Intelligent monitoring method and system for real-time working state of numerical control machine tool

Abstract

The invention belongs to the field of numerical control machine tools, and relates to an intelligent monitoring method and system for the real-time working state of a numerical control machine tool. According to the temperature data T1 of the first temperature sensor and the change rate thereof, and the temperature data T2 of the second temperature sensor and the change rate thereof, whether the work of the numerical control machine tool is abnormal is judged; or judging whether the numerical control machine tool works abnormally or not according to the humidity data H corresponding to the humidity sensor and the change rate thereof; or judging whether the numerical control machine tool works abnormally or not according to the correlation coefficient of the sound signal; through the temperature and humidity sensor and the microphone, the real-time heating and heat dissipation conditions of the machine tool during working can be reflected in time.

Description

Technical Field

[0001] The invention belongs to the field of numerically controlled machine tools, and relates to an intelligent monitoring method and system for the real-time working status of numerically controlled machine tools. Background Art

[0002] CNC machine tools are widely used in industrial production. CNC machine tools are high-precision equipment, and slight deviations can cause abnormal operation. When abnormal operation occurs, it may cause damage to the workpiece or increase the temperature of the machine tool. In extreme cases, the machine tool may even be damaged. Therefore, when CNC machine tools are working, experienced staff are required to monitor their working status at all times, and detect and correct abnormalities in time. However, since the manifestation of abnormal conditions is not easy to detect, especially when processing new workpieces, the new processing status is not understood, and the abnormal working status cannot be correctly distinguished, it is often the case that abnormal conditions cannot be discovered in time, resulting in production losses. Summary of the invention

[0003] The purpose of the present invention is to overcome the above-mentioned shortcomings of the prior art and to provide an intelligent monitoring method and system for the real-time working status of a CNC machine tool.

[0004] In order to achieve the above object, the present invention adopts the following technical solution: an intelligent monitoring method for the real-time working state of a CNC machine tool, specifically comprising the following steps:

[0005] Step 1, obtaining data information that can reflect the real-time working status of the CNC machine tool, the data information including: temperature data T1 of a first temperature sensor arranged at a liquid inlet of a coolant flow passage in a CNC machine tool workshop, temperature data T2 of a second temperature sensor arranged at a liquid outlet of a coolant flow passage in a CNC machine tool workshop; humidity data H of a humidity sensor arranged on an inner wall of a CNC machine tool workshop; and sound signals transmitted from a microphone arranged in a CNC machine tool workshop;

[0006] Step 2: judging whether the CNC machine tool is working abnormally according to the temperature data T1 of the first temperature sensor and its change rate, and the temperature data T2 of the second temperature sensor and its change rate; or judging whether the CNC machine tool is working abnormally according to the humidity data H corresponding to the humidity sensor and its change rate; or judging whether the CNC machine tool is working abnormally according to the correlation coefficient of the sound signal;

[0007] Step 3: If the CNC machine tool operates abnormally, the DSP chip sends an alarm start control signal to the alarm device.

[0008] Further, judging whether there is an abnormality in the operation of the CNC machine tool according to the temperature data T1 of the first temperature sensor and the temperature data T2 of the second temperature sensor is as follows:

[0009] When T2-T1≥2℃ or T2≥27℃, the machine tool is judged to be working abnormally, and the DSP chip sends an alarm start control signal to the alarm device.

[0010] Further, judging whether there is an abnormality in the operation of the CNC machine tool according to the change rate of the temperature data T1 of the first temperature sensor and the change rate of the temperature data T2 of the second temperature sensor is as follows:

[0011] when or At 06:00, it was determined that the machine tool was working abnormally;

[0012] in: t n The rate of change of the temperature value T1 at the moment; t n The rate of change of the temperature value T2 at the moment; t n+1 The rate of change of the temperature value T1 at the moment; t n+1 The rate of change of the temperature value T2 at the moment; t n-1 The rate of change of the temperature value T1 at the moment; t n-1 The rate of change of the temperature value T2 at the moment; t n-1 ,t n ,t n+1 are adjacent moments separated by 0.5S;

[0013] Alternatively, the rate of change can be obtained by taking the derivative of T1 with respect to time t The rate of change is obtained by taking the derivative of T2 with respect to time t when or It is determined that the machine tool is working abnormally.

[0014] Furthermore, it is determined whether the operation of the CNC machine tool is abnormal according to the humidity data H corresponding to the humidity sensor. Specifically, the humidity threshold is set to H2, and when H≥H2, it is determined that the operation of the machine tool is abnormal.

[0015] Further, the change rate of the humidity data H corresponding to the humidity sensor is used to determine whether the CNC machine tool is abnormal. Specifically, the humidity data H is derived to obtain When multiple consecutive groups of two consecutive moments t n and t n+1 When the rate of change of the humidity value H exceeds the threshold value H1, it is determined that the machine tool is operating abnormally.

[0016] Furthermore, the correlation coefficient of the sound signal is used to assist in determining whether the CNC machine tool is operating abnormally, specifically:

[0017] First, define a plurality of continuous single-segment sound signals as a sum segment, calculate the correlation coefficient of the frequency spectrum between two single segments in each sum segment, if the correlation coefficient is within a specified interval, it is determined that the sounds of the two single segments are the same sound, record and store the characteristic parameters of the same sound, classify multiple groups of the same sound according to the characteristic parameters and number them in sequence, the numbered sounds are called well-known sounds Sn, and all well-known sounds Sn form a well-known sound library;

[0018] Then, each single-segment sound signal sent by the microphone is compared with the frequency spectrum of the stored familiar sound Sn in turn to obtain the correlation coefficient; if the magnitude change of the correlation coefficient is within the specified interval, it is classified as the familiar sound Sn, otherwise it is determined to be a new sound, the characteristic parameters of the new sound are recorded and stored, and the new sound is added to the familiar sound library and numbered in sequence;

[0019] Finally, according to the recorded time, check the relevant parameters of temperature and humidity at the time of the new sound. If the characteristic parameters of the new sound change but the relevant parameters of temperature and humidity do not change, mark the new sound as a normal sound. Otherwise, mark the sound as an abnormal sound. When an abnormal sound occurs, an alarm is triggered, an alarm sound is emitted, and a yellow light flashes.

[0020] Furthermore, the characteristic parameters are: spectrum, extreme value, average value, bandwidth, time of occurrence and the number of times the same sound occurs is calculated.

[0021] Furthermore, the correlation coefficient is specifically: the temperature value at the current moment, the rate of change of the temperature value, the difference in the rate of change of the temperature value, the humidity value, and the rate of change of the humidity.

[0022] In addition, the present invention also provides an intelligent monitoring system for the real-time working status of a CNC machine tool, comprising the following modules:

[0023] Signal collection module: including a first temperature sensor arranged at the liquid inlet of the coolant flow passage in the CNC machine tool workshop, a second temperature sensor arranged at the liquid outlet of the coolant flow passage in the CNC machine tool workshop; a humidity sensor arranged on the inner wall of the CNC machine tool workshop; and a microphone arranged in the CNC machine tool workshop;

[0024] Signal processing module: judging whether the CNC machine tool is working abnormally according to the temperature data T1 of the first temperature sensor and its change rate, the temperature data T2 of the second temperature sensor and its change rate; or judging whether the CNC machine tool is working abnormally according to the humidity data H corresponding to the humidity sensor and its change rate; or assisting in judging whether the CNC machine tool is working abnormally according to the correlation coefficient of the sound signal;

[0025] Alarm module: If the CNC machine tool operates abnormally, the DSP chip sends an alarm start control signal to the alarm device.

[0026] Compared with the prior art, the present invention has the following beneficial effects:

[0027] First, the present invention arranges two temperature sensors on the passage through which the coolant flows in the CNC machine tool workshop, and the sensors are arranged at the liquid inlet and the liquid outlet respectively. Since the coolant flows directly through the machining interface between the machine tool cutter head and the workpiece after entering the machine tool workshop from the liquid inlet to cool the machining process, the difference in the temperature change rate transmitted by the two temperature sensors can reflect the real-time heating and heat dissipation of the machine tool.

[0028] Second, the present invention is also provided with a humidity sensor for monitoring the real-time humidity H in the CNC machine tool workshop. Once the humidity value H and the humidity change rate value exceed a fixed threshold, it is determined that the CNC machine tool is working abnormally and an alarm is issued;

[0029] Thirdly, the present invention is also provided with a microphone. For the sound signal transmitted by the microphone, whether the sound is abnormal is determined by the correlation coefficient of the sound and the related parameters of temperature and humidity, and an alarm is given in time when an abnormal sound occurs. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The accompanying drawings are incorporated in and constitute a part of this specification and, together with the description, serve to explain the principles of the present invention.

[0031] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0032] Figure 1 It is an overall block diagram of the monitoring system for the real-time working status of the CNC machine tool in the present invention. DETAILED DESCRIPTION

[0033] Here, exemplary embodiments will be described in detail, and the embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Instead, they are only examples of devices consistent with some aspects of the present invention as detailed in the appended claims.

[0034] Example 1

[0035] An intelligent monitoring method for the real-time working status of a CNC machine tool comprises the following steps:

[0036] Step 1, obtaining data information that can reflect the real-time working status of the CNC machine tool, the data information including: temperature data T1 of a first temperature sensor arranged at a liquid inlet of a coolant flow passage in a CNC machine tool workshop, temperature data T2 of a second temperature sensor arranged at a liquid outlet of a coolant flow passage in a CNC machine tool workshop; humidity data H of a humidity sensor arranged on an inner wall of a CNC machine tool workshop; and sound signals transmitted from a microphone arranged in a CNC machine tool workshop;

[0037] Step 2: judging whether there is any abnormality in the operation of the CNC machine tool according to the temperature data T1 and its change rate of the first temperature sensor and the temperature data T2 and its change rate of the second temperature sensor;

[0038] Step 3: If the CNC machine tool operates abnormally, the DSP chip sends an alarm start control signal to the alarm device.

[0039] like Figure 1 As shown, DSP is a control and computing chip. Temperature sensor 1 is arranged on the passage through which the coolant flows in the CNC machine tool workshop. There are two temperature sensors, which are arranged at the liquid inlet (used to monitor the temperature T1 of the coolant entering the CNC machine tool workshop) and the liquid outlet (used to monitor the temperature T2 of the coolant flowing out of the CNC machine tool workshop). Since the coolant flows directly through the machining interface between the machine tool cutter head and the workpiece after entering the machine tool workshop from the liquid inlet to cool the machining process, the difference between T2 and T1 and the difference in the rate of change can reflect the real-time heating and heat dissipation of the machine tool. The humidity sensor is arranged on the inner wall of the workshop to monitor the real-time humidity H in the CNC machine tool workshop. The alarm device can emit sound and light alarms in case of abnormalities.

[0040] Further, judging whether there is an abnormality in the operation of the CNC machine tool according to the temperature data T1 of the first temperature sensor and the temperature data T2 of the second temperature sensor is as follows:

[0041] When T2-T1≥2℃ or T2≥27℃, the machine tool is judged to be working abnormally, and the DSP chip sends an alarm start control signal to the alarm device.

[0042] In this embodiment: DSP receives data T1 and T2 from the temperature sensor, and collects data from T1 and T2 every 0.5 seconds. When T2-T1≥2℃ or T2≥27℃, an alarm is triggered, an alarm sound is sounded, a red light flashes, and the time when this occurs is recorded and stored.

[0043] Further, judging whether there is an abnormality in the operation of the CNC machine tool according to the change rate of the temperature data T1 of the first temperature sensor and the change rate of the temperature data T2 of the second temperature sensor is as follows:

[0044] when or When judging that the machine tool is working abnormally;

[0045] in: t n The rate of change of the temperature value T1 at the moment; t n The rate of change of the temperature value T2 at the moment; t n+1 The rate of change of the temperature value T1 at the moment; t n+1 The rate of change of the temperature value T2 at the moment; t n-1 The rate of change of the temperature value T1 at the moment; t n-1 The rate of change of the temperature value T2 at the moment; t n-1 ,t n ,t n+1 are adjacent moments separated by 0.5S;

[0046] Alternatively, the rate of change can be obtained by taking the derivative of T1 with respect to time t The rate of change is obtained by taking the derivative of T2 with respect to time t when or It is determined that the machine tool is working abnormally.

[0047] In this embodiment, the DSP receives the data T1 and T2 of the temperature sensor, and collects the data of T1 and T2 every 0.5 seconds, and calculates the change rate of T1 and T2 respectively. That is, take the derivative of T1 and T2 with respect to time t respectively. When three consecutive groups of two consecutive moments t n and t n+1 The rate of change of T1 and T2 exceeds the threshold, that is, When or When the machine tool is judged to be working abnormally, DSP sends an alarm start control signal to the alarm device, the alarm system sounds an alarm and flashes a yellow light, and records and stores the time when this situation occurs.

[0048] Alternatively, the DSP receives the data T1 and T2 from the temperature sensor, and collects data from T1 and T2 every 0.5 seconds, and calculates the change rates of T1 and T2 respectively. When any of the change rates is ≥1.02, the machine tool is judged to be working abnormally, and the DSP sends an alarm start control signal to the alarm device. The alarm system alarms, sounds an alarm and flashes a yellow light, and records and stores the time when this situation occurs.

[0049] In addition, the present invention also provides an intelligent monitoring system for the real-time working status of a CNC machine tool, comprising the following modules:

[0050] Signal collection module: including a first temperature sensor arranged at the liquid inlet of the coolant flow passage in the CNC machine tool workshop, a second temperature sensor arranged at the liquid outlet of the coolant flow passage in the CNC machine tool workshop; a humidity sensor arranged on the inner wall of the CNC machine tool workshop; and a microphone arranged in the CNC machine tool workshop;

[0051] Signal processing module: judging whether the CNC machine tool is working abnormally according to the temperature data T1 of the first temperature sensor and its change rate, the temperature data T2 of the second temperature sensor and its change rate; or judging whether the CNC machine tool is working abnormally according to the humidity data H corresponding to the humidity sensor and its change rate; or assisting in judging whether the CNC machine tool is working abnormally according to the correlation coefficient of the sound signal;

[0052] Alarm module: If the CNC machine tool operates abnormally, the DSP chip sends an alarm start control signal to the alarm device.

[0053] Example 2

[0054] This embodiment is different from the embodiment 1 in that: judging whether there is abnormality in the operation of the CNC machine tool according to the humidity data H corresponding to the humidity sensor and its change rate;

[0055] Furthermore, it is determined whether the operation of the CNC machine tool is abnormal according to the humidity data H corresponding to the humidity sensor. Specifically, the humidity threshold is set to H2, and when H≥H2, it is determined that the operation of the machine tool is abnormal.

[0056] In this embodiment: DSP receives data H from humidity sensor. DSP collects data of H every 0.5 seconds. When H exceeds threshold value H2, it is determined that the machine tool is working abnormally, DSP sends alarm start control signal to alarm device, alarm system alarms, sounds alarm and flashes red light.

[0057] Further, the change rate of the humidity data H corresponding to the humidity sensor is used to determine whether the CNC machine tool is abnormal. Specifically, the humidity value H is derived to obtain When multiple consecutive groups of two consecutive moments t n and t n+1 When the rate of change of H exceeds the threshold value H1, it is determined that the machine tool is operating abnormally.

[0058] In this embodiment: DSP receives data H from humidity sensor. DSP collects data of H every 0.5 seconds. Calculate the change rate of H When the rate of change of H of three consecutive groups of two consecutive moments n and n+1 exceeds the threshold H1, the machine tool is judged to be operating abnormally, and the time when this happens is recorded and stored. The DSP sends an alarm start control signal to the alarm device, and the alarm system sounds an alarm and flashes a yellow light.

[0059] Example 3

[0060] This embodiment is different from the embodiment 1 in that: the correlation coefficient of the sound signal is used to assist in determining whether the CNC machine tool is operating abnormally;

[0061] Furthermore, the correlation coefficient of the sound signal is used to assist in determining whether the CNC machine tool is operating abnormally, specifically:

[0062] First, define a plurality of continuous single-segment sound signals as a sum segment, calculate the correlation coefficient of the spectrum between two single segments in each sum segment, if the correlation coefficient is within a specified interval, it is determined that the sounds of the two single segments are the same sound, record and store the characteristic parameters of the same sound, classify multiple groups of the same sound according to the characteristic parameters and number them in sequence, the numbered sounds are called well-known sounds Sn, and all well-known sounds form a well-known sound library;

[0063] Then, each single-segment sound signal sent by the microphone is compared with the frequency spectrum of the stored familiar sound Sn in turn to obtain the correlation coefficient; if the magnitude change of the correlation coefficient is within the specified interval, it is classified as the familiar sound Sn, otherwise it is determined to be a new sound, the characteristic parameters of the new sound are recorded and stored, and the new sound is added to the familiar sound library and numbered in sequence;

[0064] Finally, according to the recorded time, check the relevant parameters of temperature and humidity at the time of the new sound. If the characteristic parameters of the new sound change but the relevant parameters of temperature and humidity do not change, mark the new sound as a normal sound. Otherwise, mark the sound as an abnormal sound. When an abnormal sound occurs, an alarm is triggered, an alarm sound is emitted, and a yellow light flashes.

[0065] Furthermore, the characteristic parameters are: spectrum, extreme value, average value, bandwidth, time of occurrence and the number of times the same sound occurs is calculated.

[0066] Furthermore, the correlation coefficient is specifically: the temperature value at this moment, the rate of change of the temperature value, the difference in the rate of change of the temperature value, the humidity value H, and the rate of change of the humidity value H.

[0067] In this embodiment: the DSP chip receives the sound signal a(t) transmitted by the microphone, collects, segments and stores the sound signal. The sound collection frequency is greater than or equal to 40kHz, and the data of the sound signal within each 1 second time interval is divided into a segment, called a single segment. The Fourier transform of the i-th single segment sound data is calculated and its absolute value is taken, recorded as F(i), which is called the spectrum of the segment sound. The 11 consecutive single segments from F(i-5) to F(i+5) are called a sum segment, and the correlation coefficient of the spectrum between the two single segments in each sum segment is calculated. If the correlation coefficient changes within plus or minus 15%, it is determined that the sound signals of the two single segments are the same. The spectrum, extreme value, average value, bandwidth (bandwidth is defined as the difference between the maximum frequency and the minimum frequency), the time of occurrence and the number of times the same sound appears are recorded and stored. These values ​​are called the characteristic parameters of the sound. According to the characteristic parameters, the sound is classified and numbered in sequence, and the numbered sound is called the familiar sound Sn. According to this step, the calculation ends for 30 minutes and goes to the next step.

[0068] Then, for each single-segment sound signal sent by the microphone, it is compared with the spectrum of the stored familiar sound Sn in turn to calculate the correlation coefficient. If the correlation coefficient changes within plus or minus 15%, the two single-segment sound signals are determined to be the same and classified into one category. Otherwise, the sound is determined to be a new sound and numbered. The spectrum, extreme value, average value, bandwidth, and time of occurrence of the new sound are recorded and stored, and the number of times the same sound appears is calculated. These values ​​are called the characteristic parameters of the sound. The sound is classified and numbered in turn according to the characteristic parameters. At this point, the numbered sound is called the familiar sound Sn.

[0069] Finally, according to the recorded time, check the sound characteristics, temperature change rate, temperature value, humidity value, humidity change rate and secondary derivative of temperature at that moment. If the sound characteristics change but the relevant parameters of temperature and humidity do not change, mark the sound as normal sound, otherwise mark the sound as abnormal sound. When abnormal sound occurs, an alarm will be triggered, sounding an alarm and flashing a yellow light.

[0070] The above description is only a specific embodiment of the present invention, so that those skilled in the art can understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention.

[0071] It should be understood that the present invention is not limited to what has been described above and that various modifications and changes may be made without departing from its scope. The scope of the present invention is limited only by the appended claims.

Claims

1. An intelligent monitoring method for the real-time working status of a CNC machine tool, characterized in that: The specific steps include: Step 1, obtaining data information that can reflect the real-time working status of the CNC machine tool, the data information including: temperature data T1 of a first temperature sensor arranged at a liquid inlet of a coolant flow passage in a CNC machine tool workshop, temperature data T2 of a second temperature sensor arranged at a liquid outlet of a coolant flow passage in a CNC machine tool workshop; humidity data H of a humidity sensor arranged on an inner wall of a CNC machine tool workshop; and sound signals transmitted from a microphone arranged in a CNC machine tool workshop; Step 2: judging whether the CNC machine tool is working abnormally according to the temperature data T1 of the first temperature sensor and its change rate, and the temperature data T2 of the second temperature sensor and its change rate; or judging whether the CNC machine tool is working abnormally according to the humidity data H corresponding to the humidity sensor and its change rate; or judging whether the CNC machine tool is working abnormally according to the correlation coefficient of the sound signal; Step 3: If the CNC machine tool operates abnormally, the DSP chip sends an alarm start control signal to the alarm device.

2. The intelligent monitoring system for real-time working status of a CNC machine tool according to claim 1 is characterized in that: According to the temperature data T1 of the first temperature sensor and the temperature data T2 of the second temperature sensor, it is judged whether there is an abnormality in the operation of the CNC machine tool, specifically: When T2-T1≥2℃ or T2≥27℃, the machine tool is judged to be working abnormally, and the DSP chip sends an alarm start control signal to the alarm device.

3. The intelligent monitoring system for real-time working status of a CNC machine tool according to claim 1 is characterized in that: Whether there is an abnormality in the operation of the CNC machine tool is determined according to the change rate of the temperature data T1 of the first temperature sensor and the change rate of the temperature data T2 of the second temperature sensor, specifically: when or When judging that the machine tool is working abnormally; in: t n The rate of change of the temperature value T1 at the moment; t n The rate of change of the temperature value T2 at the moment; t n+1 The rate of change of the temperature value T1 at the moment; t n+1 The rate of change of the temperature value T2 at the moment; t n-1 The rate of change of the temperature value T1 at the moment; t n-1 The rate of change of the temperature value T2 at the moment; t n-1 ,t n ,t n+1 are adjacent moments separated by 0.5S; Alternatively, the rate of change can be obtained by taking the derivative of T1 with respect to time t The rate of change is obtained by taking the derivative of T2 with respect to time t when or It is determined that the machine tool is working abnormally.

4. The intelligent monitoring system for real-time working status of a CNC machine tool according to claim 1 is characterized in that: According to the humidity data H corresponding to the humidity sensor, it is judged whether the operation of the CNC machine tool is abnormal. Specifically, the humidity threshold is set to H2, and when H≥H2, it is determined that the operation of the machine tool is abnormal.

5. The intelligent monitoring system for real-time working status of a CNC machine tool according to claim 1 is characterized in that: According to the change rate of the humidity data H corresponding to the humidity sensor, it is judged whether there is an abnormality in the operation of the CNC machine tool. Specifically, the humidity data H is derived to obtain When multiple consecutive groups of two consecutive moments t n and t n+1 When the rate of change of the humidity value H exceeds the threshold value H1, it is determined that the machine tool is operating abnormally.

6. The intelligent monitoring system for real-time working status of a CNC machine tool according to claim 1 is characterized in that: According to the correlation coefficient of the sound signal, it is possible to assist in judging whether there is any abnormality in the operation of the CNC machine tool: First, define a plurality of continuous single-segment sound signals as a sum segment, calculate the correlation coefficient of the frequency spectrum between two single segments in each sum segment, if the correlation coefficient is within a specified interval, it is determined that the sounds of the two single segments are the same sound, record and store the characteristic parameters of the same sound, classify multiple groups of the same sound according to the characteristic parameters and number them in sequence, the numbered sounds are called well-known sounds Sn, and all well-known sounds Sn form a well-known sound library; Then, each single-segment sound signal sent by the microphone is compared with the frequency spectrum of the stored familiar sound Sn in turn to obtain the correlation coefficient; if the magnitude change of the correlation coefficient is within the specified interval, it is classified as the familiar sound Sn, otherwise it is determined to be a new sound, the characteristic parameters of the new sound are recorded and stored, and the new sound is added to the familiar sound library and numbered in sequence; Finally, according to the recorded time, check the relevant parameters of temperature and humidity at the time of the new sound. If the characteristic parameters of the new sound change but the relevant parameters of temperature and humidity do not change, mark the new sound as a normal sound. Otherwise, mark the sound as an abnormal sound. When an abnormal sound occurs, an alarm is triggered, an alarm sound is emitted, and a yellow light flashes.

7. The intelligent monitoring system for real-time working status of a CNC machine tool according to claim 6 is characterized in that: The characteristic parameters are: spectrum, extreme value, average value, bandwidth, time of occurrence and the number of times the same sound occurs is calculated.

8. The intelligent monitoring system for real-time working status of a CNC machine tool according to claim 6, characterized in that: The correlation coefficients are specifically: the temperature value at the current moment, the rate of change of the temperature value, the difference in the rate of change of the temperature value, the humidity value, and the rate of change of the humidity.

9. An intelligent monitoring system for the real-time working status of a CNC machine tool according to any one of claims 1 to 8, characterized in that: Includes the following modules: The signal collection module includes a first temperature sensor arranged at a liquid inlet of a passage through which the coolant flows in a CNC machine tool workshop, and a second temperature sensor arranged at a liquid outlet of a passage through which the coolant flows in a CNC machine tool workshop; Humidity sensors installed on the inner wall of the CNC machine tool workshop; Microphones are installed in the CNC machine tool workshop; Signal processing module: judging whether the CNC machine tool is working abnormally according to the temperature data T1 of the first temperature sensor and its change rate, the temperature data T2 of the second temperature sensor and its change rate; or judging whether the CNC machine tool is working abnormally according to the humidity data H corresponding to the humidity sensor and its change rate; or assisting in judging whether the CNC machine tool is working abnormally according to the correlation coefficient of the sound signal; Alarm module: If the CNC machine tool operates abnormally, the DSP chip sends an alarm start control signal to the alarm device.

Images