CN-122020584-A - Printing enterprise energy consumption data acquisition and analysis system and method

CN122020584ACN 122020584 ACN122020584 ACN 122020584ACN-122020584-A

Abstract

The application provides an energy consumption data acquisition and analysis system and method for printing enterprises, wherein a layered storage system is constructed according to the diversity characteristics of the energy consumption data of the printing enterprises, real-time energy consumption data and historical summarized data are obtained from different equipment types and are subjected to separation processing, the real-time energy consumption data and the historical summarized data are subjected to layered storage according to preset equipment classification rules to obtain a data set after preliminary classification, a time period-based summarized analysis method is adopted for the energy consumption abnormal records, the energy consumption abnormal records are compared with the historical energy consumption data stored for a long time period, whether a continuous energy consumption abnormal mode exists or not is judged, based on the relevance mapping result, the relation between the energy consumption abnormal mode and key links of a production flow is excavated, and specific production steps causing energy consumption abnormality are determined.

Inventors

GONG ZHONGZHI
HUANG CHANGHAO

Assignees

湖北和润文化发展有限公司

Dates

Publication Date: 20260512
Application Date: 20251231

Claims (8)

1. The utility model provides a printing enterprise energy consumption data acquisition analysis system and method, which is characterized in that the method includes: Aiming at the diversity characteristic of the energy consumption data of printing enterprises, a layered storage system is constructed, real-time energy consumption data and historical summarized data are obtained from different equipment types, and separation treatment is carried out; Layering and storing the real-time energy consumption data and the historical summarized data through a preset equipment classification rule to obtain a data set after preliminary classification; Based on the data set after preliminary classification, a memory buffer technology is adopted to design a high-efficiency buffer strategy aiming at the high-frequency acquisition requirement of real-time energy consumption data, instantaneous energy consumption information of specific equipment is rapidly recorded, and a storage path of high-frequency access is determined; Analyzing energy consumption fluctuation characteristics under different equipment types by utilizing the high-frequency access storage path, and triggering an abnormal mark to generate an energy consumption abnormal record containing a time mark if detecting that the energy consumption value of certain equipment exceeds a preset threshold value; Comparing the energy consumption abnormal record with long-term stored historical energy consumption data by adopting a time period-based summarization analysis method aiming at the energy consumption abnormal record, and judging whether a continuous energy consumption abnormal mode exists or not; acquiring related production order information according to the energy consumption abnormal mode, and establishing binding of the energy consumption abnormal mode and a production flow through the corresponding relation between an order number and an equipment operation log to obtain a relevance mapping result; based on the relevance mapping result, a data comparison analysis technology is adopted to mine the relation between the energy consumption abnormal mode and the key links of the production flow, and specific production steps causing energy consumption abnormality are determined.
2. The system and method for collecting and analyzing energy consumption data of printing enterprises according to claim 1, wherein the step of constructing a hierarchical storage system according to the diversity of the energy consumption data of the printing enterprises, obtaining real-time energy consumption data and historical summary data from different equipment types, and performing separation processing comprises the steps of: Classifying and marking all the energy consumption data according to the equipment type to obtain a classified energy consumption data set; distinguishing real-time data from historical data through the classified energy consumption data sets, and determining real-time energy consumption data flows and historical summary data sets; storing the real-time energy consumption data stream to a high-speed access layer by adopting a layered storage system to obtain a real-time data storage position; storing the historical summary data set to an archiving storage layer by adopting a layered storage system to obtain a historical data storage position; acquiring a real-time energy consumption data stream from a high-speed access layer, judging whether a current data time stamp belongs to the latest acquisition period, and if so, marking the current data time stamp as a current real-time record; Acquiring a historical summarized data set from an archiving storage layer, judging whether the data belong to the same equipment type, and if so, associating corresponding real-time records to form an equipment-level energy consumption sequence; And separating the real-time data from the historical data through the equipment-level energy consumption sequence to obtain a separated real-time part and a separated historical part.
3. The system and method for collecting and analyzing energy consumption data of printing enterprises according to claim 1, wherein the step of hierarchically storing the real-time energy consumption data and the historical summary data according to a preset device classification rule to obtain a data set after preliminary classification comprises the steps of: performing hierarchical storage on the real-time energy consumption data according to a preset classification rule to obtain a real-time classification data subset; performing hierarchical storage on the historical summary data according to a preset classification rule to obtain a historical classification data subset; the real-time classified data subset and the historical classified data subset are combined to obtain a complete classified data set; performing equipment cluster division on the complete classified data set by adopting a clustering algorithm to determine equipment cluster groups; if the deviation between the real-time energy consumption data and the historical summarized data in the equipment clustering group exceeds a preset threshold value, marking an abnormal group; acquiring abnormal data characteristics by counting data distribution in the abnormal group; performing adjustment on a preset classification rule according to the abnormal data characteristics to obtain an updated classification rule; and re-executing hierarchical storage on the complete classified data set by adopting the updated classification rule to obtain an optimized classified data set.
4. The printing enterprise energy consumption data collection and analysis system and method according to claim 1, wherein the determining a high-frequency access storage path based on the preliminary classified data set by designing a high-efficiency cache policy by adopting a memory buffer technology according to a high-frequency collection requirement of real-time energy consumption data, and rapidly recording instantaneous energy consumption information of a specific device comprises: According to the service content and the extracted related attributes, generating a service solution scheme, surrounding a high-frequency acquisition and storage optimization target of real-time energy consumption data, combining logic links among a plurality of attributes, and gradually realizing a technical process, namely constructing an initial data stream by carrying out high-frequency acquisition on the real-time energy consumption data, marking each data point by adopting a timestamp, and acquiring an instantaneous information record of specific equipment; According to the instantaneous information record, the acquired data stream is temporarily stored in a preset memory area in batches by using a memory buffering technology, and the temporary storage position of the data in the memory is determined; Aiming at the temporary storage position in the memory, a high-efficiency caching strategy is applied, the data storage priority is dynamically adjusted, and if the data access frequency is higher than a preset threshold value, the data is migrated to a quick storage area, so that optimized storage allocation is obtained; Extracting data from the quick storage area, combining equipment information of specific equipment to generate a classification identifier, if the classification identifier is consistent with a preliminary classification result, reserving a current storage path, and judging the effectiveness of data storage; Aiming at the reserved storage path, an access optimization mechanism is implemented, the data reading time of high-frequency access is shortened, and the final storage path configuration is determined through a path index technology; Continuously monitoring the real-time energy consumption data flow according to the final storage path configuration, and triggering a data distribution mechanism to acquire a new storage allocation scheme if the newly acquired data quantity exceeds the memory buffer capacity; And updating the storage structure of the data set through a new storage allocation scheme, and associating the processed data stream with equipment information to obtain a complete energy consumption data storage record.
5. The system and method for collecting and analyzing energy consumption data of printing enterprises according to claim 1, wherein the analyzing energy consumption fluctuation characteristics under different equipment types by using the high-frequency access storage path, if detecting that an energy consumption value of a certain equipment exceeds a preset threshold, triggering an anomaly flag to generate an energy consumption anomaly record containing a time identifier, comprises: Acquiring energy consumption data of various equipment types through a high-frequency access storage path, and extracting energy consumption data records in a specified time period from the storage path by adopting a batch reading mode to obtain a preliminary energy consumption data set; Aiming at the preliminary energy consumption data set, classifying according to the equipment types, obtaining energy consumption data subsets of each equipment type, calculating energy consumption fluctuation characteristics in the subsets by using a statistical method, and determining a fluctuation range and a change trend; according to the energy consumption fluctuation characteristics, combining with a preset threshold value, comparing the energy consumption data subsets of each equipment type one by one, and if the energy consumption data of a certain equipment type exceeds the preset threshold value, triggering an abnormal mark to obtain abnormal data points; aiming at the abnormal data points, obtaining corresponding time marks, and associating the abnormal data points with the time marks by adopting a time stamp matching mode to generate an energy consumption abnormal record with the time marks; updating the equipment monitoring log through the energy consumption abnormal record, and writing the abnormal mark and the time mark into the monitoring system by adopting an automatic recording mechanism to obtain updated monitoring data; And generating an energy consumption fluctuation report of the equipment type according to the updated monitoring data, adopting a data visualization tool to display the abnormal mark and the fluctuation characteristic in a chart form, and determining a final analysis result.
6. The system and method for collecting and analyzing energy consumption data of printing enterprises according to claim 1, wherein the comparing the energy consumption abnormal record with the long-term stored historical energy consumption data by using a time-period-based summary analysis method for the energy consumption abnormal record, and judging whether a sustainable energy consumption abnormal mode exists comprises: Acquiring an energy consumption abnormal record and an original energy consumption data sequence in a corresponding time period; Grouping and summarizing the energy consumption abnormal records according to a preset time period by adopting a time period summarizing and analyzing method to obtain abnormal record sets of each time period; Extracting a historical energy consumption data sequence of the same time period from the long-term storage data; the abnormal record set collected in the current time period is aligned and compared with the historical energy consumption data sequence segment by segment through a sliding window, and a deviation value sequence of each time period is obtained; If the deviation of a plurality of continuous time periods in the deviation value sequence exceeds a preset threshold value, determining that a potential continuous abnormal mode exists; According to the potential continuous abnormal mode, extracting an energy consumption data sequence of a corresponding time period to form an abnormal mode subsequence; Detecting abnormal points of the abnormal pattern subsequence by adopting an isolated forest algorithm to obtain an abnormal pattern persistence score; If the persistence score of the abnormal mode is higher than a preset threshold value, judging and confirming that the continuous energy consumption abnormal mode exists; And carrying out mode type grouping on the confirmed continuous energy consumption abnormal modes through a time sequence clustering algorithm to obtain abnormal mode type labels.
7. The system and method for collecting and analyzing energy consumption data of printing enterprises according to claim 1, wherein the steps of obtaining relevant production order information according to the energy consumption abnormal mode, establishing binding between the energy consumption abnormal mode and a production process through a corresponding relation between an order number and an equipment operation log, and obtaining a relevance mapping result comprise the following steps: Extracting a production order record related to the energy consumption abnormality from the system through a data acquisition module to obtain a preliminary data set; according to the preliminary data set, adopting a correlation analysis method, matching the order number with the equipment operation log, and determining a corresponding operation record set; if missing or abnormal data exists in the operation record set, filling is carried out through a historical data filling module, and a complete operation log data set is obtained; after a complete operation log data set is obtained, feature extraction is carried out aiming at the corresponding relation between the energy consumption abnormal mode and the production flow, and a feature mapping table is obtained; Analyzing the distribution condition of the abnormal mode in the production flow through the characteristic mapping table, and judging key influence links; If the key influence link exceeds a preset threshold range, triggering an abnormal alarm mechanism to generate targeted flow optimization suggestion data; and automatically adjusting production flow parameters according to the flow optimization suggestion data to obtain optimized operation configuration.
8. The system and method for collecting and analyzing energy consumption data of printing enterprises according to claim 1, wherein the specific production step of mining the relation between the energy consumption abnormality mode and the key links of the production process by adopting a data comparison analysis technology based on the relevance mapping result comprises the following steps: The method comprises the steps of obtaining historical energy consumption data and flow records from a production system, constructing a complete data set containing energy consumption abnormality and production flow information, and obtaining a data set after preliminary arrangement; according to the data set after arrangement, a data comparison method is adopted to analyze the corresponding conditions of the energy consumption abnormality and each link in the production flow, and the frequency and the link distribution of the occurrence of the energy consumption abnormality are determined; If the frequency of the abnormal energy consumption in a certain link exceeds a preset threshold, marking the link as a potential abnormal source, and acquiring a marked link list; aiming at the marked link list, acquiring upstream and downstream data of the link in the production flow, analyzing the association between the upstream and downstream ring nodes and the energy consumption abnormality, and judging whether abnormal diffusion caused by chain reaction exists or not; Extracting specific steps and related links causing energy consumption abnormality from the results of chain reaction analysis, and determining the step position of an abnormality source; According to the position of the step where the abnormality source is located, acquiring detailed operation parameters and environment data of the step, and quantifying the association degree of the parameters and the energy consumption abnormality by using a support vector machine algorithm to obtain a final abnormality cause analysis result; if the final analysis result shows that a certain operation parameter is highly correlated with the energy consumption abnormality, the parameter is recorded as a key improvement point, and the data support required by the improvement direction is judged.

Description

Printing enterprise energy consumption data acquisition and analysis system and method Technical Field The invention relates to the technical field of information, in particular to a printing enterprise energy consumption data acquisition and analysis system and method. Background In the modern industrial field, energy consumption management of printing enterprises is a crucial research direction, which is directly related to the operation cost and environmental sustainability of the enterprises. The printing industry becomes a key battlefield for energy conservation and emission reduction due to various equipment types and high energy consumption ratio. The energy consumption data is reasonably monitored and analyzed, so that enterprises can be helped to optimize the production process, and important support can be provided for green development of the industry. However, current research and practice still face many challenges in this regard, and breakthrough is needed. The existing energy consumption management method is difficult to adapt to the complex production environment of printing enterprises. Many schemes lack targeted support for different device types in data processing, resulting in inaccurate classification and efficient utilization of energy consumption information. Meanwhile, the methods have defects in data storage and system docking, and high requirements of enterprises on data integrity and relevance are difficult to meet. The limitation makes enterprises often fall into the dilemma of information island when facing energy consumption optimization, and influences decision-making efficiency. The technical difficulty of the deeper level is how to construct a multi-level storage architecture capable of processing real-time information and history simultaneously. The printing enterprises have wide energy consumption data sources, which cover a plurality of devices such as drying devices, printing units and the like, the data characteristics of each device have huge differences, for example, real-time data needs to be collected at high frequency to capture instantaneous changes, and historical data needs to be summarized according to time periods for long-term analysis. This diversity in data characteristics results in a need to compromise speed and capacity in the memory design, but it is often difficult in the prior art to balance the contradiction between the two. Furthermore, the contradiction also extends to the problem of the relevance of the data to the production flow, because if the energy consumption data cannot be hooked with specific production order information, a targeted optimization basis cannot be provided for enterprises. For example, in a certain print lot, if it is not possible to clearly distinguish which equipment energy consumption is related to a specific order, it is difficult to determine which steps in the production link have abnormally high energy consumption, and thus the opportunity for improvement is missed. Therefore, how to realize the deep fusion of the energy consumption data and the production information on the basis of a multi-level storage architecture and ensure the efficient processing and accurate matching of the data in a complex equipment environment becomes a key problem of the printing enterprise energy consumption data acquisition and analysis system. Disclosure of Invention The invention provides a printing enterprise energy consumption data acquisition and analysis system and a method, which mainly comprise the following steps: Aiming at the diversity characteristic of the energy consumption data of printing enterprises, a layered storage system is constructed, real-time energy consumption data and historical summarized data are obtained from different equipment types, and separation treatment is carried out; Layering and storing the real-time energy consumption data and the historical summarized data through a preset equipment classification rule to obtain a data set after preliminary classification; Based on the data set after preliminary classification, a memory buffer technology is adopted to design a high-efficiency buffer strategy aiming at the high-frequency acquisition requirement of real-time energy consumption data, instantaneous energy consumption information of specific equipment is rapidly recorded, and a storage path of high-frequency access is determined; Analyzing energy consumption fluctuation characteristics under different equipment types by utilizing the high-frequency access storage path, and triggering an abnormal mark to generate an energy consumption abnormal record containing a time mark if detecting that the energy consumption value of certain equipment exceeds a preset threshold value; Comparing the energy consumption abnormal record with long-term stored historical energy consumption data by adopting a time period-based summarization analysis method aiming at the energy consumption abnormal record, and judging wheth