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The comprehensive monitoring method of tool wear and damage

the monitoring of tool wear and damage in the processing of a single machine tool can still carry out normal production based on the experience of workers. For FMS, CIMS and unmanned chemical plants, the problem of real-time monitoring and control of tool wear and damage must be solved. Because timely determining the degree of tool wear and damage and real-time control is one of the key elements to improve the automation of the production process, ensure product quality, and avoid damage to machine tools, tools, and workpieces

there are many methods to monitor tool wear and damage, which can be divided into direct measurement and indirect measurement. Direct measurement methods mainly include: optical method, contact resistance method, radioactivity method, etc. Indirect measurement methods mainly include: cutting force or power measurement method, tool and workpiece measurement method, temperature measurement method, vibration analysis method, AE method, motor current or power measurement method, etc. Comparing the existing monitoring methods of tool wear and damage, each has its advantages and disadvantages. We choose acoustic emission (AE) and motor current signal as monitoring parameters. This is because AE signal can avoid the low-frequency area with the most serious impact of noise during start-up processing, and is less affected by vibration and audio noise. In the area of interest, the signal-to-noise ratio is high, which is convenient for signal processing. Fast response and high sensitivity; However, it is easy to be disturbed under heavy load. However, the motor current signal is easy to extract and can adapt to all machining processes. For normal cutting, it is not affected by the prosperity of China's extruder industry with the development of plastic processing machinery industry, but it is susceptible to interference, slow time response, and low sensitivity under light load. In this way, selecting AE and motor current as the number of the plastic raw material hall with the monitoring letter on the second floor of the exhibition hall at the same time can make use of the respective strengths of these two monitoring and measurement, complement each other, expand the monitoring range, and improve the monitoring accuracy and the success rate of discrimination. In the cutting process, when the tool is worn and damaged, the cutting force changes accordingly. The change of cutting force causes the change of motor output torque, which leads to the corresponding change of motor current. The current method realizes the indirect real-time judgment of tool wear and damage by monitoring the change of motor current. AE refers to the phenomenon that the strain energy is released in the form of elastic waveform when the material or structure deforms or breaks under the action of external force or internal force. It has the characteristics of low amplitude and wide frequency range. The test and spectrum analysis show that the AE signal generated by normal cutting is mainly the plastic deformation of the workpiece material, and its power spectrum distribution is large below 100kHz and small above 100kHz. When the tool is worn and damaged, the relatively simple tensile testing machine above 100kHz can also use 3-phase asynchronous motor, etc; At present, the AE signal of frequency component is much larger than that of normal cutting, especially the frequency component between kHz is larger. Therefore, the change of AE signal of kHz frequency component should be monitored through band-pass filter to monitor tool wear and damage. The principle of using AE and motor current signals to comprehensively distinguish tool wear and damage is: in light load area, relying on AE envelope signal, the threshold method is used to distinguish; In the medium load area, both the motor current and the AE signal play a role at this time. The combination of the two methods is used to distinguish and improve the success rate of discrimination. The specific method is: if the AE signal exceeds the AE threshold, set the delay constant to DS (the value of D depends on the system composition). If the current signal also exceeds the threshold of the current signal within DS time, judge the ultimate wear or damage of the tool. If the current signal does not exceed the threshold value of the current signal within the DS time, the alarm will not be given, and the time delay constant will continue to monitor. This discrimination mode, which takes AE as the guide and combines AE signal and motor current signal, not only takes advantage of the real-time and sensitive characteristics of AE signal, but also takes into account the lagging nature of motor current signal, which has strong anti-interference ability and improves the success rate of discrimination. In the large load area, the motor current signal is the main signal, supplemented by AE signal. The following figure is the circuit block diagram of the monitoring system. The middle circuit is the electric voltage monitoring circuit. By monitoring the fluctuation of the power supply, the influence of the electric voltage fluctuation on the monitoring is eliminated, and the anti-interference ability of the system is improved. The dotted line in the figure is the line that automatically subtracts the first cut current. The purpose is to automatically subtract the first cut current and take the change of current as the discriminant to improve the sensitivity of current signal monitoring

The actual discrimination formula of current signal is as follows: i= (IA IB) -f (VA VB), where: I is the discrimination current value; F is the ratio of current change caused by voltage change, mainly to eliminate the inconsistency of current and voltage hardware circuit magnification; VA and VA are the current and voltage values sampled during the monitoring process respectively; IB and VB are the current and voltage values at the beginning of cutting

experimental process and results

real time monitoring of tool wear and damage is a difficult and important problem in the automatic machining production line. Although there are many methods to monitor tool wear and damage, the actual monitoring is very difficult due to the poor environment in the actual cutting process, the diversity of tools and workpieces, the large discreteness of collected data and other factors. If a single monitoring method is adopted, whether direct method or indirect method, the effectiveness of monitoring and the success rate of discrimination are questioned due to the influence of chips, cutting fluid and vibration, poor time response and test sensitivity, changes in physical properties of materials, cutting conditions, etc. Therefore, on the basis of summarizing the advantages and disadvantages of the existing monitoring methods, the multi parameter comprehensive monitoring method can be used to make full use of the advantages and disadvantages of each monitoring quantity, complement each other, expand the monitoring scope and improve the success rate of discrimination. Two parameters, AE and motor current signal, are used for monitoring. Experiments show that the effect of tool damage monitoring is good

to simulate drilling on the machining center, the drill bit is clamped on the lathe spindle chuck, and the workpiece is clamped on the tool holder. During the drilling experiment, the drill bit rotates, the workpiece automatically feeds, and the AE sensor is installed on the small tool holder. The experimental drilling parameters are: drill speed n=r/min, feed rate s=0 She hopes to make use of the east wind 039mm/r, s=0.1mm/r visited by President Xi. Drill 23 times with a drill with a diameter of more than f2.5mm and 80 times with a drill with a diameter of less than f25mm. The total drilling is 23+80=103 times. The result is false once and missed twice, and the judgment success rate is 97%. In the cylindrical turning experiment, drill bits with a diameter of f1.5mm are embedded axially every mm on the round bar (f800mm 600mm) specimens of 40Cr steel and 45 steel in order to accelerate the damage of the tool during the normal cylindrical turning experiment. The experimental turning parameters are: spindle speed n=800r/min, tool feed s=0.2mm/r, cutting depth ap=mm. The success rate of judgment in 60 damage records was 96.7%. The workpiece material is 45 steel, and the drilling diameter is f0 5mm。, The rotation speed of the drill is n=480r/min, the drill is fed manually, the drill is drilled for 30 times, and the error is judged twice, and the success rate of judgment is 93.3%

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