8results about How to "High alarm accuracy" patented technology

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.

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 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 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 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.

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 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 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.