自动化设备运行监控数据

设备监控系统能够实时监测设备的运行状态和参数，包括电压、电流、产量、合格率等。通过传感器和数据采集设备，系统可以收集大量的实时数据，并进行分析和处理。监控设备电压、电流、功率等数据是否超出合理范围，确保设备安全可靠运行，一旦设备出现异常情况，系统会立即发出预警信号，通知相关人员进行处理。这种实时监测和预警功能大大提高了故障的及时性和准确性，避免了设备故障对生产造成的损失，可通过移动互联，手机电脑随时随地查看，调取设备数据信息，从设备抓取实时数据，系统可以通过监测设备的运行状况和性能指标，识别出潜在的故障风险，并马上采取相应的维护措施。这种预测性维护可以避免设备故障的突发性和不可预测性，降低了维修成本和停机时间，提高了生产效率和设备利用率。系统端根据抓取的数据，定期存储数据包。一般2秒/次设备生产情况，监控记录设备数据包，为产品过程追溯，数据做质量分析，技术分析设备终端算法：历史合格率=历史合格数/历史产量；当前产量=当前产量+1；合格数=合格数+1；不合格数=不合格数+1；合格率 = 合格数/当前产量；历史产量=历史产量+1；历史合格数=历史合格数+1；历史不合格数=历史不合格数+1；运行时长=行时长+1；停机时长=停机时长+1；报警时长=报警时长+1；其他参数均为直接采集。
1、检测电压、电流，超出正常范围，发出预警，确认设备安全可靠运行；
2、统计设备报警码，报警次数远超平均次数，预警相关的气缸/传感器可能发生故障，需要维护更换；
3、监控设备合格率，当合格率偏低，发出预警；
4、监控设备不合格数量，连续N只(数量可设)不合格将发出系统预警。
经过以上几点，可识别出潜在的故障风险，并马上采取相应的维护措施。

The equipment monitoring system can perform real-time monitoring of the operating status and parameters of equipment, including voltage, current, output, pass rate, and other metrics. Equipped with sensors and data acquisition devices, the system collects massive real-time data for analysis and processing. It monitors whether key parameters such as equipment voltage, current, and power exceed reasonable ranges to ensure safe and reliable operation of the equipment. Once an abnormality occurs in the equipment, the system will immediately send out early warning signals to notify relevant personnel for handling.

This real-time monitoring and early warning function greatly improves the timeliness and accuracy of fault detection, avoiding production losses caused by equipment failures. The system supports remote access to equipment data via mobile internet, allowing users to view and retrieve information anytime and anywhere through mobile phones or computers. By capturing real-time data from equipment, the system can identify potential fault risks based on operating status and performance indicators, and take corresponding maintenance measures immediately.

This predictive maintenance can avoid sudden and unpredictable equipment failures, reduce maintenance costs and downtime, and improve production efficiency and equipment utilization rate.

The system regularly stores data packets based on the captured data. It typically records equipment production data packets every 2 seconds, and the monitoring logs these data packets for product process traceability, data-driven quality analysis, and technical analysis. The terminal algorithms of the equipment are as follows:
- Historical pass rate = Number of historical qualified products / Historical output
- Current output = Current output + 1
- Qualified count = Qualified count + 1
- Unqualified count = Unqualified count + 1
- Pass rate = Qualified count / Current output
- Historical output = Historical output + 1
- Historical qualified count = Historical qualified count + 1
- Historical unqualified count = Historical unqualified count + 1
- Operating duration = Operating duration + 1
- Downtime duration = Downtime duration + 1
- Alarm duration = Alarm duration + 1
All other parameters are collected directly.

The monitoring system includes the following four detection items:
1. Voltage and current detection: Send out early warning signals if they exceed the normal range, to ensure safe and reliable operation of the equipment;
2. Alarm code statistics: If the number of alarms far exceeds the average value, issue an early warning that the relevant cylinders/sensors may malfunction and require maintenance or replacement;
3. Pass rate monitoring: Send out an early warning when the equipment pass rate is too low;
4. Unqualified product count monitoring: Issue a system early warning when there are N consecutive unqualified products (the quantity N is configurable).

Through the above monitoring items, potential fault risks can be identified, and corresponding maintenance measures can be taken immediately.