CN-122022591-A - Grain full-link quality tracing system, method and medium

CN122022591ACN 122022591 ACN122022591 ACN 122022591ACN-122022591-A

Abstract

The application provides a grain full-link quality tracing system, method and medium, which belong to the technical field of grain safety, wherein the grain full-link quality tracing system comprises a data acquisition module, a block chain certification module, an intelligent analysis module and a cloud service module, wherein the data acquisition module is used for acquiring full-link grain data from raw material purchasing to storage, processing and circulation links in real time, the full-link grain data comprises environment data and equipment parameters, the block chain certification module is used for carrying out hash calculation on the full-link grain data acquired by the data acquisition module and manually-entered key business data and carrying out uplink certification, the intelligent analysis module is used for carrying out prediction and anomaly detection on grain quality risks based on the full-link grain data and the real-time full-link grain data, and the cloud service module is used for integrating multi-source data, providing a data interface and visual display and supporting full-link source tracing inquiry and supervision audit. The technical scheme of the application can solve the problems of data fault, tampering risk and risk early warning hysteresis in the prior art.

Inventors

LIU BIN
HU DONG
ZHANG ZHUANG
WEI BAOGUANG

Assignees

郑州华粮科技股份有限公司

Dates

Publication Date: 20260512
Application Date: 20260211

Claims (10)

1. The utility model provides a grain full link quality traceability system which characterized in that includes: The system comprises a data acquisition module, a data processing module and a data processing module, wherein the data acquisition module is used for acquiring all-link grain data from raw material purchasing to storage, processing and circulation links in real time, and the all-link grain data comprises environment data and equipment parameters; The block chain evidence storage module is used for carrying out hash calculation on all-link grain data acquired by the data acquisition module and manually-entered key service data and uploading the hash calculation to the chain evidence storage module; The intelligent analysis module is used for predicting grain quality risks and detecting anomalies by using a neural network based on the full-link grain data and the real-time full-link grain data of the uplink evidence; The cloud service module is used for integrating multi-source data, providing a data interface and visual display, and supporting full-link traceability inquiry and supervision audit.
2. The system of claim 1, wherein the data acquisition module comprises: The storage environment sensor comprises a temperature and humidity sensor, a PH value sensor and a pest sensor, wherein the temperature and humidity sensor, the PH value sensor and the pest sensor are respectively used for monitoring temperature and humidity information, PH value information and pest information; And the processing equipment interface is used for interfacing with a PLC system of the processing equipment through an OPC UA protocol so as to acquire equipment parameters of the processing equipment in real time.
3. The system of claim 1, wherein the blockchain certification module adopts a alliance chain architecture, and the consensus nodes of the alliance chain architecture comprise grain enterprises, regulatory authorities and third party detection authorities, and the certification data types comprise raw material purchase contracts, quality inspection reports, warehouse-in and warehouse-out receipts and sensor raw data.
4. The system of claim 1, wherein the intelligent analysis module comprises: The mildew prediction unit is used for inputting the full-link grain data into an LSTM neural network model and outputting to obtain future mildew probability; wherein, the all-link grain data comprises historical environmental data, grain types and storage duration; and the abnormality detection unit is used for identifying the mutation of the processing parameters based on an isolated forest algorithm and triggering equipment fault early warning.
5. The system of claim 1, wherein the cloud service module comprises: the data center is used for integrating multi-source data from the Internet of things, the blockchain and manual input and providing a unified API interface; The visualization platform is used for displaying the full-link tracing flow chart, the environment data trend chart and the risk early warning thermodynamic diagram.
6. The full link quality tracing method for the grains is characterized by comprising the following steps of: Acquiring all-link grain data from grain purchasing to storage, processing and circulation links in real time through Internet of things equipment; Carrying out hash calculation and uplink certification on the full-link grain data and manually-entered key business data by using a blockchain technology; the AI model is utilized to analyze the uplink evidence and the full-link grain data acquired in real time, so as to realize the risk early warning and anomaly detection of the full-link grain; and a full-link data query, visual display and supervision audit interface is provided through the cloud platform, so that full-link traceability query and supervision audit of grain quality are realized.
7. The method of claim 6, wherein the analyzing the full-link grain data with the AI model to realize risk early warning and anomaly detection of the full-link grain comprises: based on an LSTM mildew prediction model, predicting the input full-link grain data, and outputting to obtain future mildew probability; and identifying the processing parameter mutation in the full-link grain data based on an anomaly detection model of the isolated forest, and triggering equipment fault early warning.
8. The method of claim 6, further comprising automatically triggering the device to regulate or push the pre-warning information to the associated responsible party when an environmental anomaly or a deviation in a process parameter is detected.
9. The method of claim 6, wherein hashing and uplink certification of the full-link grain data and manually entered critical traffic data by a blockchain technique comprises: The data hash value is written into the federation chain and is authenticated by the multi-party node consensus.
10. A computer storage medium having stored thereon a computer program, wherein the computer program when executed implements the grain full link quality traceability method according to any of claims 6 to 9.

Description

Grain full-link quality tracing system, method and medium Technical Field The application belongs to the technical field of grain safety, and particularly relates to a grain full-link quality traceability system, method and medium. Background The current grain quality tracing technology mainly comprises two types, namely (1) basic internet of things monitoring, namely realizing data record of a single storage link through a temperature and humidity sensor and an ERP system, but lacking inter-link data association and risk analysis capability, and (2) traditional block chain tracing, namely, focusing on key data uplink of a processing link, wherein raw material purchasing data still depends on manual input, and the risks of 'data island' and 'tamper before uplink' exist. Moreover, conventional paper, electronic records have a large amount of unstructured data, which are difficult to integrate. To sum up, the existing grain quality tracing technology is difficult to realize quality data closed-loop tracing of full life cycles of raw material purchase, storage, processing, finished product circulation and the like, which causes the problems of data fault, tampering risk, risk early warning hysteresis and the like in the traditional grain industry quality tracing. Disclosure of Invention The technical scheme provided by the application mainly aims to provide a grain full-link quality tracing method, equipment and medium, and the scheme can solve the problems that quality data of full life cycles such as raw material purchase, storage, processing and finished product circulation are difficult to trace in a closed loop manner in the prior art, so that data fault, tampering risk and risk early warning hysteresis in the quality tracing of the traditional grain industry are caused. According to a first aspect of the present application, an embodiment of the present application provides a grain full link quality traceability system, including: the data acquisition module is used for acquiring all-link grain data of grains from raw material purchasing to storage, processing and circulation links in real time, wherein the all-link grain data comprises environmental data and equipment parameters; The block chain evidence storage module is used for carrying out hash calculation on all-link grain data acquired by the data acquisition module and manually-entered key service data and uploading the hash calculation to the chain evidence storage module; The intelligent analysis module is used for predicting grain quality risks and detecting anomalies by using a neural network based on the full-link grain data and the real-time full-link grain data of the uplink evidence; The cloud service module is used for integrating multi-source data, providing a data interface and visual display, and supporting full-link traceability inquiry and supervision audit. Preferably, the grain full-link quality traceability system, the data acquisition module comprises: the storage environment sensor comprises a temperature and humidity sensor, a PH value sensor and a pest sensor, wherein the storage environment sensor is used for respectively monitoring temperature and humidity information, PH value information and pest information; And the processing equipment interface is used for interfacing with a PLC system of the processing equipment through an OPC UA protocol so as to acquire equipment parameters of the processing equipment in real time. Preferably, the block chain evidence storage module of the grain full-link quality tracing system adopts a alliance chain architecture, wherein consensus nodes of the alliance chain architecture comprise grain enterprises, regulatory departments and third party detection institutions, and the evidence storage data types comprise raw material purchase contracts, quality inspection reports, in-out library receipts and sensor raw data. Preferably, the grain full-link quality traceability system, the intelligent analysis module comprises: The mildew prediction unit is used for inputting all-link grain data into the LSTM neural network model and outputting to obtain future mildew probability, wherein the all-link grain data comprises historical environment data, grain types and storage duration; and the abnormality detection unit is used for identifying the mutation of the processing parameters based on an isolated forest algorithm and triggering equipment fault early warning. Preferably, in the grain full-link quality traceability system, the cloud service module includes: the data center is used for integrating multi-source data from the Internet of things, the blockchain and manual input and providing a unified API interface; The visualization platform is used for displaying the full-link tracing flow chart, the environment data trend chart and the risk early warning thermodynamic diagram. According to a second aspect of the present application, the present application provides a grain full link quality tra