Plastic woven bag production process safety monitoring system

Abstract

The invention discloses a plastic woven bag production process safety monitoring system, and relates to the technical field of plastic woven bag production safety, and the system comprises a dust concentration sensor module, a temperature and humidity sensor module, a harmful chemical gas concentration sensor module, a smoke sensor module and an electrostatic monitoring sensor module through an integrated detection module. The monitoring camera and the integrated controller module are used for realizing all-directional and real-time monitoring of a production workshop; potential safety hazards such as fire disasters and dust concentration exceeding standards can be automatically identified and warned; meanwhile, the system has remote control and data transmission functions, monitoring data can be transmitted to a control center in real time, information support is provided for managers, and the safety monitoring system effectively improves the safety in the production process of the plastic woven bags, reduces the occurrence risk of safety accidents and has wide application prospects and popularization value.

Description

Technical Field

[0001] The invention relates to a safety monitoring system for a plastic woven bag production process, in particular to a system which integrates a detection module and a controller and can monitor and warn of the safety of a production environment in real time. Background Art

[0002] Plastic woven bags, also known as snakeskin bags, are a type of plastic bag widely used in the packaging industry. Its main raw materials are chemical plastic raw materials such as polypropylene (PP). The production process of plastic woven bags is complicated, including raw material preparation, melt extrusion, horizontal and weft weaving, cutting and flattening, printing and stretching, bag making and packaging. These links are interdependent and together constitute the complete production process of plastic woven bags.

[0003] However, due to the characteristics of plastic raw materials and the complexity of the production environment, there are many safety hazards. These hazards mainly include the emission of harmful gases, excessive dust concentration, inappropriate air temperature and humidity, static electricity accumulation, and potential fire risks. First, plastic raw materials are prone to fire in a high-temperature molten state, and once a fire occurs, the fire spreads rapidly and is difficult to control. At the same time, it may also produce harmful gases that are not easily detected, which is extremely harmful to the human body; secondly, the production process involves a large number of mechanical equipment, such as injection molding machines, weaving machines, bag making machines, etc. These equipment may have mechanical failures or improper operation during operation, leading to safety accidents. In addition, the environment of the production workshop, such as temperature, humidity, dust concentration, etc., may also pose a threat to production safety.

[0004] In order to ensure the safety of the plastic woven bag production process, the traditional approach is to monitor through manual inspections and fixed cameras. However, this method has obvious limitations. Manual inspections are inefficient and it is difficult to detect safety hazards in real time. Fixed cameras have a limited monitoring range and cannot achieve all-round monitoring. They also respond slowly to emergencies such as fires. Although the plastic woven bag production process safety monitoring system in the prior art can monitor the production environment to a certain extent, it still has many shortcomings. The main reasons are: the production workshop has a large area, complex airflow, and many types of harmful gases and fast concentration changes. Existing sensors often find it difficult to accurately and real-time monitor the concentration of harmful gases, resulting in untimely information feedback and difficulty in effectively preventing harmful gases from harming human health and the environment.

[0005] Secondly, the existing dust concentration sensors have errors in the measurement process due to the complex dust particle environment in the production workshop, uneven temperature and humidity distribution, and susceptibility to interference from the external environment, making it difficult to accurately reflect the actual situation of the production environment.

[0006] Therefore, it is particularly important to develop an efficient and reliable safety monitoring system for the production process of plastic woven bags. The system can realize all-round and real-time monitoring of the production workshop, timely discover and warn potential safety hazards, and provide strong protection for the safety of the production process. Summary of the invention

[0007] The purpose of the present invention is to provide a safety monitoring system for the production process of plastic woven bags, which integrates multiple sensors such as cameras, smoke sensors, temperature sensors, etc., and combines advanced image processing technology and intelligent analysis algorithms to achieve comprehensive monitoring and intelligent early warning of the production workshop. At the same time, the system also has remote control and data transmission functions, which can transmit monitoring data to the control center in real time, provide timely and accurate information support for managers, and ensure the safety and stability of the production process.

[0008] By integrating multiple sensors and controllers, real-time monitoring and early warning of various safety indicators in the production environment can be achieved to ensure the smooth progress of the production process and the health and safety of workers.

[0009] To achieve the above object, the present invention adopts the following technical solutions:

[0010] A plastic woven bag production process safety monitoring system includes the following modules:

[0011] The system startup and initialization module is used to start the system and initialize the detection modules installed in the production workshop, as well as set the initial parameters for the system operation;

[0012] This module is responsible for starting the system and initializing all detection modules installed in the production workshop. It sets the initial parameters for system operation and provides a basis for subsequent data collection, processing and anomaly detection. These initial parameters include but are not limited to the sensor's working mode, data collection frequency, data processing algorithm, etc.

[0013] A real-time data acquisition and processing module, wherein the real-time data acquisition and processing module uses sensors and data acquisition settings provided by the system startup and initialization module. The sensors collect data in the production environment in real time, including dust concentration, air temperature and humidity, concentration of harmful chemical gases, smoke conditions, and static electricity conditions. The integrated controller receives these data and performs real-time processing and analysis.

[0014] After the system startup and initialization modules are completed, the real-time data acquisition and processing module starts working. It uses the sensors and data acquisition settings provided by the system to collect key data in the production environment in real time, such as dust concentration, air temperature and humidity, harmful chemical gas concentration, smoke conditions, and static electricity conditions. These data are received by the integrated controller and immediately processed and analyzed in real time. The processing process includes data cleaning, format conversion, and analysis based on preset algorithms to ensure the accuracy and reliability of the data.

[0015] The anomaly detection and alarm triggering module, the integrated controller judges the processed data, if the data exceeds the preset threshold, the alarm is triggered, and the alarm information is transmitted to the alarm response and disposal module through a wireless signal; if the data does not exceed the threshold, the monitoring continues;

[0016] The data processed by the real-time data acquisition and processing module is passed to the anomaly detection and alarm triggering module. This module judges the data according to the preset threshold. If the data exceeds the threshold, it means that there may be safety hazards in the production environment, and the module will trigger an alarm. The alarm information is transmitted to the alarm response and disposal module via wireless signals. At the same time, the anomaly detection and alarm triggering module records the abnormal data for subsequent analysis and improvement.

[0017] An alarm response and disposal module, which notifies staff to go to the abnormal area according to the alarm information provided by the abnormality detection and alarm triggering module, and the staff judges the abnormal situation and takes corresponding treatment measures;

[0018] After receiving the alarm information, the alarm response and disposal module immediately notifies the staff to go to the abnormal area. The staff will make on-site judgments on the abnormal situation based on the detailed data and location information provided in the alarm information and take corresponding treatment measures. Treatment measures include shutting down dangerous equipment, starting the emergency ventilation system, adjusting the air temperature and humidity, evacuating personnel, etc. At the same time, the staff can also feedback the treatment results to the system to update the status and close the alarm.

[0019] Process end module, when all abnormal situations are handled or the production process is completed, the system is shut down and the process ends.

[0020] A further improvement of the present invention is that the detection module includes an air quality detection module, a smoke sensor module and an electrostatic monitoring sensor module; the air quality detection module includes a dust concentration sensor module, a temperature and humidity sensor module, and a harmful chemical gas concentration sensor module; and these sensors are installed in key areas of the production workshop to ensure the comprehensiveness and accuracy of the monitoring.

[0021] A further improvement of the present invention is that the dust concentration sensor module is installed in dust-prone areas, including raw material cutting and weaving areas, and a laser particle counter is used to monitor the dust concentration generated during the production process in real time. The laser particle counter irradiates dust particles through a laser light source and calculates the number and concentration of dust particles using the number of scattered light signals. According to the laser particle counter, the expression for dust concentration detection is obtained as follows:

[0022] Claser=klaser×Nscatter

[0023] Where: Nscatter is the number of scattered light signals, which is proportional to the number of dust particles; Claser is the dust concentration measured by the laser particle counter; klaser is the calibration coefficient of the laser particle counter, and the unit is concentration / number of scattered signals;

[0024] And in view of the specific environment in the production process of plastic woven bags, the following adjustments are made: According to the particle size distribution of dust particles of plastic products in the workshop, a particle size correction item is introduced:

[0025]

[0026] Where: C adjusted represents the adjusted dust concentration, C is the original dust concentration directly measured by the laser particle counter, n is the total number of particle size intervals, and w i represents the weight of the particles in the i-th particle size interval, represents the i-th particle size interval, with a particle size of d i The correction factor represents the effect of particles of this size on the overall dust concentration measurement;

[0027] In dust-prone areas, including raw material cutting and weaving areas, dust concentration sensors are set up respectively. The dust concentration is measured using the sensors in each area to obtain C1, C2, C3, ..., C m , where m is the number of regions;

[0028] Calculate the comprehensive dust concentration:

[0029]

[0030] Where: C total Indicates the comprehensive dust concentration, C i Indicates the original dust concentration in the ith region, RegionFactor i Indicates the regional impact factor of each area according to different dust generation and diffusion speed conditions, Weight i Represents the weight determined by the area of ​​the i-th region.

[0031] A further improvement of the present invention is that the temperature and humidity sensor modules are evenly distributed and installed around the production workshop and in the central area to monitor the air temperature and humidity in the production process in real time. The temperature and humidity sensor modules use thermistors or capacitive sensors to measure the current air temperature and humidity and transmit the data to the data acquisition module. The calculation formulas for temperature T and humidity H are as follows:

[0032] Temperature T formula:

[0033]

[0034] Where: T represents temperature, V out Represents the output voltage of the sensor, V in Represents the input voltage of the sensor, which is proportional to the temperature;

[0035] Humidity H formula:

[0036] Where: H represents humidity, V out湿 and V out干 are the output voltage of the sensor in wet and dry states, V in湿 and V in干 are the input voltage of the sensor in wet and dry states, respectively, which are proportional to the humidity.

[0037] A further improvement of the present invention is that: the harmful chemical gas concentration sensor module is installed in the working area where harmful chemical gases are generated during the production process, and a gas sensor is used to monitor the concentration of harmful chemical gases generated during the production process in real time. The gas sensor detects specific gases through electrochemistry and photochemistry;

[0038] The relationship between gas concentration and sensor output is expressed as:

[0039] C g =K×(V out -V offset )

[0040] Where: C g is the gas concentration, V out Represents the sensor output voltage, V offset It represents the output voltage of the sensor under the condition of no gas or reference gas, also known as zero offset. K is the sensitivity coefficient of the sensor.

[0041] Since the workshop environment is affected by temperature T and humidity H, which will change the zero offset and sensitivity of the sensor, an environmental factor compensation algorithm is introduced.

[0042] Harmful gas concentration C dg The formula is:

[0043]

[0044] Where: C dg Indicates the concentration of harmful gases, V out,gas Represents the output voltage of the sensor in the presence of harmful gases, V offsetcalib (T,H) represents the zero offset of temperature and humidity compensation added during calibration, K calib (T,H) represents the sensitivity coefficients for temperature and humidity compensation added during the calibration process.

[0045] A further improvement of the present invention is that the smoke sensor module is installed on the top of the workshop and uses a photoelectric smoke sensor to monitor the smoke concentration in the production process in real time. The photoelectric smoke sensor determines the smoke concentration by measuring the degree to which the light beam is absorbed by the smoke.

[0046] Smoke density C f The expression is:

[0047]

[0048] Where: C f Indicates the smoke density, k f It represents the calibration coefficient with the characteristics of the photoelectric smoke sensor and the environmental conditions. I0 represents the light intensity received by the sensor when there is no smoke, that is, the initial light intensity. I represents the light intensity received by the sensor when there is smoke.

[0049] A further improvement of the present invention is that the electrostatic monitoring sensor module is installed on the workshop production line to monitor the electrostatic conditions of plastic woven bags and production equipment, and evaluates the risk of static electricity accumulation by measuring the electrostatic potential or electrostatic charge. se , each charge source Q i , where i = 1, 2, ..., n, the potential V generated at point P i It can be expressed as:

[0050]

[0051] Where: k j is the electrostatic force constant, Q i represents the charge of the i-th charge source, r represents the distance from the point charge Q to point P, r i represents the distance from the i-th charge source to point P;

[0052] Therefore, the total potential V at point P is se It represents the sum of the potentials generated by all charge sources at point P, that is:

[0053] Where: Vse It represents the sum of the potentials generated at point P by all charge sources Q.

[0054] A further improvement of the present invention is that: the detection module also includes a monitoring camera and an integrated controller module;

[0055] The monitoring camera and integrated controller module includes: a monitoring camera and an integrated controller. The monitoring camera is installed in a production workshop. The monitoring camera is also equipped with high-definition imaging and night vision functions. The integrated controller is responsible for receiving data from various sensors and performing real-time processing and analysis.

[0056] A further improvement of the present invention is that the integrated controller also has data recording and query functions, and can store and analyze historical monitoring data; the abnormality detection and alarm triggering module also includes classification and priority setting of alarm information to ensure that emergency situations can be responded to in a timely manner.

[0057] A further improvement of the present invention is that the system also has a remote access and control function, allowing management personnel to remotely view monitoring data, adjust system settings and receive alarm information via the Internet.

[0058] Beneficial effects:

[0059] 1. The present invention integrates multiple sensors to achieve comprehensive monitoring of various safety indicators in the production environment and improve the accuracy and timeliness of monitoring. Temperature and humidity are key factors affecting the performance of harmful gas sensors. By real-time monitoring of temperature and humidity, the system can correct the data of harmful gas sensors, thereby eliminating the influence of environmental factors on the measurement results and improving the accuracy of monitoring data.

[0060] 2. The present invention adopts the design of movable monitoring camera to make the monitoring range more flexible and cover more production areas. The integrated controller can automatically analyze data and issue alarms, thus reducing manual intervention and improving emergency response speed. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 It is a system overall modular process structure diagram of the present invention;

[0062] Figure 2 It is a structural diagram of the system startup and initialization module in the present invention;

[0063] Figure 3 It is a structural diagram of the real-time data acquisition and processing module in the present invention;

[0064] Figure 4 This is a structural diagram of the sensor in the present invention for real-time data collection. DETAILED DESCRIPTION

[0065] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0066] See also Figures 1 to 4 , a plastic woven bag production process safety monitoring system, characterized by comprising:

[0067] The system startup and initialization module is used to start the system and initialize the detection modules installed in the production workshop, as well as set the initial parameters for the system operation;

[0068] A real-time data acquisition and processing module, wherein the real-time data acquisition and processing module uses sensors and data acquisition settings provided by the system startup and initialization module. The sensors collect data in the production environment in real time, including dust concentration, air temperature and humidity, concentration of harmful chemical gases, smoke conditions, and static electricity conditions. The integrated controller receives these data and performs real-time processing and analysis.

[0069] The anomaly detection and alarm triggering module, the integrated controller judges the processed data, if the data exceeds the preset threshold, the alarm is triggered, and the alarm information is transmitted to the alarm response and disposal module through a wireless signal; if the data does not exceed the threshold, the monitoring continues;

[0070] An alarm response and disposal module, which notifies staff to go to the abnormal area according to the alarm information provided by the abnormality detection and alarm triggering module, and the staff judges the abnormal situation and takes corresponding treatment measures;

[0071] Process end module, when all abnormal situations are handled or the production process is completed, the system is shut down and the process ends.

[0072] In this embodiment, the detection module includes an air quality detection module, a smoke sensor module and an electrostatic monitoring sensor module, and the air quality detection module includes a dust concentration sensor module, a temperature and humidity sensor module, and a harmful chemical gas concentration sensor module.

[0073] In this embodiment, the dust concentration sensor module is further installed in dust-prone areas, including raw material cutting and weaving areas, and a laser particle counter is used to monitor the dust concentration generated during the production process in real time. The laser particle counter irradiates dust particles through a laser light source and calculates the number and concentration of dust particles using the number of scattered light signals. According to the laser particle counter, the expression for dust concentration detection is obtained as follows:

[0074] Claser=klaser×Nscatter

[0075] Where: Nscatter is the number of scattered light signals, which is proportional to the number of dust particles; Claser is the dust concentration measured by the laser particle counter; klaser is the calibration coefficient of the laser particle counter, and the unit is concentration / number of scattered signals;

[0076] And in view of the specific environment in the production process of plastic woven bags, the following adjustments are made: According to the particle size distribution of dust particles of plastic products in the workshop, a particle size correction item is introduced:

[0077]

[0078] Where: C adjusted represents the adjusted dust concentration, C is the original dust concentration directly measured by the laser particle counter, n is the total number of particle size intervals, and w i represents the weight of the particles in the i-th particle size interval, represents the i-th particle size interval, with a particle size of d i The correction factor represents the effect of particles of this size on the overall dust concentration measurement;

[0079] In dust-prone areas, including raw material cutting and weaving areas, dust concentration sensors are set up respectively. The dust concentration is measured using the sensors in each area to obtain C1, C2, C3, ..., C m , where m is the number of regions;

[0080] Calculate the comprehensive dust concentration:

[0081]

[0082] In the formula, C total Indicates the comprehensive dust concentration, C i Indicates the original dust concentration in the ith region, RegionFactor i Indicates the regional impact factor of each area according to different dust generation and diffusion speed conditions, Weight i Represents the weight determined by the area of ​​the i-th region.

[0083] In this embodiment, the temperature and humidity sensor modules are evenly distributed and installed around the production workshop and in the central area to monitor the air temperature and humidity in the production process in real time. The temperature and humidity sensor modules use thermistors or capacitive sensors to measure the current air temperature and humidity and transmit the data to the data acquisition module.

[0084] The calculation formulas for temperature T and humidity H are as follows:

[0085] Temperature T formula:

[0086]

[0087] Where: T represents temperature, V out Represents the output voltage of the sensor, V in Represents the input voltage of the sensor, which is proportional to the temperature;

[0088] Humidity H formula:

[0089] Where: H represents humidity, V out湿 and V out干 are the output voltage of the sensor in wet and dry states, V in湿 and V in干 are the input voltage of the sensor in wet and dry states, respectively, which are proportional to the humidity.

[0090] Further, in this embodiment, the harmful chemical gas concentration sensor module is installed in the working area where harmful chemical gases are generated during the production process, and a gas sensor is used to monitor the concentration of harmful chemical gases generated during the production process in real time. The gas sensor detects specific gases through electrochemistry and photochemistry;

[0091] The relationship between gas concentration and sensor output is expressed as:

[0092] C g =K×(V out -V offset )

[0093] Where: C g is the gas concentration, V out Represents the sensor output voltage, V offset It represents the output voltage of the sensor under the condition of no gas or reference gas, also known as zero offset. K is the sensitivity coefficient of the sensor.

[0094] Since the workshop environment is affected by temperature T and humidity H, which will change the zero offset and sensitivity of the sensor, an environmental factor compensation algorithm is introduced.

[0095] Harmful gas concentration C dg The formula is:

[0096]

[0097] Where: C dg Indicates the concentration of harmful gases, V out,gas Represents the output voltage of the sensor in the presence of harmful gases, Voffsetcalib (T,H) represents the zero offset of temperature and humidity compensation added during calibration, K calib (T,H) represents the sensitivity coefficients for temperature and humidity compensation added during the calibration process.

[0098] In this embodiment, the smoke sensor module is installed on the top of the workshop and uses a photoelectric smoke sensor to monitor the smoke concentration in the production process in real time. The photoelectric smoke sensor determines the smoke concentration by measuring the degree to which the light beam is absorbed by the smoke.

[0099] Smoke density C f The expression is:

[0100]

[0101] Where: C f Indicates the smoke density, k f It represents the calibration coefficient with the characteristics of the photoelectric smoke sensor and the environmental conditions. I0 represents the light intensity received by the sensor when there is no smoke, that is, the initial light intensity. I represents the light intensity received by the sensor when there is smoke.

[0102] In this embodiment, the electrostatic monitoring sensor module is further installed on the workshop production line to monitor the electrostatic conditions of plastic woven bags and production equipment. By measuring the electrostatic potential or electrostatic charge, the risk of static electricity accumulation is evaluated. For the total potential V of a point P in the electric field generated by n charge sources, se , each charge source Q i , where i = 1, 2, ..., n, the potential V generated at point P i It can be expressed as:

[0103]

[0104] Where: k j is the electrostatic force constant, Q i represents the charge of the i-th charge source, r represents the distance from the point charge Q to point P, r i represents the distance from the i-th charge source to point P;

[0105] Therefore, the total potential V at point P is se It represents the sum of the potentials generated by all charge sources at point P, that is:

[0106] Where: V se It represents the sum of the potentials generated at point P by all charge sources Q.

[0107] Further in this embodiment, the detection module also includes a monitoring camera and an integrated controller module;

[0108] The monitoring camera and integrated controller module includes: a monitoring camera and an integrated controller. The monitoring camera is installed in a production workshop. The monitoring camera is also equipped with high-definition imaging and night vision functions. The integrated controller is responsible for receiving data from various sensors and performing real-time processing and analysis.

[0109] Furthermore, in this embodiment, the integrated controller also has data recording and query functions, and can store and analyze historical monitoring data; the abnormality detection and alarm triggering module also includes classification and priority setting of alarm information to ensure that emergency situations can be responded to in a timely manner.

[0110] Furthermore, in this embodiment, the system also has remote access and control functions, allowing management personnel to remotely view monitoring data, adjust system settings and receive alarm information via the Internet.

[0111] It should be noted that the above embodiments are only used to illustrate the technical solutions 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 solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A plastic woven bag production process safety monitoring system, characterized in that: Includes the following modules: The system startup and initialization module is used to start the system and initialize the detection modules installed in the production workshop, as well as set the initial parameters for the system operation; A real-time data acquisition and processing module, wherein the real-time data acquisition and processing module uses sensors and data acquisition settings provided by the system startup and initialization module. The sensors collect data in the production environment in real time, including dust concentration, air temperature and humidity, concentration of harmful chemical gases, smoke conditions, and static electricity conditions. The integrated controller receives these data and performs real-time processing and analysis. The anomaly detection and alarm triggering module, wherein the integrated controller judges the processed data, and if the data exceeds a preset threshold, an alarm is triggered, and the alarm information is transmitted to the alarm response and disposal module via a wireless signal; If the data does not exceed the threshold, continue monitoring; An alarm response and disposal module, which notifies staff to go to the abnormal area according to the alarm information provided by the abnormality detection and alarm triggering module, and the staff judges the abnormal situation and takes corresponding treatment measures; Process end module, when all abnormal situations are handled or the production process is completed, the system is shut down and the process ends.

2. A plastic woven bag production process safety monitoring system according to claim 1, characterized in that: The detection module includes an air quality detection module, a smoke sensor module and an electrostatic monitoring sensor module. The air quality detection module includes a dust concentration sensor module, a temperature and humidity sensor module, and a harmful chemical gas concentration sensor module.

3. A plastic woven bag production process safety monitoring system according to claim 2, characterized in that: The dust concentration sensor module is installed in dust-prone areas, including raw material cutting and weaving areas, and uses a laser particle counter to monitor the dust concentration generated during the production process in real time. The laser particle counter irradiates dust particles with a laser light source and calculates the number and concentration of dust particles using the number of scattered light signals. According to the laser particle counter, the expression for dust concentration detection is: Claser=klaser×Nscatter Where: Nscatter is the number of scattered light signals, which is proportional to the number of dust particles; Claser is the dust concentration measured by the laser particle counter; klaser is the calibration coefficient of the laser particle counter, and the unit is concentration / number of scattered signals; And in view of the specific environment in the production process of plastic woven bags, the following adjustments are made: According to the particle size distribution of dust particles of plastic products in the workshop, a particle size correction item is introduced: Where: C adjusted represents the adjusted dust concentration, C is the original dust concentration directly measured by the laser particle counter, n is the total number of particle size intervals, and w i represents the weight of the particles in the i-th particle size interval, represents the i-th particle size interval, with a particle size of d i The correction factor represents the effect of particles of this size on the overall dust concentration measurement; In dust-prone areas, including raw material cutting and weaving areas, dust concentration sensors are set up respectively. The dust concentration is measured using the sensors in each area to obtain C1, C2, C3, ..., C m , where m is the number of regions; Calculate the comprehensive dust concentration: In the formula, C total Indicates the comprehensive dust concentration, C i Indicates the original dust concentration in the ith region, RegionFactor i Indicates the regional impact factor of each area according to different dust generation and diffusion speed conditions, Weight i Represents the weight determined by the area of ​​the i-th region.

4. A plastic woven bag production process safety monitoring system according to claim 3, characterized in that: The temperature and humidity sensor modules are evenly distributed and installed around the production workshop and in the central area to monitor the air temperature and humidity in the production process in real time. The temperature and humidity sensor modules use thermistors or capacitive sensors to measure the current air temperature and humidity and transmit the data to the data acquisition module. The calculation formulas for temperature T and humidity H are as follows: Temperature T formula: Where: T represents temperature, V out Represents the output voltage of the sensor, V in Represents the input voltage of the sensor, which is proportional to the temperature; Humidity H formula: Where: H represents humidity, V out湿 and V out干 are the output voltage of the sensor in wet and dry states, V in湿 and V in干 are the input voltage of the sensor in wet and dry states, respectively, which are proportional to the humidity.

5. A plastic woven bag production process safety monitoring system according to claim 4, characterized in that: The harmful chemical gas concentration sensor module is installed in the working area where harmful chemical gases are generated during the production process, and uses a gas sensor to monitor the concentration of harmful chemical gases generated during the production process in real time. The gas sensor detects specific gases through electrochemistry and photochemistry; The relationship between gas concentration and sensor output is expressed as: C g =K×(V out -V offset ) Where: C g is the gas concentration, V out Represents the sensor output voltage, V offset It represents the output voltage of the sensor under the condition of no gas or reference gas, also known as zero offset. K is the sensitivity coefficient of the sensor. Since the workshop environment is affected by temperature T and humidity H, which will change the zero offset and sensitivity of the sensor, an environmental factor compensation algorithm is introduced. Harmful gas concentration C dg The formula is: Where: C dg Indicates the concentration of harmful gases, V out,gas Represents the output voltage of the sensor in the presence of harmful gases, V offsetcalib (T,H) represents the zero offset of temperature and humidity compensation added during calibration, K calib (T,H) represents the sensitivity coefficients for temperature and humidity compensation added during the calibration process.

6. A plastic woven bag production process safety monitoring system according to claim 5, characterized in that: The smoke sensor module is installed on the top of the workshop and uses a photoelectric smoke sensor to monitor the smoke concentration in the production process in real time. The photoelectric smoke sensor determines the smoke concentration by measuring the degree to which the light beam is absorbed by the smoke. Smoke density C f The expression is: Where: C f Indicates the smoke density, k f It represents the calibration coefficient with the characteristics of the photoelectric smoke sensor and the environmental conditions. I0 represents the light intensity received by the sensor when there is no smoke, that is, the initial light intensity. I represents the light intensity received by the sensor when there is smoke.

7. A plastic woven bag production process safety monitoring system according to claim 6, characterized in that: The static monitoring sensor module is installed on the workshop production line to monitor the static conditions of plastic woven bags and production equipment. By measuring the static potential or static charge, the risk of static accumulation is evaluated. For the total potential V at a point P in the electric field generated by n charge sources, se , each charge source Q i , where i = 1, 2, ..., n, The potential V generated at point P i It can be expressed as: Where: k j is the electrostatic force constant, Q i represents the charge of the i-th charge source, r represents the distance from the point charge Q to point P, r i represents the distance from the i-th charge source to point P; Therefore, the total potential V at point P is se It represents the sum of the potentials generated by all charge sources at point P, that is: n Where: V se It represents the sum of the potentials generated at point P by all charge sources Q.

8. A plastic woven bag production process safety monitoring system according to claim 2, characterized in that: The detection module also includes a monitoring camera and an integrated controller module; The monitoring camera and integrated controller module includes: a monitoring camera and an integrated controller. The monitoring camera is installed in a production workshop. The monitoring camera is also equipped with high-definition imaging and night vision functions. The integrated controller is responsible for receiving data from various sensors and performing real-time processing and analysis.

9. A plastic woven bag production process safety monitoring system according to claim 8, characterized in that: The integrated controller also has data recording and query functions, and can store and analyze historical monitoring data; the abnormality detection and alarm triggering module also includes classification and priority setting of alarm information.

10. The plastic woven bag production process safety monitoring system according to claim 1, characterized in that: The system also has remote access and control functions, allowing managers to remotely view monitoring data, adjust system settings and receive alarm information via the Internet.

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