Industrial Safety Risk Early Warning and Decision System

Abstract

A workplace safety risk early warning and decision-making system includes a data receiving unit, a data processing unit, a decision adjustment unit, and an output unit. The data receiving unit receives heterogeneous data containing multi-faceted information and transmits it to the data processing unit. The data processing unit uses a data preprocessing module to aggregate the heterogeneous instructions into an analysis unit, which then analyzes the data through an anomaly detection module and outputs the anomaly information for the current analysis period to a prediction module, thereby generating an initial risk prediction result. The decision adjustment unit receives the initial risk prediction result and combines it with the anomaly information for the current analysis period, process-related information, and historical risk status information to perform fusion calculations and correct the initial risk prediction result. It then outputs a final risk prediction result to the output unit, which outputs the prediction result and corresponding execution instructions, thereby achieving high-reliability risk prediction and proactive early warning.

Claims

1. An industrial safety risk early warning and decision-making system, comprising: A data receiving unit receives heterogeneous data, including anomaly-related data reflecting abnormal conditions on-site, process-related data reflecting resource consumption and output, and historical risk status data recording previous system judgment results. A data processing unit is connected to the data receiving unit and internally includes a data preprocessing module, an anomaly judgment module, and a prediction module. The data preprocessing module aggregates the heterogeneous data into an analysis unit according to a preset analysis cycle. The anomaly judgment module analyzes the data and outputs at least one anomaly indicator, a cumulative number of anomaly indicators, and an anomaly status information to the prediction module to produce an initial risk prediction result. A decision adjustment unit is connected to the data processing unit. It performs a fusion calculation on the initial risk prediction result, the cumulative number of anomaly indicators, the anomaly status information, the process-related data, and the historical risk status data. It then corrects the initial risk prediction result according to an adjustment logic to produce a final risk prediction result. An output unit is connected to the decision adjustment unit to output the final risk prediction result and generate and output an execution instruction based on the final risk prediction result. The execution instruction includes a handling level, a priority order, a notification requirement, and a contingency measure.

2. The industrial safety risk early warning decision system as described in claim 1, wherein, The abnormality-related data includes at least one or a combination of the following: number of equipment alarms, abnormal ambient gas monitoring, equipment maintenance records, false alarm reports, and violation records; the process-related data includes at least one of the following: output, resource usage, and process load indicators.

3. The industrial safety risk early warning decision system as described in claim 1, wherein, The data preprocessing module performs preprocessing on multiple raw daily data, including format conversion, time-series sorting, and numerical standardization, and aggregates them into an analysis unit with a weekly analysis cycle. Furthermore, it establishes a correspondence between the risk prediction results of the current analysis cycle and the next analysis cycle.

4. The industrial safety risk early warning decision system as described in claim 1, wherein, The anomaly detection module generates an anomaly indicator by determining whether a single indicator reaches a warning threshold, calculates the cumulative number of anomaly indicators within the same analysis period, and records the degree and status of the anomaly indicator to generate anomaly status information.

5. The industrial safety risk early warning decision system as described in claim 1, wherein, The adjustment logic includes a prediction correction mechanism. When the decision adjustment unit executes the prediction correction mechanism, if the initial risk prediction result reaches a high risk level, and the cumulative number of abnormal indicators is lower than a preset safety range and there are no significant abnormal indicators in the current analysis period, the decision adjustment unit determines that the initial risk prediction result lacks supporting conditions and lowers the initial risk prediction result by at least one risk level.

6. The industrial safety risk early warning decision system as described in claim 1, wherein, The adjustment logic includes an anomaly-driven adjustment mechanism. When the decision adjustment unit executes the anomaly-driven mechanism, if multiple anomaly indicators in the current analysis period show multi-faceted anomalies and the cumulative number reaches a preset upward adjustment threshold, the decision adjustment unit will still adjust the initial risk prediction result upward by at least one risk level, even if the initial risk prediction result does not reach the high-risk level.

7. The industrial safety risk early warning decision system as described in claim 1, wherein, The adjustment logic also includes a process load enhancement mechanism. When the decision adjustment unit executes the process load enhancement mechanism, if the process-related data shows that the output or resource consumption has increased compared to a historical baseline, the decision adjustment unit will adjust the risk level of the initial risk prediction result based on the increased load.

8. The industrial safety risk early warning decision system as described in claim 1, wherein, The adjustment logic further includes a historical risk continuation mechanism. When the decision adjustment unit executes the historical risk continuation mechanism, if the historical risk status data shows that the previous analysis period was at a high risk level, and the abnormal status information of the current analysis period shows that the abnormal indicator continues to exist or the corresponding degree of abnormality increases, the decision adjustment unit maintains or increases the risk level of the initial risk prediction result.

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