Intelligent control method and device based on data perception of steamed bun all-in-one machine

Abstract

The invention relates to the technical field of food processing, in particular to an intelligent control method and device based on data perception of a steamed bun all-in-one machine, which adopts an advanced sensor technology and a data analysis technology, realizes intelligent control of the steamed bun all-in-one machine by monitoring and analyzing the running state and parameters of the steamed bun all-in-one machine in real time, and improves the working efficiency of the steamed bun all-in-one machine. Therefore, the production efficiency is greatly improved, the energy consumption is reduced, the waste is reduced, and the quality and the safety of products are ensured. Meanwhile, the intelligent control method has high expandability and customizability, personalized setting and optimization can be carried out according to different production environments and requirements, a more flexible and convenient control mode is provided for a user, and a more efficient and optimized production management mode is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of food processing, and in particular to an intelligent control method and device based on data perception of a steamed bread all-in-one machine. Background Art

[0002] With the development of science and technology, the food processing industry has also developed rapidly. Especially in recent years, in order to meet consumers' requirements for food taste and quality, various new food processing equipment have emerged. Among them, the steamed bun machine is a new type of food processing equipment. It adopts automatic control technology to realize automatic steamed bun production, greatly improving production efficiency and reducing labor costs.

[0003] However, the traditional control method of the steamed bun machine mainly relies on the operator's experience for manual control, and this method still has some problems. For example, the operator needs to constantly observe and adjust the machine's working status and parameters during the production process, which is very labor-intensive and resource-intensive; at the same time, due to the differences in different production environments, the operator needs to perform personalized control for different situations, which also increases production costs.

[0004] Therefore, it is necessary to develop an intelligent control method based on data perception of the steamed bun machine to realize intelligent control of the machine, so as to improve production efficiency, reduce energy consumption, reduce waste, and ensure product quality and safety. Summary of the invention

[0005] The purpose of the present invention is to overcome the shortcomings of the prior art and to propose an intelligent control method and device based on data perception of a steamed bun machine.

[0006] The technical solution adopted by the present invention to solve the technical problem is:

[0007] An intelligent control method based on data perception of a steamed bread machine comprises the following steps:

[0008] Obtaining the operating status information of the steamed bun machine; the operating status information includes the operating status of the dough mixer, the operating status of the dough conveyor, the operating status of the steamed bun forming machine, and the operating status of the water adder;

[0009] Acquire real-time parameter information during the operation of the steamed bun machine; the real-time parameter information includes the dough mixing speed of the dough mixer, the temperature, humidity, weight, and fermentation time of the dough in the dough mixer, the temperature, amount, and speed of the water adder, the conveying speed of the dough conveyor, the forming speed of the steamed bun forming machine, and the number of steamed buns;

[0010] According to the acquired operation status information and real-time parameter information, the current production status is calculated and corresponding control instructions are generated;

[0011] Execute the generated control instructions to control the operation of the steamed bun machine;

[0012] According to the running status information, real-time parameter information and execution results of the control instructions of the steamed bun machine, the production status is continuously updated, and the control instructions are regenerated as needed;

[0013] Provides a real-time production status monitoring interface for operators to monitor and manage.

[0014] Furthermore, according to the acquired operation status information and real-time parameter information, the current production status is calculated and corresponding control instructions are generated, which specifically includes the following steps:

[0015] Preprocess the collected real-time parameter information, including denoising, filtering, normalization and other operations to improve data quality;

[0016] Establish a statistical analysis model to analyze and calculate the dough mixing speed of the dough mixer, the temperature, humidity, weight, fermentation time of the dough in the dough mixer, the temperature, water addition amount, and water addition speed of the water adder, integrate the operation status information, and calculate the current dough fermentation degree;

[0017] Multiple control instructions are planned according to the degree of dough fermentation. The multiple control instructions are integrated with the conveying speed of the dough conveyor, the forming speed of the steamed bun forming machine, and the steamed bun count to obtain the optimal control instruction.

[0018] Furthermore, the real-time parameter information is subjected to noise reduction and smoothing processing by using mean filtering or high filtering.

[0019] Furthermore, the statistical analysis model is:

[0020]

[0021]

[0022] Among them, s and r are variable relationship coefficients, and x i are the mean and the ith observation of the variable and surface velocity, respectively, and i are the mean and the i-th observation value of the temperature of the variable dough, and z i are the mean and the i-th observation value of the variable dough humidity, and a i are the mean and the i-th observation value of the variable dough weight, and b i are the mean and the i-th observation value of the variable dough fermentation time respectively; and c iare the mean and the i-th observation value of the variable water heater temperature, and d i are the mean and the i-th observation value of the variable water adding amount of the water adding device, and g i are the mean and the i-th observation value of the variable water adding speed of the water adder respectively.

[0023] Furthermore, the fusion operation status information is used to calculate the current dough fermentation degree, including:

[0024] The fused operation status information includes fault alarm information, maintenance record information, continuous operation time information, etc. of each device;

[0025] The random forest learning method is used to process the nonlinear relationship of the operating status information of each device;

[0026] The nonlinear relationship of the operating status information of each device is integrated with the statistical analysis model to obtain the current dough fermentation degree W:

[0027]

[0028] Among them, z is the nonlinear relationship coefficient of the operating status information of each device; when W is not less than the preset value, the fermentation degree meets the requirements.

[0029] Furthermore, multiple control instructions are planned according to the dough fermentation degree. The multiple control instructions are integrated with the conveying speed of the dough conveyor, the forming speed of the steamed bun forming machine, and the steamed bun count to obtain the optimal control instructions, which specifically include:

[0030] The relationship model between the steamed bun count H and the dough fermentation degree W, the conveying speed S, and the forming speed M of the steamed bun forming machine is established:

[0031] H = k1W + k2S + k3M;

[0032] Among them, k1, k2, and k3 are weight coefficients. The steamed bun count H can reflect the progress of production. The production speed can be changed by adjusting the dough fermentation degree W, the conveying speed S, and the forming speed M of the steamed bun forming machine.

[0033] The present invention also provides another technical solution:

[0034] An intelligent control device based on data perception of a steamed bun machine is used to implement the intelligent control method based on data perception of a steamed bun machine as in Example 1, the device comprising a dough mixer, a dough conveyor, a steamed bun forming machine, a water adder, an electric control unit, a movable platform and a control system; the control system comprises:

[0035] The information collection module is used to collect the operating status information of the steamed bun machine and the real-time parameter information during the operation process; the required information can be collected through advanced sensors and other technologies;

[0036] Data processing module, used to process the operation status information and real-time parameter information and generate control instructions;

[0037] An execution module controls the operation of the steamed bun machine according to control instructions;

[0038] A storage module is used to store raw data and processed data information;

[0039] The human-computer interaction module is used to provide a real-time production status monitoring interface for operators to monitor and manage.

[0040] Technical effects of the present invention:

[0041] Compared with the prior art, the intelligent control method based on data perception of the steamed bread machine of the present invention adopts advanced sensor technology and data analysis technology, and realizes intelligent control of the steamed bread machine by real-time monitoring and analysis of its operating status and parameters, thereby greatly improving production efficiency, reducing energy consumption, reducing waste, and ensuring product quality and safety. At the same time, the intelligent control method of the present invention also has strong scalability and customizability, and can be personalized and optimized according to different production environments and needs, providing users with a more flexible and convenient control method, and realizing a more efficient and optimized production management mode. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 This is a structural block diagram of the intelligent control device based on data perception of the steamed bun machine in the present invention. DETAILED DESCRIPTION

[0043] In order to make the purpose, technical solution and advantages of the embodiments of the present invention more clear, the technical solution in the embodiments of the present invention is clearly and completely described below in conjunction with the accompanying drawings.

[0044] Embodiment 1:

[0045] like Figure 1 As shown, the present embodiment involves an intelligent control method based on data perception of a steamed bun machine, comprising the following steps:

[0046] Step 1, obtaining the operating status information of the steamed bun machine; the operating status information includes the operating status of the dough mixer, the operating status of the dough conveyor, the operating status of the steamed bun forming machine, and the operating status of the water adder.

[0047] Step 2, obtaining real-time parameter information during the operation of the steamed bun machine; the real-time parameter information includes the kneading speed of the dough mixer, the temperature, humidity, weight, and fermentation time of the dough in the dough mixer, the temperature, amount, and speed of the water adder, the conveying speed of the noodle conveyor, the forming speed of the steamed bun forming machine, the steamed bun count, etc.

[0048] Step 3: Calculate the current production status based on the acquired operation status information and real-time parameter information, and generate corresponding control instructions, which specifically includes the following steps:

[0049] Preprocess the collected real-time parameter information, including denoising, mean filtering, normalization and other operations to improve data quality;

[0050] A statistical analysis model is established to analyze and calculate the dough mixing speed of the dough mixer, the temperature, humidity, weight, fermentation time of the dough in the dough mixer, the temperature, water addition amount, and water addition speed of the water adder after the treatment. The statistical analysis model is:

[0051]

[0052]

[0053] Among them, s and r are variable relationship coefficients, and x i are the mean and the ith observation of the variable and surface velocity, respectively, and i are the mean and the i-th observation value of the temperature of the variable dough, and z i are the mean and the i-th observation value of the variable dough humidity, and a i are the mean and the i-th observation value of the variable dough weight, and b i are the mean and the i-th observation value of the variable dough fermentation time respectively; and c i are the mean and the i-th observation value of the variable water heater temperature, and d i are the mean and the i-th observation value of the variable water adding amount of the water adding device, and g i are the mean and the i-th observation value of the variable water adding speed of the water adding device;

[0054] Integrate the running status information to calculate the current dough fermentation degree, including:

[0055] The fused operation status information includes fault alarm information, maintenance record information, continuous operation time information, etc. of each device;

[0056] The random forest learning method is used to process the nonlinear relationship of the operating status information of each device;

[0057] The nonlinear relationship of the operating status information of each device is integrated with the statistical analysis model to obtain the current dough fermentation degree W:

[0058]

[0059] Among them, z is the nonlinear relationship coefficient of the operating status information of each device; when W is not less than the preset value, the fermentation degree meets the requirements; when W is less than the preset value, the variable relationship coefficients r, s and the nonlinear relationship coefficient z are analyzed, and the operating status information and historical data are combined to further analyze potential problems.

[0060] According to the degree of dough fermentation, multiple control instructions are planned. The multiple control instructions are integrated with the conveying speed of the dough conveyor, the forming speed of the steamed bun forming machine, and the steamed bun count to obtain the optimal control instructions, including:

[0061] The relationship model between the steamed bun count H and the dough fermentation degree W, the conveying speed S, and the forming speed M of the steamed bun forming machine is established:

[0062] H = k1W + k2S + k3M;

[0063] Among them, k1, k2, and k3 are weight coefficients. The steamed bun count H can reflect the progress of production. If H is not less than the threshold, it means that there is no problem with the production line. The dough fermentation degree W, the conveying speed S, and the forming speed M of the steamed bun forming machine can be adjusted to increase the production speed. Conversely, the dough fermentation degree W, the conveying speed S, and the forming speed M of the steamed bun forming machine can be adjusted to slow down the production speed.

[0064] Step 4: Execute the generated control instructions to control the operation of the steamed bun machine;

[0065] Step 5: According to the running status information, real-time parameter information and execution results of the control instructions of the steamed bun machine, the production status is continuously updated, and the control instructions are regenerated as needed;

[0066] Step 6: Provide a real-time production status monitoring interface for operators to monitor and manage.

[0067] The present invention integrates dough kneading, dough conveying and steamed bun forming in one device, realizes intelligent control, can monitor key parameters in the production process in real time, and intelligently adjusts production conditions according to parameter changes, ensures the stability and consistency of product quality, improves production efficiency, improves product quality, and reduces energy consumption and labor costs. The present invention has stronger flexibility and scalability, and can quickly adjust parameters according to different production needs to meet diverse production needs.

[0068] Embodiment 2:

[0069] The present embodiment provides an intelligent control device based on data perception of a steamed bun machine, which is used to implement the intelligent control method based on data perception of a steamed bun machine as in Example 1, wherein the device includes a dough mixer, a dough conveyor, a steamed bun forming machine, a watering device, an electric control unit, a movable platform and a control system; the control system includes an information acquisition module, a data processing module, an execution module, a storage module and a human-computer interaction module. The information acquisition module is used to collect the operating status information of the steamed bun machine and the real-time parameter information during the operation process. The required information can be collected through advanced sensors and other technologies; the data processing module is used to process the operating status information and real-time parameter information, and generate control instructions; the execution module controls the operation of the steamed bun machine according to the control instructions; the storage module is used to store the original data and the processed data information; the human-computer interaction module is used to provide a real-time production status monitoring interface for operators to monitor and manage.

[0070] The above-mentioned specific implementation modes are only specific cases of the present invention. The patent protection scope of the present invention includes but is not limited to the above-mentioned specific implementation modes. Any appropriate changes or modifications made thereto by any ordinary technician in the technical field in accordance with the claims of the present invention shall fall within the patent protection scope of the present invention.

Claims

1. An intelligent control method based on data perception of a steamed bun machine, characterized in that: The following steps are involved: Obtaining the operating status information of the steamed bun machine; the operating status information includes the operating status of the dough mixer, the operating status of the dough conveyor, the operating status of the steamed bun forming machine, and the operating status of the water adder; Acquire real-time parameter information during the operation of the steamed bun machine; the real-time parameter information includes the dough mixing speed of the dough mixer, the temperature, humidity, weight, and fermentation time of the dough in the dough mixer, the temperature, amount, and speed of the water adder, the conveying speed of the dough conveyor, the forming speed of the steamed bun forming machine, and the number of steamed buns; According to the acquired operation status information and real-time parameter information, the current production status is calculated and corresponding control instructions are generated; Execute the generated control instructions to control the operation of the steamed bun machine; According to the running status information, real-time parameter information and execution results of the control instructions of the steamed bun machine, the production status is continuously updated, and the control instructions are regenerated as needed; Provides a real-time production status monitoring interface for operators to monitor and manage.

2. The intelligent control method based on data perception of the steamed bread machine according to claim 1 is characterized in that: According to the acquired operation status information and real-time parameter information, the current production status is calculated and the corresponding control instructions are generated, which specifically includes the following steps: Preprocess the collected real-time parameter information, including denoising, filtering, and normalization operations; Establish a statistical analysis model to analyze and calculate the dough mixing speed of the dough mixer, the temperature, humidity, weight, fermentation time of the dough in the dough mixer, the temperature, water addition amount, and water addition speed of the water adder, integrate the operation status information, and calculate the current dough fermentation degree; Multiple control instructions are planned according to the degree of dough fermentation. The multiple control instructions are integrated with the conveying speed of the dough conveyor, the forming speed of the steamed bun forming machine, and the steamed bun count to obtain the optimal control instruction.

3. The intelligent control method based on data perception of the steamed bread machine according to claim 2 is characterized in that: The real-time parameter information is subjected to noise reduction and smoothing processing by using mean filtering or high filtering.

4. The intelligent control method based on data perception of the steamed bread machine according to claim 2 is characterized in that: The statistical analysis model is: Among them, s and r are variable relationship coefficients, and x i are the mean and the ith observation of the variable and surface velocity, respectively, and i are the mean and the i-th observation value of the temperature of the variable dough, and z i are the mean and the i-th observation value of the variable dough humidity, and a i are the mean and the i-th observation value of the variable dough weight, and b i are the mean and the i-th observation value of the variable dough fermentation time respectively; and c i are the mean and the i-th observation value of the variable water heater temperature, and d i are the mean and the i-th observation value of the variable water adding amount of the water adding device, and g i are the mean and the i-th observation value of the variable water adding speed of the water adder respectively.

5. The intelligent control method based on data perception of the steamed bread machine according to claim 4 is characterized in that: The fusion operation status information is used to calculate the current dough fermentation degree, including: The fused operation status information includes fault alarm information, maintenance record information, and continuous operation time information of each device; The random forest learning method is used to process the nonlinear relationship of the operating status information of each device; The nonlinear relationship of the operating status information of each device is integrated with the statistical analysis model to obtain the current dough fermentation degree W: Among them, z is the nonlinear relationship coefficient of the operating status information of each device; when W is not less than the preset value, the fermentation degree meets the requirements.

6. The intelligent control method based on data perception of the steamed bread machine according to claim 5 is characterized in that: According to the degree of dough fermentation, multiple control instructions are planned. The multiple control instructions are integrated with the conveying speed of the dough conveyor, the forming speed of the steamed bun forming machine, and the steamed bun count to obtain the optimal control instructions, including: The relationship model between the steamed bun count H and the dough fermentation degree W, the conveying speed S, and the forming speed M of the steamed bun forming machine is established: H = k1W + k2S + k3M; Among them, k1, k2, and k3 are weight coefficients. The steamed bun count H can reflect the progress of production. The production speed can be changed by adjusting the dough fermentation degree W, the conveying speed S, and the forming speed M of the steamed bun forming machine.

7. An intelligent control device based on data perception of a steamed bun machine, characterized in that: Used to implement the method as claimed in claim 1, the device includes a dough mixer, a dough conveyor, a steamed bun forming machine, a water adder, an electronic control unit, a movable platform and a control system.

8. The intelligent control device based on data perception of the steamed bun machine according to claim 7 is characterized in that: The control system comprises: An information collection module is used to collect the operating status information of the steamed bun machine and the real-time parameter information during the operation; Data processing module, used to process the operation status information and real-time parameter information and generate control instructions; An execution module controls the operation of the steamed bun machine according to control instructions; A storage module is used to store raw data and processed data information; The human-computer interaction module is used to provide a real-time production status monitoring interface for operators to monitor and manage.

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