6148 results about "Alarm device" patented technology

The invention discloses a water receiving mechanism for a cold drink machine and a liquid level detection method. The water receiving mechanism comprises a bearing seat and a water receiving disc, the bearing seat is installed on a box body of the cold drink machine, a motor seat is arranged at one end of the bearing seat, an ice making bin is arranged at one end of the motor seat, and one end of the ice making bin is installed on the motor seat; a sliding rail groove and a water receiving disc installed in the sliding rail groove are arranged in the other end of the bearing seat, the water receiving disc is connected with the sliding rail groove in a sliding mode, and a water receiving groove in the water receiving disc is located below the ice making bin; external water receiving channels are defined between the ice making bin and the bearing seat, are respectively positioned on two sides of the bearing seat, and are communicated with the water receiving groove; at least one liquid level detection device is arranged on the upper portion of the water receiving tank and electrically connected with a controller of the cold drink machine, and the controller is further electrically connected with a sound-light alarm device on the cold drink machine. By adopting the ice-making bin, materials flowing out of the ice-making bin can be collected, and the liquid level condition in the water pan can be monitored in real time, so that stable implementation of water receiving work of the ice-making bin is ensured, and the use comfort of a user is improved.

A fault alarm device for solar power generation belongs to the field of solar fault monitoring. The system includes an edge monitoring module, a multimodal data fusion module, a fault classification module, a trend prediction module, a dynamic adjustment module and an alarm response module. The present invention improves the accuracy of fault identification by integrating multidimensional features such as photovoltaic panel current, voltage, power, ambient temperature and light intensity by using a deep learning fusion model. By introducing an attention mechanism and dynamically adjusting the alarm threshold, it effectively distinguishes environmental fluctuations from actual faults, reduces the false alarm rate and missed alarm rate, and can adapt to the complex and changeable photovoltaic system operating environment without manual intervention.

The invention relates to the field of intelligent early warning of photovoltaic electricity larceny prevention, and particularly discloses a photovoltaic electricity larceny prevention alarm device, which comprises the following steps of: firstly, acquiring an electricity utilization curve graph of a user to be analyzed in a plurality of preset time periods and transformer area line loss data of a plurality of preset time points in a power system as input data; and then performing deep convolutional coding and analysis on the input data by using a machine learning technology to obtain a classification result, wherein the classification result is used for representing whether the user to be analyzed has an electricity stealing behavior or not. Therefore, real-time early warning of photovoltaic electricity stealing behaviors can be realized, so that benefits of enterprises are effectively protected, the market order is maintained, and healthy development of the photovoltaic industry is promoted.

The invention discloses a side slope early warning method and system based on an optical fiber sensor, and relates to the technical field of side slope monitoring, and the method comprises the steps: collecting side slope deformation monitoring data and environment monitoring data, and carrying out the preprocessing of the collected deformation monitoring data; a causal association rule between the environment monitoring data and slope deformation is constructed, and the deformation space distribution range of the whole slope is predicted based on a BP neural network; and taking the slope deformation monitoring sequence as a sample, training an RNN neural network, predicting the development trend of slope deformation, carrying out early warning analysis on the overall stability of the slope, and generating an early warning result through an alarm device. According to the method, the causal association rule is constructed, the environmental monitoring data and the deformation data are combined, the space prediction precision is improved, the RNN neural network is used for training the time sequence data, and the development trend of slope deformation can be effectively predicted; and in combination with the spatial distribution data, a future deformation trend analysis and early warning result is generated, so that the timeliness and accuracy of early warning can be improved.

A warning system according to the present disclosure includes: a character information generation unit that generates, by using a captured image of the inside or the outside of a mobile body, character information indicating a character representing an event appearing in the captured image; and a warning information notification unit that issues a notification of warning information corresponding to the character information generated by the character information generation unit. In a warning method according to the present disclosure, a computer: generates, by using a captured image of the inside or the outside of a mobile body, character information indicating a character representing an event appearing in the captured image; and issues a notification of warning information corresponding to the generated character information.

The invention relates to the technical field of mine safety, and discloses a mine extreme weather emergency defense and up-and-down pre-alarm system, which comprises a ground surface monitoring module used for monitoring the water level, rainfall and environment humidity of a mine wellhead and a ground surface low-lying area in real time and generating a dynamic water level pre-alarm signal; the wellhead flood control module comprises an automatic emergency flood control door and is used for receiving the early warning signal of the earth surface monitoring module and automatically closing the flood control door when the water level reaches a warning line so as to prevent surface accumulated water from flowing backwards to the underground; and the underground early warning and evacuation module comprises a sound-light alarm device and a wireless communication system. By adopting the technical scheme of multi-sensor fusion and water level trend prediction, through multi-dimensional real-time monitoring of the wellhead water level, the rainfall intensity and the environment humidity, the pre-closing state of the flood gate is triggered in advance in combination with dynamic data analysis and an intelligent algorithm, and the technical effects of timely responding to rapid rising of the water level and reducing the operation pressure of equipment are achieved.

The invention discloses an early warning emergency processing system and method based on electric power operation, and relates to the technical field of monitoring analysis, and the method comprises the steps: obtaining an electric power equipment operation state data set, and generating an electric power operation three-dimensional dynamic model; performing abnormal operation feature extraction on the power equipment operation state data set to obtain an equipment abnormal feature map, performing dynamic risk prediction on the equipment abnormal feature map in combination with environment monitoring data, and generating a power equipment risk level distribution map; performing potential safety hazard correlation analysis according to the power equipment risk level distribution diagram and the power operation three-dimensional dynamic model, and generating a power safety early warning optimization model; and performing emergency plan matching degree calculation based on the electric power safety early warning optimization model, generating a multi-stage emergency response scheme set, performing dynamic priority adjustment on the multi-stage emergency response scheme set, executing electric power operation emergency processing operation, and outputting an alarm signal to an alarm device. The method has the effect of improving the emergency processing efficiency.

The invention discloses a fire-fighting fireproof door alarm information transmission device and method based on the Internet of Things, and relates to the technical field of fire-fighting alarm, and the method comprises the following steps: carrying out the multi-band continuous scanning of a wireless communication environment of a fireproof door alarm device deployment region after a fire emergency mode is started, identifying a target communication protocol frequency band used by the fireproof door alarm device, and obtaining spectrum parameter information of each frequency band to form a to-be-analyzed communication frequency band set; and extracting a working frequency band used by the peripheral wireless equipment based on a pre-established environment wireless equipment frequency band database. Frequency spectrum mapping is constructed through frequency spectrum scanning and an environment database, intelligent interference prediction is realized in combination with a support vector machine, coding parameters are dynamically adjusted based on interference intensity, the transmission reliability of key alarm information in a high-interference environment is improved, feedforward recognition and closed-loop regulation and control capabilities are achieved, and the method is suitable for popularization and application. And the problems of slow response and unstable transmission of a traditional system are effectively solved.

The invention discloses a household intelligent alarm device based on the Internet, and relates to the technical field of intelligent security and protection, and the device comprises an alarm information generation module which carries out the fusion of multi-source feature data, calculates an alarm index through a weighted summation method, and generates alarm information; the control instruction module is used for encrypting the alarm information, generating an encrypted data packet, sending the encrypted data packet to a remote user side through the Internet and receiving a control instruction of the user side; and the alarm command module is used for dynamically adjusting the alarm strategy based on the control instruction of the user side and generating an alarm processing command. By dynamically distributing the weight of the multi-source sensor, the adaptability of the device is improved, and false alarms caused by environment changes in the daytime and at night are reduced; in combination with historical false alarm data analysis and a self-adaptive updating algorithm, an alarm threshold is continuously optimized, the alarm accuracy is improved, and the false alarm rate and the missing report rate are reduced.

The invention discloses a pressure injury risk early warning method and equipment, and relates to the technical field of medical monitoring instruments. The pressure sensor array layout can be self-adaptive to the body shape of a patient, a key osseous process part is covered, no monitoring dead angle is ensured, a temperature compensation mechanism is built in, environmental interference is reduced, the measurement precision is improved, an abnormal pressure threshold value can be dynamically set based on individual medical record data, data verification is performed before early warning is triggered, false alarm is avoided, and the array structure is light, thin and flexible. The mask is comfortable to fit skin, supports long-term wearing and is easy to disinfect and maintain; environment temperature and humidity parameters and pressure data are subjected to fusion analysis, the influence of a high-temperature and high-humidity environment on skin microcirculation can be recognized, the risk of pressure sores can be evaluated in an auxiliary mode, a calibration algorithm is built in a sensor, environment fluctuation interference is reduced, and data reliability is ensured; and the early warning unit comprises sound-light alarm equipment which supports a multi-stage alarm mode and is used for triggering an early warning signal and pushing information when the risk index exceeds a threshold value, so that the early warning timeliness is ensured and the false alarm risk is reduced.

The invention discloses an output voltage detection method and system based on an aviation power supply, and relates to the technical field of aviation power supply voltage detection. A differential voltage sensor is connected to the output end of an aviation power supply, a high-frequency suppression capacitor is connected in parallel, the sampling rate of 20-50 times of the working frequency is set according to the type of the power supply, and the signals are collected and converted into analog voltage signals; the analog signal is subjected to two-stage filtering, is amplified to 0-5V through an instrument amplifier, and is converted into a digital voltage sequence through a 16-bit ADC (Analog to Digital Converter); calculating AC power supply effective value, peak value and other parameters, DC power supply average value, ripple coefficient and other parameters; comparing the characteristic parameters with a preset threshold value, determining that the characteristic parameters exceed the threshold value and recording related information; and a detection result is transmitted to a monitoring terminal through an RS485, data is locally stored, and a switching value is output to an alarm device when the data is abnormal. The method adapts to aviation power supply load fluctuation and environment temperature change, detection precision is high, data transmission and storage are safe, abnormity is accurately identified and early warning is carried out in advance, and aviation power supply operation and maintenance reliability and efficiency are improved.

The invention relates to the technical field of foundation pit detection, and discloses a foundation pit displacement monitoring method and system based on machine vision and monitoring equipment. The method comprises the steps that a high-definition camera collects image data of a foundation pit area in real time, the collected image data are preprocessed, reference points in the image data are analyzed through an optical flow method, displacement of the reference points in a foundation pit is estimated, and three-dimensional position changes of the reference points are calculated through the stereoscopic vision technology and image matching. The system comprises an image acquisition module, an image preprocessing module, a displacement calculation module, a filtering optimization module, an anomaly detection and early warning module and a data storage module. The equipment comprises a high-definition monitoring camera, a data processing terminal, a storage unit, an alarm device and a communication module. According to the invention, through image acquisition of a multi-camera system and a stereoscopic vision technology, comprehensive monitoring of the displacement of the foundation pit is ensured, high-quality image data can be provided in various environments, and precise acquisition of three-dimensional depth information is realized in combination with stereoscopic vision.

The invention relates to a power cable insulation state real-time monitoring and alarm device, and belongs to the technical field of power equipment state monitoring. Comprising a multi-source sensing unit which is installed at a cable body and a joint; the edge computing terminal is fixed in the cable well or the ring main unit; and the cloud early warning platform receives the processing data and outputs an alarm instruction. According to the invention, multi-parameter deep fusion is realized, four-dimensional monitoring of grounding current, temperature, partial discharge and humidity is initiated for the first time, and limitation of a single parameter is broken through; and an insulation health index IHI is proposed, and the insulation deterioration degree is quantitatively evaluated. According to the method, tan delta and IHI are calculated on site through an edge-cloud collaborative architecture edge terminal, so that the data transmission quantity is reduced; the cloud dynamic threshold value is adjusted, and the alarm accuracy is improved. According to the invention, intelligent early warning mechanism three-level alarm linkage protection equipment is arranged; and the self-calibration function ensures long-term reliability.

The present invention relates to the technical field of power equipment, and particularly to a power equipment alarm device and monitoring system. The power equipment alarm device comprises an alarm mechanism, the alarm mechanism comprising: a power cabinet; heat dissipation holes provided in the power cabinet; a baffle arranged inside the power cabinet; a warning light, a first drive assembly and a second drive assembly that are arranged on the power cabinet; a limiting assembly and a third drive assembly that are arranged on the baffle; and a locking assembly and an unlocking assembly that are mounted on the power cabinet. The first drive assembly and the second drive assembly drive the warning light to give an alarm, and the second drive assembly releases the limit on the baffle, such that the baffle blocks the heat dissipation holes, thereby achieving automatic fire extinguishing.

The invention relates to the technical field of violation monitoring, and provides an unattended system based on an AI model and video analysis, the unattended system comprises an AI language large model, a video monitoring device, an image analysis node and a linkage alarm device, the video monitoring device is configured with a sound-light alarm assembly, the image analysis node comprises a plurality of AI edge calculation boxes, and the AI edge calculation boxes are connected with the AI language large model. The linkage alarm device comprises a plurality of protocol conversion middleware. The video monitoring equipment is used for collecting a real-time video stream of a current monitoring area and inputting the real-time video stream into the image analysis node; the AI language large model is used for analyzing target image features of the image analysis nodes, determining violation behaviors of violation events and generating natural language alarm information; wherein the violation behavior is determined by an AI edge calculation box; protocol conversion configuration is performed on the linkage alarm device, and a sound-light alarm signal based on natural language alarm information can be generated on the video monitoring device in the current monitoring area through the linkage alarm device.

The invention discloses a distributed optical fiber temperature measurement system, which comprises a light source device, a sensing optical fiber, an optical signal processing device, a data acquisition device, a signal processing and computing device, a display and alarm device, a communication and data processing device and a system control center, a plurality of light sources emit light pulses to enter the sensing optical fiber, the sensing optical fiber converts temperature changes into optical signals, the optical signals are converted into electric signals through the optical signal processing equipment, the electric signals are converted into digital signals through the data acquisition equipment, and then the digital signals are transmitted to the signal processing and calculating equipment to be processed to obtain temperature values. The temperature value is transmitted to the display and alarm device, sound-light alarm is triggered when the temperature is abnormal, and data is transmitted to a remote control center to be monitored and managed by means of the communication and data processing device. According to the invention, the sensitivity and the response speed of temperature measurement can be improved by setting a synchronous control technology and assisting cooperation of a plurality of light sources.

The invention relates to the technical field of intelligent traffic, and discloses an intelligent traffic-oriented 5G + V2X module and risk early warning terminal and an application method thereof, and the intelligent traffic-oriented 5G + V2X module and risk early warning terminal comprises an equipment end and a cloud platform. The equipment end is mounted on a vehicle and comprises a real-time data acquisition module, a front-end anomaly detection model and a risk alarm; the real-time data acquisition module is responsible for acquiring data related to a vehicle and real-time data of the surrounding environment of the vehicle; the front-end anomaly detection model is deployed at an equipment end; the risk alarm triggers an alarm device when the front-end anomaly detection model detects a potential risk or an abnormal condition; the cloud platform comprises a data extraction module, a data center module and a real-time calculation module; wherein the data extraction is responsible for receiving, extracting and storing data acquired by a vehicle sensor and a camera from an equipment end; the data center stores and manages a large amount of vehicle data; accurate collection of the vehicle body motion state is improved, the position information of the vehicle is more accurate, and the tracking capacity of the system on the vehicle position and the driving track is improved.

The invention discloses an infusion monitoring system, which relates to the technical field of infusion monitoring, and comprises a controller with a display screen, an infusion pump arranged at the top of a main body case and used for regulating and controlling the infusion speed, an infusion tube fixing frame arranged on one side of the main body case, and an alarm device arranged on the surface of the main body case, a physiological parameter acquisition module, a medicine characteristic analysis module, a dynamic dripping speed regulation and control module, a liquid abnormity detection module, an AR interaction control module and an alarm cooperative processing module are arranged in the controller; a physiological parameter acquisition module, a medicine characteristic identification module, a dynamic dripping speed regulation module, a liquid abnormity detection module, an AR interaction control module and an alarm cooperative processing module are integrated. The intelligent and closed-loop infusion monitoring system is constructed, self-adaptive dripping speed adjustment based on the physiological state of the patient and the medicine characteristics is achieved, and the safety of infusion treatment is improved.

The invention discloses a real-time monitoring method for the mechanical damage state of a battery pack in the technical field of new energy automobiles, and the method comprises the steps: arranging an acceleration sensor on a bottom plate of the battery pack, combining a preset algorithm analysis technology, achieving the precise diagnosis of the health state of the battery pack after vibration impact, and improving the reliability of the battery pack. An alarm can be given in time when a potential fault is detected; acceleration response data of each sensor is continuously acquired according to a data acquisition module and is transmitted to a processing unit, and the processing unit quickly determines the specific impacted position of the bottom plate by using a built-in impact position positioning algorithm and predicts the overall vibration response of the bottom plate through a vibration response prediction algorithm. And calculating the magnitude of the mechanical shock excitation on the bottom plate, and comparing the predicted overall vibration response of the bottom plate and the mechanical shock excitation on the bottom plate with a preset threshold value. If any abnormity is found, an alarm device is triggered immediately, and a driver or a vehicle management system is notified to take corresponding measures.

The present invention relates to the technical field of exhaust valves, and specifically to a pneumatically controlled exhaust valve. The pneumatically controlled exhaust valve comprises a housing, a connecting hole being formed in one end of the housing, and an exhaust channel being formed in a side wall of the end of the housing distant from the connecting hole. An exhaust pipe is mounted in the exhaust channel, and a sealing bolt is installed at an end of an exhaust pipe channel close to an outer side wall of the housing. An exhaust hole is provided on the sealing bolt, and an end of the exhaust pipe distant from the sealing bolt is connected to a swing rod by means of a first spring, a sealing gasket being mounted at an end of the swing rod close to the exhaust pipe. A floating block is disposed in the housing, and the swing rod and the floating block are non-reliably connected. The present invention mounts an alarm device on the exhaust valve such that, when the exhaust valve leaks or cannot exhaust, the alarm device gives a prompt to a user to remind the user to clean the exhaust valve, thereby solving the problem of the time taken for limescale to affect the exhaust valve being shorter than a prescribed time for regular cleaning, causing water supply difficulties or leakage in heating pipes.

The invention provides a fault early warning protection device of a fuse and a control method. The device comprises a sensing unit used for detecting state data of a fuse, the state data comprising one or more of temperature, vibration signals, ultrasonic signals and current; the controller is in communication connection with the sensing unit, and the controller is used for determining whether the fuse is abnormal or not according to the state data; and the alarm device is in communication connection with the controller, and the alarm device is used for giving an alarm when the fuse is abnormal. According to the scheme, the problem of low efficiency of a manual fuse inspection mode in the prior art is solved.

The invention discloses an ultra-deep foundation pit supporting system selecting and monitoring method based on the digital technology, and belongs to the technical field of building construction.By inputting the specification, the geological condition, the hydrological condition and the load condition of a foundation pit into a foundation pit supporting system, a supporting system result meeting the specification is calculated and output; a complete three-dimensional foundation pit supporting system model is rapidly created in combination with Dynamo and Revit, a supporting structure construction drawing is output, and a material list and a calculation report of a supporting structure are generated; then, construction is conducted; the foundation pit supporting system model is imported into the monitoring platform, monitoring data of the foundation pit supporting system are obtained and mapped into the foundation pit supporting system model, and the current foundation pit supporting deformation condition can be visually analyzed; a data resource library is established in the monitoring platform, the monitoring data is compared with the data resource library, and the future foundation pit deformation condition is predicted; and the monitoring platform is connected with an alarm device, and when the monitoring data reaches a threshold value or the predicted deformation condition reaches the threshold value, the alarm device starts to report early warning information.

The invention relates to the technical field of industrial production detection, and discloses an AI-based industrial production process visual detection system and method. The system comprises an image acquisition module for acquiring production line real-time image data containing visible light and infrared band information; the defect detection module is used for extracting multi-level features by using an improved residual network to generate a defect probability distribution diagram; the dynamic adjustment module is used for generating a detection parameter optimization instruction through a depth deterministic strategy gradient algorithm; the multi-scale fusion module is used for outputting an enhanced defect feature map by utilizing a pyramid feature fusion network; and the execution control module constructs a distributed control instruction to drive the mechanical arm to respond to the alarm device in a linkage mode. The system can collect images in multiple dimensions, accurately detect defects, dynamically optimize detection parameters according to the environment, efficiently process defective products, and improve the industrial production quality and efficiency.

The utility model belongs to the technical field of infusion alarms, and particularly relates to an infusion alarm which comprises an alarm body and an infusion alarm device arranged on the alarm body. The supporting device comprises two fixing blocks which are symmetrically arranged on the rear side wall of the alarm main body and are provided with slots, and an inverted U-shaped supporting frame which is arranged between the two fixing blocks and is in sliding connection with the slots; the inverted U-shaped clamping frame is arranged at the tail end of the supporting frame; and the fastening rod is in threaded connection with the rear side wall of the clamping frame and is used for fixing the alarm main body and an infusion support. According to the infusion alarm device, the supporting device is arranged, so that the alarm device body can be conveniently fixed to an infusion support, the situation that the alarm device body is directly clamped on the outer side of an infusion tube and applies downward pulling force to the infusion tube is avoided, and the situation that the connecting position of the infusion tube and an infusion bottle falls off is avoided; and accompanying personnel and medical personnel can be reminded in time.

The invention provides a tumble alarm method, which is applied to a wearable tumble alarm device, the wearable tumble alarm device comprises a detection module, an alarm module and a main control module, and the tumble alarm method comprises the following steps executed by the main control module: obtaining attitude data collected by the detection module, a falling alarm device is worn on the target object; obtaining a posture data threshold value of the target object determined by the feature information of the target object in advance; and judging whether the attitude data always exceeds an attitude data threshold value of a corresponding moment in a preset time period, if so, judging that the target object falls down, and controlling an alarm module to give an alarm. According to the method, the threshold value is linked with the feature information of the wearer, so that the accuracy of tumble judgment is improved, and meanwhile, the alarm signal can be sent to the outside in time when the elderly tumble accidentally, so that people around can immediately provide necessary help, the injury degree of the elderly is effectively reduced, and the travel safety of the elderly is improved.

The invention relates to an alarm analysis system and method based on chemical industry safety production, and the system comprises an alarm basic ledger, an alarm analysis general collection, and a technology alarm analysis, and specifically comprises the steps: the alarm basic ledger, a terminal device detects the real-time data of a detection point on the device, carries out the recognition and alarm through setting a threshold value, reduces the maintenance workload of the production, and achieves the alarm analysis. Providing data support; an alarm analysis general cable: through analyzing and calculating indexes of peak value alarm, average alarm and disturbance rate, checking evaluation conditions of all alarm devices in a factory, and knowing evaluation change conditions; process alarm analysis is an important link for ensuring production safety and efficient operation in the chemical industry, accidents are prevented, and the production process is optimized. Through real-time monitoring and alarming, abnormal conditions are found and handled in time, accidents are prevented, and property loss and casualties caused by the accidents are reduced.

The invention belongs to the technical field of detection devices, and particularly discloses an electric actuating mechanism thrust detection device which comprises a fixed column, a buffer cavity is formed in the position, close to the edge of one side, of the interior of the fixed column, the inner wall of one side of the buffer cavity penetrates to the outer side of the fixed column, and a movable cavity is formed in the other side of the fixed column. A movable column is arranged between the movable cavity and the buffer cavity, a hexagonal cavity is formed in the movable column, an adjusting part is arranged in the hexagonal cavity, and an alarm device is arranged on the outer surface of the fixed column. According to the invention, through the arrangement of the adjusting member, the alarm device, the feedback assembly and the limiting assembly, when the thrust of the electric actuating mechanism is tested and the thrust of the electric actuating mechanism is greater than the upper limit of the test thrust adjusted by the adjusting member, an alarm is given in time and the equipment is limited at the same time; and damage to equipment caused by continuous forward pushing of the electric actuating mechanism is prevented.

The invention relates to a low-voltage cable with a protection structure applied to the technical field of cables, and the low-voltage cable comprises a low-voltage cable body and an anti-pull-damage protection mechanism, the anti-pull-damage protection mechanism comprises an anti-damage buffer box, a semi-cylindrical curved cable column is movably arranged in the anti-damage buffer box, and a pull detection supporting cylinder is embedded in the anti-damage buffer box in a penetrating manner; the anti-pulling-damage protection mechanism can provide a buffering protection effect for the low-voltage cable body, when the low-voltage cable body is subjected to large pulling force, the low-voltage cable body can be protected to a great extent, the low-voltage cable body is prevented from being deformed and damaged, the anti-pulling-damage protection mechanism further has an alarm function, and when the low-voltage cable body is subjected to large pulling force, the low-voltage cable body is prevented from being damaged. When the low-voltage cable body is pulled, the loss prevention intelligent alarm device starts the alarm to make an alarm sound to warn and remind related personnel and promote the related personnel to stop pulling the low-voltage cable body, so that the low-voltage cable body can be further prevented from being deformed and damaged due to large pulling force, and the safety of the low-voltage cable is greatly improved.

The utility model discloses a grinding device with a machining size in-place alarm, which comprises a lathe, a support plate, a grinding component and a size in-place alarm device, the lathe comprises a rotary clamping device and a displacement component, and the rotary clamping device is used for clamping a part to be machined and driving the part to be machined to rotate around a clamped central shaft; the supporting plate is connected with the displacement assembly, the supporting plate is vertically arranged, the plate face of the supporting plate is perpendicular to the center shaft, and the displacement assembly is used for driving the supporting plate to move. The grinding assembly is arranged on the supporting plate and used for grinding the peripheral side face of the to-be-machined part. The size in-place alarm device comprises a power supply, a transformer, an insulating seat, a fixed seat, an alarm lamp and a measuring metal rod; by arranging the size in-place alarm device, the grinding depth can be preset, an alarm is given after grinding is in place, and the grinding machine is simple in structure, low in manufacturing cost, convenient to operate and high in machining precision.

The invention provides an alarm device based on artificial intelligence voice analysis, and relates to the technical field of voice analysis. An audio acquisition sensor is arranged in a key monitoring area through an audio sensing arrangement module; an environment fluctuation identification module obtains an area environment fluctuation coefficient of the key monitoring area; an alarm threshold configuration module determines a regional alarm threshold based on the regional environment fluctuation coefficient; the abnormal keyword library module traverses the historical voice data record sequence extracted by the historical voice data acquisition module to construct a regional abnormal keyword library; the voice anomaly analyzer module constructs a regional intelligent voice anomaly analyzer based on a regional anomaly keyword library and a regional alarm threshold value; and the anomaly recognition module performs anomaly recognition on the real-time voice data by using the regional intelligent voice anomaly analyzer to obtain alarm information. According to the method and the device, the technical problem of frequent false alarm and missing alarm caused by lack of accurate identification means for audio content in a complex environment in the prior art is solved, and the alarm accuracy and the response speed are improved.