CN119152632B - Combined fire alarm system adopting photoelectric smoke detection and image transmission identification - Google Patents
Combined fire alarm system adopting photoelectric smoke detection and image transmission identification Download PDFInfo
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- G—PHYSICS
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- G08B—SIGNALLING SYSTEMS, e.g. PERSONAL CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
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- G—PHYSICS
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- G08B—SIGNALLING SYSTEMS, e.g. PERSONAL CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B17/00—Fire alarms; Alarms responsive to explosion
- G08B17/10—Actuation by presence of smoke or gases, e.g. automatic alarm devices for analysing flowing fluid materials by the use of optical means
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING SYSTEMS, e.g. PERSONAL CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B17/00—Fire alarms; Alarms responsive to explosion
- G08B17/12—Actuation by presence of radiation or particles, e.g. of infrared radiation or of ions
- G08B17/125—Actuation by presence of radiation or particles, e.g. of infrared radiation or of ions by using a video camera to detect fire or smoke
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- G—PHYSICS
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- G08B—SIGNALLING SYSTEMS, e.g. PERSONAL CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B29/00—Checking or monitoring of signalling or alarm systems; Prevention or correction of operating errors, e.g. preventing unauthorised operation
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- H—ELECTRICITY
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Abstract
The invention relates to the field of fire alarm monitoring and discloses a combined fire alarm system adopting photoelectric smoke detection and image transmission identification, which comprises a dust cover, wherein a dust screen is arranged in the dust screen, a convex lens is arranged in the dust screen, a transparent sheet is arranged on one side of the convex lens, a buzzer is arranged between the convex lens and the transparent sheet, an antenna is connected with an upper cover through the buzzer, a two-dimensional code sticker is arranged on one side, close to the antenna, of the upper cover, a camera module is arranged on the upper cover through double-sided adhesion, a flame module is arranged on the upper cover through double-sided adhesion, and one side of the upper cover is in butt joint with a labyrinth cover. Through photoelectric smoke detection module, temperature sensing module and image transmission recognition module, realize multi-level fire detection and report to the police, rethread intelligent data fusion module, with the data integration analysis of multiple sensor to the different environmental conditions of automatic adaptation improves fire detection's accuracy and timeliness.
Description
Technical Field
The invention relates to the technical field of fire alarm monitoring, in particular to a composite fire alarm system adopting photoelectric smoke detection and image transmission identification.
Background
The existing fire alarm systems generally rely on a series of fixed parameters and thresholds to detect fire, the systems mainly adopt traditional devices such as photoelectric smoke detectors and temperature sensors to identify fire signals by detecting changes of smoke concentration and environmental temperature, the photoelectric smoke detectors detect smoke particles in air by using a scattering principle of light beams, when the smoke particles reach a certain set concentration, the systems trigger alarms, the temperature sensors judge whether fire occurs or not by monitoring rising trend of environmental temperature, and when the temperature exceeds a certain preset threshold, the alarms are activated, the systems have good detection performance under specific environmental conditions, basic fire alarm functions can be provided for many occasions, in addition, the systems are generally integrated in safety infrastructures of buildings, an economic and efficient fire early warning solution is provided, the traditional fire alarm systems are generally simple in design, easy to install and maintain and can adapt to general indoor environments, however, the systems also face technical limitations.
First, in existing fire alarm systems, a single type of sensor (e.g., a photoelectric smoke detector or a temperature sensor) generally cannot provide sufficient fire detection accuracy and timeliness in a complex environment, and these systems may be disturbed by environmental factors such as dust, humidity changes, and temperature fluctuations, resulting in false positives or false negatives, while the signal of the single sensor may be insufficient to accurately identify the occurrence of a fire at an early stage, and conventional systems often rely on a single sensing parameter, and lack comprehensive analysis of multiple fire indications, resulting in limited detection performance;
Second, conventional fire alarm systems typically operate at fixed parameters that are set, lack the ability to adapt to environmental changes, and when environmental conditions such as temperature, humidity, air quality, light conditions, and noise levels change, the sensitivity and response characteristics of the sensor may be affected, resulting in an increased false alarm rate, which makes it difficult for the system to maintain a high level of detection accuracy and reliability;
Finally, in many existing fire alarm systems, fault detection and maintenance usually rely on periodic manual inspection, or repair is performed after a fault occurs, and this passive maintenance mode may cause a fault to be not found in time, thereby affecting the normal operation and detection reliability of the system, in addition, the lack of predictive capability of potential faults also makes preventive maintenance not be effectively performed, increasing the maintenance cost and complexity of the system, and finally, when the hardware of the composite fire alarm system is installed, the hardware of the composite fire alarm system is often directly installed on a wall through bolts, and when the hardware of the composite fire alarm system is used for a long time, the hardware of the composite fire alarm system is difficult to quickly remove due to rusting of the bolts.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a combined fire alarm system adopting photoelectric smoke detection and image transmission identification, which solves the problem that the detection of a single sensor is easy to be limited.
The invention is realized by adopting a photoelectric smoke detection and image transmission identification combined fire alarm system, which comprises:
The anti-dust device comprises a dust cover, wherein a dust screen is integrally formed in the dust cover, an upper cover is integrally formed below the dust cover, a dust screen blocking quality inspection transmitting pipe and a dust screen blocking quality inspection receiving pipe are arranged on the upper cover, the dust screen blocking quality inspection transmitting pipe and the dust screen blocking quality inspection receiving pipe are both positioned between the dust screens, a convex lens is arranged in the upper cover, an optical filter is arranged on one side of the convex lens, and a buzzer is arranged between the convex lens and the optical filter;
the antenna is connected with the upper cover through the buzzer, a two-dimensional code sticker is arranged on one side, close to the antenna, of the upper cover, a camera module is arranged on the upper cover through a double-sided adhesive tape, a flame module is arranged on the upper cover through a double-sided adhesive tape, and one side of the upper cover is in butt joint with the labyrinth cover;
The labyrinth is arranged in the upper cover through the labyrinth cover, a first transmitting pipe and a second transmitting pipe are distributed on one side of the labyrinth at equal intervals, a receiving pipe is arranged between the first transmitting pipe and the second transmitting pipe, a shielding cover is arranged on one side of the receiving pipe, and the shielding cover is used for shielding the position of the receiving pipe;
The PCBA main board is arranged on one side of the labyrinth far away from the labyrinth cover, and battery spring anodes and battery spring cathodes are distributed on one side of the PCBA main board at equal intervals;
The base is connected with the upper cover, a support is fixed inside the base, a battery is mounted inside the support, and a foot pad is fixed on one side, away from the support, of the base.
Preferably, a first locking plate is detachably arranged on the base, a locking member is detachably mounted on the first locking plate, a second locking plate is detachably mounted on the bottom of the locking member, and the locking member comprises:
the locking machine frame is detachably arranged on the first locking plate, an embedded block is detachably arranged in the locking machine frame, and a clamping cavity is formed between the locking machine frame and the embedded block;
The external plug board is slidably arranged in the locking machine frame, a first roller is rotatably arranged at the tail end of the external plug board, an ear board is detachably arranged on the external plug board, a side plug rod is detachably arranged on the ear board, the side plug rod penetrates through the locking machine frame, a connecting spring is also removably sleeved on the side plug rod, the connecting spring is respectively contacted with the ear board and the locking machine frame, and a limiting disc is arranged at one end of the side plug rod penetrating out of the locking machine frame;
The limiting insert ring is detachably arranged on the second locking plate, a blocking block is detachably arranged on the limiting insert ring, a first inclined surface is arranged on the blocking block, a penetrating opening is further formed in the blocking block, the penetrating opening can penetrate into the limiting insert ring, and the penetrating opening can enable the outer insert plate to penetrate through;
The reinforcing plugboard is slidably arranged in the limiting plugboard in a penetrating way, one end of the reinforcing plugboard is initially positioned in the penetrating way, an inclined plate is integrally formed on the reinforcing plugboard, a bonding pad is integrally formed on the inclined plate, a first connecting substrate is detachably arranged on the reinforcing plugboard, and a hanging spring is removably hung on the first connecting substrate;
the second connecting substrate is detachably arranged in the limiting plug ring and is hung by the hanging spring;
the unlocking seat is provided with an unlocking backing plate in an integrated manner on the side surface, a second inclined plane is arranged in the unlocking seat, a cross locking shaft is detachably arranged on the bottom surface of the unlocking seat, the cross locking shaft can sequentially penetrate through the locking machine frame, the limiting insert ring and the embedded block;
The unlocking rod is detachably arranged at one end of the outer plugboard, a second roller is rotatably arranged at the other end of the unlocking rod, and the second roller is positioned above the unlocking base plate;
And the limiting lantern ring is detachably arranged on the locking machine frame and can be used for the unlocking rod to pass through.
Preferably, the PCBA main board comprises a photoelectric smoke detection module, an image transmission identification module, a temperature sensing module, an intelligent data fusion module, a self-diagnosis and calibration mechanism module, an edge calculation and distributed processing module, an environment compensation technology module and a data transmission module;
The photoelectric smoke sensing detection module is used for detecting smoke particles in the air;
The image transmission recognition module is used for capturing images of fire scene and carrying out recognition analysis;
The temperature sensing module is used for monitoring the environmental temperature change;
The intelligent data fusion module is used for integrating various sensor data;
the self-diagnosis and calibration mechanism module is used for maintaining the accuracy and reliability of the system sensor;
The edge computing and distributed processing module is used for improving the real-time response capability of the system;
The environment compensation technology module is used for reducing interference of environment factors on system detection;
The data transmission module is used for realizing efficient transmission of images and data.
Preferably, the photoelectric smoke sensing detection module comprises a light source and receiving unit and a sensitivity adjusting unit:
The light source and the receiving unit are used for detecting smoke scattering through the light beam and judging smoke concentration;
The sensitivity adjustment unit is used for automatically adjusting the sensitivity to adapt to different environmental conditions.
Preferably, the image transmission and identification module comprises a camera capturing unit, an image analysis unit and an image compression and transmission unit;
the camera shooting capturing unit captures fire scene images in real time by using a camera;
The image analysis unit adopts a convolutional neural network algorithm to identify flame and smoke characteristics;
the convolution neural network algorithm formula specifically comprises:
;
Wherein the method comprises the steps of In order to activate the function output,For the convolution kernel weights,In order to input the characteristics of the feature,As a result of the bias term,Is an activation function;
The image compression and transmission unit is used for compressing the image data into a JPEG format and transmitting the image data to the central processing unit through a network.
Preferably, the temperature sensing module comprises a temperature detection unit and a threshold alarm unit;
The temperature detection unit adopts a digital temperature sensor to detect and record the change of the environmental temperature in real time;
the threshold value alarm unit is used for triggering the buzzer to give an alarm when detecting abnormal temperature change, the absolute temperature of the threshold value is set to be higher than 70 ℃, and the abnormal temperature change value exceeds the set threshold value.
Preferably, the intelligent data fusion module comprises a Bayesian network fusion unit, a Kalman filtering processing unit and a dynamic weight adjustment unit;
Bayesian network fusion unit:
The function is that probability analysis is carried out on different sensor data through a Bayesian network;
The Bayesian network algorithm formula is as follows:
;
For given evidence Time hypothesisIs used to determine the posterior probability of (1),To assume thatProof of the followingIs a function of the likelihood of (a),To assume thatIs used to determine the prior probability of (c) for a given channel,Is evidence ofEdge probability of (2);
the Kalman filtering processing unit adopts a Kalman filtering algorithm to dynamically adjust and optimize sensor data;
The specific formula of the Kalman filtering algorithm is as follows:
;
Wherein, In order to predict the state estimate,In order to predict the covariance matrix,In order for the kalman gain to be achieved,For the purpose of observing the quantity,、、The state transition, control and observation matrices are respectively,In order to observe the matrix,、A process noise covariance matrix and an observed noise covariance matrix,Is a matrix of control inputs,Is the control vector of the control signal,Is an identity matrix of the unit cell,Time is;
the dynamic weight adjusting unit automatically adjusts the fusion weight according to the sensor data characteristics.
Preferably, the self-diagnosis and calibration mechanism module comprises a self-diagnosis detection unit, an automatic calibration module and a fault feedback and alarm unit;
the self-diagnosis detection unit is used for continuously monitoring the working state of the sensor and identifying faults and anomalies;
the working state means that the sensor output is stable and within an expected range, the data acquisition and processing are normal, and the self-checking signal feedback is normal;
The fault feedback comprises hardware faults and software faults;
Such anomalies include, but are not limited to, environmental anomalies, signal anomalies, and sensitivity anomalies;
the automatic calibration module is used for automatically executing a sensor calibration process;
The fault feedback and alarm unit is used for giving an alarm to a user when a fault is detected.
Preferably, the edge computing and distributed processing module comprises an edge computing node unit, a distributed processing architecture and a real-time response module;
the edge computing node unit is used for carrying out local data processing on the sensor node;
The distributed processing architecture is used for realizing data processing of multi-node cooperation;
the real-time response module is used for optimizing data processing and decision speed.
Preferably, the environmental compensation technical module comprises an environmental characteristic learning unit, an automatic compensation unit and an environmental monitoring and adjusting unit;
The environmental characteristic learning unit analyzes and stores environmental characteristic data by utilizing a random forest model;
the random forest model building and training comprises the following steps:
s1, data collection and preparation, namely continuously collecting data from various sensors (temperature, humidity, air quality, illumination and noise), processing missing data, abnormal values and noise, ensuring the data quality, and finally determining key environmental characteristics related to fire detection;
s2, establishing a model, namely selecting a random forest as an environmental characteristic learning model, dividing a data set into a training set, a verification set and a test set (such as 70% training, 15% verification and 15% test), and setting parameters of the random forest such as the number and the maximum depth of trees;
S3, training a random forest model by using training set data, optimizing model parameters by using a cross verification method (such as K-fold cross-validation) to prevent over fitting, and finally identifying the features with the greatest influence on output by feature importance analysis in the training process;
S4, evaluating the performance of the model on a test set, using indexes such as accuracy, recall and F1-score, then adjusting model parameters according to evaluation results, further improving model accuracy, and finally integrating the trained model into an environmental characteristic learning unit for analyzing and updating environmental characteristic data in real time;
The environmental characteristics include temperature, humidity, air quality, lighting conditions, airflow rate, and noise level;
The automatic compensation unit is used for dynamically adjusting the output of the sensor according to the environmental characteristic library;
the environment monitoring and adjusting unit is used for monitoring environment changes in real time and automatically adjusting system parameters according to requirements;
the data transmission module comprises a wired transmission unit, a wireless transmission unit and a data compression and encryption unit;
The wired transmission unit performs data transmission through optical fiber or Ethernet;
the wireless transmission module performs wireless data transmission by utilizing Wi-Fi, bluetooth or Zigbee;
The data compression and encryption unit is used for compressing and encrypting data.
The invention provides a composite fire alarm system adopting photoelectric smoke detection and image transmission identification, which has the following beneficial effects:
1. Through the whole arranged locking component, firstly, the unlocking seat needs to be lifted to move upwards so that the cross locking shaft penetrates out of the locking machine frame from the inner embedded block, the limiting insert ring and the locking machine frame in sequence, in the process of moving upwards the unlocking seat, the second inclined plane integrally moves upwards, and as the second inclined plane is mutually attached with the second roller, the second roller can be synchronously pushed to translate rightwards in the process of moving upwards the second inclined plane, and simultaneously the unlocking rod slides in the limiting sleeve ring, so that the unlocking rod is prevented from shaking leftwards and rightwards and being unstable when being pushed by the second inclined plane, and meanwhile, after being blocked by the unlocking base plate, the unlocking seat can be effectively prevented from being completely separated from the second roller, and as the unlocking rod is connected with the outer insert plate, after the cross locking shaft is positioned in the vertical direction, the outer plugboard can be driven to move rightward simultaneously, so that the first idler wheel is integrally withdrawn from the limiting plug ring, the bonding pad is simultaneously positioned for removing the embedded block, the positioning of the outer plugboard to the limiting plug ring is also removed, the limiting plug ring is pulled to separate the limiting plug ring from the locking machine frame, the base can be quickly taken off from the wall when the base is connected with the wall through the arranged locking component, the integrated combined fire alarm system hardware adopting photoelectric smoke detection and image transmission identification is convenient to mount and dismount, and the combined fire alarm system hardware adopting photoelectric smoke detection and image transmission identification is convenient to mount, dismount and maintain.
2. The invention realizes multi-level fire detection and alarm through the photoelectric smoke detection module, the temperature sensing module and the image transmission identification module, and integrates and analyzes the data of various sensors through the intelligent data fusion module, thereby automatically adapting to different environmental conditions and improving the accuracy and timeliness of fire detection.
3. According to the invention, the sensor output is dynamically adjusted according to the real-time environmental data through the automatic compensation unit, and the environmental monitoring and adjusting unit automatically adjusts the system parameters according to the monitored environmental change, so that the self-adaptive compensation of the environmental change is realized, and the detection precision and reliability are improved.
4. The invention analyzes the historical fault data and predicts the potential faults through the self-diagnosis and calibration mechanism module, and the mechanism not only can rapidly alarm when the faults occur, but also can predict the time and the position of the faults possibly occurring in advance, thereby arranging preventive maintenance and improving the reliability and the maintenance efficiency of the whole fire alarm system.
Drawings
FIG. 1 is an exploded view of the hardware of a combined fire alarm system for photo-induced smoke detection and image transmission recognition of the present invention;
FIG. 2 is a schematic diagram of the hardware combination of the combined fire alarm system for photoelectric smoke detection and image transmission recognition according to the present invention;
FIG. 3 is a schematic diagram of a combined fire alarm system hardware combination for photoelectric smoke detection and image transmission recognition from another perspective;
FIG. 4 is a schematic view of the overall structure of the locking member of the present invention;
FIG. 5 is a schematic view showing the structure of the spacing insert ring and the blocking piece of the present invention when combined;
FIG. 6 is a schematic view of the combination of the stop collar and the stop block from another perspective;
FIG. 7 is a schematic view of a locking frame and an external board of the present invention;
FIG. 8 is an exploded view of the structure of the present invention when the locking frame is connected to the external plug board;
FIG. 9 is a schematic diagram of a PCBA board system module in accordance with the present invention;
FIG. 10 is a schematic diagram of a photoelectric smoke detection module according to the present invention;
FIG. 11 is a schematic diagram of an image transmission identification module according to the present invention;
FIG. 12 is a schematic diagram of a temperature sensing module according to the present invention;
FIG. 13 is a schematic diagram of an intelligent data fusion module according to the present invention;
FIG. 14 is a schematic diagram of a self-diagnostic and calibration mechanism module according to the present invention;
FIG. 15 is a schematic diagram of an edge computing and distributed processing module according to the present invention;
FIG. 16 is a schematic diagram of an environmental compensation technique module according to the present invention;
fig. 17 is a schematic diagram of a data transmission module according to the present invention.
The dustproof cover 1, the dustproof cover 2, the dustproof net 3, the convex lens 4, the optical filter 5, the buzzer, the antenna 6, the antenna 7, the two-dimensional code sticker 8, the upper cover 9, the camera module 10, the flame module 11, the double-sided sticker 1, the double-sided sticker 2, the double-sided sticker 13, the labyrinth cover 14, the labyrinth 15, the first transmitting pipe 16, the second transmitting pipe 17, the receiving pipe 18, the shielding cover 19, the battery spring positive pole 20, the battery spring negative pole 21, the PCBA main board 22, the battery 23, the support 24, the base, the 25, the foot pad 26, the first locking plate 27, the second locking plate 28, the locking member 281, the locking machine frame 282, the inner embedding block 283, the outer embedding plate 284, the first roller 285, the ear plate 286, the side inserting rod 287, the connecting spring 288, the limiting inserting ring 289, the limiting inserting ring 2810, the blocking block 1, the first inclined plane, the second inclined plane 2, the penetrating opening 3, the reinforcing, the cross-shaped board 2814, the foot pad 2816, the first locking plate 2817, the second locking plate 289, the unlocking sleeve 289, the second locking plate 2818, the second locking plate 289, the unlocking sleeve 289, the locking plate 289.
Detailed Description
The following description of the embodiments of the present invention will be made more apparent and fully hereinafter with reference to the accompanying drawings, in which some, but not all embodiments of the invention are shown. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Examples:
referring to fig. 1 to 8, an embodiment of the present invention provides a composite fire alarm system using photoelectric smoke detection and image transmission recognition, including:
The anti-dust cover 1 is internally provided with a dust screen 2 in an integrated manner, an upper cover 8 is integrally formed below the anti-dust cover 1, a dust screen blocking quality inspection transmitting pipe and a dust screen blocking quality inspection receiving pipe are arranged on the upper cover 8, the dust screen blocking quality inspection transmitting pipe and the dust screen blocking quality inspection receiving pipe are both positioned between the dust screen 2, a convex lens 3 is arranged in the upper cover 8, an optical filter 4 is arranged on one side of the convex lens 3, and a buzzer 5 is arranged between the convex lens 3 and the optical filter 4;
The antenna 6 is connected with the upper cover 8 through the buzzer 5, a two-dimensional code sticker 7 is arranged on one side, close to the antenna 6, of the upper cover 8, the upper cover 8 is provided with a camera module 9 through a double-sided tape I11, the upper cover 8 is provided with a flame module 10 through a double-sided tape II 12, and one side of the upper cover 8 is butted with the labyrinth cover 13;
The labyrinth 14 is arranged in the upper cover 8 through the labyrinth cover 13, a first transmitting pipe 15 and a second transmitting pipe 16 are equidistantly distributed on one side of the labyrinth 14, a receiving pipe 17 is arranged between the first transmitting pipe 15 and the second transmitting pipe 16, a shielding cover 18 is arranged on one side of the receiving pipe 17, and the shielding cover 18 is used for shielding the position of the receiving pipe 17;
the PCBA main board 21 is arranged on one side of the labyrinth 14 far away from the labyrinth cover 13, and battery spring anodes 19 and battery spring cathodes 20 are distributed on one side of the PCBA main board 21 at equal intervals;
The base 24 is connected with the upper cover 8, a support 23 is fixed in the base 24, a battery 22 is arranged in the support 23, and a foot pad 25 is fixed on one side of the base 24 away from the support 23;
Next, the optical filter 4 is explained more specifically, firstly, the optical filter 4 is of a model of 850nm, the visible light below 850nm is shielded and filtered, the privacy of photographing cannot be leaked, and when the flame light above 850nm passes through the optical filter 4, the flame light is captured, photographed and imaged;
When the hardware of the combined fire alarm system for photoelectric smoke detection and image transmission identification is installed on site, an initial pass rate value of a dust screen is formed, when equipment periodically sends heartbeat packets, the equipment is carried out every two weeks, light waves are emitted by a dust screen blocking quality inspection emission tube, and the light waves are finally received by a dust screen blocking quality inspection receiving tube through the dust screen;
of course, in other embodiments, the pass rate value may be set according to the actual situation, for example, between eighty percent and sixty percent, and of course, other pass rate values are also possible.
In order to further facilitate the further rapid mounting and dismounting of the entire base 24, a more specific structure and construction is then provided for the closure member 28 as a whole for further explanation, a first locking plate 26 is also detachably arranged on the base 24, a closure member 28 is detachably mounted on the first locking plate 26, a second locking plate 27 is detachably mounted on the bottom of the closure member 28, the closure member 28 comprises a closure frame 281, which is detachably mounted on the first locking plate 26, an inner insert 282 is detachably mounted in the closure frame, a clamping cavity is formed between the inner insert 282, an outer insert 283 is slidably arranged in the closure frame 281, a first roller 284 is rotatably arranged at a tail end of the outer insert 283, an ear plate 285 is detachably arranged on the outer insert, a side insert 286 is detachably arranged on the ear plate 285, a side insert 286 is detachably mounted in the closure frame 281, a connecting spring is also detachably sleeved on the side insert 286, a contact ring 287 is detachably mounted on the inner insert 2892, a contact ring 2892 is integrally provided with the inner insert 2892, a stop ring 2892 is integrally provided on the inner insert 2892, a stop ring 2892 is integrally formed on the inner insert 2892, a stop ring 2892 is integrally provided on the inner insert 2892, a stop plate is integrally provided on the inner insert 2892, and a stop plate is integrally provided on the inner insert 2892 is integrally formed on the inner insert 2892, the reinforced plugboard 2813 is also detachably provided with a first connecting base plate 2816, a hanging spring 2818 is removably hung on the first connecting base plate 2816, a second connecting base plate 2817 is detachably arranged in a limit plug-in ring 289 and is hung by the hanging spring 2818, an unlocking base 2819 is integrally formed on the side surface of the unlocking base 2819, an unlocking base plate 2820 is integrally formed in the side surface of the unlocking base 2819, a second inclined surface 2821 is arranged in the unlocking base plate, a cross locking shaft 2822 is detachably arranged on the bottom surface of the unlocking base plate, the cross locking shaft 2822 can sequentially penetrate through a locking machine frame 281, the limit plug-in ring 289 and an inner insert 282, an unlocking rod 2823 is detachably arranged on one end of an outer plug-in plate 283, a second roller 2824 is rotatably arranged on the other end of the unlocking base plate 2820, and a limit sleeve ring 2825 is detachably arranged on the locking machine frame 281 and can enable the unlocking rod 2823 to penetrate through;
In further explaining the principle of quick assembly and disassembly of the whole base 24 and the wall, a worker firstly installs the second locking plate 27 on the pre-installation plane, and needs to say that the limiting insert ring 289 is connected with the second locking plate 27, so that in the process of pushing the limiting insert ring 289 into the locking machine frame 281, the limiting insert ring 289 firstly penetrates into a clamping cavity formed by the locking machine frame 281 and the inner insert 282, meanwhile, the inner insert 282 can also penetrate into the limiting insert ring 289, in the process of pushing the limiting insert ring 289 into the locking machine frame 281, firstly, the outer insert plate 283 and the first roller 284 move on the first inclined plane 2811, and in the process of sliding the first roller 284 into the limit position of the first inclined plane 2810, when the first roller 284 and the outer insert plate 283 slide into the through hole 2812, the outer insert plate 283 rapidly enters into the through hole 2812, and positioning of the limiting insert ring 2810 is completed;
Meanwhile, after the outer insert plate 283 rapidly enters the through hole 2812 to position the limit insert ring 289, the reinforcement insert plate 2813 is triggered to work, after the outer insert plate 283 enters the through hole 2812, the reinforcement insert plate 2813 is driven to move forwards, meanwhile, the hanging spring 2818 is driven to stretch, so that the attaching pad 2815 clamps and stabilizes the inner insert block 282, the limit insert ring 289 and the blocking block 2810 can be positioned on the whole outer insert plate 283, the inner insert block 282 can be synchronously positioned, the limit insert ring 289 is pushed into a clamping cavity, the inner insert block 282 penetrates into the limit insert ring 289, the inner insert block 282 is clamped and positioned inside and outside, the unlocking seat 2819 drives the cross locking shaft 2822 to sequentially penetrate into the locking machine frame 281, the limit insert ring 289 and the inner insert block 282, and the cross locking shaft 2822 is in a cross shape, and the cross locking shaft 2822 can be further contacted with the limit insert ring 289 and the whole locking machine frame 289, and the whole locking machine frame 28282 can be contacted with each other;
When the spacing lock ring 289 is unlocked, firstly, the unlocking seat 2819 needs to be lifted to move upwards, so that the cross locking shaft 2822 sequentially moves from the inner embedded block 282, the spacing lock ring 289, the locking machine frame 281 penetrates out, in the process of moving upwards the unlocking seat 2819, the second inclined plane 2821 integrally moves upwards, as the second inclined plane 2821 is mutually attached to the second roller 2824, in the process of moving upwards the second inclined plane 2821, the second roller 2824 can be synchronously pushed to move rightwards, meanwhile, the unlocking rod 2823 slides in the spacing sleeve 2825, so that the situation that the unlocking rod 2823 shakes left and right and is unstable when being pushed by the second inclined plane 2821 is prevented, meanwhile, after being blocked by the unlocking plate 2820, the unlocking seat 2819 is effectively prevented from completely separating from the second roller 2824, and as the unlocking rod 2823 is connected with the outer plug plate 283, after the cross locking shaft 2822 is positioned in the upper and lower directions, the whole can simultaneously move upwards, the locking plate 2825 can simultaneously move outwards, and the whole plug ring 289 can be pulled out of the inner embedded block 289, and the whole wall can be simultaneously, and the spacing lock ring 289 can be removed from the wall by the spacing sleeve 289, and the whole plug ring 289 can be simultaneously, and the spacing sleeve 289 can be simultaneously pulled from the wall by the spacing sleeve 289.
In other embodiments, in order to further solve the problem of dust environmental pollution of the labyrinth darkroom of the smoke sensor, a micro motor or other micro vibration device can be installed in the base, and dust particles attached to the surface of the photoelectric emission and receiving tube are loosened and fall off by generating micro vibration inside the smoke sensor, and the micro vibration can shake the dust off the surface and discharge the dust outside the sensor through air flow. Compared with vibration modes such as an ion generator, the energy required by micro vibration is low, and the overall power consumption of the device is not increased remarkably. The micro vibration can not generate ozone or other harmful substances, and is harmless to the environment and human body.
The PCBA motherboard 21 includes a photo-induced smoke detection module, an image transmission recognition module, a temperature sensing module, an intelligent data fusion module, a self-diagnosis and calibration mechanism module, an edge calculation and distributed processing module, an environmental compensation technology module, and a data transmission module;
the photoelectric smoke detection module is used for detecting smoke particles in the air;
the image transmission recognition module is used for capturing images of fire scene and carrying out recognition analysis;
the temperature sensing module is used for monitoring the environmental temperature change;
The intelligent data fusion module is used for integrating various sensor data;
The self-diagnosis and calibration mechanism module is used for maintaining the accuracy and reliability of the system sensor;
the edge computing and distributed processing module is used for improving the real-time response capability of the system;
the environment compensation technology module is used for reducing interference of environment factors on system detection;
The data transmission module is used for realizing efficient transmission of images and data.
Specifically, the dust cover 1 and the dust screen 2 protect the internal components from dust and other particulate matters, meanwhile, the definition of the optical components is ensured, the convex lens 3 is used for focusing the optical signals from the fire scene and transmitting light through the transparent sheet 4, the buzzer 5 is positioned between the convex lens 3 and the transparent sheet 4, when abnormal conditions are detected, the buzzer 5 gives out an acoustic alarm, the antenna 6 is connected with the upper cover 8 through the buzzer 5 and is used for sending and receiving wireless signals so as to realize remote monitoring and data transmission, the upper cover 8 is provided with the camera module 9 and the flame module 10 which are fixed through the double-sided tape 11 and the double-sided tape 12, the modules are respectively used for capturing and analyzing fire images and monitoring flame signals and transmitting the data to the PCBA main board 21 for further processing, the labyrinth 14 structure is arranged inside the upper cover 8 through the labyrinth cover 13, the first and second transmitting tubes 15 and 16 alternately transmit light signals, the receiving tube 17 receives and detects signal changes caused by smoke or obstacles, the shielding cover 18 positions and shields the receiving tube 17 to prevent the interference of ambient light, when the smoke passes through the maze 14, the photoelectric smoke detection module detects smoke particles in the air and activates the alarm process, meanwhile, the image transmission recognition module captures the fire scene image and carries out real-time recognition analysis, if the fire image or smoke concentration exceeds a set threshold value, the temperature change information monitored by the temperature sensing module is transmitted to the intelligent data fusion module, the module integrates smoke, image and temperature data to carry out comprehensive judgment, the self-diagnosis and calibration mechanism module continuously monitors and calibrates the sensor in the whole process to ensure the accuracy and reliability of the data, the edge calculation and distributed processing module carries out real-time processing on the data, the system response speed is improved, the interference of environmental factors is reduced through an environmental compensation technology module, finally, the processed images and data are transmitted in a high-efficiency wireless mode through the antenna 6 by the data transmission module, the processed images and data are sent to a remote monitoring center or a cloud platform for further processing and response, the whole system is powered by a battery 22 in a base 24, the battery spring positive electrode 19 and the battery spring negative electrode 20 ensure continuous supply of power, the battery spring positive electrode and the battery spring negative electrode 20 are fixed through a support 23, and the foot pad 25 provides stability and anti-skid effects of equipment.
Referring to fig. 10 to 12, the photoelectric smoke detection module includes a light source and receiving unit and a sensitivity adjustment unit:
The light source and the receiving unit are used for detecting smoke scattering through the light beam and judging smoke concentration;
the sensitivity adjusting unit is used for automatically adjusting the sensitivity to adapt to different environmental conditions;
the image transmission recognition module comprises a camera capturing unit, an image analysis unit and an image compression and transmission unit;
the camera shooting capturing unit captures a fire scene image in real time by using a camera;
the image analysis unit adopts a convolutional neural network algorithm to identify flame and smoke characteristics;
The convolution neural network algorithm formula specifically comprises:
;
Wherein the method comprises the steps of In order to activate the function output,For the convolution kernel weights,In order to input the characteristics of the feature,As a result of the bias term,For activating the function, directly outputting when the input is greater than 0, otherwise outputting 0;
The image compression and transmission unit is used for compressing the image data into a JPEG format and transmitting the image data to the central processing unit through a network;
the temperature sensing module comprises a temperature detection unit and a threshold alarm unit;
The temperature detection unit adopts a digital temperature sensor to monitor and record the change of the environmental temperature in real time;
The threshold value alarm unit is used for triggering the buzzer 5 to give an alarm when detecting abnormal temperature change, and the absolute temperature of the threshold value is set to be higher than 70 ℃, and the abnormal temperature change value exceeds the set threshold value.
The image transmission recognition module consists of a camera capturing unit, an image analysis unit and an image compression and transmission unit, wherein the camera is responsible for capturing fire scene images in real time, the image analysis unit recognizes flame and smoke characteristics by utilizing a convolutional neural network algorithm, the analyzed images are compressed by a JPEG format and then transmitted to a core for processing, the temperature sensing module comprises a temperature detection unit and a threshold alarm unit, a digital temperature sensor such as DS18B20 is adopted for monitoring and recording the ambient temperature in real time, when the absolute temperature is higher than 70 ℃, the threshold alarm unit triggers an alarm, the photoelectric smoke detection provides preliminary smoke alarm, the image recognition verifies the accuracy of the alarm, the temperature monitoring provides additional safety guarantee, and finally multiple detection results are transmitted to a distributed processing architecture by the compression and transmission unit, so that whether faults occur or not is determined by double image recognition and temperature recognition.
Referring to fig. 13-15, the intelligent data fusion module includes a bayesian network fusion unit, a kalman filter processing unit and a dynamic weight adjustment unit;
Bayesian network fusion unit:
The function is that probability analysis is carried out on different sensor data through a Bayesian network;
the Bayesian network algorithm formula is:
;
For given evidence Time hypothesisIs used to determine the posterior probability of (1),To assume thatProof of the followingIs a function of the likelihood of (a),To assume thatIs used to determine the prior probability of (c) for a given channel,Is evidence ofEdge probability of (2);
the Kalman filtering processing unit adopts a Kalman filtering algorithm to dynamically adjust and optimize the sensor data;
The specific formula of the Kalman filtering algorithm is as follows:
;
Wherein, In order to predict the state estimate,In order to predict the covariance matrix,In order for the kalman gain to be achieved,For the purpose of observing the quantity,、、The state transition, control and observation matrices are respectively,In order to observe the matrix,、A process noise covariance matrix and an observed noise covariance matrix,Is a matrix of control inputs,Is the control vector of the control signal,Is an identity matrix of the unit cell,Time is;
The dynamic weight adjusting unit automatically adjusts the fusion weight according to the data characteristics of the sensor;
The self-diagnosis and calibration mechanism module comprises a self-diagnosis detection unit, an automatic calibration module and a fault feedback and alarm unit;
the self-diagnosis detection unit is used for continuously monitoring the working state of the sensor and identifying faults and anomalies;
The working state means that the sensor output is stable and within an expected range, the data acquisition and processing are normal, and the self-checking signal feedback is normal;
Fault feedback includes hardware faults and software faults;
anomalies include, but are not limited to, environmental anomalies, signal anomalies, and sensitivity anomalies;
The automatic calibration module is used for automatically executing a sensor calibration process;
The fault feedback and alarm unit is used for giving an alarm to a user when a fault is detected;
the edge computing and distributed processing module comprises an edge computing node unit, a distributed processing architecture and a real-time response module;
The edge computing node unit is used for carrying out local data processing on the sensor node;
the distributed processing architecture is used for realizing data processing of multi-node cooperation;
the real-time response module is used for optimizing the data processing and decision making speed.
Specifically, the Bayesian network fusion unit judges the possibility of fire disaster by carrying out probability analysis on different sensor data so as to improve the accuracy of data fusion; the Kalman filtering processing unit dynamically adjusts and optimizes sensor data, filters noise and abnormal fluctuation, ensures stability and accuracy of the data, automatically adjusts fusion weights according to changes of sensor data characteristics, enables contribution of data of each sensor to overall judgment to dynamically change according to actual conditions, continuously monitors working states of the sensors, ensures stable output of the sensors, ensures normal data acquisition and processing, self-checking signal feedback, timely identifies hardware faults (such as signal loss or circuit problems) and software faults (such as data processing errors), simultaneously identifies environment anomalies (such as temperature change and electromagnetic interference), signal anomalies (such as excessive noise) and sensitivity anomalies (such as sensitivity reduction), automatically executes a calibration process according to preset periods or detected anomalies, ensures accuracy and consistency of the sensors, immediately sends an alarm to inform users when the fault feedback and alarm unit detects the faults, and the edge computing node unit is responsible for carrying out data processing on each sensor node, reduces delay of data transmission, reduces the central processing, and improves the response of the data processing system through a plurality of distributed data processing systems through the coordination system, and the system can respond to the data processing system in real time by optimizing the data processing system, and the system has the data processing system has the advantages of being capable of optimizing the response and the data processing system, the high-efficiency operation and accurate monitoring of the fire alarm system are realized, and stable and reliable fire detection and alarm service is ensured to be provided in changeable and complex environments.
Referring to fig. 16-17, the environmental compensation technical module includes an environmental feature learning unit, an automatic compensation unit and an environmental monitoring and adjusting unit;
the environmental characteristic learning unit analyzes and stores environmental characteristic data by using a random forest model;
The random forest model building and training comprises the following steps:
s1, data collection and preparation, namely continuously collecting data from various sensors (temperature, humidity, air quality, illumination and noise), processing missing data, abnormal values and noise, ensuring the data quality, and finally determining key environmental characteristics related to fire detection;
s2, establishing a model, namely selecting a random forest as an environmental characteristic learning model, dividing a data set into a training set, a verification set and a test set (such as 70% training, 15% verification and 15% test), and setting parameters of the random forest such as the number and the maximum depth of trees;
S3, training a random forest model by using training set data, optimizing model parameters by using a cross verification method (such as K-foldcross-verification) to prevent overfitting, and finally identifying the characteristics with the greatest influence on output by characteristic importance analysis in the training process;
S4, evaluating the performance of the model on a test set, using indexes such as accuracy, recall and F1-score, then adjusting model parameters according to evaluation results, further improving model accuracy, and finally integrating the trained model into an environmental characteristic learning unit for analyzing and updating environmental characteristic data in real time;
Environmental characteristics include temperature, humidity, air quality, lighting conditions, airflow rate, and noise level;
the automatic compensation unit is used for dynamically adjusting the output of the sensor according to the environmental characteristic library;
The environment monitoring and adjusting unit is used for monitoring environment changes in real time and automatically adjusting system parameters according to requirements;
The data transmission module comprises a wired transmission unit, a wireless transmission unit and a data compression and encryption unit;
the wired transmission unit performs data transmission through optical fiber or Ethernet;
The wireless transmission module performs wireless data transmission by utilizing Wi-Fi, bluetooth or Zigbee;
The data compression and encryption unit is used for compressing and encrypting data.
The method comprises the steps of analyzing and storing key environmental characteristic data by an environmental characteristic learning unit through a random forest model, wherein the characteristics comprise temperature, humidity, air quality, illumination condition, air flow rate and noise level, establishing and training of the random forest model comprises four steps of firstly collecting and preparing data, guaranteeing that the data acquired from a sensor are processed and then are reliable in quality, identifying key characteristics related to fire detection, secondly, dividing a data set into training, verifying and testing sets and setting model parameters by a model establishing link, then conducting model training, guaranteeing generalization capability of the model through cross verification optimization parameters, simultaneously identifying the characteristics with the greatest influence on output, finally evaluating the model on the testing set, verifying the performance of the model through indexes such as accuracy, recall rate and F1-score, dynamically adjusting the output of the sensor according to the environmental characteristic database updated in real time by an automatic compensation unit, accordingly monitoring and adjusting the parameters of the system in real time, effectively transmitting a line, compressing and transmitting data by a wireless transmission unit, ensuring that the data is compressed by a wireless transmission condition or the wireless transmission condition is not required by a wireless transmission system, and the data compression condition is required to be more tightly compressed by a wireless transmission unit, and the wireless transmission condition is met, the data transmission condition is not required to be compressed and the wireless condition is met, and the data transmission condition is required to be compressed and is compressed and compressed by the wireless transmission condition is required to be more than the data is compressed and is compressed, and is compressed and is safe, meanwhile, the efficiency and the safety of data transmission are ensured, and comprehensive support is provided for fire detection and alarm.
Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
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| CN117542174A (en) * | 2023-10-30 | 2024-02-09 | 福建防护家科技有限公司 | Fire detection alarm based on Internet of things environment sampling intelligent algorithm and system thereof |
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