Intelligent chemical workshop safety prevention and control system based on big data of Internet of Things

Abstract

The invention discloses an intelligent chemical workshop safety prevention and control system based on Internet of Things big data, and relates to the technical field of workshop safety prevention and control. Comprising a data acquisition module, a data collaboration module, an early warning module and a management module. Key parameters corresponding to the chemical workshop are acquired through the acquisition module; processing the key parameters to obtain a process stage k model; obtaining an abnormal key position according to the process stage k model, and generating an early warning signal; setting a plurality of management terminals, setting alarm identifiers corresponding to the early warning signals, and sending the corresponding early warning signals to the corresponding management terminals for early warning through the alarm identifiers; and the accuracy of data regulation and control is effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of workshop safety control, and in particular to an intelligent chemical workshop safety control system based on Internet of Things big data. Background Art

[0002] As a high-risk working environment, chemical workshops are extremely important to prevent potential safety hazards. The primary concern is the risk of chemical leakage, which may lead to fire, explosion and poisoning accidents. To prevent such incidents, it is necessary to set up a special chemical storage area, strictly implement the classification storage and regular inspection system, and ensure the standardized operation of chemicals during use. Secondly, machine and equipment failure is also a major hidden danger, which may cause work interruption and casualties. There are relatively complete control systems for chemical workshop safety control in the prior art, but there is a lack of synergy between the subsystems of the chemical workshop control system. For example, due to the particularity of chemical workshops, there is complexity in the management of diverse data, resulting in inaccurate data control; for this reason, the present invention provides an intelligent chemical workshop safety control system based on Internet of Things big data. Summary of the invention

[0003] In order to solve the above technical problems, the present invention provides an intelligent chemical workshop safety control system based on Internet of Things big data; The purpose of the present invention can be achieved by the following technical solutions: an intelligent factory safety control system based on IoT big data, including a data acquisition module, a data collaboration module, an early warning module and a management module; The data acquisition module is used to collect key parameters corresponding to the chemical workshop; The data association module is used to process key parameters to obtain a process stage k model; The early warning module is used to obtain abnormal key positions according to the process stage k model and generate early warning signals; The management module is used to wirelessly connect to a plurality of management terminals and set an alarm mark corresponding to the early warning signal, and send the corresponding early warning signal to the corresponding management terminal through the alarm mark for early warning.

[0004] Furthermore, the process of the data acquisition module collecting key parameters corresponding to the chemical workshop includes: Obtain each process stage in the entire process of chemical production and mark them as process stage 1, process stage 2, ..., process stage n, where n is a positive integer; collect raw material data at process stage 1; deploy a sensor data network corresponding to each process stage at process stage k to collect key parameters and key positions corresponding to the process stage, where 1<k≤n; The key parameters include production environment parameters and equipment parameters.

[0005] Furthermore, the process of the data association module processing the key parameters to obtain the process stage k model includes: A raw material data standard comparison library corresponding to process stage 1 is set, several process stages directly associated with process stage n are obtained, and a process data transmission channel is set to connect process stage n with several directly associated process stages k, so as to transmit production data produced by process stage n to several directly associated process stages k; Set the principle equipment parameters corresponding to the equipment parameters of the key parameters of process stage k, and mark the corresponding key positions; spatially connect all the key positions corresponding to process stage k to generate the process stage production space, set the production key area in the process stage production space, and set an origin in the production key area, establish the xyz production key area three-dimensional space model corresponding to the production key area according to the origin, map the key positions of the production environment parameters corresponding to the sensor data network in the corresponding three-dimensional space models of each xyz production key area, and connect the key positions through the origin to form the production environment parameter vector corresponding to process stage k, map the production environment parameter vector in the xyz direction of the xyz production key area three-dimensional space model to obtain the directional production environment parameter vector in the xyz direction, and then construct the process stage k model.

[0006] Furthermore, the process of the early warning module obtaining abnormal key positions according to the process stage k model and generating early warning signals includes: Compare the raw material data corresponding to process stage 1 with the corresponding raw material data standard comparison library, obtain abnormal raw material data and normal raw material data, adjust the abnormal raw material data to standard raw material data according to the raw material data standard comparison library, and integrate it with the normal raw material data to generate a standard raw material data packet; then transmit the standard raw material data packet to the process stage k model corresponding to the connected several process stages k according to the process data transmission channel; and obtain the standard production environment parameters and standard equipment parameters corresponding to the standard raw material data packet in the process stage k, and then send them to the corresponding process stage k model; Based on the process stage k model, the equipment parameters collected at the process stage k are compared with the corresponding principle equipment parameters and standard equipment parameters at the same time. If both the principle equipment parameters and the standard equipment parameters are met, the key position corresponding to the equipment parameter is marked as a normal key position; if only the principle equipment parameters are met, the key position corresponding to the equipment parameter is marked as the first abnormal key position; if only the standard equipment parameters are met, the key position corresponding to the equipment parameter is marked as the second abnormal key position; if both the principle equipment parameters and the standard equipment parameters are not met, the key position corresponding to the equipment parameter is marked as the third abnormal key position.

[0007] Furthermore, a standard mapping angle corresponding to the production key area is set, and the standard production environment parameters are mapped in the xyz direction of the three-dimensional space model of the xyz production key area through the standard mapping angle, and the directional standard production environment parameter vector in the xyz direction is obtained, and compared with the corresponding directional production environment parameter vector. If the directional production environment parameter vector meets the directional standard production environment parameter vector, the corresponding directional production environment parameter vector is marked as an abnormal vector; otherwise, it is marked as a normal vector; If there is an abnormal vector, the key position corresponding to the production environment parameter is marked as an abnormal key position; Corresponding warning signals are generated for the first abnormal key position, the second abnormal key position, the third abnormal key position and the abnormal key position.

[0008] Furthermore, the process of the management module setting the alarm mark corresponding to the early warning signal includes: The alarm identification of the first abnormal key position, the second abnormal key position, the third abnormal key position and the warning signal corresponding to the abnormal key position is used to generate a safety alarm identification, a control alarm identification, a safety-control alarm identification and a production environment alarm identification.

[0009] Furthermore, the process of sending the corresponding early warning signal to the corresponding management terminal for management through the alarm mark includes: Generate a safety alarm mark, a control alarm mark, a safety-control alarm mark and a production environment alarm mark from the alarm marks of the first abnormal key position, the second abnormal key position, the third abnormal key position and the warning signal corresponding to the abnormal key position; If the management terminal receives the security alarm mark, the corresponding first abnormal key position is obtained, and then the device parameters corresponding to the first abnormal key position are adjusted according to the principle device parameters; If the management terminal receives the control alarm mark, the corresponding second abnormal key position is obtained, and then the device parameters corresponding to the second abnormal key position are controlled according to the standard device parameters; If the management terminal receives the safety-regulation alarm mark, the corresponding third abnormal key position is obtained, and then the device parameters corresponding to the third abnormal key position are regulated according to the principle device parameters and the standard device parameters; If the management terminal receives a production environment alarm mark, the corresponding abnormal key position is obtained, and then the production environment parameters corresponding to the abnormal key position are adjusted.

[0010] Furthermore, once the equipment parameters and production environment parameters corresponding to process stage k are decoded and controlled through the process stage k model, the standard production environment parameters are transmitted to the corresponding process stage k for production to obtain production data, and so on.

[0011] Compared with the prior art, the beneficial effects of the present invention are: the present invention collects key parameters corresponding to the chemical workshop through the collection module; processes the key parameters to obtain the process stage k model; obtains abnormal key positions according to the process stage k model, and generates an early warning signal; sets up several management terminals, and sets alarm labels corresponding to the early warning signals, and sends the corresponding early warning signals to the corresponding management terminals through the alarm labels for early warning; effectively improves the accuracy of data control. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0013] Figure 1 It is a schematic diagram of the present invention. DETAILED DESCRIPTION

[0014] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0015] like Figure 1 As shown, an intelligent factory safety prevention and control system based on IoT big data includes a data acquisition module, a data collaboration module, an early warning module and a management module; The data acquisition module is used to collect key parameters corresponding to the chemical workshop; The data association module is used to process key parameters to obtain a process stage k model; The early warning module is used to obtain abnormal key positions according to the process stage k model and generate early warning signals; The management module is used to wirelessly connect to a plurality of management terminals and set an alarm mark corresponding to the early warning signal, and send the corresponding early warning signal to the corresponding management terminal through the alarm mark for early warning.

[0016] The process of the data acquisition module collecting key parameters corresponding to the chemical workshop includes: Obtain each process stage in the entire process of chemical production and mark them as process stage 1, process stage 2, ..., process stage n, where n is a positive integer; collect raw material data at process stage 1; deploy a sensor data network corresponding to each process stage at process stage k to collect key parameters and key positions corresponding to the process stage, where 1<k≤n; The key parameters include production environment parameters and equipment parameters; In the above embodiment, it needs to be further explained that each process stage in the entire chemical production process includes but is not limited to the raw material pretreatment stage, separation and purification stage, product drying stage, product packaging stage, etc.; the raw material data is used to represent the materials required for chemical production, which may include liquids, solids, etc.; and then the corresponding raw material data is obtained.

[0017] The process of the data association module processing the key parameters to obtain the process stage k model includes: A raw material data standard comparison library corresponding to process stage 1 is set, several process stages directly associated with process stage n are obtained, and a process data transmission channel is set to connect process stage n with several directly associated process stages k, so as to transmit production data produced by process stage n to several directly associated process stages k; Set the principle equipment parameters corresponding to the equipment parameters of the key parameters of process stage k, and mark the corresponding key positions; spatially connect all the key positions corresponding to process stage k to generate the process stage production space, set the production key area in the process stage production space, and set an origin in the production key area, establish the xyz production key area three-dimensional space model corresponding to the production key area according to the origin, map the key positions of the production environment parameters corresponding to the sensor data network in the corresponding three-dimensional space models of each xyz production key area, and connect the key positions through the origin to form the production environment parameter vector corresponding to process stage k, map the production environment parameter vector in the xyz direction of the xyz production key area three-dimensional space model to obtain the directional production environment parameter vector in the xyz direction, and then construct the process stage k model.

[0018] In the above embodiment, it needs to be further explained that the production environment parameters and equipment parameters are related to the quality of chemical production. Therefore, the production environment parameters and equipment parameters of each process stage are modeled to better control the production situation of each process stage.

[0019] The process of the early warning module obtaining abnormal key positions according to the process stage k model and generating early warning signals includes: Compare the raw material data corresponding to process stage 1 with the corresponding raw material data standard comparison library, obtain abnormal raw material data and normal raw material data, adjust the abnormal raw material data to standard raw material data according to the raw material data standard comparison library, and integrate it with the normal raw material data to generate a standard raw material data packet; then transmit the standard raw material data packet to the process stage k model corresponding to the connected several process stages k according to the process data transmission channel; and obtain the standard production environment parameters and standard equipment parameters corresponding to the standard raw material data packet in the process stage k, and then send them to the corresponding process stage k model; Based on the process stage k model, the equipment parameters collected at the process stage k are compared with the corresponding principle equipment parameters and standard equipment parameters at the same time. If both the principle equipment parameters and the standard equipment parameters are met, the key position corresponding to the equipment parameter is marked as a normal key position; if only the principle equipment parameters are met, the key position corresponding to the equipment parameter is marked as the first abnormal key position; if only the standard equipment parameters are met, the key position corresponding to the equipment parameter is marked as the second abnormal key position; if both the principle equipment parameters and the standard equipment parameters are not met, the key position corresponding to the equipment parameter is marked as the third abnormal key position; Set the standard mapping angle corresponding to the key production area, map the standard production environment parameters in the xyz direction of the three-dimensional space model of the xyz key production area through the standard mapping angle, obtain the directional standard production environment parameter vector in the xyz direction, and compare it with the corresponding directional production environment parameter vector. If the directional production environment parameter vector meets the directional standard production environment parameter vector, the corresponding directional production environment parameter vector is marked as an abnormal vector; otherwise, it is marked as a normal vector. If there is an abnormal vector, the key position corresponding to the production environment parameter is marked as an abnormal key position; Corresponding warning signals are generated for the first abnormal key position, the second abnormal key position, the third abnormal key position and the abnormal key position.

[0020] In the above embodiment, it needs to be further explained that the production environment parameters in different directions are monitored through the spatial model to ensure that the production environment parameters in different directions are within the standard range; secondly, the monitoring of equipment parameters only needs to monitor whether it is safe and complies with the principle equipment parameters, and it is also necessary to monitor whether it complies with the standard equipment parameters during the production process. Only when the standards are met at the same time can the equipment safety be monitored.

[0021] The management module is wirelessly connected to several management terminals, and an alarm mark corresponding to the early warning signal is set. The process of sending the corresponding early warning signal to the corresponding management terminal for management through the alarm mark includes: Generate a safety alarm mark, a control alarm mark, a safety-control alarm mark and a production environment alarm mark from the alarm marks of the first abnormal key position, the second abnormal key position, the third abnormal key position and the warning signal corresponding to the abnormal key position; If the management terminal receives the security alarm mark, the corresponding first abnormal key position is obtained, and then the device parameters corresponding to the first abnormal key position are adjusted according to the principle device parameters; If the management terminal receives the control alarm mark, the corresponding second abnormal key position is obtained, and then the device parameters corresponding to the second abnormal key position are controlled according to the standard device parameters; If the management terminal receives the safety-regulation alarm mark, the corresponding third abnormal key position is obtained, and then the device parameters corresponding to the third abnormal key position are regulated according to the principle device parameters and the standard device parameters; If the management terminal receives a production environment alarm mark, it obtains the corresponding abnormal key position, and then adjusts the production environment parameters corresponding to the abnormal key position; Once the equipment parameters and production environment parameters corresponding to process stage k are decoded and controlled through the process stage k model, the standard production environment parameters are transmitted to the corresponding process stage k for production to obtain production data, and so on.

[0022] Working principle: collect key parameters corresponding to the chemical workshop through the collection module; process the key parameters to obtain the process stage k model; obtain the abnormal key position according to the process stage k model, and generate an early warning signal; set up several management terminals, and set the alarm mark corresponding to the early warning signal, and send the corresponding early warning signal to the corresponding management terminal through the alarm mark for early warning.

[0023] The features and exemplary embodiments of various aspects of the present application are described in detail above. In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is further described in detail in combination with the drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application rather than to limit the present application. For those skilled in the art, the present application can be implemented without some of these specific details. The above description of the embodiments is merely to provide a better understanding of the present application by showing examples of the present application.

[0024] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. An intelligent factory safety control system based on IoT big data, characterized in that: It includes data collection module, data collaboration module, early warning module and management module; The data acquisition module is used to collect key parameters corresponding to the chemical workshop; The data association module is used to process key parameters to obtain a process stage k model; The early warning module is used to obtain abnormal key positions according to the process stage k model and generate early warning signals; The management module is used to wirelessly connect to a plurality of management terminals and set an alarm mark corresponding to the early warning signal, and send the corresponding early warning signal to the corresponding management terminal through the alarm mark for early warning.

2. According to the intelligent chemical workshop safety control system based on Internet of Things big data according to claim 1, it is characterized in that: The process of the data acquisition module collecting key parameters corresponding to the chemical workshop includes: Obtain each process stage in the entire process of chemical production and mark them as process stage 1, process stage 2, ..., process stage n, where n is a positive integer; collect raw material data at process stage 1; deploy a sensor data network corresponding to each process stage at process stage k to collect key parameters and key positions corresponding to the process stage, where 1<k≤n; The key parameters include production environment parameters and equipment parameters.

3. According to claim 2, the intelligent chemical workshop safety control system based on Internet of Things big data is characterized in that: The process of the data association module processing the key parameters to obtain the process stage k model includes: A raw material data standard comparison library corresponding to process stage 1 is set, several process stages directly associated with process stage n are obtained, and a process data transmission channel is set to connect process stage n with several directly associated process stages k, so as to transmit production data produced by process stage n to several directly associated process stages k; Set the principle equipment parameters corresponding to the equipment parameters of the key parameters of process stage k, and mark the corresponding key positions; spatially connect all the key positions corresponding to process stage k to generate the process stage production space, set the production key area in the process stage production space, and set an origin in the production key area, establish the xyz production key area three-dimensional space model corresponding to the production key area according to the origin, map the key positions of the production environment parameters corresponding to the sensor data network in the corresponding three-dimensional space models of each xyz production key area, and connect the key positions through the origin to form the production environment parameter vector corresponding to process stage k, map the production environment parameter vector in the xyz direction of the xyz production key area three-dimensional space model to obtain the directional production environment parameter vector in the xyz direction, and then construct the process stage k model.

4. According to claim 3, the intelligent chemical workshop safety control system based on Internet of Things big data is characterized in that: The process of the early warning module obtaining abnormal key positions according to the process stage k model and generating early warning signals includes: Compare the raw material data corresponding to process stage 1 with the corresponding raw material data standard comparison library, obtain abnormal raw material data and normal raw material data, adjust the abnormal raw material data to standard raw material data according to the raw material data standard comparison library, and integrate it with the normal raw material data to generate a standard raw material data packet; then transmit the standard raw material data packet to the process stage k model corresponding to the connected several process stages k according to the process data transmission channel; and obtain the standard production environment parameters and standard equipment parameters corresponding to the standard raw material data packet in the process stage k, and then send them to the corresponding process stage k model; Based on the process stage k model, the equipment parameters collected at the process stage k are compared with the corresponding principle equipment parameters and standard equipment parameters at the same time. If both the principle equipment parameters and the standard equipment parameters are met, the key position corresponding to the equipment parameter is marked as a normal key position; if only the principle equipment parameters are met, the key position corresponding to the equipment parameter is marked as the first abnormal key position; if only the standard equipment parameters are met, the key position corresponding to the equipment parameter is marked as the second abnormal key position; if both the principle equipment parameters and the standard equipment parameters are not met, the key position corresponding to the equipment parameter is marked as the third abnormal key position.

5. According to claim 4, the intelligent chemical workshop safety control system based on Internet of Things big data is characterized in that: Set the standard mapping angle corresponding to the key production area, map the standard production environment parameters in the xyz direction of the three-dimensional space model of the xyz key production area through the standard mapping angle, obtain the directional standard production environment parameter vector in the xyz direction, and compare it with the corresponding directional production environment parameter vector. If the directional production environment parameter vector meets the directional standard production environment parameter vector, the corresponding directional production environment parameter vector is marked as an abnormal vector; otherwise, it is marked as a normal vector. If there is an abnormal vector, the key position corresponding to the production environment parameter is marked as an abnormal key position; Corresponding warning signals are generated for the first abnormal key position, the second abnormal key position, the third abnormal key position and the abnormal key position.

6. According to claim 5, the intelligent chemical workshop safety control system based on Internet of Things big data is characterized in that: The process of the management module setting the alarm mark corresponding to the early warning signal includes: The alarm identification of the first abnormal key position, the second abnormal key position, the third abnormal key position and the alarm identification of the abnormal key position corresponding to the early warning signal is used to generate a safety alarm identification, a control alarm identification, a safety-control alarm identification and a production environment alarm identification.

7. The intelligent chemical workshop safety control system based on Internet of Things big data according to claim 6 is characterized in that: The process of sending the corresponding warning signal to the corresponding management terminal for management through the alarm mark includes: Generate a safety alarm mark, a control alarm mark, a safety-control alarm mark and a production environment alarm mark from the alarm marks of the first abnormal key position, the second abnormal key position, the third abnormal key position and the warning signal corresponding to the abnormal key position; If the management terminal receives the security alarm mark, the corresponding first abnormal key position is obtained, and then the device parameters corresponding to the first abnormal key position are adjusted according to the principle device parameters; If the management terminal receives the control alarm mark, the corresponding second abnormal key position is obtained, and then the device parameters corresponding to the second abnormal key position are controlled according to the standard device parameters; If the management terminal receives the safety-regulation alarm mark, the corresponding third abnormal key position is obtained, and then the device parameters corresponding to the third abnormal key position are regulated according to the principle device parameters and the standard device parameters; If the management terminal receives a production environment alarm mark, the corresponding abnormal key position is obtained, and then the production environment parameters corresponding to the abnormal key position are adjusted.

8. The intelligent chemical workshop safety control system based on Internet of Things big data according to claim 7 is characterized in that: Once the equipment parameters and production environment parameters corresponding to process stage k are decoded and controlled through the process stage k model, the standard production environment parameters are transmitted to the corresponding process stage k for production to obtain production data, and so on.

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