Full-process monitoring and management system for automatic food processing production line

Abstract

The invention relates to the field of food processing, in particular to a food processing automatic production line full-process monitoring management system which comprises a production process monitoring module, an equipment monitoring module, a production process monitoring module, a quality detection module, a processing production comprehensive evaluation module and a management database. The system detects and analyzes the production process parameters of food processing to obtain the stability of the production process, analyzes the operation state parameters of the processing devices to obtain the operation stability degree of the processing devices, and obtains the production process conformity through the process conformity parameters of food. The food quality evaluation coefficient is obtained through the food quality parameters, the food processing and production comprehensive evaluation index is obtained through comprehensive analysis and fed back, problems possibly occurring in the production process can be found in time, the quality of final products can be better controlled, and it is ensured that consumers obtain high-quality food.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of food processing, in particular to a full-process monitoring and management system for food processing automation production line. BACKGROUND

[0002] With the continuous progress of science and technology and the development of social economy, the food industry is facing increasing demand and higher quality requirements. In this context, food processing automation production line emerges as the times require.

[0003] On the one hand, the traditional food processing method often has problems such as low efficiency, high labor cost, and unstable quality. On the other hand, consumers have higher and higher expectations for the quality, safety and diversity of food. Automation production line can better ensure the quality consistency of food through precise control and monitoring system, reduce the quality fluctuation caused by human factors, and also can adapt to the processing needs of various types of food, providing more diversified choices for consumers.

[0004] For example, the existing Chinese patent with application number 202410285630.1 discloses a food processing production control method and system based on Internet of Things technology. The scheme obtains the types of production equipment used in each stage of convenient food production and related data, then calculates the processing difference value of different equipment based on these data, presets the difference threshold for fault warning, and calculates the production line loss value according to the number of fault warning equipment and the total number of equipment. If the threshold is exceeded, a production line shutdown and maintenance warning is issued to ensure the smooth progress of the food processing process and the protection of product quality.

[0005] However, this scheme has the following shortcomings: this scheme mainly focuses on equipment monitoring and fault warning in the food processing production process, but ignores the detection of food processing operations such as temperature, pressure, processing time, and process operation, as well as the detection of food quality, which may lead to the fact that defects or errors in the food processing process cannot be discovered in time, which may affect the final form or characteristics of the food, resulting in quality differences in some batches of food. SUMMARY

[0006] In order to overcome the shortcomings in the background art, the embodiments of the present application provide a full-process monitoring and management system for food processing automation production line, which can effectively solve the problems involved in the above background art.

[0007] The purpose of the present application can be achieved by the following technical scheme: the present application provides a full-process monitoring and management system for food processing automation production line, comprising: a production process monitoring module, used for acquiring production process parameters of food processing, analyzing the stability of the production process, the production process parameters including temperature compliance, pressure compliance, and raw material conveying flow per unit time.

[0008] An equipment monitoring module is configured to acquire current values and voltage values of each piece of processing equipment at each time point, analyze running state parameters of each piece of processing equipment, and evaluate the running stability of the processing equipment, wherein the running state parameters include current fluctuation degree, voltage fluctuation degree, and power fluctuation degree.

[0009] A production process monitoring module is configured to track the progress of food at each process, analyze process compliance parameters of the food, and obtain a production process compliance degree, wherein the process compliance parameters include processing time compliance degree of each batch of food, operator compliance degree of each process, and process operation compliance degree.

[0010] A quality detection module is configured to detect quality parameters of the food, and evaluate a food quality evaluation coefficient, wherein the quality parameters include moisture content, food additive content, and microbial content.

[0011] A processing production comprehensive evaluation module is configured to analyze a processing production comprehensive evaluation index of the food according to the stability of the production process, the running stability of the processing equipment, the production process compliance degree, and the food quality evaluation coefficient, and to feed back the processing production comprehensive evaluation index.

[0012] A management database is configured to store preset standard processing time of each process and an operator arrangement table.

[0013] Preferably, the specific detection method of the production process parameter of the food processing is as follows: during the running of the equipment, a plurality of time points with equal time intervals are selected according to a preset time length, a thermal image of each piece of processing equipment at each time point is generated by an infrared thermal imager, chroma values of each pixel point in the thermal image of each piece of processing equipment at each time point are acquired, and a chroma value average of the thermal image of each piece of processing equipment at each time point is obtained by mean calculation, and is compared with a temperature corresponding to a preset chroma value range, so as to match the temperature of each piece of processing equipment at each time point.

[0014] The processing workshop is divided into regions according to a preset area, the temperature at the center point of each region of the processing workshop at each time point is acquired, and the temperature of the processing workshop at each time point is obtained by mean calculation.

[0015] The temperature compliance degree of the food processing is obtained by fusion calculation based on the temperature of each piece of processing equipment at each time point and the temperature of the processing workshop at each time point.

[0016] The pressure value of each piece of processing equipment at each time point is detected by a pressure sensor, and compared with a preset equipment safety pressure, so as to obtain a food processing pressure compliance degree.

[0017] A plurality of time periods with equal length are selected, the raw material delivery amount in each time period is weighed by a weighing device, the delivery flow rate of each time period is obtained by dividing the raw material delivery amount by the time length of the time period, and the unit time delivery flow rate is obtained by mean calculation.

[0018] Preferably, the specific analysis method of the stability of the production process is to compare the raw material conveying flow per unit time with the preset raw material standard conveying flow per unit time, and combine the temperature compliance degree and the pressure compliance degree of food processing to obtain the stability of the production process.

[0019] Preferably, the specific analysis method of the running state parameter of each processing equipment is to obtain the current value and voltage value of each processing equipment at each time point, calculate the current fluctuation degree and voltage fluctuation degree of each processing equipment by calculating the mean square deviation, and then calculate the power fluctuation degree of each processing equipment, and finally obtain the running stability degree of the processing equipment based on the current fluctuation degree, voltage fluctuation degree and power fluctuation degree of each processing equipment.

[0020] Preferably, the specific analysis method of the flow compliance parameter of the food is as follows: first, assign a unique identifier to each batch of food according to the setting, scan the identifier of each batch of food by a code scanning device to obtain the time when each batch of food enters each process and the time when each batch of food leaves each process, and obtain the processing time of each batch of food in each process by subtracting the time when each batch of food enters each process from the time when each batch of food leaves each process, and then read the preset standard processing time of each process from the management database, compare the processing time of each batch of food in each process with the standard processing time of each process to obtain the processing time compliance degree of each batch of food.

[0021] Secondly, record the work number of each operator corresponding to each process before the start of each process to obtain the work number of each operator in each process, and read the operator arrangement table from the management database to extract the work number of each operator arranged in each process to obtain the arranged operator work number set of each process, and then compare the work number of each operator in each process with the arranged operator work number set to obtain the operator compliance degree of each process.

[0022] Thirdly, record the actual operation steps performed by each operator in each process at the end of each process to obtain each operation step of each operator in each process, and then compare each operation step of each operator in each process with the preset standard step of each process to obtain the process operation compliance degree.

[0023] Read the processing time compliance degree of each batch of food, the operator compliance degree of each process, and the process operation compliance degree, and then fuse and calculate to obtain the production flow compliance degree.

[0024] Preferably, the specific detection method of the moisture content of the food is as follows: a plurality of food samples are randomly taken from each batch of food, denoted as batch food samples, the batch food samples are weighed, denoted as batch food sample weights, the batch food samples are placed in an oven, dried at a specified temperature until the batch food samples reach a constant weight, denoted as batch food sample dry weights, the moisture content of the batch food samples is obtained by comparing the batch food sample weights with the batch food sample dry weights, and the average value is calculated to obtain the moisture content of the food.

[0025] Preferably, the specific detection method of the food additive content of the food is as follows: an acid or base solution of a specified concentration is prepared, a specified amount of each batch food sample is weighed, dissolved in a solvent, and an indicator is added to obtain a batch food sample solution, a standard acid or base solution is gradually added to the batch food sample solution, stirring constantly until the indicator changes color to reach the endpoint, the volume of the acid or base solution consumed from the start of addition to the endpoint is recorded, and the food additive content of the food is calculated.

[0026] Preferably, the specific detection method of the microbial content of the food is as follows: a specified amount of each batch food sample is weighed, homogenized to obtain a batch food sample homogenate, the batch food sample homogenate is divided into a specified number of portions, each portion is added with a specified amount of sterile water to prepare a sample solution of each dilution ratio, denoted as batch food sample solution of each dilution ratio, each sample solution is inoculated into a specific culture medium for incubation, and after a specified period of time, the colonies on the culture medium corresponding to the batch food sample solution of each dilution ratio are counted to obtain the colony count of the batch food sample solution of each dilution ratio, the average colony count of each dilution ratio sample solution is calculated, the product of the average colony count of each dilution ratio sample solution and the corresponding dilution ratio is calculated, and the microbial content of the food is obtained by dividing the product by the amount of food sample in the sample solution of the corresponding dilution ratio.

[0027] Preferably, the specific analysis method of the food quality evaluation coefficient is as follows: the moisture content, food additive content, and microbial content of the food are compared with the reference values of the food moisture content, food additive content, and microbial content, respectively, and the food quality evaluation coefficient is calculated by fusion.

[0028] Preferably, the specific analysis method of the processing production comprehensive evaluation module is: based on the stability of the production process, the running stability degree of the processing equipment, the production process compliance, and the fusion calculation of the food quality evaluation coefficient to obtain the food processing production comprehensive evaluation index, and the food processing production comprehensive evaluation index is compared with the preset comprehensive evaluation index threshold value, if the food processing production comprehensive evaluation index is greater than or equal to the preset comprehensive evaluation index threshold value, it indicates that the food processing production comprehensive evaluation index is qualified, if the food processing production comprehensive evaluation index is less than the preset comprehensive evaluation index threshold value, it indicates that the food processing production comprehensive evaluation index is unqualified, and feedback is given to the system.

[0029] Compared with the prior art, the present application has the following beneficial effects: 1. The present application can timely understand whether the production process is stable by detecting the production process parameters of food processing and analyzing the stability of the production process, which helps to ensure the consistency and reliability of food production and improve the stability of product quality.

[0030] 2. The present application can accurately master the running state of each processing equipment and discover equipment abnormalities in advance by detecting the current value and voltage value of each processing equipment at each time point, analyzing the running state parameters of each processing equipment, and further analyzing the running stability degree of the processing equipment.

[0031] 3. The present application can clearly determine the compliance degree of the production process by analyzing the process compliance parameters of the food and further obtaining the production process compliance, which is beneficial to optimize the process, improve the production efficiency, and ensure that the production is carried out according to the standard.

[0032] 4. The present application can improve the production process to improve food quality and enhance market competitiveness by detecting the quality parameters of the food and analyzing the food quality evaluation coefficient.

[0033] 5. The present application can comprehensively evaluate the food processing production situation by analyzing the food processing production comprehensive evaluation index according to the stability of the production process, the running stability degree of the processing equipment, the production process compliance, and the food quality evaluation coefficient, and feeding back the food processing production comprehensive evaluation index, which is convenient for formulating more reasonable production strategies and management decisions and promoting the improvement of the overall production level. BRIEF DESCRIPTION OF DRAWINGS

[0034] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiment description. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0035] Figure 1The system module connection diagram of the present application.

[0036] Figure 2 The Figure 1 The flowchart of the flow of the food in the production flow monitoring module in conformity with the parameters.

[0037] Figure 3 The Figure 1 The flowchart of the flow of the food in the production flow monitoring module in conformity with the parameters. DETAILED DESCRIPTION

[0038] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the protection scope of the present application.

[0039] Please refer to Figure 1 As shown in the figure, a food processing automatic production line full-process monitoring management system includes a production process monitoring module, an equipment monitoring module, a production flow monitoring module, a quality detection module, a processing production comprehensive evaluation module, and a management database.

[0040] The management database is connected with the production process monitoring module, the equipment monitoring module, the production flow monitoring module, the quality detection module, and the processing production comprehensive evaluation module. The processing production comprehensive evaluation module is connected with the production process monitoring module, the equipment monitoring module, the production flow monitoring module, and the quality detection module.

[0041] The production process monitoring module is used to obtain the production process parameters of food processing and analyze the stability of the production process. The production process parameters include the temperature compliance degree, the pressure compliance degree, and the raw material conveying flow per unit time.

[0042] The specific detection method of the production process parameters of food processing is as follows: during the operation of the equipment, a plurality of time points with equal time intervals are selected according to the set time length. A thermal image of each processing equipment corresponding to each time point is generated by an infrared thermal imager. The chroma value of each pixel point in the thermal image of each processing equipment at each time point is obtained. The average value of the chroma value of the thermal image of each processing equipment at each time point is calculated by the mean value. The average value is compared with the temperature corresponding to the preset chroma value range, so as to match the temperature of each processing equipment at each time point.

[0043] According to the set area, the processing workshop is divided into regions. The temperature at the center point of each region at each time point is obtained. Then, the temperature at each time point in the processing workshop is obtained by mean value calculation.

[0044] The temperature compliance degree of food processing is calculated by fusing the temperature of each processing equipment at each time point and the temperature of the processing workshop at each time point; the equipment and environmental temperature can be comprehensively monitored, and temperature abnormalities can be found in time to ensure that the equipment operates at an appropriate temperature, avoid high or low temperature affecting production and equipment life, and also help to ensure food processing quality.

[0045] The temperature of each processing equipment at each time point and the temperature of the processing workshop at each time point are extracted, and then the temperature compliance degree of food processing is calculated by summing according to the weight.

[0046] For example, the weight corresponding to the temperature of the processing equipment and the temperature of the processing workshop is 0.7, 0.3.

[0047] The pressure compliance degree of food processing is obtained by comparing the pressure value of each processing equipment at each time point with the preset equipment safety pressure through the pressure sensor; it helps to ensure that the equipment operating pressure is within a safe range, prevent pressure abnormalities from causing safety problems, and ensure production safety and equipment stability.

[0048] Select several equal time periods, weigh the raw material delivery amount in each time period with a weighing device, divide by the time period length to obtain the delivery flow rate in each time period, and then calculate the unit time delivery flow rate by mean value; the delivery of raw materials can be accurately mastered, the production schedule can be reasonably arranged, the stability and accuracy of raw material supply can be ensured, and the production efficiency and product quality consistency can be improved.

[0049] The specific analysis method of the stability of the production process is: comparing the raw material delivery flow rate in unit time with the preset raw material standard delivery flow rate in unit time, and fusing the temperature compliance degree and the pressure compliance degree of food processing to calculate the stability of the production process; the overall condition of the production process can be more accurately reflected, factors that may affect the stability of the production process can be found in time, so that targeted measures can be taken for adjustment and optimization, and the smooth progress of production and the stability of product quality can be ensured.

[0050] The temperature compliance degree, the pressure compliance degree, and the raw material delivery flow rate in unit time of food processing are extracted, and then the stability of the production process is calculated by summing according to the weight.

[0051] For example, the weight corresponding to the temperature compliance degree, the pressure compliance degree, and the raw material delivery flow rate in unit time of food processing is 0.5, 0.3, and 0.2.

[0052] The equipment monitoring module is used to obtain the current value and voltage value of each processing equipment at each time point, analyze the running state parameters of each processing equipment, evaluate the running stability degree of the processing equipment, and the running state parameters include current fluctuation degree, voltage fluctuation degree, and power fluctuation degree.

[0053] The specific analysis method of the operation state parameters of each processing equipment is: obtaining the current value and voltage value of each processing equipment at each time point, calculating the current fluctuation degree and voltage fluctuation degree of each processing equipment by calculating the mean square deviation, and calculating the power fluctuation degree of each processing equipment, and calculating the operation stability degree of the processing equipment based on the current fluctuation degree, voltage fluctuation degree and power fluctuation degree of each processing equipment. It is helpful to find abnormal fluctuation of current and voltage in time, avoid damage to equipment caused by unstable current and voltage, ensure normal operation of equipment, and prolong service life of equipment.

[0054] The specific analysis method of the operation stability degree of the processing equipment is: obtaining the current value and voltage value of each processing equipment at each time point, calculating the current fluctuation degree and voltage fluctuation degree of each processing equipment by calculating the mean square deviation, and calculating the power fluctuation degree of each processing equipment, and calculating the operation stability degree of the processing equipment based on the current fluctuation degree, voltage fluctuation degree and power fluctuation degree of each processing equipment. It can more comprehensively and accurately understand the operation condition of the processing equipment, so as to take targeted maintenance, adjustment and other measures, improve the reliability and stability of the equipment operation, and further ensure the smooth progress of the whole production process.

[0055] The current fluctuation degree, voltage fluctuation degree and power fluctuation degree of each processing equipment are extracted, and then the operation stability degree of the processing equipment is calculated by summing up according to the weight.

[0056] For example, the weights corresponding to the current fluctuation degree, voltage fluctuation degree and power fluctuation degree of the processing equipment are 0.3, 0.3 and 0.4.

[0057] The production process monitoring module is used to track the progress of food in each process, analyze the process compliance parameters of food, and then obtain the production process compliance degree. The process compliance parameters include the processing time compliance degree of each batch of food, the operation personnel compliance degree of each process, and the process operation compliance degree.

[0058] Please refer to Figure 2As shown, the process of the food meets the parameter specific analysis method: first, according to the set of each batch of food distribution unique identification, through the scanning equipment to scan the identification of each batch of food to obtain the time of each batch of food into each process, the time of each batch of food leaving each process, by the time of each batch of food into each process, the time of each batch of food leaving each process is subtracted, the processing time of each batch of food in each process is obtained, the preset standard processing time of each process is read from the management database, and the processing time of each batch of food in each process is compared to obtain the processing time compliance of each batch of food; It is helpful to ensure that food processing is carried out according to the specified time, to ensure the consistency and stability of product quality, to find out the abnormal processing time in time, to facilitate the adoption of corrective measures, and to improve the controllability of the production process.

[0059] Second, record the work number of each operation personnel corresponding to each process before each process starts, obtain the work number of each operation personnel in each process, and read the operation personnel arrangement table from the management database, extract the work number of each operation personnel arranged in each process from the operation personnel arrangement table, obtain the operation personnel work number set arranged in each process, and compare the work number of each operation personnel in each process with the operation personnel work number set arranged in each process to obtain the operation personnel compliance of each process; It can ensure the accuracy and compliance of personnel arrangement, ensure that each process is performed by suitable personnel, which is very important for ensuring the professionalism and quality control of operation, and also facilitates personnel management and responsibility tracing.

[0060] It should be noted that the specific analysis method of the operation personnel compliance of each process is to read the work number of each operation personnel in each process and the operation personnel work number set arranged in each process, match the work number of each operation personnel in each process in the operation personnel work number set arranged in each process in sequence according to the process order, and if the work number of an operation personnel in a process exists in the operation personnel work number set arranged in the process, it means that the operation personnel in the process meets the arrangement, and the work number of each operation personnel in each process is matched in sequence, and the number of operation personnel meeting the arrangement in each process is obtained by statistics, and the number of operation personnel meeting the arrangement in each process is compared with the number of operation personnel arranged in each process to obtain the operation personnel compliance of each process.

[0061] Third, record the actual operation steps performed by each operation personnel in each process at the end of each process, obtain each operation step of each operation personnel in each process, and compare each operation step of each operation personnel in each process with each standard step of each process to obtain the process operation compliance; It can ensure that the operation personnel work according to the specified process and standard, guarantee product quality and production standardization, and facilitate clear responsibility when problems occur.

[0062] It should be noted that the specific analysis method of the operation compliance of the process is that: reading each operation step of each operator of each process, and comparing it with each standard step of each process, if the operation step of the operator of the process is consistent with the standard step of the process, it means that the operation step of the operator of the process is qualified, and the qualified number of operation steps of each operator of each process is obtained by comparison, and the operation compliance of each operator of each process is obtained by comparing the number of standard steps of each process, and the operation compliance of the process is obtained by mean value calculation.

[0063] The specific analysis method of the production process compliance is: reading the processing time compliance of each batch of food, the operator compliance of each process, and the operation compliance of the process, and fusing calculation to obtain the production process compliance; which is helpful to comprehensively and objectively analyze and monitor the production process, so as to timely find out problems and take corresponding measures to improve and optimize, and improve the production efficiency and product quality.

[0064] The processing time compliance of each batch of food, the operator compliance of each process, and the operation compliance of the process are extracted, and then summed and calculated according to the weight to obtain the production process compliance.

[0065] For example, the weight of the processing time compliance of the food, the operator compliance, and the operation compliance of the process is 0.3, 0.3, and 0.4.

[0066] The quality detection module is used for detecting the quality parameters of the food, evaluating the food quality evaluation coefficient, and the quality parameters include the moisture content, the food additive content, and the microbial content.

[0067] The specific detection method of the moisture content of the food is: a plurality of food samples are randomly taken from each batch of food, denoted as batch food samples, the batch food samples are weighed, denoted as batch food sample weight, the batch food samples are placed in an oven, dried at a specified temperature until the batch food samples reach a constant weight, denoted as batch food sample dried weight, the moisture content of the batch food samples is obtained by comparing the batch food sample weight with the batch food sample dried weight, and the average value is obtained to obtain the moisture content of the food; which can accurately measure the moisture content of the food, provide key data for the production, processing and quality control of the food, and help to ensure that the product meets the relevant standards.

[0068] It should be noted that the specific operation method of the batch food sample dried weight is: A1: the batch food samples are placed in an oven, and the oven is set to a fixed temperature, a plurality of drying time points are taken at a set time interval, the weight of the batch food samples at each drying time point is detected in real time at a fixed temperature, denoted as batch food sample weight at each drying time point;

[0069] A2: The weight difference value of each adjacent drying time point of each food sample in the batch is obtained by subtracting the drying weight of each food sample in the batch at adjacent drying time points, and the minimum value is screened out. The drying time point corresponding to the minimum weight difference value of each adjacent drying time point of each food sample in the batch is recorded as the constant weight time point of each food sample in the batch.

[0070] A3: The weight of the constant weight time point of each food sample in the batch is extracted from the weight of each drying time point of each food sample in the batch, and is recorded as the drying weight of each food sample in the batch.

[0071] The specific detection method of the food additive content of the food is: configuring an acid-base solution with a set concentration, weighing a set amount from each food sample in the batch, dissolving it in a solvent and adding an indicator to obtain a batch of food sample solutions, gradually adding a standard acid-base solution to the batch of food sample solutions, constantly stirring until the indicator changes color to reach the endpoint, recording the volume of the acid-base solution consumed by the batch of food sample solutions from the start of dropping to the endpoint, and calculating the food additive content of the food; the food additive content in the food can be accurately determined, the food safety and compliance are ensured, and the use of food additives is effectively monitored, preventing excessive use from causing potential threats to consumer health.

[0072] The specific detection method of the microbial content of the food is: weighing a set amount from each batch of food samples, preparing a batch of food sample homogenate by homogenization method, dividing the batch of food sample homogenate into a set number of parts, and adding a set amount of sterile water to each part to prepare sample solutions of each dilution ratio, which are recorded as batch of food sample solution of each dilution ratio, inoculating each part into a specific culture medium for culture, and counting the colonies on the culture medium corresponding to the batch of food sample solution of each dilution ratio after a set period of time to obtain the colony count of the batch of food sample solution of each dilution ratio, calculating the average colony count of each dilution ratio sample solution to obtain the average colony count of each dilution ratio sample solution, and calculating the product of the average colony count of each dilution ratio sample solution and the corresponding dilution ratio, and then dividing the product by the amount of food sample in the sample solution of the corresponding dilution ratio to obtain the microbial content of the food; by diluting and counting each batch of food, the microbial content in the food can be accurately understood, which is crucial for judging the hygiene status, shelf life and potential food safety risks of the food.

[0073] The specific analysis method of the food quality evaluation coefficient is: comparing the moisture content, the food additive content and the microbial content of the food with the reference values of the preset moisture content, the food additive content and the microbial content of the food, and obtaining the food quality evaluation coefficient through fusion calculation; important indicators such as moisture content, food additive content and microbial content can be comprehensively evaluated, the limitations of single index can be avoided, feedback can be provided for the food production process, and the optimization and improvement of the production process can be guided.

[0074] The ratio of the moisture content, the food additive content and the microbial content of the food to the reference values of the preset moisture content, the food additive content and the microbial content of the food is extracted, and then the food quality evaluation coefficient is obtained by summing calculation according to the weight.

[0075] For example, the weights corresponding to the moisture content, the food additive content and the microbial content of the food are 0.2, 0.3 and 0.5.

[0076] The processing and production comprehensive evaluation module is used to analyze the processing and production comprehensive evaluation index of the food according to the stability of the production process, the running stability of the processing equipment, the production process compliance and the food quality evaluation coefficient, and to feed back the processing and production comprehensive evaluation index.

[0077] Please refer to Figure 3 The specific analysis method of the processing and production comprehensive evaluation module is: based on the stability of the production process, the running stability of the processing equipment, the production process compliance and the food quality evaluation coefficient, the processing and production comprehensive evaluation index of the food is obtained by fusion calculation, and the processing and production comprehensive evaluation index of the food is compared with the preset comprehensive evaluation index threshold value, if the processing and production comprehensive evaluation index of the food is greater than or equal to the preset comprehensive evaluation index threshold value, it means that the processing and production comprehensive evaluation index of the food is qualified, if the processing and production comprehensive evaluation index of the food is less than the preset comprehensive evaluation index threshold value, it means that the processing and production comprehensive evaluation index of the food is unqualified, and feedback is given to the system; by comprehensively considering the multiple aspects of the production process, the evaluation of food processing and production is more comprehensive and systematic, and the one-sidedness is avoided, which helps to ensure that the food processing and production meets certain standards and requirements, so as to ensure the quality and safety of food.

[0078] The stability of the production process, the running stability of the processing equipment, the production process compliance and the food quality evaluation coefficient are extracted, and then the processing and production comprehensive evaluation index of the food is obtained by summing calculation according to the weight.

[0079] For example, the weights corresponding to the stability of the production process, the running stability of the processing equipment, the production process compliance and the food quality evaluation coefficient are 0.2, 0.1, 0.3 and 0.4.

[0080] A management database is configured to store preset standard processing time of each process, and an operator arrangement table.

[0081] The application can detect the production process parameters of food processing, analyze the stability of the production process, analyze the running stability of the processing equipment through the running state parameters of each processing equipment, obtain the production process compliance degree through the process compliance parameters of the food, obtain the food quality evaluation coefficient through the quality parameters of the food, and then comprehensively analyze the food processing production comprehensive evaluation index, and feed back it, so as to timely find out the possible problems in the production process, take timely measures for adjustment and improvement, better control the quality of the final product, and ensure that consumers obtain high-quality food.

[0082] Although the embodiments of the application have been shown and described above, it should be understood that the above embodiments are exemplary and should not be construed as limiting the application. Those skilled in the art can make changes, modifications, replacements and variations to the above embodiments within the scope of the application, which are still covered by the protection scope of the application.

Claims

1. A food processing automation production line full-process monitoring management system, characterized in that, The system specifically comprises the following modules: A production process monitoring module for obtaining food processing production process parameters, analyzing production process stability, and production process parameters including temperature compliance, pressure compliance, and raw material delivery flow per unit time; An equipment monitoring module for obtaining current and voltage values of each processing equipment at each time point, analyzing operating state parameters of each processing equipment, evaluating the operating stability of the processing equipment, and operating state parameters including current fluctuation, voltage fluctuation, and power fluctuation; A production process monitoring module for tracking the progress of food in each process, analyzing process compliance parameters of food, and obtaining production process compliance, and process compliance parameters including processing time compliance of each batch of food, operator compliance of each process, and process operation compliance; A quality detection module for detecting food quality parameters and evaluating food quality evaluation coefficients, and quality parameters including moisture content, food additive content, and microbial content; A comprehensive evaluation module for analyzing food processing comprehensive evaluation index based on production process stability, processing equipment operating stability, production process compliance, and food quality evaluation coefficient, and feeding back the index; A management database for storing preset standard processing time of each process and operator arrangement table.

2. The full-process monitoring and management system for food processing automation production line according to claim 1, characterized in that, The specific detection method of the production process parameters of the food processing is as follows: During equipment operation, a plurality of time points with equal time intervals are selected according to a set time, a thermal image of each processing equipment at each time point is generated by an infrared thermal imager, the chroma value of each pixel point in the thermal image of each processing equipment at each time point is obtained, the average chroma value of the thermal image of each processing equipment at each time point is calculated by mean value, and the average chroma value is compared with the temperature corresponding to the preset chroma value range, so as to match the temperature of each processing equipment at each time point; According to a set area, the processing workshop is divided into regions, the temperature at the center point of each region at each time point is obtained, and the temperature at each time point of the processing workshop is obtained by mean value calculation; The temperature compliance of the food processing is obtained by fusion calculation based on the temperature of each processing equipment at each time point and the temperature of the processing workshop at each time point; The pressure value of each processing equipment at each time point is detected by a pressure sensor, compared with the preset equipment safety pressure, and the pressure compliance of the food processing is obtained; A plurality of equal time periods are selected, the raw material delivery amount in each time period is weighed by a weighing device, the delivery flow in each time period is obtained by dividing the time period length, and the unit time delivery flow is obtained by mean value calculation.

3. The system according to claim 2, wherein, The specific analysis method of the production process stability is as follows: The raw material delivery flow per unit time is compared with the preset standard raw material delivery flow per unit time, and the production process stability is obtained by fusion calculation combined with the temperature compliance and pressure compliance of the food processing.

4. The full-process monitoring and management system for food processing automation production lines according to claim 3, characterized in that, The specific analysis method of the operating stability of the processing equipment is as follows: The current value and the voltage value of each processing equipment at each time point are acquired, the current fluctuation degree, the voltage fluctuation degree and the power fluctuation degree of each processing equipment are calculated by calculating the mean square deviation, and the running stability degree of the processing equipment is calculated based on the current fluctuation degree, the voltage fluctuation degree and the power fluctuation degree of each processing equipment.

5. The full-process monitoring and management system for food processing automation production lines according to claim 1, characterized in that, The specific analysis method of the process compliance parameter of the food is as follows: Firstly, a unique identifier is assigned to each batch of food according to the setting, the time when each batch of food enters each process and the time when each batch of food leaves each process are acquired by scanning the identifier of each batch of food through a scanning device, the processing time of each batch of food in each process is obtained by subtracting the time when each batch of food enters each process from the time when each batch of food leaves each process, the preset standard processing time of each process is read from the management database, and the processing time compliance of each batch of food is obtained by comparing the processing time of each batch of food in each process with the preset standard processing time of each process; Secondly, the work number of each operator corresponding to each process is recorded before the start of each process to obtain the work number of each operator in each process, and the work number of each operator arranged in each process is extracted from the operator arrangement table in the management database to obtain the work number set of the operators arranged in each process, and the work number of each operator in each process is compared with the work number set to obtain the operator compliance of each process; Thirdly, the actual operation steps performed by each operator in each process are recorded at the end of each process to obtain the operation steps of each operator in each process, and the operation steps are compared with the preset standard steps of each process to obtain the operation compliance of each process. The processing time compliance of each batch of food, the operator compliance of each process and the operation compliance of each process are read to obtain the production process compliance by fusion calculation.

6. The full-process monitoring and management system for food processing automation production lines according to claim 1, characterized in that, The specific detection method of the moisture content of the food is as follows: A certain amount of food sample is randomly taken from each batch of food, denoted as batch food sample, the batch food sample is weighed, denoted as batch food sample weight, the batch food sample is placed in an oven and dried at a specified temperature until the batch food sample reaches a constant weight, denoted as batch food sample dried weight, the moisture content of the batch food sample is obtained by comparing the batch food sample weight with the batch food sample dried weight, and the average value is calculated to obtain the moisture content of the food.

7. The system according to claim 6, wherein, The specific detection method of the food additive content of the food is as follows: An acid-base solution with a certain concentration is prepared, a certain amount of food sample is taken from each batch of food, dissolved in a solvent and added with an indicator to obtain a batch food sample solution, standard acid-base solution is gradually added to the batch food sample solution, and the solution is constantly stirred until the indicator changes color to reach the endpoint, the volume of acid-base solution consumed from the start of addition to the endpoint of the batch food sample solution is recorded, and the food additive content of the food is calculated.

8. The system according to claim 7, wherein, The specific detection method of the microbial content of the food is as follows: A set amount of food sample is weighed from each batch of food sample, and a homogenate of each batch of food sample is prepared by a homogenization method. The homogenate of each batch of food sample is divided into a set number of portions, and a set amount of sterile water is added to each portion to prepare sample solutions of each dilution factor, which are denoted as batch food sample solutions of each dilution factor. Each batch food sample solution of each dilution factor is inoculated into a specific culture medium for incubation, and the colonies on the culture medium corresponding to each batch food sample solution of each dilution factor are counted after a set period of time. The colony counts of each batch food sample solution of each dilution factor are averaged to obtain the average colony count of each dilution factor sample solution. The average colony count of each dilution factor sample solution is multiplied by the corresponding dilution factor, and the product is divided by the amount of food sample in the sample solution of the corresponding dilution factor to obtain the microbial content of the food.

9. The system according to claim 8, wherein, The specific analysis method of the food quality evaluation coefficient is as follows: The moisture content, food additive content, and microbial content of the food are compared with the reference values of the food moisture content, food additive content, and microbial content, respectively, and the food quality evaluation coefficient is obtained by fusion calculation.

10. The full-process monitoring and management system for food processing automation production lines according to claim 1, characterized in that, The specific analysis method of the processing and production comprehensive evaluation module is as follows: Based on the stability of the production process, the running stability of the processing equipment, the production process compliance, and the food quality evaluation coefficient, the processing and production comprehensive evaluation index of the food is obtained by fusion calculation. The processing and production comprehensive evaluation index of the food is compared with the preset comprehensive evaluation index threshold value. If the processing and production comprehensive evaluation index of the food is greater than or equal to the preset comprehensive evaluation index threshold value, it indicates that the processing and production comprehensive evaluation index of the food is qualified. If the processing and production comprehensive evaluation index of the food is less than the preset comprehensive evaluation index threshold value, it indicates that the processing and production comprehensive evaluation index of the food is unqualified, and feedback is provided to the system.

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