and the exciting light in the second double-color piece is guided to the illumination imaging module for imaging. Illumination can be achieved in the exciting light working state, exciting light switching operation in the prior art is avoided, and efficiency can be remarkably improved.

According to the slab continuous casting crystallizer flow field detection device and method, a mounting hole is formed in the end face of a crystallizer copper plate in the continuous casting throwing direction, the axis of the mounting hole is parallel to the working face of the crystallizer copper plate, and the distance between the axis of the mounting hole and the working face of the crystallizer copper plate is larger than or equal to 10 mm; a kerf is arranged on the working surface of the crystallizer copper plate along the thickness direction of the crystallizer copper plate, the center line of the kerf and the axis of the mounting hole are positioned on the same vertical plane, and the end of the kerf is communicated with the mounting hole; the optical fiber temperature measurement sensor is laid at the bottom of the kerf and in the mounting hole, the optical fiber temperature measurement sensor in the mounting hole is sleeved with a sealing ring, and the outer side end of the optical fiber temperature measurement sensor is locked in the mounting hole through a fastening nut; and a sealing material is filled in the kerf after the optical fiber temperature measurement sensor is laid. According to the invention, the temperature of the crystallizer copper plate can be dynamically detected in real time with high precision and high density, so that the initial solidification process of molten steel in the crystallizer and the flowing state of the molten steel are indirectly reflected, and conditions are created for optimizing the flow field of the slab continuous casting crystallizer and improving the quality of continuous casting products in combination with an electromagnetic flow control technology.

The invention discloses an optical detection device and a sample analyzer, in the optical detection device, a bright / dark field illumination assembly is used for emitting an illumination light beam, and a fluorescence excitation assembly is used for emitting an excitation light beam; the bearing table is used for bearing a to-be-detected sample; the infinite objective lens and the barrel lens are used for imaging a to-be-detected sample in a bright field to form a bright field imaging light beam, imaging the to-be-detected sample in a dark field to form a dark field imaging light beam, and performing microscopic imaging on fluorescent particles in the to-be-detected sample to form a fluorescent imaging light beam; the imaging receiving assembly is used for receiving the bright field imaging light beam, the dark field imaging light beam and the fluorescence imaging light beam. The optical detection device is an infinite microscopic optical system, can perform bright / dark field detection on the to-be-detected sample, can perform fluorescence detection on the to-be-detected sample, is compact in structure, high in sharing rate of all optical elements, saves optical element materials, and is low in cost.

The invention relates to an electrically-assisted biaxial stretching forming limit testing system and method for a plated plate, and belongs to the technical field of bipolar plate testing.The testing method comprises the following steps that a bipolar plate sample is heated through pulse current and then stretched; and meanwhile, temperature, displacement, load and surface deformation images of the bipolar plate sample during stretching are collected, ultrasonic detection is carried out, and a basic forming limit curve is established based on a plastic instability criterion and is dynamically corrected. Dynamic evolution of necking initiation, expansion and interface failure in the stretching process can be synchronously tracked, actual working condition requirements can be better met, interface thermal mismatch aggravated by Joule heat is avoided, and the influence of insufficient sensitivity of a general ultrasonic algorithm can be made up through multi-physics field detection. The failure criterion is redefined as the critical state of plating-substrate interface separation, and the error of the critical failure point predicted by the forming limit curve is further reduced.