Machine tool bearing is the key component of machine tool, its running state directly affects the performance and life of machine tool. The running temperature of the bearing is one of the important parameters to reflect its running state. This paper will discuss how to effectively monitor and analyze the running temperature of machine tool bearings from the aspects of the importance of temperature monitoring, working principle, practical operation and case analysis.
During the operation of machine tool bearings, due to friction, poor lubrication, overload and other reasons, heat will be generated, resulting in an increase in bearing temperature. Excessive temperature will cause the mechanical properties of bearing materials to decline, accelerate bearing wear, and even lead to bearing failure. Therefore, monitoring and analysis of the operating temperature of the machine tool bearing can timely detect potential problems, avoid bearing damage, and ensure the normal operation of the machine tool.
The basic principle of temperature monitoring is to use the sensor to convert the temperature signal into an electrical signal, which is then processed and displayed by an instrument or a computer. Commonly used temperature sensors are thermal resistance, thermocouple and so on. Among them, thermal resistance is the use of material resistance changes with temperature characteristics to measure the temperature; Thermocouples use the thermoelectric potential generated by two different metals at the contact point to measure temperature.
In the temperature monitoring of machine tool bearings, the temperature sensor is usually installed on the bearing seat or bearing to monitor the temperature change of the bearing in real time. At the same time, the alarm threshold can also be set to send an alarm signal when the bearing temperature exceeds a certain range, reminding the operator to deal with it in time.
Data collection: In actual operation, it is necessary to collect the temperature data of machine tool bearings regularly. The collection frequency can be set on a case-by-case basis, such as once per hour or once per shift. At the same time, ensure that the temperature sensor is installed in the correct position to avoid being affected by other heat sources.
Data analysis: The collected temperature data needs to be analyzed and processed. The temperature change of the bearing can be evaluated by drawing the temperature change curve, calculating the average temperature and the standard difference. At the same time, it can also be combined with other parameters, such as bearing vibration, noise, etc., to comprehensively analyze the running state of the bearing.
Problem treatment: When the bearing temperature is found to increase abnormally during the analysis process, timely measures should be taken to deal with it. For example, check lubrication status, adjust bearing clearance, replace worn parts, etc. At the same time, abnormal situations and handling measures should also be recorded for future analysis and summary.
Taking the main shaft bearing of a certain type of CNC machine tool as an example, the bearing has an obvious temperature rise during operation. The data collected by the temperature monitoring system shows that the bearing temperature has risen from the normal range of 40 ° C to 70 ° C in a short time. Combined with the analysis of other parameters, it is found that the vibration and noise of the bearing are also increased.
In response to this problem, the operator first checked the lubrication condition and found that the lubricating oil was insufficient and of poor quality. After changing the lubricating oil and adjusting the bearing clearance, the bearing temperature gradually returns to the normal range, and the vibration and noise are also reduced. The timely discovery and treatment of the problem avoided bearing damage and ensured the normal operation of the machine tool.
This paper discusses the importance of monitoring and analysis of running temperature of machine tool bearings, working principle and practical operation. The function and value of temperature monitoring in practical application are illustrated by case analysis. With the continuous development of science and technology, the temperature monitoring of machine tool bearings in the future will be more intelligent and refined. For example, wireless sensor networks can be used to achieve remote monitoring of multiple bearings; Artificial intelligence algorithms can be used to conduct in-depth analysis and prediction of temperature data. The development of these technologies will provide more possibilities and convenience for the temperature monitoring and analysis of machine tool bearings.
