A tea quality data security monitoring method and system

Abstract

The present invention relates to the technical field of tea quality, and discloses a tea quality data security monitoring method and system, including a tea data collection module, a tea data analysis module, a tea data security monitoring module and a loss prediction module, wherein the tea data collection module includes a tea growth data collection unit, a tea picking data collection unit, a tea production data collection unit and a tea storage data collection unit, and the tea data analysis module is used to analyze the collected growth problem data, tea appearance data, production index and storage index to obtain quality evaluation data. The system compares the collected growth problem data, tea appearance data, production index and storage index with the standard data one by one and inputs them into the quality evaluation function for quality evaluation to obtain quality evaluation data, thereby realizing the evaluation of the overall production of tea, and reflecting the overall tea quality and safety situation from the comprehensive data.

Description

Technical Field

[0001] The present invention relates to the technical field of tea quality, and in particular to a method and system for safely monitoring tea quality data. Background Art

[0002] The quality of tea raw materials (fresh tea leaves) has a decisive influence on the quality of finished tea. Monitoring the quality of fresh tea buds (fresh leaves to be picked) during the growth period and timely grasping the quality of tea buds are of great significance for guiding the refined planting technology of tea gardens and ensuring the quality of tea raw materials.

[0003] Traditionally, the quality indicators of fresh tea leaves, such as tea polyphenols, free amino acids, water extracts, caffeine, soluble sugars, etc., are mostly determined by chemical detection methods, such as spectrophotometry and high-performance liquid chromatography. However, these methods are based on laboratory testing, which not only have the disadvantages of sample destructiveness and high personnel skill requirements, but also have the characteristics of time-consuming and labor-intensive, time-lag, and cannot grasp the quality of tea in a timely manner and provide production feedback. In recent years, spectral analysis technology has become increasingly mature. It has the advantages of being fast, non-destructive, accurate, and simple. It can describe the characteristic frequencies and combination bands of CH, OH, and NH groups in the spectral wavelength range of 380 to 2500nm, and is used to analyze most compounds. Tea quality also belongs to this type of hydrogen-containing group. However, most studies have used laboratory-based desktop spectrometers. Although this shortens the time to obtain quality results, it still requires the destruction of tea leaves for sampling. This point-to-surface measurement method is easily affected by sample sampling errors, and the results are highly unstable. In addition, most of these devices are expensive and cannot be moved. A small number of studies have used portable spectrometers for diagnosis, such as ASD field spectrometers, which use hyperspectral acquisition technology, but the high cost of these instruments and the need for high operating skills and powerful data processing backends also make them difficult to become routine testing tools for growers.

[0004] At present, tea quality testing technology is mainly focused on the testing of finished tea products during tea processing, while ignoring the impact of the entire process of growth, picking, production, and storage of the current batch of tea. There are multiple factors in each process that affect the quality of tea. Therefore, a means of secure monitoring of tea quality data is needed to ensure the overall quality of tea. Summary of the invention

[0005] 1. Technical issues to be resolved

[0006] In view of the deficiencies in the prior art, the present invention provides a method and system for securely monitoring tea quality data, which has the advantages of overall evaluation of tea quality and ensuring production safety, thereby solving the above-mentioned technical problems.

[0007] (II) Technical solution

[0008] To achieve the above object, the present invention provides the following technical solutions: a tea quality data security monitoring system, comprising a tea data collection module, a tea data analysis module, a tea data security monitoring module and a loss prediction module;

[0009] The tea data collection module includes a tea growth data collection unit, a tea picking data collection unit, a tea production data collection unit and a tea storage data collection unit. The tea growth data collection unit is used to collect growth problem data occurring during tea growth. The tea picking data collection unit is used to collect tea appearance data during tea picking. The tea production data collection unit is used to collect production indicators during tea production. The tea storage data collection unit is used to collect storage indicators during tea storage. The tea data collection module sends the collected tea growth problem data, tea appearance data, production indicators and storage indicators to the tea data analysis module and the tea data security monitoring module.

[0010] The tea data analysis module is used to analyze the collected growth problem data, tea appearance data, production indicators, and storage indicators to obtain quality assessment data;

[0011] The tea data security monitoring module is used to perform real-time detection on the data security of tea production indicators and storage indicators, and includes a production safety monitoring unit and a storage safety monitoring unit. The production safety monitoring unit is used to monitor the production process of tea and provide timely feedback to the loss prediction module for loss prediction; the storage safety monitoring unit is used to monitor the storage process of tea and provide timely feedback to the loss prediction module for loss prediction.

[0012] As a preferred technical solution of the present invention, the tea growth data collection unit collects growth problem data during the tea growth process, including the highest temperature during the tea growth process, the lowest temperature during the tea growth process, and the number of insect pests experienced during the tea growth process. The specific expression is as follows:

[0013]

[0014] Among them, among them, Indicates A growth problem dataset with growth cycles, Indicates The highest temperature during the growth of tea leaves in a growth cycle, Indicates The lowest temperature during the growth cycle of tea leaves. Indicates The number of times the tea leaves experience pests during a growth cycle.

[0015] As a preferred technical solution of the present invention, the tea quality data of the tea picking data collection unit during the tea picking process includes the total weight of the tea leaves and the completeness of the tea leaves, and the specific expression thereof is as follows:

[0016]

[0017] in, Indicates A tea quality dataset of growth cycles, Indicates The total weight of tea leaves during the tea picking process in a growth cycle, Indicates The integrity of tea leaves during the tea picking process of a growth cycle.

[0018] As a preferred technical solution of the present invention, the production index of the tea production process of the tea production data collection unit includes the number of production equipment shutdowns and damages and the number of tea contaminations during the production process, and the expression is as follows:

[0019]

[0020] in, Indicates A tea production index dataset for a growth cycle, Indicates The number of production equipment downtime and damage during the tea production process during a growth cycle, Indicates The number of times tea leaves are contaminated during the tea production process during a growth cycle.

[0021] As a preferred technical solution of the present invention, the loss prediction module calculates the loss caused by the number of shutdowns and damages of production equipment and tea contamination during the production process as follows:

[0022]

[0023] in, Indicates The total losses caused by the downtime and damage of production equipment and tea contamination during the tea production process during a growth cycle are Indicates that the current process is process, It represents the total processing cost from the first process to the first process. Indicates The processing cost of the i-th step in the tea production process of a growth cycle, No. The maintenance cost corresponding to the shutdown of tea production equipment during a growth cycle, Indicates The time loss cost corresponding to the number of tea contaminations in a growth cycle.

[0024] As a preferred technical solution of the present invention, the tea storage data acquisition unit detects storage indicators including the number of storage temperature fluctuations during tea storage. When the storage temperature difference during storage is greater than the storage temperature fluctuation threshold, the number of storage temperature fluctuations Plus one.

[0025] As a preferred technical solution of the present invention, the loss prediction module performs loss prediction on the storage process of tea leaves, and the corresponding loss function is as follows:

[0026]

[0027] in, represents the loss function of the storage process of tea leaves, Indicates the number of storage temperature fluctuations. Represents the coefficient of fluctuation.

[0028] As a preferred technical solution of the present invention, the tea data analysis module compares the collected growth problem data, tea appearance data, production indicators, storage indicators with the preset standard data one by one and inputs them into the quality evaluation function for quality evaluation to obtain quality evaluation data.

[0029] As a preferred technical solution of the present invention, the quality evaluation function is expressed as follows:

[0030]

[0031] in, Indicates The highest temperature during the growth of tea leaves in a growth cycle, Indicates The lowest temperature during the growth cycle of tea leaves. Indicates The number of times the tea leaves experience pests during the growth cycle, Indicates The total weight of tea leaves during the tea picking process in a growth cycle, Indicates The completeness of tea leaves during the tea picking process of the growth cycle, Indicates The number of production equipment downtime and damage during the tea production process during a growth cycle, Indicates The number of tea contaminations during the tea production process during a growth cycle, Indicates Number of storage temperature fluctuations per growth cycle, Indicates The highest temperature during the growth of tea leaves in a growth cycle, Indicates The lowest temperature during the growth cycle of tea leaves. Indicates The number of times the tea leaves experience pests during the growth cycle, Indicates The total weight of tea leaves during the tea picking process in a growth cycle, Indicates The completeness of tea leaves during the tea picking process of the growth cycle, Indicates The number of production equipment downtime and damage during the tea production process during a growth cycle, Indicates The number of tea contaminations during the tea production process during a growth cycle, Indicates Number of storage temperature fluctuations during a growth cycle.

[0032] The present invention provides a tea quality data security monitoring method, based on the above-mentioned tea quality data security monitoring system, comprising the following steps:

[0033] S1. Collect tea growth problem data, tea appearance data, production index, and storage index through the tea data collection module, and transmit them to the tea data analysis module after the collection is completed;

[0034] S2, the tea data security monitoring module monitors the tea production process and tea storage process in real time, and predicts losses when quality data security occurs;

[0035] S3. After receiving the growth problem data, tea appearance data, production index, and storage index, the tea data analysis module compares them with the preset standard data one by one, and calculates and analyzes the tea quality assessment data.

[0036] Compared with the prior art, the present invention provides a method and system for safely monitoring tea quality data, which has the following beneficial effects:

[0037] 1. The present invention compares the collected growth problem data, tea quality data, production indicators, storage indicators with the preset standard data one by one and inputs them into the quality evaluation function for quality evaluation to obtain quality evaluation data, thereby realizing the evaluation of the overall production of tea and reflecting the overall tea quality and safety situation from the comprehensive data.

[0038] 2. The present invention calculates the losses by respectively calculating the storage temperature fluctuations during tea storage and tea production, the number of production equipment shutdowns and damages, and the number of tea contaminations, thereby ensuring a warning effect on subsequent production links and allowing producers to better estimate costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 It is a schematic diagram of the system framework of the present invention;

[0040] Figure 2 It is a schematic diagram of the process of the present invention. DETAILED DESCRIPTION

[0041] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0042] See also Figure 1-Figure 2 , a tea quality data security monitoring system, including a tea data collection module, a tea data analysis module, a tea data security monitoring module and a loss prediction module;

[0043] The tea data collection module includes a tea growth data collection unit, a tea picking data collection unit, a tea production data collection unit and a tea storage data collection unit. The tea growth data collection unit is used to collect growth problem data that occurs during the growth of tea leaves. The growth problem data collected by the tea growth data collection unit during the growth of tea leaves include the highest temperature during the growth of tea leaves, the lowest temperature during the growth of tea leaves, and the number of insect pests experienced during the growth of tea leaves. The tea picking data collection unit is used to collect tea quality data during the tea picking process. The tea quality data includes the total weight of the tea leaves and the completeness of the tea leaves. The tea production data collection unit is used to collect production indicators during the tea production process, including the number of production equipment shutdowns and damages and the number of tea contaminations during the production process. The tea storage data acquisition unit is used to collect storage indicators during tea storage, including the number of storage temperature fluctuations. When the storage temperature difference during storage is greater than the storage temperature fluctuation threshold, the number of storage temperature fluctuations Plus one, the tea data collection module collects tea growth problem data, tea appearance data, production indicators, and storage indicators and sends them to the tea data analysis module and the tea data security monitoring module;

[0044] Indicates A growth problem dataset with growth cycles, Indicates The highest temperature during the growth of tea leaves in a growth cycle, Indicates The lowest temperature during the growth cycle of tea leaves. Indicates The number of times the tea leaves experience pests during the growth cycle, Indicates A tea quality dataset of growth cycles, Indicates The total weight of tea leaves during the tea picking process in a growth cycle, Indicates The completeness of tea leaves during the tea picking process of the growth cycle, Indicates A tea production index dataset for a growth cycle, Indicates The number of production equipment downtime and damage during the tea production process during a growth cycle, Indicates The number of tea contaminations during the tea production process during a growth cycle;

[0045] The tea data analysis module is used to analyze the collected growth problem data, tea quality data, production index, and storage index to obtain quality assessment data. The tea data analysis module compares the collected growth problem data, tea quality data, production index, and storage index with the preset standard data (here, the data of t-1 growth cycle is used as the standard data. If the data of t-1 growth cycle does not meet the standard, it is postponed in sequence until the data that meets the standard requirements is obtained) one by one and inputs them into the quality assessment function for quality assessment to obtain quality assessment data;

[0046] The quality assessment function is expressed as follows:

[0047]

[0048] in, Indicates The highest temperature during the growth of tea leaves in a growth cycle, Indicates The lowest temperature during the growth cycle of tea leaves. Indicates The number of times the tea leaves experience pests during the growth cycle, Indicates The total weight of tea leaves during the tea picking process in a growth cycle, Indicates The completeness of tea leaves during the tea picking process of the growth cycle, Indicates The number of production equipment downtime and damage during the tea production process during a growth cycle, Indicates The number of tea contaminations during the tea production process during a growth cycle, Indicates Number of storage temperature fluctuations per growth cycle, Indicates The highest temperature during the growth of tea leaves in a growth cycle, Indicates The lowest temperature during the growth cycle of tea leaves. Indicates The number of times the tea leaves experience pests during the growth cycle, Indicates The total weight of tea leaves during the tea picking process in a growth cycle, Indicates The completeness of tea leaves during the tea picking process of the growth cycle, Indicates The number of production equipment downtime and damage during the tea production process during a growth cycle, Indicates The number of tea contaminations during the tea production process during a growth cycle, Indicates Number of storage temperature fluctuations during a growth cycle.

[0049] The tea data security monitoring module is used to perform real-time detection of tea production index and storage index data security. It includes a production safety monitoring unit and a storage safety monitoring unit. The production safety monitoring unit is used to monitor the tea production process and provide timely feedback to the loss prediction module for loss prediction. The storage safety monitoring unit is used to monitor the storage process of tea and provide timely feedback to the loss prediction module for loss prediction. The loss prediction module calculates the losses caused by the number of production equipment shutdowns and damages and tea contamination during the production process:

[0050]

[0051] The loss function of the loss prediction module for the storage process of tea leaves is as follows:

[0052]

[0053] in, Indicates The total losses caused by the downtime and damage of production equipment and tea contamination during the tea production process during a growth cycle are Indicates that the current process is process, It represents the total processing cost from the first process to the first process. Indicates The processing cost of the i-th step in the tea production process of a growth cycle, No. The maintenance cost corresponding to the shutdown of tea production equipment during a growth cycle, Indicates The time loss cost corresponding to the number of tea contaminations in a growth cycle, represents the loss function of the storage process of tea leaves, Indicates the number of storage temperature fluctuations. Represents the coefficient of fluctuation.

[0054] The present invention also provides a tea quality data security monitoring method, based on the above-mentioned tea quality data security monitoring system, comprising the following steps:

[0055] S1. Collect tea growth problem data, tea appearance data, production index, and storage index through the tea data collection module, and transmit them to the tea data analysis module after the collection is completed;

[0056] S2, the tea data security monitoring module monitors the tea production process and tea storage process in real time, and predicts losses when quality data security occurs;

[0057] S3. After receiving the growth problem data, tea appearance data, production index, and storage index, the tea data analysis module compares them with the preset standard data one by one, and calculates and analyzes the tea quality assessment data.

[0058] Embodiment 1:

[0059] Through experiments, the following data are given for the quality assessment function to be calculated:

[0060] , ℃, , , , 4 , , , , ton, ton, , ;

[0061] Substituting the above values ​​into the quality assessment function, the calculated results are as follows:

[0062]

[0063] The final calculated value of the quality assessment function is 0.31125, which is a positive increase relative to the standard quality, and the increase value is 0.31125, indicating that the safety level of the t-th growth cycle is higher than that of the standard, thus achieving an evaluation of the overall production of tea, and reflecting the overall quality and safety of tea from the comprehensive data;

[0064] Embodiment 2:

[0065] The data of the production process are as follows:

[0066] I=3 (number of processes)

[0067] =5000 (total processing cost of the first process)

[0068] =3000 (total processing cost of the second process)

[0069] =4000 (total processing cost of the third process)

[0070] Calculate the loss during the generation process:

[0071]

[0072] in, , which indicates the time and price of its maintenance. The loss cost in the tea quality inspection is calculated through the loss function, so that the problem should be avoided in the next production, which can well ensure the quality of tea and the safety of the tea production process;

[0073] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A tea quality data security monitoring system, characterized by: It includes tea data collection module, tea data analysis module, tea data security monitoring module and loss prediction module; The tea data collection module includes a tea growth data collection unit, a tea picking data collection unit, a tea production data collection unit and a tea storage data collection unit. The tea growth data collection unit is used to collect growth problem data occurring during tea growth. The tea picking data collection unit is used to collect tea appearance data during tea picking. The tea production data collection unit is used to collect production indicators during tea production. The tea storage data collection unit is used to collect storage indicators during tea storage. The tea data collection module sends the collected tea growth problem data, tea appearance data, production indicators and storage indicators to the tea data analysis module and the tea data security monitoring module. The tea data analysis module is used to analyze the collected growth problem data, tea appearance data, production indicators and storage indicators to obtain quality assessment data; The tea data security monitoring module is used to perform real-time data security detection on the production index and storage index of tea, and includes a production safety monitoring unit and a storage safety monitoring unit. The production safety monitoring unit is used to monitor the production process of tea according to the production index, and timely feedback to the loss prediction module for loss prediction. The storage safety monitoring unit is used to monitor the storage process of tea according to the storage index, and timely feedback to the loss prediction module for loss prediction. The production index of the tea production data collection unit in the tea production process includes the number of production equipment shutdowns and damages and the number of tea contaminations in the production process, and its expression is as follows: ； in, Indicates A tea production index dataset for a growth cycle, Indicates The number of production equipment downtime and damage during the tea production process during a growth cycle, Indicates The number of tea contaminations during the tea production process during a growth cycle; The tea storage data acquisition unit collects storage indicators that appear during tea storage, including the number of storage temperature fluctuations. When the storage temperature difference during storage is greater than the storage temperature fluctuation threshold, the number of storage temperature fluctuations plus one; The loss prediction module predicts the loss of the tea storage process and the corresponding loss function is as follows: ； in, represents the loss function of the storage process of tea leaves, Indicates the number of storage temperature fluctuations. represents the coefficient of volatility; The tea data analysis module compares the collected growth problem data, tea appearance data, production index and storage index with the preset standard data one by one and inputs them into the quality evaluation function for quality evaluation to obtain quality evaluation data; The quality assessment function is expressed as follows: ； in, Indicates The highest temperature during the growth of tea leaves in a growth cycle, Indicates The lowest temperature during the growth cycle of tea leaves. Indicates The number of times the tea leaves experience pests during the growth cycle, Indicates The total weight of tea leaves during the tea picking process in a growth cycle, Indicates The completeness of tea leaves during the tea picking process of the growth cycle, Indicates The number of production equipment downtime and damage during the tea production process during a growth cycle, Indicates The number of tea contaminations during the tea production process during a growth cycle, Indicates Number of storage temperature fluctuations per growth cycle, Indicates The highest temperature during the growth of tea leaves in a growth cycle, Indicates The lowest temperature during the growth cycle of tea leaves. Indicates The number of times the tea leaves experience pests during the growth cycle, Indicates The total weight of tea leaves during the tea picking process in a growth cycle, Indicates The completeness of tea leaves during the tea picking process of the growth cycle, Indicates The number of production equipment downtime and damage during the tea production process during a growth cycle, Indicates The number of tea contaminations during the tea production process during a growth cycle, Indicates Number of storage temperature fluctuations during a growth cycle.

2. A tea quality data security monitoring system according to claim 1, characterized in that: The tea growth data collection unit collects growth problem data during the tea growth process, including the highest temperature during the tea growth process, the lowest temperature during the tea growth process, and the number of insect pests experienced during the tea growth process. The specific expression is as follows: ； in, Indicates A growth problem dataset with growth cycles, Indicates The highest temperature during the growth of tea leaves in a growth cycle, Indicates The lowest temperature during the growth cycle of tea leaves. Indicates The number of times the tea leaves experience pests during a growth cycle.

3. A tea quality data security monitoring system according to claim 1, characterized in that: The tea quality data collected by the tea picking data collection unit during the tea picking process includes the total weight of the tea leaves and the completeness of the tea leaves, and the specific expressions are as follows: ； in, Indicates A tea quality dataset of growth cycles, Indicates The total weight of tea leaves during the tea picking process in a growth cycle, Indicates The integrity of tea leaves during the tea picking process of a growth cycle.

4. A tea quality data security monitoring system according to claim 1, characterized in that: The loss prediction module calculates the loss caused by the number of production equipment shutdowns and damages and tea contamination during the production process as follows: ； in, Indicates The total losses caused by the downtime and damage of production equipment and tea contamination during the tea production process during a growth cycle are Indicates that the current process is process, It represents the total processing cost from the first process to the first process. Indicates The processing cost of the i-th step in the tea production process of a growth cycle, Indicates The maintenance cost corresponding to the shutdown of tea production equipment during a growth cycle, Indicates The time loss cost corresponding to the number of tea contaminations in a growth cycle.

5. A tea quality data security monitoring method, based on a tea quality data security monitoring system according to any one of claims 1 to 4, characterized in that: The following steps are involved: S1. Collecting tea growth problem data, tea appearance data, production indexes and storage indexes through the tea data collection module, and transmitting them to the tea data analysis module after the collection is completed; S2, the tea data security monitoring module monitors the tea production process and tea storage process in real time, and predicts losses when quality data security occurs; S3. After receiving the growth problem data, tea appearance data, production index and storage index, the tea data analysis module compares them with the preset standard data one by one, and calculates and analyzes the tea quality assessment data.

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