31results about How to "High alarm accuracy" patented technology

The invention provides an ancient building adaptive composite fire detection alarm model construction method, and relates to the field of fire detection, and the method comprises the following steps: firstly, carrying out on-site survey to obtain an ancient building structure and internal decoration combustibles and layout, and employing a cone calorimeter to measure the combustion performance parameters of building materials and decorations; then, FDS software is adopted for conducting three-dimensional modeling and computational grid division, boundary and condition setting, fire point and fire source power setting, detection point position setting and the like on the internal space and display of the historic building, and data sets of CO concentration, CO2 concentration, O2 concentration, smoke shading rate and temperature parameter changes in the fire occurrence and development process are obtained through numerical simulation calculation; and finally, learning and training the initial multi-characteristic parameter data of the fire through a BP neural network, continuously correcting and optimizing in application, and constructing a self-adaptive fire alarm model, thereby more accurately and comprehensively sensing the fire of the ancient building, and realizing accurate early warning of the early fire.

The embodiment of the invention discloses a parking warning method and device and a vehicle, and belongs to the technical field of vehicles. The method is used for a vehicle machine, the vehicle machine is connected with a vehicle state detection device in a vehicle through a CAN bus, and the method comprises the steps that under the condition that the vehicle is in a stop state, a target vehicle state signal sent by at least one target vehicle state detection device is obtained through the CAN bus, the different target vehicle state signals are used for representing the states of different vehicle parts; based on the target vehicle state signal, vehicle leaving trend identification is carried out, a vehicle leaving trend identification result is obtained, and the vehicle leaving trend identification result is used for representing whether the driver has a trend of leaving the vehicle or not; and when the vehicle leaving trend identification result represents that the driver has a trend of leaving the vehicle and the current gear is a non-parking gear, carrying out parking state risk warning. By the adoption of the technical scheme, the parking state of a driver when the driver leaves the vehicle can be monitored, accurate warning is achieved, and vehicle sliding is avoided.

The invention provides a vibration optical fiber alarm threshold adjustment method, device and equipment and a storage medium, and belongs to the technical field of perimeter security and protection, and the method comprises the steps: obtaining vibration signals and environment parameter data collected based on a vibration optical fiber sensor and an environment sensor which are installed on a perimeter; extracting signal features of the vibration signals and data features of the environmental parameter data; inputting the signal features and the data features into an alarm threshold adjustment model to obtain a reference threshold; and obtaining the current threshold value of the vibration optical fiber, and adjusting the current threshold value of the vibration optical fiber as the reference threshold value. According to the method, the signal features and the data features are input into the alarm threshold adjustment model to obtain the reference threshold, false alarms caused by environmental factors and normal activities are reduced, it is ensured that the alarm can be triggered timely and accurately when a real intrusion behavior occurs, and the alarm accuracy of the perimeter security system is improved.

The invention discloses an oil pipeline leakage monitoring method based on a pipeline transportation pressure prediction model, and relates to the technical field of pipeline leakage monitoring, and the method comprises the steps: building a pipeline transportation pressure prediction model through the pressure data of each preset position on a preset oil pipeline when the preset oil pipeline is in a normal transportation working condition; inputting the actual pressure of each preset position at the first moment into a pipeline transportation pressure prediction model, calculating to obtain the predicted pressure of each preset position at the second moment, and calculating the pressure deviation between the predicted pressure and the actual pressure of each preset position at the second moment; and whether the pressure deviation corresponding to each preset position exceeds a corresponding preset pressure deviation threshold value or not is judged, and when the pressure deviation corresponding to any preset position exceeds the preset pressure deviation threshold value corresponding to the preset position, it is judged that the preset oil pipeline leaks. Whether the pipeline leaks or not can be accurately judged.

The embodiment of the invention discloses a chemical equipment fault diagnosis and maintenance system, and belongs to the technical field of equipment monitoring, and the system comprises an equipment monitoring module which is installed on equipment and is used for monitoring and reading various data during the operation of the equipment; the data acquisition module is used for acquiring the equipment operation data monitored and read by the equipment monitoring module, and compressing, filtering and uploading the acquired data; and the monitoring diagnosis module is used for receiving the equipment operation data uploaded by the data acquisition module, performing fault diagnosis on the data, and performing fault maintenance on target equipment according to a fault diagnosis result. According to the embodiment of the invention, the cost can be reduced, the equipment reliability can be improved, and online monitoring, real-time fault alarm and hidden danger prediction reminding of the equipment are realized; and the influence of sensor errors on fault diagnosis is reduced.

The utility model relates to a fire alarm device, in particular to a novel self-powered building fire alarm device. Comprising a power supply structure and an alarm structure. The power supply structure comprises a solar photovoltaic device and a storage battery, the solar photovoltaic device and the storage battery are both fixedly arranged on the roof, the solar photovoltaic device is electrically connected with the storage battery, and the storage battery is electrically connected with the alarm structure through a cable; the alarm structure comprises a shell, a temperature sensor, a first buzzer, a light alarm, a smoke sensor, a second buzzer and a controller, the shell is connected with a building wall, and the temperature sensor, the first buzzer, the light alarm, the smoke sensor and the second buzzer are arranged outside the shell; the temperature sensor, the first buzzer, the light alarm, the smoke sensor and the second buzzer are in signal connection with the controller, and the controller is arranged in the shell. The technical problem that a storage battery of an existing fire alarm device is internally arranged, so that spontaneous combustion is prone to occurring, and working stability is affected is solved.

The invention relates to a tire abnormal wear alarm method and a storage medium, and the method comprises the following steps: when a vehicle starting signal is input, collecting a four-wheel speed signal according to a preset condition; when the time for accumulatively collecting the four-wheel speed signals reaches preset time, whether the difference of the four-wheel speed exceeds a preset difference value or not is judged according to the four-wheel speed signals; and if so, sending out a tire abnormal wear alarm. The four-wheel speed signals are collected only when the preset condition is met, various influence factors are eliminated, the influence on the difference of the four-wheel speed is avoided, and the alarm accuracy is improved.

The invention discloses a monitoring method and system for operation safety of an industrial machine, a storage medium and electronic equipment. The method comprises the following steps: acquiring and displaying a three-dimensional alarm area of the industrial machine in an imaging visual field of image data acquisition equipment; acquiring and displaying position information of a human body target appearing in the imaging view; and alarm processing is carried out after the alarm signal is received. According to the invention, the alarm accuracy of industrial machinery operation safety monitoring can be effectively improved.

The invention discloses a data alarm processing method and system of an energy management system, belongs to the technical field of data alarm processing, and is used for solving the problems that the processing efficiency of the current data alarm processing method is low, the message processing is lagged, and the data alarm processing efficiency is high along with the finer energy management work of an enterprise. And the enterprise energy data problem is not timely processed. The method comprises the following steps: installing an energy measuring instrument group in equipment to be measured, and setting the running state of each energy measuring instrument in the energy measuring instrument group; in the energy management system, performing alarm setting on each energy measuring instrument in the energy measuring instrument group; acquiring first energy data of the energy measuring instrument group, and transmitting the first energy data to the energy management system for data alarm processing; and exchanging the operation states of the energy measuring instruments in the energy measuring instrument group, acquiring second energy data of the energy measuring instrument group, and transmitting the second energy data to the energy management system for data alarm processing again.

The invention discloses an identification method and system based on error signals before and after starting and stopping of equipment, and belongs to the technical field of state monitoring of rotating equipment. The method comprises the following steps: acquiring equipment measurement point data, presetting a start-stop threshold and an alarm threshold, and if the start-stop threshold is not preset, processing the measurement point data to obtain the start-stop threshold; then the start-stop state of the equipment is judged according to the start-stop threshold value; the method comprises the steps of classifying all data, calculating a probability density function and a differential entropy, finally obtaining an index factor of start-stop abnormal data, then identifying the start-stop abnormal data based on a sliding window, marking the start-stop abnormal data, retrieving whether the data exceeding a preset alarm threshold is abnormal data, and if yes, canceling the alarm. Start-stop state identification is carried out based on the equipment vibration condition, then false signal discrimination is further carried out on data before and after start-stop, false alarms caused by working condition fluctuation before and after start-stop of the equipment are reduced, and the alarm accuracy of a monitoring system can be improved.

This invention discloses a feeder for an enameling machine with a replenishment reminder function, comprising: a holding rack, a sensor mounting bracket, a lifting plate, a weighing module, a lifting drive mechanism, and a control system. The holding rack includes a circular base, multiple protective vertical rods, and a circular top frame; the bottom of the protective vertical rods is connected to the circular base, and the top of the protective vertical rods is connected to the circular top frame; the multiple protective vertical rods are spaced apart around the axis of the circular base to form a wire receiving area. The sensor mounting bracket is installed on the holding rack; the sensor mounting bracket connects to sensors indicating the presence or absence of a first object, a second object, and a third object. The weighing module is installed on the holding rack. The lifting drive mechanism is detachably driven by the lifting plate. The control system is electrically connected to an alarm device. It has the function of reminding workers to replenish materials, thereby ensuring production efficiency.

The present invention discloses a method and device for testing machine performance, and relates to the field of computer technology. A specific implementation of the method includes: repeatedly performing performance tests on a machine to obtain multiple target test results; calculating the multiple target test results based on a performance benchmark value, and judging the performance of the machine according to the calculation results; wherein the performance benchmark value is obtained by the following method: repeatedly performing performance tests on the machine to obtain multiple benchmark test results, thereby calculating the performance benchmark value. This implementation can solve the technical problem of a large number of false alarms.

The invention discloses an intelligent security and protection system for an airport boundary, and the system comprises a front-end sensing system, a data transmission system and a central control system which are sequentially connected through an electric signal and a communication signal. Any partition front-end sensing system is provided with a nine-axis sensor capable of collecting dynamic signals and static signals of the surrounding environment of the fence in real time, an edge calculation all-in-one machine connected with the nine-axis sensor, and a switch connected with the edge calculation all-in-one machine; the edge calculation all-in-one machine receives environment data sensed by the nine-axis sensor and attitude data generated by attitude changes of the nine-axis sensor, and the edge calculation all-in-one machine processes the signal data to extract features. The nine-axis sensor selected by the invention performs machine learning and modeling based on a time-frequency characteristic time sequence spectrogram, combines information of a wind speed and rainfall sensor, optimizes weather interference except extreme meteorological conditions by processing data information, and is linked with a video to reduce a false alarm rate.

The invention belongs to the technical field of photoelectric smoke fire detection, and discloses a photoelectric smoke fire detection alarm false alarm resisting method based on particle size inversion, which comprises the following steps: S1, regularly detecting light intensity information scattered by particles; s2, judging whether a suspected fire signal is detected or not; s3, repeatedly and continuously sampling, and calculating the particle size r through a particle size inversion method; s4, judging the size relationship between the particle size r and a preset fire smoke particle r *; if r is far greater than r * or far less than r *, determining that the signal is a non-fire signal, and the fire detector does not give an alarm; if r is close to r *, fire particles are judged, and the alarm gives an alarm. According to dynamic change characteristics of scattered light intensity brought by thermal motion of particulate matters with different particle sizes, particle sizes of the particulate matters are inverted by adopting a particle size inversion method, fire smoke particles and large particles such as dust, fog drops and eggs are distinguished according to the particle sizes, and false alarm resistance of the fire detector is formed.

The present invention discloses a fire monitoring method and device, wherein the fire monitoring method obtains the actual smoke signal strength monitored by multiple smoke detectors, compares the measured signal value with the calculated smoke signal strength calculated by using an estimation formula, takes the measured signal value reaching or exceeding the calculated smoke signal strength as the real fire condition, and searches for nodes that meet the fire condition in real time. This method uses the central maximum measured signal value being greater than a certain threshold and the existence of multiple nodes meeting the real fire condition as the judgment basis for fire alarm, which can significantly improve the alarm accuracy of smoke detectors, reduce false alarms, and shorten the alarm time.

This disclosure provides an alarm method, apparatus, device, and medium. The method includes: in response to an alarm event generated by an alarm system, acquiring a curve image corresponding to the alarm event; inputting the curve image into an image classification model to obtain a classification result output by the image classification model; and outputting alarm information corresponding to the alarm event based on the classification result. This disclosure can reduce the probability of false alarms, thereby improving alarm accuracy.

The invention belongs to the field of medical sickbeds, and provides an electric sickbed based on critical patient head inclination angle alarming, the electric sickbed comprises a bed body, a fixed box is fixedly mounted at the bottom of the bed body, a swing rod is rotatably connected in the fixed box, and the rotation direction of the swing rod is perpendicular to the length direction of the bed body; a lifting rod assembly is vertically and slidably mounted at the top of the swing rod, a second rotating seat is mounted at one end of the lifting rod assembly, and a sliding block is mounted on the second rotating seat. A plurality of flexible film pressure sensors are arranged on the pillow, head pressure distribution of a patient can be detected, the head position and the inclination angle of the patient can be judged through processing of the data processing module, a threshold value is set in the controller in advance, and when the head inclination angle of the patient is too large, the patient can be reminded to take out the patient. The controller can control the alarm to give an alarm to remind medical staff to timely return to right the head of the patient, so that secondary injury to the head of the patient is avoided.

The present application belongs to the technical field of energy storage system operation and maintenance and data diagnosis, and particularly relates to an energy storage data diagnosis method and device for a zero-carbon service area of a highway, which identifies abnormalities and triggers self-checking by real-time monitoring of energy storage system asset SN set, channel-asset binding and channel physical characteristic data; identifies natural or artificial anchor points and determines a time window through charging session and grid-connected power steady-state constraint, extracts channel fingerprint characteristics, matches asset SN historical characteristic templates according to the operation mode, and calculates the normalized difference degree to check the binding relationship; when the binding is mismatched, the optimal rematching scheme is solved through bipartite graph matching according to the physical topology constraint, and is independently verified through a station-level power closed audit model, and after verification, the hierarchical reconstruction diagnosis baseline is verified, the multi-state is combined, a hierarchical gating strategy is adopted to output an alarm and a diagnosis conclusion, and the accuracy of the alarm is improved, the number of misdispatched work orders is reduced, the diagnosis conclusion is traceable and auditable, and stable support is provided for zero-carbon operation accounting.

The present disclosure relates to an alarm method, device, storage medium and electronic equipment, the alarm method comprising: determining a first offset degree of a current index value of a target index relative to a value in a preset target threshold interval; determining a second offset degree of the current index value of the target index according to a distance between the current index value of the target index and a plurality of historical index values of the target index; obtaining a target offset degree corresponding to the current index value of the target index according to the first offset degree and the second offset degree; and determining that the current index value of the target index is abnormal and performing alarm if the target offset degree is greater than or equal to an offset degree threshold corresponding to the target index. Compared with the scheme of alarm discrimination based on a single set of fixed threshold interval, the present technical scheme has higher alarm accuracy and lower false negative rate.

The invention relates to the technical field of alarm signal processing, and discloses a gas alarm detector alarm signal processing method comprising the following steps: carrying out address coding on a gas alarm detector to form an address code which is unique and not repeated; receiving a gas concentration signal sent by a gas alarm detector, wherein the gas concentration signal comprises a gas concentration value and an address code; determining an installation scene of the gas alarm detector according to the address code; acquiring environmental data of an installation scene of the gas alarm detector, and setting a gas concentration alarm threshold value according to the environmental data; and generating an alarm signal according to the gas concentration value and the gas concentration alarm threshold value, and carrying out sound-light alarm. According to the method, the alarm accuracy can be effectively improved, the richness and readability of the alarm information are enhanced, the user is helped to quickly position the problem, and the self-adaptive adjustment of alarm processing is realized to adapt to different environments and use scenes.

The present invention relates to a battery temperature monitoring system and method, the system comprises a battery, a battery detection device, a power supply monitoring server and an infrared thermal imaging camera for detecting the battery temperature, the infrared thermal imaging camera is connected to the power supply monitoring server via a switch, the input end of the battery detection device is connected to the battery, the output end of the battery detection device is connected to the power supply monitoring server via a switch, and the power supply monitoring server determines whether the current battery temperature is within a normal alarm threshold range according to the current state of the battery and the acquired temperature information. The present invention uses an infrared thermal imaging camera to detect the battery temperature in all directions, and can timely detect the high temperature fire caused by leakage at different shell positions of the battery, and the detection means should be safe and reliable, not destroy or affect the stability of the connection between the batteries, not aggravate the self-discharge of the battery, and have high alarm accuracy.

This invention discloses an integrated intelligent fire protection linkage and property emergency response system for high-quality residential buildings, relating to the field of smart fire protection. It includes: a sensing and triggering module for configuring the acquisition period and trigger threshold, acquiring real-time physical quantity signals related to fire risks across the entire residential area based on the acquisition period, and generating and outputting alarm signals based on the trigger threshold; and a filtering module for receiving the initial signal output from the sensing and triggering module, cross-validating it with related signals from the residential environment, and eliminating invalid interference signals and filtering valid fire alarm signals. This invention effectively filters invalid interference by accurately acquiring real-time fire-related physical quantity signals from the residential building, dynamically adjusting judgment criteria based on environmental factors, significantly improving alarm accuracy, avoiding false alarms, and simultaneously executing graded response actions based on risk levels to ensure precise coordination and efficient operation of fire protection facilities.

The embodiment of the present invention provides a method and device for determining an alarm message, including: obtaining a prompt message and multimedia information, wherein the prompt message is a message obtained by detecting the multimedia information; determining the similarity between the multimedia information and each semantic element in a preset semantic element set to obtain a first similarity set, wherein the prompt message includes at least one target semantic element, and the target semantic element is an element in the semantic element set; determining whether the prompt message is an alarm message through the first similarity set. Through the present invention, the problem of pushing a large number of invalid alarm messages during the detection process in the related art is solved, thereby achieving the effect of improving the accuracy of the alarm.

The invention relates to the technical field of intelligent fire protection, in particular to an intelligent fire protection multi-level alarm strategy optimization method and system based on big data. During use, by building a multi-source heterogeneous data acquisition system supporting multi-protocol compatibility, plug and play of cross-manufacturer equipment is achieved, hardware transformation is not needed, the deployment efficiency is greatly improved, and the deployment cost is reduced. An isolated forest algorithm is adopted to eliminate extreme abnormal values, principal component analysis and a weighted fusion algorithm are combined to optimize feature data quality, a fire risk prediction model is constructed based on a combined model of XGBoost and a random forest, and a dual check mechanism of multi-sensor cross validation and YOLOv8 video recheck is matched, so that the false alarm rate and the missing report rate of the system are reduced, and the alarm accuracy is improved.

The invention relates to the field of security alarm, and discloses a network security alarm system and method based on big data, and the system comprises a network data collection module which collects network traffic and security data from network equipment and system logs, and stores the data obtained by the network data collection module in a database. Calling the data in the database, performing security analysis according to a preset alarm rule, calculating to obtain a security alarm index, comparing the security alarm index with a security threshold interval preset by the system, if the security alarm index is within the security threshold interval, judging that the current network is secure, and if the security alarm index is not within the security threshold interval, judging that the current network is not secure. Otherwise, judging that the current network has a security risk, then generating alarm information according to a result that the network security analysis module judges that the current network has the security risk, sending the alarm information to a system background, and finally performing descending sorting according to a security alarm index to generate an arrangement sequence of the alarm information. And taking the arrangement sequence as a response priority.

The present application discloses a sound source alarm method and device, a storage medium and an electronic device. The method includes: controlling a sound source input device to obtain sound source data in a target area; determining first sound source data and second sound source data from the sound source data, wherein the first sound source data and the second sound source data represent sound source data collected by the first sound source input device and the second sound source input device for a target sound source in the same time period, and the first sound source input device is different from the second sound source input device; analyzing the frequency components of the first sound source data and the second sound source data to determine the target coordinates of the target sound source; determining the behavior state of the target sound source based on the change of the target coordinates within a preset time period, and generating an alarm message when the behavior state is the target behavior state. The present application solves the technical problem of low accuracy of regional alarms due to low real-time and accuracy in detecting the behavior of objects in the area.

The present invention relates to a fire very early detection warning alarm system and method. Subway tunnel fires are extremely harmful to human life and property, and it is necessary to propose relevant methods for very early fire detection of subway tunnel fires. Each detector in the system is connected to a group of alarm monitoring modules, and all alarm monitoring modules are connected to an alarm controller; in the detector, the infrared light sensor and the ultraviolet light sensor are connected to an industrial-grade computing chip, and the high-definition camera is connected to an image sensor and then to an industrial-grade computing chip; the industrial-grade computing chip is connected to a signal comparison unit, and the signal comparison unit is connected to a signal relay, and the signal relay is connected to a terminal of a wiring board and outputs a signal. The present invention can effectively avoid false fire alarms, greatly improve the accuracy of the early warning alarm of the fire detector, can transmit real-time video images on the scene, and also greatly facilitate the investigation of the cause of the later fire accident.

The invention relates to the technical field of hydropower station equipment monitoring, and provides a hydropower station equipment fault alarm method and system, and the method comprises the steps: obtaining a plurality of pieces of multi-source heterogeneous monitoring data of hydropower station equipment under a plurality of health historical working conditions; determining a reference feature template according to the plurality of health historical working conditions and the plurality of corresponding multi-source heterogeneous monitoring data; acquiring real-time heterogeneous monitoring data of the hydropower station equipment under the current working condition; according to the current working condition, the corresponding real-time heterogeneous monitoring data, the reference feature template and the fault feature knowledge base, identifying the early fault type of the hydropower station equipment; and multi-stage fault alarm is carried out according to the early fault type identification result. The problems that a traditional hydropower station equipment alarm method depends on a fixed threshold value and is difficult to adapt to working condition changes, multi-source heterogeneous monitoring data lacks effective fusion, early fault features are not sensitive, and false alarm and missing alarm are likely to happen are solved.

The invention belongs to the technical field of aviation monitoring sensor design, and discloses a temperature alarm composite sensor and an alarm method.The temperature alarm composite sensor comprises a shell and an outer sleeve, a socket and an end cover are arranged on the shell, a circuit board is packaged in the shell and connected with the socket, the outer sleeve is fixedly connected to the end cover, and a temperature probe is installed at the end of the outer sleeve; the temperature probe comprises two platinum resistors which are not in contact with each other, and the two platinum resistors are connected with the circuit board. By adopting the temperature probe dual-redundancy design and the temperature probe is arranged in front, the dynamic response is fast; the temperature probe is subjected to signal conditioning, the temperature measurement precision is high, and the alarm precision is high.

The present invention discloses a smoke concentration detection system for a cargo hold of a civil aircraft based on polarized light. It includes an adjustable light emitting module, an adjustable polarized light receiving module, and a logic control and data processing module; the adjustable light emitting module is used to output infrared or blue light signals with variable intensity, which enter the adjustable polarized light receiving module after being scattered by smoke particles; the adjustable polarized light receiving module is used to convert the light signal into an electrical signal and then input it into the logic control and data processing module; the input logic control and data processing module is used to perform data processing on the electrical signal to judge smoke and interference, and at the same time adjust the amplification factor according to the signal intensity of the adjustable polarized light receiving module. The present invention has a wide detection concentration range, good detection concentration continuity, high adjustment accuracy, and reliable alarm.