201results about How to "Avoid false positives" patented technology

The embodiment of the invention provides a battery car detection method and device and electronic equipment. According to the embodiment of the invention, whether the battery car is suspected to exist in the current image frame or not is determined based on the target detection result corresponding to the current image frame for the collected current image frame, and then when it is determined that the battery car is suspected to exist in the current image frame, the battery car is determined to be suspected to exist in the current image frame. And according to the target detection result corresponding to each image frame acquired within a period of time starting from the acquisition ending moment of the current image frame, determining whether the battery car exists in the specified scene again so as to determine whether to output a battery car alarm instruction, thereby realizing battery car detection in the specified scene through automation. According to the battery car detection system, the situation of missing detection of the battery car caused by a manual mode is avoided, whether the battery car exists or not is detected secondarily, the accuracy of battery car detection is improved, and the situation of false alarm of the battery car is effectively avoided.

The invention discloses a full-performance integrated test system abnormity monitoring method and device based on an electric energy meter. The invention discloses a full-performance integrated test system anomaly monitoring method, which comprises the steps of constructing a historical state matrix, recording past state change, performing difference comparison on a current state and a historical state by using time decay and disturbance correction, calculating a difference degree function, judging whether an anomaly exists or not, and analyzing an anomaly trend through a backtracking mechanism. Confirming the continuity of the abnormity; after determining that the anomaly has continuity, performing deep analysis by utilizing multivariable collaborative reasoning, capturing complex interaction among variables through nonlinear convolution, constructing comprehensive state representation, and determining an anomaly source, designing a feedback anomaly processing algorithm and calculating an optimal recovery path through a collaborative reasoning function in combination with a current state; and gradually adjusting the state to restore system normality. The method not only can detect and infer anomalies, but also can adaptively adjust the current state, gradually repair the anomalies and return to the normal state.

The invention belongs to the technical field of natural disaster monitoring and early warning, and particularly discloses a landslide deformation monitoring device which comprises monitoring piers, the monitoring piers are arranged on the two sides of a crack, a monitoring box is fixedly arranged on the upper side of one monitoring pier, and a rope end fastening mechanism is arranged on the upper side of the other monitoring pier. A winding disc, a displacement monitoring mechanism and a centrifugal driving anti-interference mechanism are arranged in the monitoring box, the winding disc is rotationally arranged on the side wall of the monitoring box in a clamped mode, the displacement monitoring mechanism is located on the rope outlet side of the winding disc, the centrifugal driving anti-interference mechanism and the winding disc are coaxially arranged, and the winding disc is connected with a tension pre-tightening mechanism on the outer side of the monitoring box. A solar power assembly is arranged on the upper side of the monitoring box. According to the invention, a pure mechanical structure is utilized to judge the real reason of the change of the monitoring value, the influence of external interference on the crack width monitoring result is effectively eliminated, so that false alarm is avoided, the requirement of frequently going to the site for troubleshooting is reduced, the installation is simple, convenient and rapid, complex operation is not needed, and the device can be rapidly deployed in various terrain environments.

The invention discloses a loss diagnosis and health management system and method for a transformer, and belongs to the technical field of intelligent transformers, and the system comprises a thermal fingerprint module which is used for recording a temperature drop curve of each part of the transformer after planned power failure, and obtaining a thermal inertia fingerprint of the transformer based on the fitting of multiple temperature drop curves; the theoretical temperature module is used for calculating the theoretical cold body temperature of each part of the transformer based on the real-time environment temperature and the thermal inertia fingerprint when the transformer runs; the net temperature rise module is used for acquiring the actual temperature value of each part of the transformer and subtracting the corresponding theoretical cold body temperature from the actual temperature value; weak thermal characteristic signals caused by insulation aging and loss abnormity of the transformer can be accurately extracted from strong background noise such as load fluctuation and environment temperature through technologies such as thermal inertia fingerprint construction and net temperature rise separation, early diagnosis of progressive health deterioration is realized, support is provided for intervening potential faults in advance, and the fault diagnosis accuracy is improved. And the passive situation of post-treatment of operation and maintenance is changed.

The invention belongs to the technical field of mold monitoring, and particularly relates to a defect monitoring system and method for an injection mold, and the defect monitoring system comprises water gap cutting mechanisms which are used for detecting one or more defects of an injection molding part, the water gap cutting mechanisms at the two ends of the mold start to work, and after injection molding, the number of the injection molding part of the whole mold product is one or more; the material pulling assembly is used for carrying out material pulling output on a formed injection molding part at the discharging opening of the fixed mold or carrying out material pulling on the current discharging opening to remove damaged hardware when it is detected that one or more injection molding parts are bad; the control system is used for supervising injection molding of hardware in the fixed mold and controlling the water gap cutting-off mechanism and the material pulling assembly to work to remove damaged hardware in the mold cavity when detecting that one or more injection molding pieces are bad, so that the utilization rate of good products in one mold is reduced, meanwhile, plastic materials are saved, and the production efficiency is improved. And the rejection rate of hardware is reduced, and the effects of saving product cost and improving efficiency are achieved.

The invention discloses a wear online identification and compensation control system and method for a high-pressure distribution plunger and barrel assembly, and the system comprises a data collection module which is used for collecting working condition data and state data; a health state dynamic baseline model obtained through offline training is arranged in the data processing module, and the wear level of the plunger and barrel assembly is recognized by calculating the residual error between actual state data and health state data predicted by the model under the current working condition; and the compensation control module is used for generating a self-adaptive compensation control instruction according to the identified wear grade and the current working condition and sending the self-adaptive compensation control instruction to an execution mechanism. According to the method, the dynamic base line synchronous with the real-time working condition is constructed, early weak wear characteristics can be separated from strong working condition interference, the recognition sensitivity and accuracy are improved, the influence of wear on the system performance is actively counteracted through closed-loop adaptive compensation control, the service life of equipment is expected to be prolonged, and the system performance is improved. And technical support is provided for predictive wear monitoring management.

This invention provides a method for detecting sensor anomalies in nuclear power plants. The method includes: constructing a principal component analysis model, calculating the Q-statistic, and determining a first threshold; training a Bayesian long short-term memory neural network model and calibrating its prediction interval; calculating a second and third threshold based on the predicted value and uncertainty output by the calibrated model; inputting test data into the two models to obtain the Q-statistic, predicted value, and uncertainty, and comparing them with the corresponding thresholds to obtain three judgment results; and making a final judgment on the three results using a logical judgment table. This invention integrates spatiotemporal characteristics and uncertainty assessment, achieving high-precision and high-reliability sensor anomaly detection with only normal operating data, exhibiting high reliability and robustness.

The application discloses a Chinese pear psylla MIRA-CRISPR / Cas12a detection kit and method, and belongs to the technical field of rapid detection of pest resistance. In view of the target resistance mutation (GluCl gene V267I site) of Chinese pear psylla to abamectin, the application first combines the CRISPR / Cas12a system with the MIRA isothermal amplification technology, and establishes a visual detection system with high specificity and high sensitivity. The kit comprises MIRA amplification primers, specific crRNA, Cas12a protease and a fluorescent reporter probe. During detection, only a single head of pear psylla sample is needed, after rapid DNA extraction, MIRA amplification and CRISPR cutting reaction are carried out under the condition of constant temperature of 37 DEG C, the total time consumption is not more than 1 hour, and the result is directly visually judged by a portable blue light lamp (green fluorescence is displayed for a positive sample). The application is simple in operation, does not need large instruments, and the result is intuitive, so that real-time monitoring of the abamectin resistance of Chinese pear psylla in the field can be realized, and technical support is provided for scientific rotation of drugs and precise prevention and control.

The present invention discloses a dam body temperature monitoring system, which belongs to the field of dam monitoring technology. The system includes monitoring equipment and a protective tube, wherein the protective tube is arranged inside the dam body along the length direction of the dam body, and the dam body is cast in layers, and each layer of the cast dam body is provided with a protective tube, and the protective tubes in the adjacent layers of the dam body are connected between the head and tail with a semicircular tube, and an elastic tube is arranged inside the protective tube, and a temperature-sensitive optical fiber is arranged inside the elastic tube, and the outer end of the temperature-sensitive optical fiber is electrically connected to a controller; the elastic tube expands when heated and contracts when cooled, and water flows into the elastic tube, and differential pressure detectors are arranged at intervals on the elastic tube, and the differential pressure detectors are connected to a data transmission line, and the differential pressure detectors are connected to a data analysis module through the data transmission line. Through the present invention, it is possible to realize real-time monitoring of temperature changes in different sections inside the dam body, and the monitoring will not be affected by sudden temperature changes in small areas inside the dam body, and the monitoring range is larger.

The application discloses a high-pressure gas particle counter with a laser diode as a light source, which comprises an optical detection unit, a gas path system and a standard particle reference system, wherein the optical detection unit is used for generating laser and dividing the laser into two independent light paths, i.e., a main light path and an auxiliary light path, and is used for irradiating a main detection area and an auxiliary detection area respectively and receiving a particle scattering light signal and converting the particle scattering light signal into an electric signal; the gas path system is used for selectively conveying a high-pressure gas to be measured and a standard particle gas to the main detection area and the auxiliary detection area; the application belongs to the technical field of gas particulate pollution monitoring, and aims to solve the problem that the output light power of a laser diode in the prior art will drift with the increase of working time and the change of temperature, thereby causing the measurement reference to be inaccurate, and achieves the technical effect that a real-time online dynamic calibration mechanism is constructed by introducing an auxiliary reference light path and the standard particle reference system, and the problem of the measurement reference drift caused by factors such as light source aging and temperature drift is effectively overcome.

The application relates to the technical field of intelligent automobiles, in particular to a double-winding motor steer-by-wire steering actuator, a system and an angle detection method, wherein the steering actuator comprises a connecting mechanism, a steering mechanism for transmitting a steering torque to the connecting mechanism to drive a wheel to steer, wherein no detection component is arranged on the steering mechanism, the detection component is used for detecting a steering angle of the vehicle, a speed reduction mechanism for transmitting the steering torque to the steering mechanism, and a double-winding motor for outputting the steering torque, wherein the steering mechanism comprises a first angle sensor and a second angle sensor, and the steering angle of the vehicle is calculated according to the rotor angle detected by the first angle sensor and / or the second angle sensor. Thus, the problems in the prior art that the steering actuator of the steer-by-wire system occupies a large space, has a large volume and a high cost, has a low fault tolerance rate, and cannot be processed according to the fault type after the steering angle fails, so that the vehicle driving safety cannot be ensured are solved.

The utility model provides an AGV forklift goods detection stabilizing device, and belongs to the technical field of automatic guided vehicles. The device comprises a fixing plate, a main goods detecting part, a central goods detecting part, an auxiliary goods detecting part and a control unit. The main goods detecting part comprises two goods detecting assemblies, each goods detecting assembly is provided with a fixing frame, a goods detecting baffle, an elastic limiting piece and a first proximity switch, and when the included angle between the goods detecting baffle and the fixing frame is smaller than or equal to 5 degrees, a first detecting signal is output; the central cargo detection part comprises an inductive sensor, detects the cargo insertion state and outputs a second detection signal; the auxiliary goods detecting component comprises a second proximity switch, and when goods enter the sensing range, a third detection signal is output. The control unit receives the three paths of signals at the same time, and outputs a signal of detecting goods in place only after the three paths of signals are all continuously conducted for at least preset time. According to the utility model, the cargo insertion stability is ensured through multiple detection mechanisms, and the safety and reliability of the operation of the AGV forklift are improved.

The application provides an open coal pile spontaneous combustion prevention control method and system, the method comprises the following steps: acquiring the coal pile temperature, oxygen concentration and flammable gas concentration of the target position inside the open coal pile in real time; determining the temperature change rate, oxygen concentration change rate and flammable gas concentration change rate according to the coal pile temperature, oxygen concentration and flammable gas concentration of the target position in the preset time window; determining the spontaneous combustion risk level of the target position according to the temperature change rate, oxygen concentration change rate and flammable gas concentration change rate and the corresponding preset change rate threshold; and executing the spontaneous combustion prevention warning measure according to the spontaneous combustion risk level. The application cooperatively judges the spontaneous combustion risk level through the change rate indexes of the three data of temperature, oxygen concentration and flammable gas concentration, not only reduces the interference of environmental fluctuations on a single index, avoids the false alarm or missed alarm problem, but also can discover the risk in advance, timely performs the cooling spontaneous combustion prevention, and improves the coal pile safety.

The utility model discloses a kind of anti-falling alarm sickbed, comprising: monitoring fence is at least set in the both sides of bed body;Monitoring fence includes being set on the baffle several first grid bars and being set on the substrate several second grid bars, several first grid bars and several second grid bars one-to-one, elastically sliding connection;Second grid bar is internally provided with distance sensor;Processor is connected with several distance sensor circuit;Alarm and processor wireless signal connection.The utility model sets monitoring fence in the periphery of bed body, and trigger is formed by the first grid bar, second grid bar and the distance sensor located in second grid bar of elastically sliding connection, when patient exists the behavior of climbing fence, patient's own weight triggers and sends to alarm, can form reminder to accompanying personnel, the utility model only forms alarm when monitoring fence is pressed, avoid the false alarm situation that exists when normal use occurs, can improve alarm accuracy, reduce the situation that medical resource waste occurs.

The application relates to the technical field of automobile transmission shaft production, in particular to a safety management system for automobile transmission shaft production based on big data, which comprises a data acquisition module, which is used for collecting production parameter data, environment parameter data, operator behavior data and quality inspection data of multiple production devices in the automobile transmission shaft production process in real time, and constructing an original safety data set; a big data processing platform, which is in communication connection with the data acquisition module, is used for cleaning, fusing and standardizing the original safety data set, and generating a standardized safety data set; a safety risk research and judgment module, which is connected with the big data processing platform, is used for storing a dynamic safety threshold model, and identifying abnormal states and safety risks in the transmission shaft production process in real time based on the standardized safety data set, and outputting quantitative research and judgment results; the safety risk research and judgment module realizes the whole domain monitoring, hierarchical early warning, millisecond-level emergency shutdown and closed-loop control of the transmission shaft production safety, and significantly improves the response speed and management efficiency.

The invention provides fluorescent quantitative PCR primers, a kit and a method for detecting fowl adenovirus 4, and belongs to the technical field of biological detection. The nucleotide sequence of the fluorescent quantitative PCR primer pair for detecting the fowl adenovirus 4 provided by the invention is shown as SEQ ID NO.1 and SEQ ID NO.2 or a complementary sequence of the SEQ ID NO.1 and SEQ ID NO.2. The fluorescent quantitative PCR primer and the method for detecting the fowl adenovirus 4, provided by the invention, are high in sensitivity and strong in specificity, and are negative when being used for detecting fowl adenovirus 8, Newcastle disease virus, H9 subtype avian influenza virus, infectious bronchitis virus, infectious bursal disease virus, Marek's disease virus, egg drop syndrome virus and mycoplasma synoviae, and can be used for detecting fowl adenovirus 8, Newcastle disease virus, H9 subtype avian influenza virus, infectious bronchitis virus, infectious bursal disease virus, Marek's disease virus, egg drop syndrome virus and mycoplasma synoviae. And false positive can be effectively avoided.

The invention provides a radar point cloud-based foreign object intrusion detection method and system in a working area, and the method comprises the steps: setting a detection area range according to the working space of a mechanical connecting rod, and dynamically generating a direction bounding box (OBB) of the connecting rod through obtaining the posture state information and size data of the working connecting rod in real time; spatial screening is carried out on original radar point cloud data, only point cloud data which are located in a detection area and are not located in an OBB are reserved, and background point clouds outside the detection area and point clouds generated by a connecting rod are filtered out; and performing multi-dimensional anomaly detection on the filtered point cloud data, and comprehensively judging whether a continuously existing foreign object intrusion event exists or not. Through a linkage mechanism of point cloud filtering, background modeling and clustering verification, high-precision, low-false-alarm and real-time industrial intrusion detection is realized, and the problems of poor adaptability, high false alarm rate and the like of a traditional method in a complex environment are solved.

This utility model relates to the field of mining engineering equipment technology, and in particular to an intelligent control device for mine filling. It includes a base, a main control box fixedly connected to the top of the base, and two conveying barrels mirror-distributed around the main control box. Flange pipes communicating with the inner walls of the two conveying barrels are fixedly connected to the tops of the two conveying barrels. Flow meters are fixedly connected to the inner walls of the flange pipes. A mixing tank is installed on the outer wall of the base, and a stirring rod is rotatably connected to the inner wall of the mixing tank. A liquid level sensor is fixedly connected to the inner wall of the mixing tank. The flow meter collects the material conveying volume of the main material bin and the auxiliary material bin in real time. The controller automatically compares the actual conveying ratio with the set value, avoiding the mixing ratio error caused by manual observation of material level and manual speed adjustment, ensuring that the ratio of main material to auxiliary material remains stable within a reasonable range. A concentration sensor monitors the mixing state of the filling slurry in the mixing tank, ensuring the basic quality of the filling slurry and improving the strength stability of the filling material.

This disclosure provides a distance determination method, apparatus, and storage medium. The method includes: determining whether data acquired by an infrared distance sensor of an electronic device is greater than a distance threshold and less than a first proximity threshold; if so, acquiring light-sensing data; determining whether the light-sensing data is greater than a preset light-sensing value; if so, determining a second proximity threshold; and determining the positional state between an obstruction and the screen of the electronic device based on the second proximity threshold and the data acquired by the infrared distance sensor. This disclosure, based on data acquired by the infrared distance sensor, the first proximity threshold, the distance threshold, the light-sensing data, and an oil stain algorithm, performs multi-level precise differentiation of the positional state between the obstruction and the screen of the electronic device, effectively avoiding false alarms caused by misinterpreting obstructions as oil stains for optimization, and improving the response accuracy of the electronic device's screen.

This application relates to the field of fire early warning technology, and in particular to an intelligent fire early warning method and device for student dormitories. The method includes: collecting smoke concentration data, gas concentration data, flame signal data, and human movement status data; determining whether human movement exists based on the human movement status data; if no human movement exists, performing a fire risk assessment based on comparisons between smoke concentration data and preset smoke thresholds, comparisons between gas concentration data and preset gas thresholds, and whether the flame signal data is non-zero; if human movement exists, performing a fire risk assessment based on comparisons between flame signal data and preset flame thresholds, and whether the flame signal data is continuously rising. Therefore, this method is applicable to situations involving spontaneous combustion or electrical fires in student dormitories, avoiding false alarms caused by student activities, proactively identifying when students ignite other substances with candles or lighters, and avoiding false alarms due to dust or smog caused by heavy fog or dormitory cleaning.

The invention provides a vehicle-mounted highway tunnel brightness real-time monitoring and early warning system, and belongs to the technical field of vehicle driving, and the system comprises a data obtaining module which obtains tunnel brightness test data through a real vehicle driving experiment; the image preprocessing module obtains a tunnel driving image and preprocesses the tunnel driving image to obtain a seven-dimensional spatial-temporal feature vector; the brightness identification monitoring module establishes a tunnel brightness identification model according to the test data and the seven-dimensional spatial-temporal feature vector, and extracts a tunnel brightness value; the threshold generation and early warning module classifies the brightness values by using an improved clustering algorithm to obtain a tunnel dangerous brightness threshold and performs early warning; and the vehicle-mounted integrated module connects the tunnel brightness identification model and the tunnel dangerous brightness threshold to the vehicle to realize real-time monitoring and early warning. The problems that tunnel safety protection is high in deployment threshold and high in cost due to the fact that a professional brightness detection instrument is needed to obtain accurate brightness detection capacity when a vehicle enters and exits a tunnel, and an existing early warning mechanism lacks dynamic environment continuous quantitative evaluation are solved.

The application provides a mountainous large bridge comprehensive analysis method based on an intelligent inspection unmanned aerial vehicle, and belongs to the technical field of bridge health management. The method comprises the following steps: performing spatial overlap degree matching on each bridge disease entity identified in the current inspection and the same-position disease entity in a historical inspection archive, and determining the continuous evolution sequence of each bridge disease; determining the visual rendering coefficient of the corresponding bridge disease in the preset bridge three-dimensional model from the time sequence variation of the disease characteristic parameters in the continuous evolution sequence, and constructing a disease density distribution hot area; when the time sequence variation of the bridge disease extracted in the disease density distribution hot area exceeds the allowable evolution interval of the corresponding disease type, performing difference analysis on the neighborhood structure surface information of the bridge disease in the bridge three-dimensional model and the original design parameters of the mountainous large bridge; and updating the allowable evolution interval according to the difference analysis result. The technical scheme provided by the application can dynamically distinguish the normal damage development and abnormal accelerated degradation in the mountainous large bridge.

The utility model discloses a kind of toxic and harmful gas detection alarm control system, it is related to the technical field of instrument automatic control.The system includes field alarm, toxic gas detector, gas alarm controller, air switch, AC contactor, thermal overload relay and exhaust fan.Toxic gas detector real-time monitoring toxic gas concentration in environment, and signal transmission to gas alarm controller;Two early warning thresholds are provided in controller, when concentration reaches first threshold, trigger sound light alarm, reach second threshold, drive relay control exhaust fan start, quickly exclude leakage gas.The utility model integrates multipoint centralized monitoring, hierarchical response and overload protection function, supports 4-20mA anti-interference signal transmission, applicable to metallurgy, chemical industry and other flammable and explosive places.Has short response time, false alarm rate is low and the like characteristics, can effectively prevent personal injury and fire explosion accident, improve industrial safety protection capability.

This invention belongs to the field of analytical detection technology and discloses an analytical method for detecting N-nitrosobaricitinib impurities in baricitinib tablets. The method includes solution preparation and detection steps: blank, 0.9 ng / ml reference standard, and test sample solutions are prepared using a 40%–60% acetonitrile aqueous solution as a diluent; an Agilent Poroshell 120 EC-C18 column is used with 0.1% formic acid-methanol gradient elution; mass spectrometry is performed using an AJS ESI ion source in MRM scanning mode; and the content is calculated using the external standard method. This method is simple to operate, rapid in analysis, highly specific, highly sensitive (detection limit 4.30 ppb), and exhibits excellent precision, accuracy, and linearity. It can accurately quantify target impurities, providing reliable technical support for the quality control of baricitinib tablets.

The invention discloses an underground water multi-pollutant rapid prediction and diagnosis system, which comprises a multi-parameter sensing and data acquisition module used for acquiring underground water quality parameters in real time; the edge pretreatment unit is used for carrying out edge pretreatment on the underground water quality parameters; the off-line synthetic data engine is used for generating synthetic training data of transient extreme working conditions; the feature engineering processing unit is used for constructing interaction features based on a geochemical mechanism; the AutoML reasoning unit is used for deducing and outputting a pollutant concentration predicted value through a model; and the physical-data dual-drive fault diagnosis module is used for diagnosing the authenticity of pollution according to three-dimensional calculation results of the physical residual calculated by the physical residual calculation unit, the mean square error of the sensor data calculated by the data reconstruction error unit and the difference between the observed value and the predicted value calculated by the statistical test unit. And judging whether to give an alarm according to the diagnosis result. According to the scheme, the specific pollutants can be accurately identified, and the authenticity of pollution can be accurately identified.

The application discloses a kind of rail vehicle pipe joint loosening detection method and system, belong to rail transit vehicle pipe joint detection field;The method comprises: local posture decoupling, detects pipe joint structure features and establishes local coordinate system, estimates local transformation;Marked line skeleton extraction extracts anti-loose mark line candidate area and skeleton, obtains the detected mark line track and template mark line track;Homologous track comparison, according to the boundary division fixed side, active side and cross-seam neighborhood section, template mark line track is mapped into reference mark line track, and the joint deviation feature of the detected mark line track is calculated;Loosening determination output, according to joint deviation feature and registration confidence, calculate loosening risk score, output pipe joint state result.Template image homologous reference, local coordinate system eliminates visual angle deviation, curve topological structure represents anti-loose mark line, distinguishes line drawing non-standard and real loosening, avoids false alarm and miss report, improves detection accuracy and robustness.

The application relates to a railway foreign matter alarm method, device and equipment and a storage medium, and relates to the technical field of image processing. The method comprises the following steps: acquiring a to-be-detected image comprising a railway; determining a to-be-detected region comprising the railway in the to-be-detected image according to the to-be-detected image and a semantic segmentation model; in the case where the number of to-be-detected regions is one, judging whether a target foreign matter exists in the to-be-detected region according to the to-be-detected image and a foreign matter classification model; the foreign matter classification model is used for detecting foreign matters of a preset type in the to-be-detected image, and the type of the target foreign matter is a type other than a train in the preset type; and in the case where the target foreign matter exists in the to-be-detected region, an alarm is given. The application is used for improving the accuracy of railway foreign matter detection.

The utility model relates to the technical field of intelligent door magnetic sensors, in particular to a false alarm prevention intelligent door magnetic sensor with a distance adjusting function, which comprises a door frame, an opening and closing door is rotatably connected in the door frame, a permanent magnet is fixedly connected on the side wall of the door frame, and a door magnetic sensor body is arranged on the side wall of the opening and closing door. An adjusting mechanism used for adjusting the distance between the door magnetic sensor body and the permanent magnet is arranged on the side wall of the door magnetic sensor body and comprises a sliding rail fixedly connected to the side wall of the opening and closing door, a sliding rail block is slidably connected to the outer wall of the sliding rail, and two rotating wheels are rotationally connected to the top and the bottom of the inner wall of the sliding rail block correspondingly. Compared with the prior art, the situation that due to the fact that the distance between the magnetic inductor body and the permanent magnet is too short, the magnetic inductor is too sensitive, and misinformation occurs is avoided, the opening and closing state of the opening and closing door can be accurately detected, the possibility of misinformation is greatly reduced, and the reliability of a security and protection system is improved.

The invention discloses a flow type single molecule detection probe and method based on rolling circle amplification and application in the technical field of biomolecule detection. The flow type single molecule detection probe comprises a plurality of groups of magnetic bead detection probes and antibody binding probes which are used in pairs, each magnetic bead detection probe comprises a superparamagnetic microsphere, and the surface of the superparamagnetic microsphere is covalently connected with a plurality of fixed antibody probes; each fixed antibody probe comprises a first antibody and a first fixed DNA chain; each antibody binding probe comprises a second antibody and a second fixed DNA chain; aiming at the same target antigen, the first antibody and the second antibody in the same group can be specifically combined with different epitopes of the target antigen to form a sandwich immune complex. According to the invention, the hairpin structure DNA probe is combined with the adjacent ligation and rolling circle amplification technology to form dual specific screening of immune recognition and DNA ligation, so that the signal-to-noise ratio and sensitivity of detection are remarkably improved, and the design complexity, development cost and cross reaction risk of a multi-target detection system are greatly reduced.