CN112437165A - Remote monitoring type real-time monitoring system and method for detection workflow - Google Patents
Remote monitoring type real-time monitoring system and method for detection workflow Download PDFInfo
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Abstract
The invention relates to a remote monitoring type real-time monitoring system and a method for detecting a working process, which comprises field monitoring terminals, field data processing terminals, intelligent communication gateways, a data communication network and a monitoring platform based on a convolutional neural network system. The using method comprises three steps of system networking, monitoring operation, data analysis and the like. On one hand, the invention can effectively meet the requirements of various environments and different detection operation activities, and has good universality; on the other hand, the monitoring and identifying operation of the detection working quality can be accurately realized, the working behavior state of the working personnel is pre-judged and analyzed, and the alarm prompt is timely carried out on the abnormal state of the target object.
Description
Technical Field
The invention relates to a remote monitoring type real-time monitoring system and a method for detecting a working process, belonging to the technical field of video signal processing and data communication.
Background
At present, in activities and works such as industrial and agricultural production, daily inspection and the like, corresponding detection work needs to be carried out on specific articles and personnel through detection procedures, particularly in the detection of biological medicines, food processing and important electromechanical products, the detection process is relatively complex, although the prior art has more sound detection means and perfect detection management system and means, however, in practical work, it is found that currently, during the detection work, a comprehensive and effective remote monitoring means is lacked, the whole-course accurate monitoring operation of detection workers, detection work content and the like cannot be realized, thereby causing the lack of effective monitoring of the detection work and failing to find operation holes and defects existing in the detection work in time, therefore, the current detection and supervision work difficulty is high, the detection efficiency and precision of the detection work quality are poor, and great hidden dangers exist in production and management activities.
Therefore, in view of the current situation, it is urgently needed to develop a universal remote monitoring system for detecting work so as to meet the needs of actual work.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a remote monitoring type real-time monitoring system and a method for detecting a working process, so as to achieve the purpose of use in actual use work.
In order to achieve the purpose, the invention is realized by the following technical scheme:
a remote monitoring type real-time monitoring system for detecting work flow comprises a field monitoring terminal, a field data processing terminal, an intelligent communication gateway, a data communication network and a monitoring platform based on a convolutional neural network system, at least one field data processing terminal, each field data processing terminal is connected with a plurality of field monitoring terminals through an intelligent communication gateway to form a working group, the intelligent communication gateway of each working group establishes data connection with a monitoring platform based on a convolutional neural network system through a data communication network, and the intelligent communication gateways between the working groups are mutually connected to form at least one monitoring local area network, the on-site monitoring terminal and the on-site data processing terminal are positioned at the detection working site, the system is electrically connected with a power supply system of a detection working site, and the site monitoring terminals are uniformly distributed along the direction of a detection working flow; the on-site monitoring terminal comprises a bearing rack, a driving guide rail, a detection head, a sliding block, a rotary table mechanism, a video monitoring device, a human body sensor and a driving circuit, wherein the rear end face of the bearing rack is connected with a building, the axis of the bearing rack is distributed in parallel with the direction of a detection working line, the driving guide rail is embedded in the front end face of the bearing rack and is distributed in parallel with the axis of the bearing rack, at least one detection head is connected with the driving guide rail in a sliding mode through the sliding block, the rear end face of the detection head is hinged with the front end face of the sliding block through the rotary table mechanism, the detection head is located at least 20 cm above a detection working face, the detection head is of a closed cavity structure with a rectangular axial section, the video monitoring device and the human body sensor are embedded in the outer surface of the detection head, the axis of the video monitoring device and the, The turntable mechanism, the video monitoring device and the human body sensor are electrically connected, and data communication connection is established between the turntable mechanism, the video monitoring device and the human body sensor and the intelligent communication gateway.
Furthermore, the monitoring platform based on the convolutional neural network system is one or two of a BP neural network system and a CNN neural network, and an LSTM-based intelligent prediction system, a deep learning subsystem of the deep learning neural network system and an image recognition system are additionally arranged in the monitoring platform based on the convolutional neural network system.
Furthermore, the field data processing terminal is a circuit system based on any one or two of an industrial computer and an internet-of-things controller, and is provided with at least one serial port communication circuit.
Furthermore, the driving circuit comprises a circuit system based on an FPGA chip, a data communication bus, an MOS driving circuit, an I/O communication circuit, a crystal oscillator clock circuit, a voltage stabilizing circuit, a serial communication circuit and a wiring terminal, wherein the circuit system based on the FPGA chip is electrically connected with the data communication bus and the voltage stabilizing circuit, the data communication bus is further electrically connected with the MOS driving circuit, the I/O communication circuit, the crystal oscillator clock circuit, the voltage stabilizing circuit and the serial communication circuit, the MOS driving circuit is further electrically connected with the I/O communication circuit and the voltage stabilizing circuit respectively, and the voltage stabilizing circuit, the I/O communication circuit and the serial communication circuit are electrically connected with the wiring terminal.
Furthermore, the video monitoring device comprises a base, a CCD camera, a 3D camera and an auxiliary illuminating lamp, wherein the 3D camera and the CCD camera are symmetrically distributed on two sides of the auxiliary illuminating lamp, the rear end faces of the CCD camera, the 3D camera and the auxiliary illuminating lamp are connected with the front end face of the base, and optical axes of the CCD camera, the 3D camera and the auxiliary illuminating lamp are distributed in parallel and are vertically distributed with the front end face of the base.
A use method of a remote monitoring type detection workflow real-time monitoring system comprises the following steps;
s1, system networking, assembling the site monitoring terminal, the site data processing terminal, the intelligent communication gateway, the data communication network and the monitoring platform based on the convolutional neural network system, wherein the monitoring platform based on the convolutional neural network system is arranged in a main monitoring room, the site monitoring terminal and the site data processing terminal are arranged on a detection working site, the intelligent communication gateway is respectively arranged in the detection working site and the main monitoring room, and finally, the site monitoring terminal, the site data processing terminal, the intelligent communication gateway and the monitoring platform based on the convolutional neural network system establish data connection through the data communication network, thereby completing the networking assembly of the invention;
s2, monitoring operation, after the step S1 is completed, when a worker performs detection operation, firstly, the position of the worker is detected through a human body sensor on the site monitoring terminal, the detection head is adjusted to the working position of the worker through the driving guide rail, then, a video monitoring device of the detection head performs face recognition on the worker on one hand to complete identity recognition operation, and performs whole-course monitoring on the working process of the worker on the other hand, and feeds a monitoring result back to a monitoring platform based on a convolutional neural network system;
and S3, analyzing the data, transmitting the data acquisition image obtained in the step S2 to a monitoring platform based on big data, matching the acquired identity of the worker with the work content and the work habit of the worker by a convolutional neural network system to meet the requirement of accurate monitoring of detection operation, deeply learning the work habit of the worker by an intelligent prediction system and a deep learning neural network system based on LSTM to obtain the daily work behavior habit parameters of the worker for later use, and comparing the behavior habit parameters with the field work state of the worker to timely find the abnormal work state condition of the worker, thereby timely finding work errors and work accident conditions, alarming and correcting.
On one hand, the system has simple structure, flexible and convenient use, good universality and convenient system construction and maintenance, can effectively meet the use requirements of various environments and different detection operation activities, and can simultaneously realize the requirement of multi-machine cooperative operation in a large area range; on the other hand, the operation data processing capacity is high, the monitoring operation is met, meanwhile, the monitoring and identifying operation on the detection working quality can be accurately realized, the working behavior state of a worker is pre-judged and analyzed, and the alarm prompt is timely carried out on the abnormal state of the target object, so that the convenience, the reliability and the flexibility of the detection working monitoring operation are greatly improved.
Drawings
The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.
FIG. 1 is a schematic diagram of the system of the present invention;
FIG. 2 is a schematic structural diagram of an on-site monitoring terminal;
FIG. 3 is a schematic view of a video surveillance apparatus;
FIG. 4 is a schematic diagram of a driving circuit;
FIG. 5 is a flow chart of the method of the present invention.
The reference numbers in the figures: the system comprises an on-site monitoring terminal 1, an on-site data processing terminal 2, an intelligent communication gateway 3, a data communication network 4, a monitoring platform 5 based on a convolutional neural network system, a bearing rack 11, a driving guide rail 12, a detection head 13, a sliding block 14, a rotary table mechanism 15, a video monitoring device 16, a human body sensor 17, a driving circuit 18, a base 161, a CCD camera 162, a 3D camera 163 and an auxiliary illuminating lamp 164.
Detailed Description
In order to make the technical means, the creation characteristics, the achievement purposes and the effects of the invention easy to understand, the invention is further described with the specific embodiments.
As shown in FIGS. 1-4, a remote monitoring type real-time monitoring system for detecting work flow comprises at least one field monitoring terminal 1, at least one field data processing terminal 2, at least one intelligent communication gateway 3, at least one data communication network 4 and a monitoring platform 5 based on a convolutional neural network system, wherein each field data processing terminal 2 is connected with a plurality of field monitoring terminals 1 through the intelligent communication gateway 3 to form a working group, the intelligent communication gateway 3 of each working group is connected with the monitoring platform 5 based on the convolutional neural network system through the data communication network 4, the intelligent communication gateways 3 of each working group are connected with each other to form at least one monitoring local area network, the field monitoring terminals 1 and the field data processing terminals 2 are positioned at a detection working site and are electrically connected with a power supply system of the detection working site, and the on-site monitoring terminals 1 are uniformly distributed along the direction of the detection working flow.
In this embodiment, the monitoring platform 5 based on the convolutional neural network system is based on any one or two of a BP neural network system and a CNN neural network, and an LSTM-based intelligent prediction system, a deep learning subsystem of the deep learning neural network system, and an image recognition system are additionally provided in the monitoring platform 5 based on the convolutional neural network system.
In this embodiment, the field data processing terminal 2 is a circuit system based on one or two of an industrial computer and an internet-of-things controller, and the field data processing terminal 2 is provided with at least one serial communication circuit,
it should be noted that the on-site monitoring terminal 1 includes a bearing rack 11, a driving guide rail 12, a detecting head 13, a sliding block 14, a rotating table mechanism 15, a video monitoring device 16, a human body sensor 17 and a driving circuit 18, wherein the rear end face of the bearing rack 11 is connected with a building, the axis of the bearing rack 11 is distributed in parallel with the direction of a detection work assembly line, the driving guide rail 12 is embedded in the front end face of the bearing rack 11 and is distributed in parallel with the axis of the bearing rack 11, at least one detecting head 13 is connected with the driving guide rail 12 in a sliding manner through the sliding block 14, the rear end face of the detecting head 13 is hinged with the front end face of the sliding block 14 through the rotating table mechanism 15, the detecting head 13 is located at least 20 cm above a detection work surface, the detecting head 13 is a closed cavity structure with a rectangular axial section, the video monitoring device 16 and the human body sensor 17 are embedded in the outer surface, and the driving circuit 18 is embedded in the detection head 13, and is electrically connected with the driving guide rail 12, the turntable mechanism 15, the video monitoring device 16 and the human body sensor 17, and is also connected with the intelligent communication gateway 3 in a data communication way.
Further preferably, the driving circuit 18 comprises a circuit system based on an FPGA chip, a data communication bus, an MOS driving circuit, an I/O communication circuit, a crystal oscillator clock circuit, a voltage stabilizing circuit, a serial communication circuit and a connecting terminal, wherein the circuit system based on the FPGA chip is electrically connected with the data communication bus and the voltage stabilizing circuit, the data communication bus is further electrically connected with the MOS driving circuit, the I/O communication circuit, the crystal oscillator clock circuit, the voltage stabilizing circuit and the serial communication circuit, the MOS driving circuit is further electrically connected with the I/O communication circuit and the voltage stabilizing circuit respectively, and the voltage stabilizing circuit, the I/O communication circuit and the serial communication circuit are electrically connected with the connecting terminals.
Further preferably, the video monitoring device 16 includes a base 161, a CCD camera 162, a 3D camera 163 and an auxiliary illuminating lamp 164, wherein the 3D camera 163 and the CCD camera 162 are symmetrically disposed on two sides of the auxiliary illuminating lamp 164, rear end faces of the CCD camera 162, the 3D camera 163 and the auxiliary illuminating lamp 164 are connected to a front end face of the base 161, and optical axes of the CCD camera 162, the 3D camera 163 and the auxiliary illuminating lamp 164 are distributed in parallel and vertically disposed on the front end face of the base 161.
As shown in fig. 5, a method for using a remote monitoring type real-time monitoring system for detecting a work flow includes the following steps;
s1, system networking, firstly, assembling the site monitoring terminal 1, the site data processing terminal 2, the intelligent communication gateway 3, the data communication network 4 and the monitoring platform 5 based on the convolutional neural network system, wherein the monitoring platform 5 based on the convolutional neural network system is arranged in a main monitoring room, the site monitoring terminal 1 and the site data processing terminal 2 are arranged at a detection working site, the intelligent communication gateway 3 is respectively arranged at the detection working site and the main monitoring room, and finally, the site monitoring terminal 1, the site data processing terminal 2, the intelligent communication gateway 3 and the monitoring platform 5 based on the convolutional neural network system are connected through the data communication network 4 to complete networking assembly of the invention;
s2, monitoring operation, after the step S1 is completed, when a worker performs detection operation, firstly, the position of the worker is detected through the human body sensor 17 on the on-site monitoring terminal 1, the detection head 13 is adjusted to the working position of the worker through the driving guide rail 12, then, the video monitoring device of the detection head 13 performs face identification on the one hand to complete identity identification operation on the other hand to perform whole-course monitoring on the working process of the worker, and a monitoring result is fed back to the monitoring platform 5 based on the convolutional neural network system;
and S3, analyzing the data, transmitting the data acquisition image obtained in the step S2 to a monitoring platform based on big data, matching the acquired identity of the worker with the work content and the work habit of the worker by a convolutional neural network system to meet the requirement of accurate monitoring of detection operation, deeply learning the work habit of the worker by an intelligent prediction system and a deep learning neural network system based on LSTM to obtain the daily work behavior habit parameters of the worker for later use, and comparing the behavior habit parameters with the field work state of the worker to timely find the abnormal work state condition of the worker, thereby timely finding work errors and work accident conditions, alarming and correcting.
On one hand, the system has simple structure, flexible and convenient use, good universality and convenient system construction and maintenance, can effectively meet the use requirements of various environments and different detection operation activities, and can simultaneously realize the requirement of multi-machine cooperative operation in a large area range; on the other hand, the operation data processing capacity is high, the monitoring operation is met, meanwhile, the monitoring and identifying operation on the detection working quality can be accurately realized, the working behavior state of a worker is pre-judged and analyzed, and the alarm prompt is timely carried out on the abnormal state of the target object, so that the convenience, the reliability and the flexibility of the detection working monitoring operation are greatly improved.
It will be appreciated by persons skilled in the art that the present invention is not limited by the embodiments described above. The foregoing embodiments and description have been presented only to illustrate the principles of the invention. Various changes and modifications can be made without departing from the spirit and scope of the invention. Such variations and modifications are intended to be within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (6)
1. The utility model provides a remote monitoring formula detects real-time monitoring system of work flow which characterized in that: the on-site monitoring system comprises on-site monitoring terminals (1), on-site data processing terminals (2), intelligent communication gateways (3), a data communication network (4) and a monitoring platform (5) based on a convolutional neural network system, wherein at least one on-site data processing terminal (2) is arranged, each on-site data processing terminal (2) is connected with a plurality of on-site monitoring terminals (1) through an intelligent communication gateway (3) to form a working group, the intelligent communication gateways (3) of each working group are connected with the monitoring platform (5) based on the convolutional neural network system through the data communication network (4), the intelligent communication gateways (3) among the working groups are mutually connected to form at least one monitoring local area network, the on-site monitoring terminals (1) and the on-site data processing terminals (2) are positioned at a detection working site and are electrically connected with a power supply system of the detection working site, the field monitoring terminals (1) are uniformly distributed along the direction of the detection working flow; the on-site monitoring terminal (1) comprises a bearing rack (11), a driving guide rail (12), a detection head (13), a sliding block (14), a rotary table mechanism (15), a video monitoring device (16), a human body sensor (17) and a driving circuit (18), wherein the rear end face of the bearing rack (11) is connected with a building, the axis of the bearing rack is distributed in parallel with the direction of a detection working production line, the driving guide rail (12) is embedded in the front end face of the bearing rack (11) and distributed in parallel with the axis of the bearing rack (11), at least one detection head (13) is connected with the driving guide rail (12) in a sliding mode through the sliding block (14), the rear end face of the detection head (13) is hinged to the front end face of the sliding block (14) through the rotary table mechanism (15), the detection head (13) is located above the detection working face by at least 20 cm, and the detection head (13) is of a closed, the video monitoring device (16) and the human body sensor (17) are embedded in the outer surface of the detection head (13), the axis of the video monitoring device and the axis of the human body sensor form an included angle of 0-90 degrees with the detection operation surface, the driving circuit (18) is embedded in the detection head (13), and is electrically connected with the driving guide rail (12), the rotary table mechanism (15), the video monitoring device (16) and the human body sensor (17), and a data communication connection is established between the video monitoring device and the intelligent communication gateway (3).
2. The system according to claim 1, wherein the system comprises: the monitoring platform (5) based on the convolutional neural network system is any one or two of a BP neural network system and a CNN neural network, and an LSTM-based intelligent prediction system, a deep learning subsystem of the deep learning neural network system and an image recognition system are additionally arranged in the monitoring platform (5) based on the convolutional neural network system.
3. The system according to claim 1, wherein the system comprises: the field data processing terminal (2) is a circuit system based on any one or two of an industrial computer and an internet-of-things controller, and the field data processing terminal (2) is provided with at least one serial port communication circuit.
4. The system according to claim 1, wherein the system comprises: the drive circuit (18) comprises a circuit system based on an FPGA chip, a data communication bus, an MOS drive circuit, an I/O communication circuit, a crystal oscillator clock circuit, a voltage stabilizing circuit, a serial communication circuit and connecting terminals, wherein the circuit system based on the FPGA chip is electrically connected with the data communication bus and the voltage stabilizing circuit, the data communication bus is further electrically connected with the MOS drive circuit, the I/O communication circuit, the crystal oscillator clock circuit, the voltage stabilizing circuit and the serial communication circuit, the MOS drive circuit is further electrically connected with the I/O communication circuit and the voltage stabilizing circuit respectively, and the voltage stabilizing circuit, the I/O communication circuit and the serial communication circuit are electrically connected with the connecting terminals.
5. The system according to claim 1, wherein the system comprises: video monitoring device include base (161), a CCD camera (162), a 3D camera (163) and an auxiliary lighting lamp (164), wherein 3D camera (163), CCD camera (162) symmetric distribution are in auxiliary lighting lamp (164) both sides, CCD camera (162), 3D camera (163) and auxiliary lighting lamp (164) rear end face are connected with base (161) preceding terminal surface, and optical axis parallel distribution between CCD camera (162), 3D camera (163) and auxiliary lighting lamp (164), with base (161) preceding terminal surface vertical distribution.
6. The method for using a remote monitoring type detection workflow real-time monitoring system according to claim 1, wherein the method comprises the following steps: comprises the following steps;
s1, system networking, namely, firstly assembling a field monitoring terminal (1), a field data processing terminal (2), an intelligent communication gateway (3), a data communication network (4) and a monitoring platform (5) based on a convolutional neural network system, wherein the monitoring platform (5) based on the convolutional neural network system is arranged in a main monitoring room, the field monitoring terminal (1) and the field data processing terminal (2) are arranged at a detection working site, the intelligent communication gateway (3) is respectively arranged at the detection working site and the main monitoring room, and finally, the field monitoring terminal (1), the field data processing terminal (2), the intelligent communication gateway (3) and the monitoring platform based on the convolutional neural network system establish data connection through the data communication network (4) so as to finish networking assembly;
s2, monitoring operation, after the step S1 is completed, when a worker performs detection operation, the position of the worker is detected through a human body sensor (17) in the field monitoring terminal (1), the detection head (13) is adjusted to the working position of the worker through the driving guide rail (12), and then the face of the worker is identified through a video monitoring device of the detection head (13), so that identity identification operation is completed; monitoring the whole working process of a worker, and feeding a monitoring result back to a monitoring platform (5) based on a convolutional neural network system;
and S3, analyzing the data, transmitting the data acquisition image obtained in the step S2 to a monitoring platform based on big data, matching the acquired identity of the worker with the work content and the work habit of the worker by a convolutional neural network system to meet the requirement of accurate monitoring of detection operation, deeply learning the work habit of the worker by an intelligent prediction system and a deep learning neural network system based on LSTM to obtain the daily work behavior habit parameters of the worker for later use, and comparing the daily work behavior habit parameters with the field work state of the worker to timely find the abnormal work state condition of the worker, thereby timely finding the work fault and work accident condition and alarming and correcting.
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Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103676838A (en) * | 2013-10-25 | 2014-03-26 | 国家电网公司 | Electric power line basic construction intelligent safety monitoring system and monitoring method |
| CN203630583U (en) * | 2013-10-25 | 2014-06-04 | 国家电网公司 | Power line foundation construction intelligence safety monitoring system |
| CN109143909A (en) * | 2017-06-13 | 2019-01-04 | 南京埃塔斯智能科技有限公司 | Intellectual drug production management system based on VR technology |
| CN110045708A (en) * | 2019-05-13 | 2019-07-23 | 深圳市虎匠科技投资发展有限公司 | A kind of wisdom fielded system and method remotely monitored based on Internet of Things |
| CN110187677A (en) * | 2019-04-18 | 2019-08-30 | 南京铁工机械有限公司 | A kind of steel bar processing equipment production line long-distance management system and application method |
| CN110196579A (en) * | 2019-04-18 | 2019-09-03 | 南京铁工机械有限公司 | A kind of steel bar processing equipment remote failure diagnosis system and application method |
| CN110991399A (en) * | 2019-12-18 | 2020-04-10 | 南京泰晟科技实业有限公司 | Fatigue driving early warning system and method based on face recognition technology |
| CN112147946A (en) * | 2020-11-26 | 2020-12-29 | 上海盟扩软件科技有限公司南京分公司 | Remote monitoring type anti-cheating refueling data supervision system and method for gas station |
| CN112245824A (en) * | 2020-12-21 | 2021-01-22 | 南京厨功夫消防设备有限公司 | Remote monitoring type intelligent control system for kitchen automatic fire extinguishing device and use method thereof |
| CN112255991A (en) * | 2020-12-21 | 2021-01-22 | 江苏新鹏塑化科技有限公司 | Remote monitoring type carbon black master batch production and preparation control system and method thereof |
-
2021
- 2021-01-26 CN CN202110100522.9A patent/CN112437165B/en active Active
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103676838A (en) * | 2013-10-25 | 2014-03-26 | 国家电网公司 | Electric power line basic construction intelligent safety monitoring system and monitoring method |
| CN203630583U (en) * | 2013-10-25 | 2014-06-04 | 国家电网公司 | Power line foundation construction intelligence safety monitoring system |
| CN109143909A (en) * | 2017-06-13 | 2019-01-04 | 南京埃塔斯智能科技有限公司 | Intellectual drug production management system based on VR technology |
| CN110187677A (en) * | 2019-04-18 | 2019-08-30 | 南京铁工机械有限公司 | A kind of steel bar processing equipment production line long-distance management system and application method |
| CN110196579A (en) * | 2019-04-18 | 2019-09-03 | 南京铁工机械有限公司 | A kind of steel bar processing equipment remote failure diagnosis system and application method |
| CN110045708A (en) * | 2019-05-13 | 2019-07-23 | 深圳市虎匠科技投资发展有限公司 | A kind of wisdom fielded system and method remotely monitored based on Internet of Things |
| CN110991399A (en) * | 2019-12-18 | 2020-04-10 | 南京泰晟科技实业有限公司 | Fatigue driving early warning system and method based on face recognition technology |
| CN112147946A (en) * | 2020-11-26 | 2020-12-29 | 上海盟扩软件科技有限公司南京分公司 | Remote monitoring type anti-cheating refueling data supervision system and method for gas station |
| CN112245824A (en) * | 2020-12-21 | 2021-01-22 | 南京厨功夫消防设备有限公司 | Remote monitoring type intelligent control system for kitchen automatic fire extinguishing device and use method thereof |
| CN112255991A (en) * | 2020-12-21 | 2021-01-22 | 江苏新鹏塑化科技有限公司 | Remote monitoring type carbon black master batch production and preparation control system and method thereof |
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| CN112924158A (en) * | 2021-04-14 | 2021-06-08 | 道尔道科技有限公司 | Damper health monitoring system and method based on real-time monitoring of Internet of things |
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| CN113172931B (en) * | 2021-04-29 | 2021-11-30 | 南京晓庄学院 | Remote monitoring type intelligent control system and method for hydraulic single-row punching machine |
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| CN115619067A (en) * | 2022-09-14 | 2023-01-17 | 华准智能检测技术(武汉)有限公司 | Quality detection information management method, quality detection information management device, quality detection information management equipment and storage medium |
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