Workshop Monitoring Method, System, Equipment and Medium Based on Industrial Internet of Things

Abstract

The present application discloses a workshop monitoring method, system, device and medium based on the industrial Internet of Things, relating to the technical field of the Internet of Things. The method includes: obtaining a processing task of a target production line in the workshop, and determining a target production rate and at least one target processing device of the target production line according to the processing task; determining optimal environmental parameters of the at least one target processing device according to the target production rate, and dividing the workshop into at least one environmental adjustment area according to the optimal environmental parameters and the at least one target processing device; for each of the at least one environmental adjustment area, obtaining distribution data of each environmental adjustment terminal in the workshop, and determining target adjustment parameters corresponding to each of the environmental adjustment terminals in the environmental adjustment area according to the distribution data; generating an environmental adjustment instruction according to the target adjustment parameters. The present application has the effect of improving the intelligent level of the workshop.

Description

Technical Field

[0001] This application relates to the technical field of industrial Internet of Things, and particularly to a workshop monitoring method, system, device and medium based on the industrial Internet of Things. Background Art

[0002] In modern industrial production, the monitoring and regulation of the workshop environment are crucial for improving production efficiency, ensuring product quality, and protecting employees' health. Currently, many enterprises still adopt traditional environmental regulation methods, such as simple regulation of mechanical ventilation and air conditioning systems. These methods usually rely on manual monitoring and manual adjustment, lacking real-time feedback, resulting in unstable environmental parameters and being unable to respond in a timely manner to the changing demands within the workshop.

[0003] In addition, although existing sensor devices can monitor temperature, humidity, air quality, etc. to a certain extent, their integration level is not high, and most systems lack effective data connection and collaboration. This makes it difficult to achieve optimized automation and intelligent management of the workshop environment regulation.

[0004] Therefore, overall, the current intelligent level of workshops is still relatively low, and modern technical means have not been fully utilized to achieve efficient and accurate environmental control. With the development of industrial Internet of Things technology, there is great potential for intelligent improvement of future workshop environment regulation, and urgent improvement is needed to enhance production efficiency. Summary of the Invention

[0005] In order to improve the intelligent level of workshops, this application provides a workshop monitoring method, system, device and medium based on the industrial Internet of Things.

[0006] In the first aspect, this application provides a workshop monitoring method based on the industrial Internet of Things, adopting the following technical solutions:

[0007] A workshop monitoring method based on the industrial Internet of Things is applied to an industrial Internet of Things system. The industrial Internet of Things system includes a management platform, a sensing network platform, and an object platform that are sequentially communicatively connected. The method is executed by the management platform and includes:

[0008] Obtain the processing tasks of the target production line in the workshop, and determine the target production rate and at least one target processing device of the target production line according to the processing tasks;

[0009] Determine the optimal environmental parameters of the at least one target processing device according to the target production rate, and divide the workshop into at least one environmental regulation area according to the optimal environmental parameters and the at least one target processing device;

[0010] For each of the at least one environmental conditioning area, obtain the distribution data of each environmental conditioning terminal in the workshop, and determine the target adjustment parameters corresponding to each of the environmental conditioning terminals in the environmental conditioning area according to the distribution data;

[0011] Generate an environmental conditioning instruction according to the target adjustment parameters to control the corresponding environmental conditioning terminals in the at least one environmental conditioning area, so that at least one target processing device in the workshop operates under the corresponding optimal environmental parameters.

[0012] By adopting the above technical solution, obtain the processing tasks of the target production line in the workshop, determine the target production rate and at least one target processing device of the target production line according to the processing tasks, then determine the optimal environmental parameters of at least one target processing device according to the target production rate, divide the workshop into at least one environmental conditioning area according to the optimal environmental parameters and at least one target processing device, and then for each of the at least one environmental conditioning area, obtain the distribution data of each environmental conditioning terminal in the workshop, and determine the target adjustment parameters corresponding to each of the environmental conditioning terminals in the environmental conditioning area according to the distribution data, and finally generate an environmental conditioning instruction according to the target adjustment parameters to control the corresponding environmental conditioning terminals in the at least one environmental conditioning area, so that at least one target processing device in the workshop operates under the corresponding optimal environmental parameters; in the above manner, the intelligent adjustment of the environment everywhere in the workshop is realized. Compared with the manual adjustment method, it can respond to the changing needs in the workshop in a timely manner, and then realize the efficient and precise adjustment and control of the environment everywhere in the workshop, thereby improving the intelligent, automated and informationized level of the workshop, and better meeting the production needs of modern industrial intelligence and automation.

[0013] Optionally, the step of determining the target production rate and at least one target processing device of the target production line according to the processing task includes:

[0014] Obtain the processing quantity, processing deadline and processing procedures of the target production line according to the processing task;

[0015] Determine the target production rate of the target production line according to the processing quantity and the processing procedures, and determine at least one target processing device from the target production line according to the processing procedures.

[0016] By adopting the above technical solution, in order to determine the target production rate and at least one target processing device, obtain the processing quantity, processing deadline and processing procedures of the target production line according to the processing task, then determine the target production rate of the target production line according to the processing quantity and the processing procedures, and determine at least one target processing device from the target production line according to the processing procedures.

[0017] Optionally, the step of determining the optimal environmental parameters of the at least one target processing device according to the target production rate includes:

[0018] Obtain the historical processing rate of the at least one target processing device, and determine the processing rate ratio of the at least one target processing device according to the historical processing rate;

[0019] Determine the target processing rate corresponding to each target processing device according to the target production rate and the processing rate ratio;

[0020] For each target processing device, obtain the evaluation data of the target processing device by the evaluator, where the evaluation data includes rate data and environmental parameter data, and generate a corresponding environmental parameter vector according to the environmental parameter data;

[0021] Fit the data relationship between the rate data and the environmental parameter vector according to the rate data and the environmental parameter vector to obtain a corresponding fitting function;

[0022] Input the target processing rate into the fitting function to obtain the optimal environmental parameters corresponding to the target processing device.

[0023] By adopting the above technical solution, in order to determine the optimal environmental parameters of at least one target processing device, obtain the historical processing rate of at least one target processing device, determine the processing rate ratio of at least one target processing device according to the historical processing rate, then determine the target processing rate corresponding to each target processing device according to the target production rate and the processing rate ratio, then for each target processing device, obtain the evaluation data of the target processing device by the evaluator, the evaluation data includes rate data and environmental parameter data, and generate a corresponding environmental parameter vector according to the environmental parameter data, then fit the data relationship between the rate data and the environmental parameter vector according to the rate data and the environmental parameter vector to obtain a corresponding fitting function, and finally input the target processing rate into the fitting function to obtain the optimal environmental parameters corresponding to the target processing device.

[0024] Optionally, the step of dividing the workshop into at least one environmental regulation area according to the optimal environmental parameters and the at least one target processing device includes:

[0025] Obtain the scan data of the workshop, and generate an environmental model corresponding to the workshop according to the scan data;

[0026] Obtain the preset grid division accuracy, and perform grid division on the internal space of the workshop according to the grid division accuracy and the environmental model to obtain corresponding grid data;

[0027] Determine the target grids and non-target grids according to the grid data; the grids in the internal space include the target grids and the non-target grids, and the target grids are the grids corresponding to the spaces where the at least one target processing device is located;

[0028] Determine the first environmental parameters corresponding to each of the target grids according to the optimal environmental parameters of the at least one target processing device, and determine the second environmental parameters corresponding to each of the non-target grids according to the first environmental parameters;

[0029] Determine the first environmental impact factors corresponding to each of the target grids according to the first environmental parameters corresponding to each of the target grids, and determine the second environmental impact factors corresponding to each of the non-target grids according to the second environmental parameters corresponding to each of the target grids;

[0030] Perform clustering analysis on the grids in the internal space according to the first environmental impact factors and the second environmental impact factors to obtain the corresponding clustering results;

[0031] Merge the grids in the internal space according to the clustering results to obtain at least one environmental regulation area.

[0032] By adopting the above technical solution, in order to divide the workshop into at least one environmental regulation area, obtain the scan data of the workshop, generate the environmental model corresponding to the workshop according to the scan data, then obtain the preset grid division accuracy, and perform grid division on the internal space of the workshop according to the grid division accuracy and the environmental model to obtain the corresponding grid data, and then determine the target grids and non-target grids according to the grid data. The grids in the internal space include the target grids and the non-target grids, and the target grids are the grids corresponding to the spaces where the at least one target processing device is located. Then determine the first environmental parameters corresponding to each of the target grids according to the optimal environmental parameters of the at least one target processing device, and determine the second environmental parameters corresponding to each of the non-target grids according to the first environmental parameters. Then determine the first environmental impact factors corresponding to each of the target grids according to the first environmental parameters corresponding to each of the target grids, and determine the second environmental impact factors corresponding to each of the non-target grids according to the second environmental parameters corresponding to each of the target grids. Then perform clustering analysis on the grids in the internal space according to the first environmental impact factors and the second environmental impact factors to obtain the corresponding clustering results, and finally merge the grids in the internal space according to the clustering results to obtain at least one environmental regulation area.

[0033] Optionally, the first environmental parameters include a first temperature parameter and a first humidity parameter, and the step of determining the first environmental impact factors corresponding to each of the target grids according to the first environmental parameters corresponding to each of the target grids includes:

[0034] Input the first temperature parameter corresponding to each of the target grids into a pre-set temperature influence function to obtain a temperature influence value, and input the first humidity parameter corresponding to each of the target grids into a pre-set humidity influence function to obtain a humidity influence value;

[0035] Obtain the first weight corresponding to the temperature influence value and the second weight corresponding to the humidity influence value, and determine a first environmental influence factor based on the first weight, the second weight, the temperature influence value, and the humidity influence value.

[0036] By adopting the above technical solution, in order to determine the first environmental influence factor corresponding to each target grid, first input the first temperature parameter corresponding to each target grid into a pre-set temperature influence function to obtain a temperature influence value, and input the first humidity parameter corresponding to each target grid into a pre-set humidity influence function to obtain a humidity influence value. Then obtain the first weight corresponding to the temperature influence value and the second weight corresponding to the humidity influence value, and determine the first environmental influence factor based on the first weight, the second weight, the temperature influence value, and the humidity influence value.

[0037] Optionally, the step of determining the target adjustment parameter corresponding to each of the environmental adjustment terminals in the environmental adjustment area according to the distribution data includes:

[0038] For each of the at least one environmental adjustment area, determine the area adjustment source corresponding to the environmental adjustment area according to the environmental model and the distribution data; the area adjustment source is the environmental adjustment terminal in the environmental adjustment area;

[0039] Determine the average environmental parameter of the environmental adjustment area according to the grid data;

[0040] Determine the target adjustment parameter corresponding to each of the environmental adjustment terminals in the environmental adjustment area according to the average environmental parameter.

[0041] By adopting the above technical solution, in order to determine the target adjustment parameter corresponding to each environmental adjustment terminal, for each of the at least one environmental adjustment area, determine the area adjustment source corresponding to the environmental adjustment area according to the environmental model and the distribution data. The area adjustment source is the environmental adjustment terminal in the environmental adjustment area. Then determine the average environmental parameter of the environmental adjustment area according to the grid data, and finally determine the target adjustment parameter corresponding to each of the environmental adjustment terminals in the environmental adjustment area according to the average environmental parameter.

[0042] Optionally, the average environmental parameter includes an average temperature and an average humidity, and the step of determining the average environmental parameter of the environmental adjustment area according to the grid data includes:

[0043] For each of the at least one environmental conditioning area, temperature data and humidity data corresponding to the grids within the environmental conditioning area are obtained according to the grid data, the first environmental parameter, and the second environmental parameter;

[0044] The grid average temperature within the environmental conditioning area is determined according to the temperature data, and the grid average temperature is used as the average temperature parameter of the environmental conditioning area;

[0045] The grid average humidity within the environmental conditioning area is determined according to the humidity data, and the grid average humidity is used as the average humidity parameter of the environmental conditioning area.

[0046] By adopting the above technical solution, in order to determine the average environmental parameters of the environmental conditioning area, for each of the at least one environmental conditioning area, temperature data and humidity data corresponding to the grids within the environmental conditioning area are obtained according to the grid data, the first environmental parameter, and the second environmental parameter. Then, the grid average temperature within the environmental conditioning area is determined according to the temperature data, and the grid average temperature is used as the average temperature parameter of the environmental conditioning area. Finally, the grid average humidity within the environmental conditioning area is determined according to the humidity data, and the grid average humidity is used as the average humidity parameter of the environmental conditioning area.

[0047] In a second aspect, the present application also provides a workshop monitoring system based on the industrial Internet of Things, adopting the following technical solution:

[0048] A workshop monitoring system based on the industrial Internet of Things includes a management platform, a sensing network platform, and an object platform that are communicatively connected in sequence. The sensing network platform is used to collect data through sensors. The object platform includes each production line and the processing equipment in each production line. The management platform is configured with:

[0049] A target production rate determination module, which is used to obtain the processing tasks of the target production line in the workshop and determine the target production rate and at least one target processing equipment of the target production line according to the processing tasks;

[0050] An environmental conditioning area division module, which is used to determine the optimal environmental parameters of the at least one target processing equipment according to the target production rate, and divide the workshop into at least one environmental conditioning area according to the optimal environmental parameters and the at least one target processing equipment;

[0051] An environmental conditioning area generation module, which is used to, for each of the at least one environmental conditioning area, obtain the distribution data of each environmental conditioning terminal in the workshop and determine the target adjustment parameters corresponding to each environmental conditioning terminal within the environmental conditioning area according to the distribution data;

[0052] An environment adjustment instruction generation module, configured to generate an environment adjustment instruction according to the target adjustment parameter, so as to control the corresponding environment adjustment terminals in at least one environment adjustment area, so that at least one target processing device in the workshop operates under the corresponding optimal environment parameters.

[0053] In a third aspect, the present application further provides a computer device, adopting the following technical solution:

[0054] A computer device includes a memory and a processor. A computer program that can run on the processor is stored on the memory. When the processor executes the computer program, the method described in the first aspect is implemented.

[0055] In a fourth aspect, the present application further provides a computer-readable storage medium, adopting the following technical solution:

[0056] A computer-readable storage medium stores a computer program that can be loaded and executed by a processor to implement the method described in the first aspect.

[0057] In summary, the present application at least includes the following beneficial technical effects: obtaining the processing tasks of the target production line in the workshop, determining the target production rate and at least one target processing device of the target production line according to the processing tasks, then determining the optimal environment parameters of at least one target processing device according to the target production rate, and dividing the workshop into at least one environment adjustment area according to the optimal environment parameters and at least one target processing device. Then, for each of the at least one environment adjustment area, obtaining the distribution data of each environment adjustment terminal in the workshop, and determining the target adjustment parameter corresponding to each environment adjustment terminal in the environment adjustment area according to the distribution data. Finally, generating an environment adjustment instruction according to the target adjustment parameter to control the corresponding environment adjustment terminals in at least one environment adjustment area, so that at least one target processing device in the workshop operates under the corresponding optimal environment parameters; through the above method, the intelligent adjustment of the environment everywhere in the workshop is realized. Compared with the manual adjustment method, it can respond to the changing needs in the workshop in a timely manner, and then realize the efficient and accurate adjustment and control of the environment everywhere in the workshop, thereby improving the intelligent, automated and informationized level of the workshop, and better meeting the production needs of modern industrial intelligence and automation. Description of the Drawings

[0058] Figure 1 It is a schematic diagram of the overall process of an embodiment of the present application.

[0059] Figure 2 It is a schematic diagram of the structure of one application scenario of the system in an embodiment of the present application.

[0060] Figure 3 It is a schematic structural diagram of another application scenario of the system according to an embodiment of the present application.

[0061] Figure 4 It is a block diagram of the structure of the computer device of the present application. Specific embodiments

[0062] In order to make the objectives, technical solutions and advantages of the present application more clear and understandable, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0063] The embodiment of the present application discloses a workshop monitoring method based on the industrial Internet of Things.

[0064] Referring to Figure 1 , the workshop monitoring method based on the industrial Internet of Things is applied to an industrial Internet of Things system. The industrial Internet of Things system includes a management platform, a sensing network platform, and an object platform that are communicatively connected in sequence. The method is executed by the management platform and includes:

[0065] Step S11: Obtain the processing tasks of the target production line in the workshop, and determine the target production rate and at least one target processing device of the target production line according to the processing tasks.

[0066] It should be noted that at least one target processing device means that the minimum number of target processing devices is one. There are usually multiple processing devices on the target production line. For different processing tasks, different processing devices on the target production line are usually called for processing. The at least one target processing device is the processing device selected from the target production line according to the processing tasks.

[0067] Step S12: Determine the optimal environmental parameters of at least one target processing device according to the target production rate, and divide the workshop into at least one environmental adjustment area according to the optimal environmental parameters and at least one target processing device.

[0068] Specifically, for each target processing device among the at least one target processing device, determine the optimal environmental parameters of each target processing device according to the target production rate of each target processing device, and divide the workshop into at least one environmental adjustment area according to the optimal environmental parameters of each target processing device and the target processing device.

[0069] Step S13: For each environmental adjustment area among the at least one environmental adjustment area, obtain the distribution data of each environmental adjustment terminal in the workshop, and determine the target adjustment parameters corresponding to each environmental adjustment terminal in the environmental adjustment area according to the distribution data.

[0070] It should be noted that the optimal environmental parameters may include parameters such as temperature, humidity, air flow velocity, and light intensity. For temperature, the temperature in the workshop is monitored and adjusted in real time through air conditioners, heaters or cooling systems to maintain it within the optimal operating temperature range of the equipment. The specific range can be adjusted according to the recommendations of the equipment manufacturer or evaluation data; for humidity, a humidifier or dehumidifier is used to control the relative humidity in the workshop to ensure that the materials and equipment are in a suitable moist environment; for air flow velocity, the air flow velocity can be actively adjusted by installing fans, ventilation systems or air purifiers to improve equipment cooling and the comfort of the working environment; for light intensity, the brightness of the lighting equipment is adjusted, such as using dimmable lamps, to ensure that there is sufficient light in the working area to improve production efficiency and processing accuracy.

[0071] It should be further noted that the environmental adjustment terminal may include a temperature adjustment source, a humidity adjustment source, an air flow adjustment source, a light adjustment source, etc. The temperature adjustment source may be an air conditioner, a heater or a cooling system, etc. The humidity adjustment source may be a humidifier, a dehumidifier, a dryer, etc. The air flow adjustment source may be a fan, a ventilation system, an air purifier, etc. The light adjustment source is usually a lighting fixture.

[0072] Step S14: Generate an environmental adjustment instruction according to the target adjustment parameter to control the corresponding environmental adjustment terminal in at least one environmental adjustment area, so that at least one target processing device in the workshop operates under the corresponding optimal environmental parameters.

[0073] It should be noted that at least one environmental adjustment area means an environmental adjustment area with a quantity of not less than one. Through the target adjustment parameter in step S14, the environmental adjustment terminals in each environmental adjustment area can be adjusted, so that each target processing device in each environmental adjustment area operates under its corresponding optimal environmental parameters, thereby achieving precise control of the environmental parameters in the workshop and ensuring production quality and efficiency at the same time.

[0074] In the above embodiments, the processing tasks of the target production line in the workshop are obtained, and the target production rate of the target production line and at least one target processing device are determined according to the processing tasks. Then, the optimal environmental parameters of at least one target processing device are determined according to the target production rate, and the workshop is divided into at least one environmental regulation area according to the optimal environmental parameters and at least one target processing device. Then, for each of the at least one environmental regulation area, the distribution data of each environmental regulation terminal in the workshop is obtained, and the target regulation parameters corresponding to each environmental regulation terminal in the environmental regulation area are determined according to the distribution data. Finally, an environmental regulation instruction is generated according to the target regulation parameters to control the corresponding environmental regulation terminals in at least one environmental regulation area, so that at least one target processing device in the workshop operates under the corresponding optimal environmental parameters; through the above method, the intelligent regulation of the environment everywhere in the workshop is realized. Compared with the manual regulation method, it can respond to the changing needs in the workshop in a timely manner, and then realize the efficient and accurate regulation and control of the environment everywhere in the workshop, thereby improving the intelligent, automated and informatized level of the workshop, and better meeting the production needs of modern industrial intelligence and automation.

[0075] As a further embodiment of the method, the step of determining the target production rate of the target production line and at least one target processing device according to the processing tasks includes:

[0076] Step S21, obtaining the processing quantity, processing deadline and processing procedures of the target production line according to the processing tasks.

[0077] It should be noted that the task information to be processed is extracted from the production scheduling system or the work order management system. These information usually include the processing quantity, processing deadline and processing procedures. The processing quantity represents the number of product pieces to be produced in the order, the processing deadline represents the delivery time of the order, which determines the time frame of production, and the processing procedures represent the various procedures to be executed, which may include cutting, welding, assembly, etc.

[0078] Step S22, determining the target production rate of the target production line according to the processing quantity and processing procedures, and determining at least one target processing device from the target production line according to the processing procedures.

[0079] It should be noted that the target production rate is calculated based on the processing quantity and processing deadline. The formula is usually: Target production rate = Processing quantity / Processing deadline (hours). This target production rate represents the number of production pieces that need to be completed per unit of time. According to the requirements of the processing procedures, evaluate the available production equipment, including the processing capacity, efficiency, and working mode of the equipment. Select at least one piece of equipment that meets the requirements of the processing procedures. The following factors may need to be considered: Whether the maximum production capacity of the equipment meets the target production rate; The availability of the equipment, confirm whether the equipment is available as planned; The type of equipment required for specific procedures.

[0080] In the above embodiment, in order to determine the target production rate and at least one target processing equipment, the processing quantity, processing deadline, and processing procedures of the target production line are obtained according to the processing task, and then the target production rate of the target production line is determined based on the processing quantity and processing procedures, and at least one target processing equipment is determined from the target production line according to the processing procedures.

[0081] As a further embodiment of the method, the steps of determining the optimal environmental parameters of at least one target processing equipment according to the target production rate include:

[0082] Step S31, obtain the historical processing rates of at least one target processing equipment, and determine the processing rate ratios of at least one target processing equipment according to the historical processing rates.

[0083] Step S32, determine the target processing rates corresponding to each target processing equipment according to the target production rate and the processing rate ratios.

[0084] Step S33, for each target processing equipment, obtain the evaluation data of the target processing equipment by the evaluators. The evaluation data includes rate data and environmental parameter data, and generate the corresponding environmental parameter vector according to the environmental parameter data.

[0085] Step S34, fit the data relationship between the rate data and the environmental parameter vector according to the rate data and the environmental parameter vector to obtain the corresponding fitting function.

[0086] Step S35, input the target processing rate into the fitting function to obtain the optimal environmental parameters corresponding to the target processing equipment.

[0087] In the above embodiments, in order to determine the optimal environmental parameters of at least one target processing device, the historical processing rate of at least one target processing device is obtained, and the processing rate ratio of at least one target processing device is determined according to the historical processing rate. Then, the target processing rate corresponding to each target processing device is determined according to the target production rate and the processing rate ratio. Then, for each target processing device, the evaluation data of the target processing device by the evaluator is obtained. The evaluation data includes rate data and environmental parameter data, and the corresponding environmental parameter vector is generated according to the environmental parameter data. Then, the data relationship between the rate data and the environmental parameter vector is fitted according to the rate data and the environmental parameter vector to obtain the corresponding fitting function. Finally, the target processing rate is input into the fitting function to obtain the optimal environmental parameters corresponding to the target processing device.

[0088] As a further embodiment of the method, the step of dividing the workshop into at least one environmental regulation area according to the optimal environmental parameters and at least one target processing device includes:

[0089] Step S41, obtaining the scan data of the workshop and generating the environmental model corresponding to the workshop according to the scan data.

[0090] Step S42, obtaining the preset grid division accuracy and dividing the internal space of the workshop into grids according to the grid division accuracy and the environmental model to obtain the corresponding grid data.

[0091] Step S43, determining the target grids and non-target grids according to the grid data.

[0092] Among them, the grids of the internal space include target grids and non-target grids, and the target grids are the grids corresponding to the spaces where at least one target processing device is located.

[0093] It can be understood that the non-target grids are the other grids in the grids of the internal space except the target grids.

[0094] Step S44, determining the first environmental parameters corresponding to each target grid according to the optimal environmental parameters of at least one target processing device, and determining the second environmental parameters corresponding to each non-target grid according to the first environmental parameters.

[0095] Step S45, determining the first environmental impact factor corresponding to each target grid according to the first environmental parameters corresponding to each target grid, and determining the second environmental impact factor corresponding to each non-target grid according to the second environmental parameters corresponding to each target grid.

[0096] Step S46, performing clustering analysis on the grids of the internal space according to the first environmental impact factor and the second environmental impact factor to obtain the corresponding clustering result.

[0097] Step S47: Merge the grids of the internal space according to the clustering result to obtain at least one environmental regulation area.

[0098] In the above embodiment, in order to divide the workshop into at least one environmental regulation area, the scanning data of the workshop is acquired, and an environmental model corresponding to the workshop is generated according to the scanning data. Then, the preset grid division accuracy is obtained, and the internal space of the workshop is divided into grids according to the grid division accuracy and the environmental model to obtain the corresponding grid data. Then, the target grids and non-target grids are determined according to the grid data. The grids of the internal space include target grids and non-target grids. The target grids are the grids corresponding to the spaces where at least one target processing device is located. Then, the first environmental parameters corresponding to each target grid are determined according to the optimal environmental parameters of at least one target processing device, and the second environmental parameters corresponding to each non-target grid are determined according to the first environmental parameters. Then, the first environmental impact factors corresponding to each target grid are determined according to the first environmental parameters corresponding to each target grid, and the second environmental impact factors corresponding to each non-target grid are determined according to the second environmental parameters corresponding to each non-target grid. Then, cluster analysis is performed on the grids of the internal space according to the first environmental impact factors and the second environmental impact factors to obtain the corresponding clustering result. Finally, the grids of the internal space are merged according to the clustering result to obtain at least one environmental regulation area.

[0099] As a further implementation of the method, the first environmental parameters include the first temperature parameter and the first humidity parameter. The step of determining the first environmental impact factor corresponding to each target grid according to the first environmental parameters corresponding to each target grid includes:

[0100] Step S51: Input the first temperature parameters corresponding to each target grid into a preset temperature impact function to obtain temperature impact values, and input the first humidity parameters corresponding to each target grid into a preset humidity impact function to obtain humidity impact values.

[0101] It should be noted that in this application, the temperature impact function is:

[0102]

[0103] where t represents the first temperature parameter, is a critical low temperature, is a critical high temperature.

[0104] The humidity impact function is:

[0105]

[0106] where h represents the first humidity parameter, is a critical low temperature, is a critical high temperature.

[0107] Step S52: Obtain the first weight corresponding to the temperature influence value and the second weight corresponding to the humidity influence value, and determine the first environmental influence factor according to the first weight, the second weight, the temperature influence value, and the humidity influence value.

[0108] It should be noted that the calculation method of the second environmental influence factor in step S45 is the same as that of the first environmental influence factor. Specifically, the second environmental influence factor includes a second temperature parameter and a second humidity parameter. The second temperature parameters corresponding to each non-target grid are respectively input into a pre-set temperature influence function to obtain a second temperature influence value, and the second humidity parameters corresponding to each non-target grid are input into a pre-set humidity influence function to obtain a second humidity influence value; obtain the first weight corresponding to the temperature influence value and the second weight corresponding to the humidity influence value, and determine the second environmental influence factor according to the first weight, the second weight, the second temperature influence value, and the second humidity influence value.

[0109] In the above embodiment, in order to determine the first environmental influence factor corresponding to each target grid, the first temperature parameters corresponding to each target grid are first input into a pre-set temperature influence function to obtain a temperature influence value, and the first humidity parameters corresponding to each target grid are input into a pre-set humidity influence function to obtain a humidity influence value. Then, obtain the first weight corresponding to the temperature influence value and the second weight corresponding to the humidity influence value, and determine the first environmental influence factor according to the first weight, the second weight, the temperature influence value, and the humidity influence value.

[0110] As a further embodiment of the method, the step of determining the target adjustment parameter corresponding to each environmental adjustment terminal in the environmental adjustment area according to the distribution data includes:

[0111] Step S61: For each environmental adjustment area in at least one environmental adjustment area, determine the area adjustment source corresponding to the environmental adjustment area according to the environmental model and the distribution data.

[0112] Among them, the area adjustment source is the environmental adjustment terminal in the environmental adjustment area.

[0113] Step S62: Determine the average environmental parameter of the environmental adjustment area according to the grid data.

[0114] Step S63: Determine the target adjustment parameter corresponding to each environmental adjustment terminal in the environmental adjustment area according to the average environmental parameter.

[0115] It should be noted that in step S63, the average environmental parameters can be used as the target adjustment parameters corresponding to each environmental adjustment terminal in the environmental adjustment area, or the target adjustment parameters can be set to values higher or lower than the average environmental parameters according to the temperature difference and humidity difference inside and outside the workshop.

[0116] In the above embodiment, in order to determine the target adjustment parameters corresponding to each environmental adjustment terminal, for each environmental adjustment area in at least one environmental adjustment area, the area adjustment source corresponding to the environmental adjustment area is determined according to the environmental model and distribution data. The area adjustment source is the environmental adjustment terminal in the environmental adjustment area, then the average environmental parameters of the environmental adjustment area are determined according to the grid data, and finally the target adjustment parameters corresponding to each environmental adjustment terminal in the environmental adjustment area are determined according to the average environmental parameters.

[0117] As a further embodiment of the method, the average environmental parameters include the average temperature and the average humidity. The step of determining the average environmental parameters of the environmental adjustment area according to the grid data includes:

[0118] Step S71, for each environmental adjustment area in at least one environmental adjustment area, obtain the temperature data and humidity data corresponding to the grid in the environmental adjustment area according to the grid data, the first environmental parameter, and the second environmental parameter.

[0119] Step S72, determine the grid average temperature in the environmental adjustment area according to the temperature data, and use the grid average temperature as the average temperature parameter of the environmental adjustment area.

[0120] Step S73, determine the grid average humidity in the environmental adjustment area according to the humidity data, and use the grid average humidity as the average humidity parameter of the environmental adjustment area.

[0121] In the above embodiment, in order to determine the average environmental parameters of the environmental adjustment area, for each environmental adjustment area in at least one environmental adjustment area, obtain the temperature data and humidity data corresponding to the grid in the environmental adjustment area according to the grid data, the first environmental parameter, and the second environmental parameter, then determine the grid average temperature in the environmental adjustment area according to the temperature data, and use the grid average temperature as the average temperature parameter of the environmental adjustment area, and finally determine the grid average humidity in the environmental adjustment area according to the humidity data, and use the grid average humidity as the average humidity parameter of the environmental adjustment area.

[0122] The embodiment of the present application also discloses a workshop monitoring system based on the industrial Internet of Things.

[0123] Reference Figure 2, A workshop monitoring system based on the industrial Internet of Things, including a management platform, a sensing network platform, and an object platform that are sequentially communicatively connected. The sensing network platform is used to collect data through sensors. The object platform includes each production line and the processing equipment in each production line. The management platform is configured with:

[0124] A target production rate determination module, configured to obtain the processing tasks of the target production line in the workshop, and determine the target production rate of the target production line and at least one target processing equipment according to the processing tasks;

[0125] An environmental regulation area division module, configured to determine the optimal environmental parameters of at least one target processing equipment according to the target production rate, and divide the workshop into at least one environmental regulation area according to the optimal environmental parameters and at least one target processing equipment;

[0126] An environmental regulation area generation module, configured to, for each environmental regulation area among at least one environmental regulation area, obtain the distribution data of each environmental regulation terminal in the workshop, and determine the target regulation parameters corresponding to each environmental regulation terminal in the environmental regulation area according to the distribution data;

[0127] An environmental regulation instruction generation module, configured to generate an environmental regulation instruction according to the target regulation parameters to control the corresponding environmental regulation terminals in at least one environmental regulation area, so that at least one target processing equipment in the workshop operates under the corresponding optimal environmental parameters.

[0128] The overall framework of another application scenario of the workshop monitoring system based on the industrial Internet of Things in this application is as Figure 3 shown, and may include a user platform, a service platform, a management platform, a sensing network platform, and an object platform that interact sequentially, forming a five-platform architecture based on the Internet of Things. Among them, the management platform includes a target production rate determination module, an environmental regulation area division module, an environmental regulation area generation module, and an environmental regulation instruction generation module; the service platform includes a service general database, n service sub-platforms, and n service sub-databases. Each service sub-platform can communicate with the corresponding service sub-database, and each service sub-database can communicate with the service general database.

[0129] Specifically, in the above-mentioned another application scenario, the workshop monitoring system based on the industrial Internet of Things includes a management platform, and the management platform is configured to: obtain the processing tasks of the target production line in the workshop, and determine the target production rate and at least one target processing device of the target production line according to the processing tasks; determine the optimal environmental parameters of at least one target processing device according to the target production rate, and divide the workshop into at least one environmental regulation area according to the optimal environmental parameters and at least one target processing device; for each of the at least one environmental regulation area, obtain the distribution data of each environmental regulation terminal in the workshop, and determine the target regulation parameters corresponding to each environmental regulation terminal in the environmental regulation area according to the distribution data; generate an environmental regulation instruction according to the target regulation parameters to control the corresponding environmental regulation terminals in at least one environmental regulation area, so that at least one target processing device in the workshop operates under the corresponding optimal environmental parameters.

[0130] Through the interaction between the various functional platforms of the workshop monitoring system based on the industrial Internet of Things based on the above three-platform or five-platform, a perfect closed-loop information operation logic is established, ensuring the orderly operation of perception information and control information, and realizing the intelligent management of equipment.

[0131] The workshop monitoring system based on the industrial Internet of Things of the present invention can implement any one of the methods in the workshop monitoring method based on the industrial Internet of Things, and the specific working process of the workshop monitoring system based on the industrial Internet of Things of the present invention can refer to the corresponding process in the above-mentioned workshop monitoring method based on the industrial Internet of Things.

[0132] The embodiment of the present application also discloses a computer device.

[0133] Reference Figure 4 , a computer device includes a memory and a processor, a computer program is stored on the memory and can run on the processor, and when the processor executes the computer program, it implements any one of the above-mentioned workshop monitoring methods based on the industrial Internet of Things.

[0134] The embodiment of the present application also discloses a computer-readable storage medium.

[0135] A computer-readable storage medium stores a computer program that can be loaded and executed by a processor to implement any one of the above-mentioned workshop monitoring methods based on the industrial Internet of Things.

[0136] Among them, the computer-readable storage medium can be any tangible medium that contains or stores a program, and this program can be used by or in combination with an instruction execution system, device, or device; the program code contained on the computer-readable medium can be transmitted by any suitable medium, including but not limited to wireless, wire, optical fiber, RF, etc., or any suitable combination of the above.

[0137] The above are all preferred embodiments of the present application, and the protection scope of the present application is not limited thereby. Any feature disclosed in this specification (including the abstract and drawings), unless specifically described, can be replaced by other equivalent or similar-purpose alternative features. That is, unless specifically described, each feature is only an example of a series of equivalent or similar features.

Claims

1. A workshop monitoring method based on the industrial Internet of Things, characterized in that, Applied to an industrial Internet of Things system, the industrial Internet of Things system includes a management platform, a sensing network platform, and an object platform that are communicatively connected in sequence. The method is executed by the management platform and includes: Obtain the processing tasks of the target production line in the workshop, and determine the target production rate and at least one target processing device of the target production line according to the processing tasks; Determine the optimal environmental parameters of the at least one target processing device according to the target production rate, and divide the workshop into at least one environmental adjustment area according to the optimal environmental parameters and the at least one target processing device; For each of the at least one environmental adjustment area, obtain the distribution data of each environmental adjustment terminal in the workshop, and determine the target adjustment parameters corresponding to each environmental adjustment terminal in the environmental adjustment area according to the distribution data; Generate an environmental adjustment instruction according to the target adjustment parameters to control the corresponding environmental adjustment terminals in the at least one environmental adjustment area, so that the at least one target processing device in the workshop operates under the corresponding optimal environmental parameters; The step of determining the optimal environmental parameters of the at least one target processing device according to the target production rate includes: Obtain the historical processing rates of the at least one target processing device, and determine the processing rate ratios of the at least one target processing device according to the historical processing rates; Determine the target processing rates corresponding to the respective target processing devices according to the target production rate and the processing rate ratios; For each target processing device, obtain the evaluation data of the evaluation personnel on the target processing device. The evaluation data includes rate data and environmental parameter data, and generate a corresponding environmental parameter vector according to the environmental parameter data; Fit the data relationship between the rate data and the environmental parameter vector according to the rate data and the environmental parameter vector to obtain a corresponding fitting function; Input the target processing rate into the fitting function to obtain the optimal environmental parameters corresponding to the target processing device; The step of dividing the workshop into at least one environmental adjustment area according to the optimal environmental parameters and the at least one target processing device includes: Obtain the scan data of the workshop, and generate an environmental model corresponding to the workshop according to the scan data; Obtain the preset grid division accuracy, and divide the internal space of the workshop into grids according to the grid division accuracy and the environmental model to obtain corresponding grid data; Determine the target grids and non-target grids according to the grid data; the grids of the internal space include the target grids and non-target grids, and the target grids are the grids corresponding to the spaces where the at least one target processing device is located; Determine the first environmental parameters corresponding to each target grid according to the optimal environmental parameters of the at least one target processing device, and determine the second environmental parameters corresponding to each non-target grid according to the first environmental parameters; Determine the first environmental impact factors corresponding to each of the target grids according to the first environmental parameters corresponding to each of the target grids, and determine the second environmental impact factors corresponding to each of the non-target grids according to the second environmental parameters corresponding to each of the target grids; Perform clustering analysis on the grids in the internal space according to the first environmental impact factor and the second environmental impact factor to obtain the corresponding clustering results; Merge the grids in the internal space according to the clustering results to obtain at least one environmental regulation area.

2. The workshop monitoring method based on industrial Internet of Things according to claim 1, characterized in that The step of determining the target production rate of the target production line and at least one target processing device according to the processing task includes: Obtain the processing quantity, processing deadline, and processing procedures of the target production line according to the processing task; Determine the target production rate of the target production line according to the processing quantity and the processing procedures, and determine at least one target processing device from the target production line according to the processing procedures.

3. The workshop monitoring method based on industrial Internet of Things according to claim 1, characterized in that, The first environmental parameters include first temperature parameters and first humidity parameters. The step of determining the first environmental impact factors corresponding to each of the target grids according to the first environmental parameters corresponding to each of the target grids includes: Input the first temperature parameters corresponding to each of the target grids into a pre-set temperature impact function respectively to obtain temperature impact values, and input the first humidity parameters corresponding to each of the target grids into a pre-set humidity impact function to obtain humidity impact values; Obtain the first weight corresponding to the temperature impact value and the second weight corresponding to the humidity impact value, and determine the first environmental impact factor according to the first weight, the second weight, the temperature impact value, and the humidity impact value.

4. The workshop monitoring method based on the industrial Internet of Things according to claim 1, characterized in that The step of determining the target adjustment parameters corresponding to each of the environmental adjustment terminals in the environmental adjustment area according to the distribution data includes: For each of the at least one environmental adjustment area, determine the area adjustment source corresponding to the environmental adjustment area according to the environmental model and the distribution data; the area adjustment source is the environmental adjustment terminal in the environmental adjustment area; Determine the average environmental parameters of the environmental adjustment area according to the grid data; Determine the target adjustment parameters corresponding to each of the environmental adjustment terminals in the environmental adjustment area according to the average environmental parameters.

5. The workshop monitoring method based on industrial Internet of Things according to claim 4, characterized in that The average environmental parameters include average temperature and average humidity. The step of determining the average environmental parameters of the environmental adjustment area according to the grid data includes: For each of the at least one environmental adjustment area, obtain the temperature data and humidity data corresponding to the grids in the environmental adjustment area according to the grid data, the second environmental parameters, and the second environmental parameters; Determine the grid average temperature in the environmental adjustment area according to the temperature data, and use the grid average temperature as the average temperature parameter of the environmental adjustment area; Determine the grid average humidity in the environmental adjustment area according to the humidity data, and use the grid average humidity as the average humidity parameter of the environmental adjustment area.

6. A workshop monitoring system based on the industrial Internet of Things, characterized in that, It includes a management platform, a sensor network platform, and an object platform that are communicatively connected in sequence. The sensor network platform is used to collect data through sensors. The object platform includes each production line and the processing equipment in each production line. The management platform is configured with: A target production rate determination module, which is used to obtain the processing tasks of the target production line in the workshop and determine the target production rate of the target production line and at least one target processing equipment according to the processing tasks; An environmental regulation area division module, which is used to determine the optimal environmental parameters of the at least one target processing equipment according to the target production rate, and divide the workshop into at least one environmental regulation area according to the optimal environmental parameters and the at least one target processing equipment, where the optimal environmental parameters include temperature, humidity, air flow velocity, and light intensity; An environmental regulation area generation module, which is used to, for each of the at least one environmental regulation area, obtain the distribution data of each environmental regulation terminal in the workshop and determine the target regulation parameters corresponding to each environmental regulation terminal in the environmental regulation area according to the distribution data; An environmental regulation instruction generation module, which is used to generate an environmental regulation instruction according to the target regulation parameters to control the corresponding environmental regulation terminals in the at least one environmental regulation area, so that the at least one target processing equipment in the workshop operates under the corresponding optimal environmental parameters; The step of determining the optimal environmental parameters of the at least one target processing equipment according to the target production rate includes: Obtaining the historical processing rate of the at least one target processing equipment and determining the processing rate ratio of the at least one target processing equipment according to the historical processing rate; Determining the target processing rate corresponding to each target processing equipment according to the target production rate and the processing rate ratio; For each target processing equipment, obtaining the evaluation data of the evaluation personnel on the target processing equipment, where the evaluation data includes rate data and environmental parameter data, and generating a corresponding environmental parameter vector according to the environmental parameter data; Fitting the data relationship between the rate data and the environmental parameter vector according to the rate data and the environmental parameter vector to obtain a corresponding fitting function; Inputting the target processing rate into the fitting function to obtain the optimal environmental parameters corresponding to the target processing equipment; The step of dividing the workshop into at least one environmental regulation area according to the optimal environmental parameters and the at least one target processing equipment includes: Obtaining the scan data of the workshop and generating an environmental model corresponding to the workshop according to the scan data; Obtaining the preset grid division accuracy and dividing the internal space of the workshop into grids according to the grid division accuracy and the environmental model to obtain corresponding grid data; Determining the target grids and non-target grids according to the grid data; the grids in the internal space include the target grids and the non-target grids, and the target grids are the grids corresponding to the spaces where the at least one target processing equipment is located; Determine the first environmental parameter corresponding to each of the target grids according to the optimal environmental parameters of the at least one target processing device, and determine the second environmental parameter corresponding to each of the non-target grids according to the first environmental parameter; Determine the first environmental impact factor corresponding to each of the target grids according to the first environmental parameter corresponding to each of the target grids, and determine the second environmental impact factor corresponding to each of the non-target grids according to the second environmental parameter corresponding to each of the non-target grids; Perform clustering analysis on the grids of the internal space according to the first environmental impact factor and the second environmental impact factor to obtain the corresponding clustering result; Merge the grids of the internal space according to the clustering result to obtain at least one environmental regulation area.

7. A computer device, characterized in that, It includes a memory and a processor. A computer program that can run on the processor is stored on the memory. When the processor executes the computer program, the method described in any one of claims 1 to 5 is implemented.

8. A computer-readable storage medium, characterized in that, A computer program is stored that can be loaded and executed by a processor to implement the method described in any one of claims 1 to 5.

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