A drum automatic adjustment method based on shearer cutting vibration signal

Abstract

The present invention discloses a method for automatically adjusting a drum based on a coal mining machine cutting vibration signal. Before adjusting the drum, the coal mining machine drum is first controlled to cut the coal seam and the roof / floor rock layer respectively, and the vibration signal of each part in the Y direction is obtained for time-frequency domain conversion to obtain the respective signal frequency domain energy distribution; finally, a threshold for judging the roof / floor rock layer is established according to the respective high-frequency and medium-frequency energy proportions when the coal seam and the roof / floor rock layer are cut; during actual coal mining and automatic adjustment of the drum, it is only necessary to obtain the vibration signal in the Y direction within a set time period for time-frequency domain conversion to obtain the high-frequency and medium-frequency energy proportions within the current time period, and after comparing the proportions with the thresholds of the roof / floor rock layer respectively, the current drum position can be determined, and it can be determined whether the drum height needs to be adjusted; each analysis process is fast, so that the rock property changes currently cut by the drum can be identified in real time, and the drum height can be adjusted in time.

Description

Technical Field

[0001] The invention relates to an automatic drum adjustment method, in particular to an automatic drum adjustment method based on a shearer cutting vibration signal, and belongs to the technical field of shearer coal cutting. Background Art

[0002] The shearer is the most important mining equipment in a fully mechanized mining face. During coal seam cutting operations, underground workers usually control the shearer's current operating status using a handheld wireless remote control or a head station, such as adjusting the shearer's traction speed or the drum's cutting height. However, workers need to follow the shearer along the working face for a long time, observing the current situation of the coal mining face to complete the cutting operation. In the harsh underground working environment, workers work long hours, have heavy workloads, and experience high labor intensity, resulting in low work efficiency and endangering the safety of workers and equipment. Due to the harsh working environment underground in coal mines, with high dust and low visibility, workers can easily misjudge the shearer's cutting status, resulting in an inability to adjust the shearer's drum height in a timely manner. When the shearer drum height is adjusted too high, the drum cuts rock, causing accelerated wear of the picks, shortening the shearer's life, and causing cut gangue to fall into the coal, increasing the cost of later coal washing. It also creates a dusty and noisy working environment, endangering the lives of workers. When the shearer drum height is adjusted too low, the top and bottom coal residues are too thick, resulting in a low recovery rate at the mining face and reduced economic efficiency. The fundamental solution to this problem is to vigorously develop intelligent and automated control technologies for shearers, that is, to achieve automatic adjustment of the drum during the shearer cutting process. Key technologies involved include automatic recognition of the coal-rock interface. The automatic recognition technology of coal-rock interface means that the coal mining machine can automatically recognize the coal-rock interface during cutting, so that the drum automatically adjusts its height when it reaches the coal-rock interface, and keeps the drum cutting the coal seam all the time. There are currently some automatic recognition technologies for coal-rock interface, but there are generally many detection equipments that need to be deployed, and the data processing is relatively complicated and the real-time performance is poor. Once the installation accuracy of a certain detection equipment does not meet the requirements, the accuracy of the entire automatic recognition process will be reduced. Therefore, how to provide a method that only requires the deployment of less detection equipment and can quickly process the acquired data, identify the rock property changes of the current drum cutting in real time, and thus determine whether the drum height needs to be adjusted, is one of the research directions of this industry. Summary of the Invention

[0003] In response to the problems existing in the above-mentioned prior art, the present invention provides a method for automatic adjustment of the drum based on the cutting vibration signal of the coal mining machine. It only requires the deployment of less detection equipment, and can quickly process the acquired data, identify the rock property changes of the current drum cutting in real time, and thus determine whether the drum height needs to be adjusted.

[0004] In order to achieve the above object, the technical solution adopted by the present invention is: a method for automatically adjusting the drum based on the cutting vibration signal of the coal mining machine, the specific steps are:

[0005] Step 1: Lay out the acquisition device and data processing device: The acquisition device is two three-component vibration sensors, which are respectively arranged behind the bearings of the two rollers of the coal mining machine. Each three-component sensor is coupled with the corresponding coal mining machine roller through a bolt connection to ensure the stability of vibration data acquisition, and the three component directions of each three-component vibration sensor are along the direction of the roadway, along the direction of the cutting eye, and vertical to the top and bottom plates; the data processing device is a signal processing base station, which is placed inside the coal mining machine body. The two three-component vibration sensors are connected to the signal processing base station through a data line, which is used to feed back the real-time vibration signals collected by each to the signal processing base station for analysis and processing. The signal processing base station is connected to the coal mining machine body control system to adjust the height of the coal mining machine roller according to the analysis and processing results;

[0006] Step 2: Establish an observation system: Establish an observation coordinate system based on the mining face, define the direction along the roadway as the X direction of the three-component sensor, the direction along the cut as the Y direction of the three-component sensor, and the direction perpendicular to the roof and floor as the Z direction of the three-component sensor; the Y and Z directions are the cutting directions of the drum;

[0007] Step 3: Establish judgment criteria: Before the shearer performs automatic drum adjustment, the shearer drum is first controlled to cut the coal seam, roof rock layer, and floor rock layer respectively, and the cutting time of each part is the same. The three-component vibration signals of the above three parts in the cutting time period are respectively collected through two three-component vibration sensors, and the vibration signal in the Y direction of each three-component vibration sensor is obtained. Then, the vibration signal in the Y direction when cutting the above three parts is converted into time-frequency domain to obtain the signal frequency domain energy distribution in the cutting time period of each part; finally, according to the high-frequency and medium-frequency energy proportions of each coal seam, roof rock layer, and floor rock layer when cutting, the threshold value for judging the roof rock layer and the threshold value for judging the floor rock layer are respectively established;

[0008] Step 4. Coal rock identification and drum height adjustment of the coal mining machine: During the coal mining process of the coal mining machine, the two three-component vibration sensors feed back the collected vibration signals of the two drums to the signal processing base station in real time. The signal processing base station converts the vibration signal in the Y direction of the collected signal into the time-frequency domain at set intervals to obtain the signal frequency domain energy distribution within the current set time period, and then obtains the high-frequency and medium-frequency energy proportions within the current time period, and compares them with the thresholds of the roof rock layer and the bottom rock layer in step 3. If the high-frequency and medium-frequency energy proportions of the two three-component vibration sensors do not exceed the respective thresholds of the roof rock layer and the bottom rock layer, it means that both drums are in the coal seam cutting state at this time; if the high-frequency and medium-frequency energy proportions of any three-component vibration sensor exceed the respective thresholds of the roof rock layer or the bottom rock layer, it means that the drum corresponding to the three-component vibration sensor is in the rock layer cutting state. At this time, the signal processing base station lowers or raises the height of the drum through the coal mining machine body control system to put it in the coal seam cutting state.

[0009] Furthermore, in step 1, each three-component vibration sensor is provided with a protective housing, and the data line between the three-component vibration sensor and the signal processing base station is provided with a protective device, which is a protective cover. This prevents coal lumps and other debris from damaging the three-component vibration sensor or the data line during the coal mining process, thereby affecting coal mining efficiency.

[0010] Furthermore, the specific process of establishing the judgment criteria in step 3 is as follows:

[0011] A. Conduct training on cutting coal and rock on the working face. Control one of the drums of the coal mining machine to cut the coal seam, roof rock layer, and floor rock layer respectively. The cutting time of each part is 1 minute. The three-component vibration sensor corresponding to the drum collects the Y-direction vibration signals of the drum cutting the coal seam for 1 minute, the roof rock layer for 1 minute, and the floor rock layer for 1 minute, which are recorded as s respectively. c 、s r 、s f ;

[0012] B. Perform time-frequency transformation on the Y-direction vibration signal obtained in step A, and obtain the high-frequency band, medium-frequency band and low-frequency band of the cutting coal seam, cutting roof rock layer and cutting floor rock layer in the 1 minute time period, which are s ch 、s cm 、s cl 、s rh 、s rm 、s rl 、s fh 、s fm 、s fl ;

[0013] C. Based on the results obtained in step B, calculate the energy sum of the high-frequency, medium-frequency and low-frequency signals of the cutting coal seam, cutting roof rock layer and cutting floor rock layer within a 1-minute time period, which are expressed as Es respectively. ch 、Es cm 、Es cl 、Es rh 、Es rm 、Es rl 、Es fh 、Es fm 、Es fl ;

[0014] D. Based on the results calculated in step C, calculate the proportion of high-frequency energy and medium-frequency energy in the cut coal seam, cut roof rock layer, and cut floor rock layer within a 1-minute time period, respectively, and express them as: n ch 、n cm 、n rh 、n rm 、n fh 、n fm ; n rh and n rm Together as the threshold of the roof rock layer; n fh and n fm together as the threshold of the basement rock layer;

[0015] E. Repeat steps A to D for another drum to obtain the threshold values of the top rock layer and the bottom rock layer of the other drum.

[0016] Furthermore, in step 3, a time-frequency domain conversion is performed to obtain the frequency domain energy distribution of the signal within each cut time period. Specifically, the vibration signals of the 1-minute coal seam, 1-minute roof rock layer, and 1-minute floor rock layer are cut and time-frequency transformed. The specific formula is as follows:

[0017]

[0018] Where f(t) is s c 、s r 、s f The frequency domain distribution of the cut coal seam, cut roof rock layer and cut floor rock layer and their energy distribution in different frequency bands are obtained respectively. The vibration signal frequency of the shearer drum below 300 Hz is defined as the low frequency band, 300-1500 Hz is defined as the medium frequency band, and above 1500 Hz is defined as the high frequency band. The energy summation of the low, medium and high frequency bands of the cut coal seam, cut roof rock layer and cut floor rock layer within the 1 minute cutting time period is calculated respectively. The specific formula is as follows:

[0019]

[0020] In the formula, low frequency band: m = 1, n = 300; medium frequency band: m = 301, n = 1500; high frequency band: m = 1501, n = half of the sampling frequency of the acquisition device.

[0021] Furthermore, the two rollers are defined as Roller 1 and Roller 2, with Roller 1 set to cut the coal seam near the roof and Roller 2 set to cut the coal seam near the floor. During the coal mining process, the vibration signal collected by Roller 1 only needs to be compared with the threshold of the roof rock layer, and the height of Roller 1 is adjusted based on the comparison result; the vibration signal collected by Roller 2 only needs to be compared with the threshold of the floor rock layer, and the height of Roller 2 is adjusted based on the comparison result. This setting further reduces the comparison process, as each roller only needs to be compared with a single threshold, making the roller adjustment more real-time.

[0022] Compared with the prior art, the present invention has the following advantages:

[0023] 1. The present invention first defines the direction of each component of the three-component vibration sensor, and then before automatically adjusting the drum, first controls the coal mining machine drum to cut the coal seam, roof rock layer and floor rock layer respectively, and obtains the three-component vibration signal of each part through the three-component vibration sensor, then performs time-frequency domain conversion on the vibration signal of each part in the Y direction, and obtains the signal frequency domain energy distribution within the cutting time period of each part; finally, according to the proportion of high-frequency and medium-frequency energy of each when cutting the coal seam, roof rock layer and floor rock layer, the threshold value of judging the roof rock layer and the threshold value of judging the floor rock layer are established respectively. Threshold value; subsequently, when the coal mining machine actually mines coal and automatically adjusts the drum, it only needs to obtain the vibration signal in the Y direction within the set time period through the three-component vibration sensor for time-frequency domain conversion, so as to obtain the proportion of high-frequency and medium-frequency energy in the current time period. After comparing this proportion with the threshold value of the roof rock layer and the threshold value of the bottom rock layer respectively, the current position of the drum can be determined, and it can be determined whether the drum height needs to be adjusted up or down; each analysis process is fast, so that the rock property changes currently cut by the drum can be identified in real time, and the drum height can be adjusted in time to ensure the smooth progress of coal mining.

[0024] 2. The detection equipment of the present invention consists of only two three-component vibration sensors, which are respectively arranged behind the bearings of the two rollers. The signal processing base station can use the one already provided by the coal mining machine, or be set up separately. No other detection equipment is required, which not only makes installation convenient, but also reduces the failure rate and makes maintenance more convenient due to the small number of detection devices, thereby ensuring the accuracy of data acquisition and providing a stable source of vibration data for subsequent coal and rock identification and roller adjustment. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 It is a schematic diagram of the layout of the acquisition device and data processing device of the present invention;

[0026] Figure 2 It is a schematic diagram of the protection structure of the acquisition device and the data line in the present invention;

[0027] Figure 3 It is the frequency domain diagram of the coal-rock change interface in the present invention;

[0028] Figure 4 This is a diagram showing the proportion of high-frequency energy when one of the rollers of the present invention cuts the roof rock layer. DETAILED DESCRIPTION

[0029] The present invention will be further described below.

[0030] like Figure 1 As shown, the specific steps of the present invention are:

[0031] Step 1: Lay out the acquisition device and data processing device: The acquisition device is two three-component vibration sensors, which are respectively arranged behind the bearings of the two rollers of the coal mining machine. Each three-component sensor is coupled with the corresponding coal mining machine roller by bolt connection to ensure the stability of vibration data acquisition, and the three component directions of each three-component vibration sensor are respectively along the direction of the roadway, along the direction of the cutting eye, and vertical to the top and bottom plates; the data processing device is a signal processing base station, which is placed inside the coal mining machine body. The two three-component vibration sensors are connected to the signal processing base station through a data line, which is used to feed back the real-time vibration signals collected by each to the signal processing base station for analysis and processing. The signal processing base station is connected to the coal mining machine body control system to adjust the height of the coal mining machine roller according to the analysis and processing results; the two rollers are respectively defined as roller one and roller two, where roller one is set to cut the coal seam close to the top plate, and roller two is set to cut the coal seam close to the bottom plate;

[0032] Step 2: Establish an observation system: Establish an observation coordinate system based on the mining face, define the direction along the roadway as the X direction of the three-component sensor, the direction along the cut as the Y direction of the three-component sensor, and the direction perpendicular to the roof and floor as the Z direction of the three-component sensor; the Y and Z directions are the cutting directions of the drum;

[0033] Step 3: Establish judgment criteria: Before the shearer performs automatic drum adjustment, the shearer drum is controlled to cut the coal seam, roof rock layer, and floor rock layer respectively, and the cutting time of each part is the same. The three-component vibration signals of the three parts in the cutting time period are collected by two three-component vibration sensors respectively, and the vibration signal in the Y direction of each three-component vibration sensor is obtained. Then, the vibration signal in the Y direction when cutting the three parts is converted into time-frequency domain, as shown in FIG. Figure 3As shown, the frequency domain energy distribution of the signal within the cutting time period of each part is obtained; finally, according to the proportion of high-frequency and medium-frequency energy of each coal seam, roof rock layer and bottom rock layer when cutting, the threshold value for judging the roof rock layer and the threshold value for judging the bottom rock layer are established respectively. Since roller one cuts the coal seam close to the roof and roller two cuts the coal seam close to the bottom, during the coal mining process, the vibration signal collected by roller one only needs to be compared with the threshold value of its roof rock layer, and the height of roller one is adjusted according to the comparison result; the vibration signal collected by roller two only needs to be compared with the threshold value of its bottom rock layer, and the height of roller two is adjusted according to the comparison result. This setting can further reduce the comparison process, and each roller only needs to be compared with one threshold, making the real-time performance of roller adjustment better;

[0034] The specific process is:

[0035] A. Conduct training on cutting coal and rock on the working face. Control the shearer drum to cut the coal seam and roof rock layer respectively. The cutting time of each part is 1 minute. The Y-direction vibration signal of the drum cutting the coal seam and roof rock layer for 1 minute is collected through the three-component vibration sensor corresponding to the drum, and recorded as s c and s r ;

[0036] B. Perform time-frequency transformation on the Y-direction vibration signal obtained in step A, and obtain the high-frequency band, medium-frequency band and low-frequency band of the cutting coal seam and the cutting roof rock layer within a 1-minute time period, which are s ch 、s cm 、s cl 、s rh 、s rm 、s rl The time-frequency domain conversion is specifically performed as follows: the vibration signals of the 1-minute coal seam and the 1-minute roof rock layer are cut and the time-frequency conversion is performed. The specific formula is as follows:

[0037]

[0038] Where f(t) is s c and s r , the frequency domain distribution of the cut coal seam and the cut roof rock layer and their energy distribution in different frequency bands are obtained respectively;

[0039] C. Based on the results obtained in step B, calculate the energy sum of the high-frequency, medium-frequency, and low-frequency signals of the cut coal seam and the cut roof rock layer within a 1-minute time period. Specifically, define the vibration signal frequency of the shearer drum below 300 Hz as the low-frequency band, 300-1500 Hz as the medium-frequency band, and above 1500 Hz as the high-frequency band. The energy sum of the low, medium, and high-frequency bands of the cut coal seam and the cut roof rock layer within a 1-minute cutting time period is calculated. The specific formula is as follows:

[0040]

[0041] In the formula, low frequency band: m=1, n=300; medium frequency band: m=301, n=1500; high frequency band: m=1501, n=5000.

[0042] After calculation, the energy sums are obtained and expressed as Es ch 、Es cm 、Es cl 、Es rh 、Es rm 、Es rl ;

[0043] D. Based on the results calculated in step C, calculate the proportion of high-frequency energy and medium-frequency energy in the cut coal seam and the cut roof rock layer in the 1-minute time period, respectively, and express them as: n ch 、n cm 、n rh 、n rm ; For example, the high-frequency energy ratio of cutting the roof rock layer is n rh =Es rh / (Es rh +Es rm +Es rl ),like Figure 4 As shown, n rh =0.4, and the other energy proportions are calculated in sequence according to the formula. rh and n rm Together they serve as the threshold for the roller to cut the roof rock layer;

[0044] E. Repeat steps A to D for the second drum. The only difference is that it cuts the coal seam and the bottom rock layer for 1 minute respectively. Finally, the proportion of high-frequency energy in the bottom rock layer cut within 1 minute is obtained. fh and the proportion of intermediate frequency energy n fm , and finally n fh and n fm Together they serve as the threshold for the second roller cutting bottom rock layer;

[0045] Step 4: Coal rock identification and drum height adjustment of the coal mining machine: During the coal mining process of the coal mining machine, the two three-component vibration sensors feed back the vibration signals of the two drums collected to the signal processing base station in real time, such as Figure 3 As shown, the signal processing base station converts the vibration signal in the Y direction of the collected signal into the time-frequency domain at set intervals to obtain the signal frequency domain energy distribution within the current set time period, and then obtains the high-frequency and medium-frequency energy proportions within the current time period. The three-component vibration sensors corresponding to roller one and roller two are compared with the corresponding roof rock layer threshold and bottom rock layer threshold in step three respectively. If the high-frequency and medium-frequency energy proportions of the two three-component vibration sensors do not exceed their respective corresponding roof rock layer thresholds or bottom rock layer thresholds, it means that both rollers are in the coal seam cutting state at this time; if the high-frequency and medium-frequency energy proportions of any three-component vibration sensor exceed the corresponding roof rock layer threshold or bottom rock layer threshold (the standard for exceeding the threshold: taking roller one exceeding the roof rock layer threshold as an example, that is, the currently obtained high-frequency energy proportion exceeds n rh value, and the current intermediate frequency energy ratio exceeds n rm value, at this time, it is judged that the roller one corresponding to the three-component vibration sensor is in the state of cutting the top rock layer, and the judgment process of roller two cutting the bottom rock layer is similar to this), then it means that the roller corresponding to the three-component vibration sensor is in the state of cutting the rock layer. At this time, the signal processing base station lowers or raises the height of the roller through the coal mining machine body control system, so that it is in the state of cutting the coal seam.

[0046] As an improvement of the present invention, Figure 2 As shown, in step 1, each three-component vibration sensor is provided with a protective housing, and the data line between the three-component vibration sensor and the signal processing base station is provided with a protective device, which is a protective cover. This prevents coal lumps and other debris from damaging the three-component vibration sensor or the data line during the coal mining process, thereby affecting coal mining efficiency.

[0047] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for automatically adjusting the drum of a coal mining machine based on the cutting vibration signal, characterized in that: The specific steps are: Step 1: Lay out the acquisition device and data processing device: The acquisition device is two three-component vibration sensors, which are respectively arranged behind the bearings of the two rollers of the coal mining machine. Each three-component sensor is coupled with the corresponding coal mining machine roller through a bolt connection to ensure the stability of vibration data acquisition, and the three component directions of each three-component vibration sensor are along the direction of the roadway, along the direction of the cutting eye, and vertical to the top and bottom plates; the data processing device is a signal processing base station, which is placed inside the coal mining machine body. The two three-component vibration sensors are connected to the signal processing base station through a data line, which is used to feed back the real-time vibration signals collected by each to the signal processing base station for analysis and processing. The signal processing base station is connected to the coal mining machine body control system to adjust the height of the coal mining machine roller according to the analysis and processing results; Step 2: Establish an observation system: Establish an observation coordinate system based on the mining face, define the direction along the roadway as the X direction of the three-component sensor, the direction along the cut as the Y direction of the three-component sensor, and the direction perpendicular to the roof and floor as the Z direction of the three-component sensor; the Y and Z directions are the cutting directions of the drum; Step 3: Establish judgment criteria: Before the shearer performs automatic drum adjustment, the shearer drum is first controlled to cut the coal seam, roof rock layer, and floor rock layer separately, and the cutting time of each part is the same. The three-component vibration signals of the above three parts in the cutting time period are respectively collected through two three-component vibration sensors, and the vibration signal in the Y direction of each three-component vibration sensor is obtained. Then, the vibration signal in the Y direction when cutting the above three parts is converted into time-frequency domain to obtain the signal frequency domain energy distribution in the cutting time period of each part; finally, according to the high-frequency and medium-frequency energy proportions of each coal seam, roof rock layer, and floor rock layer when cutting, the threshold value for judging the roof rock layer and the threshold value for judging the floor rock layer are respectively established; Step 4. Coal rock identification and drum height adjustment of the coal mining machine: During the coal mining process of the coal mining machine, the two three-component vibration sensors feed back the collected vibration signals of the two drums to the signal processing base station in real time. The signal processing base station converts the vibration signal in the Y direction of the collected signal into the time-frequency domain at set intervals to obtain the signal frequency domain energy distribution within the current set time period, and then obtains the high-frequency and medium-frequency energy proportions within the current time period, and compares them with the thresholds of the roof rock layer and the bottom rock layer in step 3. If the high-frequency and medium-frequency energy proportions of the two three-component vibration sensors do not exceed the respective thresholds of the roof rock layer and the bottom rock layer, it means that both drums are in the coal seam cutting state at this time; if the high-frequency and medium-frequency energy proportions of any three-component vibration sensor exceed the respective thresholds of the roof rock layer or the bottom rock layer, it means that the drum corresponding to the three-component vibration sensor is in the rock layer cutting state. At this time, the signal processing base station lowers or raises the height of the drum through the coal mining machine body control system to put it in the coal seam cutting state.

2. The method for automatically adjusting the drum based on the shearer cutting vibration signal according to claim 1, characterized in that: In the step 1, each three-component vibration sensor is provided with a protective shell on the outside, and the data line between the three-component vibration sensor and the signal processing base station is provided with a protective device on the outside, and the protective device is a protective cover.

3. The method for automatically adjusting the drum based on the shearer cutting vibration signal according to claim 1, characterized in that: The specific process of establishing the judgment criteria in step 3 is as follows: A. Conduct training on cutting coal and rock on the working face. Control one of the drums of the coal mining machine to cut the coal seam, roof rock layer, and floor rock layer respectively. The cutting time of each part is 1 minute. The three-component vibration sensor corresponding to the drum collects the Y-direction vibration signals of the drum cutting the coal seam for 1 minute, the roof rock layer for 1 minute, and the floor rock layer for 1 minute, which are recorded as s respectively. c 、s r 、s f ; B. Perform time-frequency transformation on the Y-direction vibration signal obtained in step A, and obtain the high-frequency band, medium-frequency band and low-frequency band of the cutting coal seam, cutting roof rock layer and cutting floor rock layer in the 1 minute time period, which are s ch 、s cm 、s cl 、s rh 、s rm 、s rl 、s fh 、s fm 、s fl ; C. Based on the results obtained in step B, calculate the energy sum of the high-frequency, medium-frequency and low-frequency signals of the cutting coal seam, cutting roof rock layer and cutting floor rock layer within a 1-minute time period, which are expressed as Es respectively. ch 、Es cm 、Es cl 、Es rh 、Es rm 、Es rl 、Es fh 、Es fm 、Es fl ; D. Based on the results calculated in step C, calculate the proportion of high-frequency energy and medium-frequency energy in the cut coal seam, cut roof rock layer, and cut floor rock layer within a 1-minute time period, respectively, and express them as: n ch 、n cm 、n rh 、n rm 、n fh 、n fm ; n rh and n rm Together as the threshold of the roof rock layer; n fh and n fm together as the threshold of the basement rock layer; E. Repeat steps A to D for another drum to obtain the threshold values of the top rock layer and the bottom rock layer of the other drum.

4. The method for automatically adjusting the drum based on the cutting vibration signal of the coal mining machine according to claim 3, characterized in that: In step 3, a time-frequency domain conversion is performed to obtain the frequency domain energy distribution of the signal within each cut time period. Specifically, the vibration signals of the 1-minute coal seam, 1-minute roof rock layer, and 1-minute floor rock layer are cut and the time-frequency conversion is performed. The specific formula is as follows: ； in s respectively c 、s r 、s f The frequency domain distribution of the cut coal seam, cut roof rock layer and cut floor rock layer and their energy distribution in different frequency bands are obtained respectively. The vibration signal frequency of the shearer drum below 300 Hz is defined as the low frequency band, 300-1500 Hz is defined as the medium frequency band, and above 1500 Hz is defined as the high frequency band. The energy sum of the low, medium and high frequency bands of the cut coal seam, cut roof rock layer and cut floor rock layer within the 1 minute cutting time period is calculated respectively. The specific formula is as follows: ； In the formula, low frequency band: m=1, n=300; medium frequency band: m=301, n=1500; high frequency band: m=1501, n=half of the sampling frequency of the acquisition device.

5. The method for automatically adjusting the drum based on the shearer cutting vibration signal according to claim 1, characterized in that: The two rollers are defined as roller one and roller two, respectively, where roller one is set to cut the coal seam close to the roof, and roller two is set to cut the coal seam close to the bottom plate. During the coal mining process, the vibration signal collected by roller one only needs to be compared with the threshold of its roof rock layer, and the height of roller one is adjusted according to the comparison result; the vibration signal collected by roller two only needs to be compared with the threshold of its bottom rock layer, and the height of roller two is adjusted according to the comparison result.

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