A method for dynamic evaluation of drum cutting performance degradation

Abstract

The application provides a drum cutting performance degradation dynamic evaluation method, which obtains a real coal rock cutting resistance benchmark value through a diamond pick equipped with an embedded strain gauge; an ideal cutting load characteristic database under different working conditions is simulated and constructed in combination with drum structure parameters and motion parameters; cutting motor current and machine body vibration signals are synchronously collected to calculate actual cutting load characteristic quantities; actual characteristic quantities are compared with corresponding working condition parameters of the ideal database, a deviation rate is calculated, and three-level dynamic evaluation of health, early warning and shutdown is realized according to a preset grading standard. Dynamic quantitative evaluation and early warning of the drum cutting performance degradation state are realized, and the continuity and equipment reliability of thin coal seam mining are effectively guaranteed.

Description

Technical Field

[0001] This invention relates to the field of intelligent monitoring technology for coal mining equipment, and in particular to a method for dynamic evaluation of the performance degradation of drum cutting. Background Technology

[0002] The coal mining machine is the core equipment in a fully mechanized mining face, and its operational reliability directly determines the production efficiency and safety of the coal mine. As the executing component of the coal mining machine that directly crushes coal and rock, the cutting performance of the cutting drum directly affects the overall production capacity and energy consumption level of the machine. Under complex geological conditions such as thin coal seams, the drum cutting teeth are subjected to severe loads of high impact and strong wear. The wear rate of the cutting teeth is rapid, and the cutting load characteristics change significantly as the condition of the cutting teeth deteriorates. If this is not identified and warned in time, it can easily lead to major failures such as reduced cutting capacity, transmission system overload, or even damage to the drum structure. Therefore, dynamic evaluation and deterioration warning of the cutting performance of the coal mining machine drum are of vital importance for ensuring the continuity of thin coal seam mining and improving the intelligence level of coal mining equipment.

[0003] However, existing monitoring and evaluation technologies for the performance of coal mining machine drum cutting still have the following shortcomings: First, the cutting load perception benchmark is lacking. The drum cutting load is the most direct physical quantity reflecting the properties of coal and rock and the cutting conditions, but it is difficult to directly measure the force on the cutting teeth in actual engineering. Existing technologies mostly use indirect methods, such as inferring the cutting load from signals like motor current and machine vibration. However, due to the complexity of sensor installation locations and signal transmission paths, the calculated results have significant errors compared to the actual force on the cutting teeth. More importantly, as the cutting teeth wear continuously during mining, their geometry changes, causing the cutting load under the same conditions to shift. This renders load inversion methods based on fixed mapping relationships ineffective, making it impossible to establish an accurate benchmark for the actual coal and rock cutting impedance. Second, ideal cutting characteristics lack standardized basis. The drum cutting process is a typical nonlinear, time-varying, and high-impact process, and its load characteristics dynamically change with working parameters such as coal and rock hardness, traction speed, and cutting depth. Existing studies mostly rely on offline simulations or empirical formulas to estimate cutting loads, but these methods are limited by computational efficiency and model accuracy, making it difficult to cover the actual needs of rapidly changing working conditions during thin coal seam mining. The lack of systematic research and standardized characteristic databases for ideal cutting performance under different working conditions makes it impossible to provide a quantifiable reference benchmark for judging the quality of actual cutting conditions. Third, performance degradation assessment lacks a dynamic comparison mechanism. Current coal mining machine condition monitoring systems mostly adopt fixed threshold alarm strategies, i.e., setting alarm limits for single signals such as current and vibration, triggering an alarm when the monitored value exceeds the limit. This type of method fails to consider the significant impact of changes in working conditions on signal characteristics; under different coal and rock hardness or cutting parameters, the same alarm threshold may generate a large number of false alarms or missed alarms. Furthermore, existing methods lack refined grading of the degree of cutting performance degradation, making it difficult to achieve a progressive assessment from healthy to early warning to shutdown, and failing to provide a scientific basis for equipment maintenance decisions. Summary of the Invention

[0004] This invention provides a dynamic evaluation method for the performance degradation of drum cutting, which solves the problems in the prior art of making it difficult to quantitatively evaluate the degree of performance degradation of drum cutting in real time and the inability to effectively warn of cutting abnormalities caused by wear of cutting teeth.

[0005] To achieve the above-mentioned objectives, the present invention adopts the following technical solution:

[0006] A method for dynamically evaluating the performance degradation of drum cutting includes the following steps:

[0007] Step S1, benchmark calibration: Multiple diamond cutting teeth with embedded strain gauges are evenly installed on each spiral blade of the coal mining machine drum. The real coal and rock cutting impedance benchmark value is obtained through signal calibration, temperature drift compensation and error correction.

[0008] Step S2, Database Construction: Combining the structural parameters and motion parameters of the coal mining machine drum with the real coal and rock cutting impedance benchmark value obtained in step S1, establish a drum cutting load mechanical model, simulate the drum cutting process under different working conditions, construct an ideal cutting load characteristic database, and clarify the characteristic threshold of ideal cutting performance under different working conditions.

[0009] Step S3, Actual Load Inversion: Synchronously acquire the current signal of the cutting motor, and calculate the characteristic quantities of the actual cutting load of the drum through time domain analysis and frequency domain analysis;

[0010] Step S4: Calculate the load deviation: Compare the actual cutting load characteristic quantity in step S3 with the characteristic parameters of the corresponding working condition in the ideal cutting load characteristic database in step S2, and calculate the comprehensive load characteristic deviation rate.

[0011] Step S5, Deterioration Grading Assessment: Based on the comprehensive deviation rate obtained in S4, divide the threshold ranges of the three evaluation levels of health, early warning, and shutdown, and formulate corresponding response strategies.

[0012] In some embodiments, step S1, calibrating the reference value of actual coal and rock cutting impedance includes the following steps:

[0013] Step S11: Embed a high-precision impact-resistant strain gauge inside the diamond cutting tooth holder, construct a conversion circuit using a Wheatstone circuit full-bridge differential connection, and use the characteristic of mutual cancellation of temperature drift between adjacent bridge arms to achieve hardware-level temperature drift compensation, converting the mechanical strain signal collected by the strain gauge into an electrical signal that can be wirelessly transmitted.

[0014] Step S12: Through signal calibration and error correction, the wirelessly transmitted electrical signal is equivalently converted into the actual cutting load borne by the cutting teeth, ensuring that the cutting teeth always remain sharp and avoiding distortion of the cutting load due to wear of the cutting teeth.

[0015] Step S13: Calculate the cutting impedance of the coal and rock, and use the obtained cutting impedance as the reference value of the actual coal and rock cutting impedance. The formula for calculating the cutting impedance is as follows:

[0016]

[0017] in, For coal and rock cutting resistance; The average cutting load; For the cutting thickness.

[0018] In some embodiments, in step S2, constructing the ideal truncated load feature database includes the following steps:

[0019] Step S21: Obtain the structural and kinematic parameters of the coal mining machine drum. The structural parameters include drum diameter, number of cutting teeth, cut pitch, helix angle, circumferential position angle of cutting teeth, and axial lever arm. The kinematic parameters include drum rotation speed, traction speed, instantaneous cutting thickness, cutting width of cutting teeth, and friction coefficient. Combine the actual coal and rock cutting resistance benchmark value to establish a drum cutting load mechanical model.

[0020] Step S22: Set up various working conditions in the simulated thin coal seam mining process, including different coal and rock hardness grades, different cutting speeds, different traction speeds and different roof and floor undulations, and use the drum cutting load mechanical model to simulate and calculate the drum cutting process under each working condition.

[0021] Step S23: Extract the characteristic parameter set representing the ideal cutting load under each working condition from the simulation calculation results of each working condition, including the load mean, load peak, load fluctuation coefficient and load impact frequency; associate and store different working conditions with the corresponding ideal cutting load characteristic parameter set to build a standardized ideal cutting load characteristic database, and define the characteristic threshold range of the ideal cutting performance for each working condition.

[0022] In some embodiments, establishing the mechanical model of the drum cutting load in step S21 specifically includes the following steps:

[0023] Step S211: Define the coordinate system and basic parameters: Establish a global coordinate system with the geometric center of the drum as the origin, the drum axis as the Z-axis, the horizontal direction perpendicular to the Z-axis as the X-axis, and the vertical direction perpendicular to the XZ plane as the Y-axis. The direction pointing towards the coal face is the positive direction of the Z-axis. Determine the drum diameter D, the total number of cutting teeth N, the cutting tooth pitch t, ​​and the helix angle. , No. The position of each cutting tooth is determined by the circumferential position angle. With axial lever arm Sure;

[0024] Step S212, Calculate the force on a single tooth: When the drum is working, the force on the cutting tooth is mainly divided into feed resistance. Cutting resistance Lateral force The calculation method is as follows:

[0025] Feed resistance: ;in, The coefficient of friction;

[0026] Cutting resistance: ;in, For coal and rock cutting resistance, The thickness is the instantaneous cutting thickness of the cutting teeth. This refers to the cutting width of the cutting teeth. The correction coefficient was obtained through a single-tooth cutting experiment. and in combination with formula Calculated;

[0027] Lateral force: ;in, Depending on the arrangement of the cutting teeth and the helix angle Lateral force coefficients reflecting the variation of the coal and rock brittleness coefficient λ. The value range is 0.1-0.3;

[0028] Step S213: Obtain the dynamic component force of the cutting tooth: based on the circumferential position angle of the cutting tooth. By applying the principles of force composition and decomposition, the feed resistance, cutting resistance, and lateral force are decomposed into directions in the global coordinate system, thereby obtaining the dynamic force components of the cutting tooth. , , The specific formula is as follows:

[0029]

[0030] in, For feed resistance, To cut off resistance, It is a lateral force; The dynamic component of the cutting tooth in the X direction of the global coordinate system is given by... and Shared contribution; The dynamic component of the cutting tooth in the Y direction of the global coordinate system is given by... and Shared contribution; The dynamic component of the cutting tooth in the Z direction of the global coordinate system is equivalent to the lateral force. ;

[0031] Step S214: Based on the coordinate system defined in step S211, the first... The coordinates of each cutting tooth are From step S213, we can know that the first The force vector on each cutting tooth is Then the first The torque generated by the force vector on each cutting tooth about the origin. The total dynamic torque of the drum can be obtained by summing the values ​​of all the cutting teeth on the drum, which is the mechanical model of the drum cutting load, as follows:

[0032]

[0033] in, This represents the total dynamic torque component of the drum around the X-axis; This represents the total dynamic torque component of the drum around the Y-axis; The total dynamic torque component of the drum around the Z-axis; This refers to the diameter of the roller.

[0034] In some embodiments, step S3, calculating the actual cutting load characteristic quantity, includes the following steps:

[0035] Step S31. Synchronous signal acquisition: Install current sensors and voltage sensors at the output end of the coal mining machine drum cutting motor to acquire the three-phase current and three-phase voltage of the motor in real time. At the same time, install photoelectric encoders at the non-load end shaft extension of the motor to obtain the rotor position angle in real time.

[0036] Step S32: After transforming the collected three-phase current and three-phase voltage using coordinate transformation, the back electromotive force is integrated using the voltage model method to obtain the stator flux linkage component. The real-time electromagnetic torque of the motor is then calculated based on the electromagnetic torque formula. The formula is as follows:

[0037]

[0038] in, This represents the number of pole pairs of the motor. , For stator flux linkage components, , It is the current component;

[0039] Step S33: Based on the transmission ratio and transmission efficiency between the motor output torque and the drum cutting load, convert the motor electromagnetic torque calculated in step S32 into the drum cutting torque; perform time-domain statistical analysis on the converted drum cutting torque, and extract the mean torque, peak torque, and torque fluctuation coefficient as cutting load characteristic parameters; perform frequency-domain analysis on the converted drum cutting torque, extract the spectral amplitude at the cutting tooth passing frequency and its harmonics, and determine the main impact frequency as the impact characteristic parameter based on the spectral amplitude; combine the extracted load characteristic parameters and impact characteristic parameters into a four-dimensional feature vector, which serves as the actual cutting load characteristic quantity of the drum, and the feature dimensions of the actual characteristic quantity correspond one-to-one with the feature dimensions in the ideal cutting load characteristic database.

[0040] In some embodiments, calculating the load deviation in step S4 includes the following steps:

[0041] Step S41: Determine the current working conditions based on the actual operating parameters of the coal mining machine, extract the set of ideal cutting load characteristic parameters corresponding to the current working conditions from the ideal cutting load characteristic database, and obtain the actual cutting load characteristic quantity calculated in step S3.

[0042] Step S42: Compare the actual cutting load characteristic quantity with the corresponding characteristic parameter in the ideal cutting load characteristic parameter set item by item, and calculate the single deviation rate of each characteristic parameter. :

[0043]

[0044] in, These are the actual cut-off load characteristic parameters. To determine the ideal truncated load characteristic parameters, take all individual deviation rates. The maximum value in the range is used as the overall deviation rate. ;

[0045] In some embodiments, step S5, the degradation criterion division includes the following steps:

[0046] Step S51: Set the degradation level. Based on the magnitude of the overall deviation rate, set the threshold ranges for the three evaluation levels: health, warning, and shutdown, as follows:

[0047] ≤20% is considered a healthy state, and the equipment is operating normally; The system is deemed to be in a warning state, and a minor warning signal is issued to remind staff to strengthen patrols. If the system reaches >40%, an immediate shutdown warning will be issued to prevent equipment damage.

[0048] Step S52: While calculating the overall deviation rate, monitor whether the actual cutting load characteristics show any preset abnormal operating conditions. Abnormal operating conditions include one or more of the following: load peak exceeding the preset safety threshold, abnormal spectral peaks in vibration frequency components, and instantaneous surge in impact energy. When any abnormal operating condition is detected, the machine is directly determined to be in a shutdown state, regardless of the overall deviation rate determination result.

[0049] Compared with existing technologies, the beneficial effects of this invention are as follows: This invention effectively solves the problem of the lack of a cutting load sensing benchmark in existing technologies. By embedding strain gauges in the cutting teeth and combining temperature drift compensation and error correction, a precise and true benchmark value of coal and rock cutting impedance is obtained, avoiding load back-calculation failure caused by cutting tooth wear. A database of ideal cutting load characteristics under multiple working conditions is constructed, and a mechanical model is established in conjunction with drum parameters to cover complex working conditions in thin coal seams, providing a quantifiable ideal reference benchmark and addressing the shortcomings of existing methods in adapting to rapidly changing working conditions. A dynamic comparison and evaluation mechanism is established to compare actual and ideal load characteristics, classify three levels of thresholds—health, early warning, and shutdown—and, combined with abnormal working condition monitoring, reduce false alarms and missed alarms, achieve refined grading of performance degradation, provide a scientific basis for maintenance decisions, ensure the continuity of thin coal seam mining, and improve the intelligence level of coal mining equipment. Attached Figure Description

[0050] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used together with the embodiments of the invention to explain the invention and do not constitute a limitation thereof.

[0051] Figure 1 A flowchart of a dynamic evaluation method for the degradation of drum cutting performance provided in an embodiment of this application;

[0052] Figure 2 Flowchart for establishing the mechanical model of the drum cutting load provided for embodiments of this application

[0053] Figure 3 A schematic diagram illustrating the construction of an ideal truncated load feature database for embodiments of this application;

[0054] Figure 4 A flowchart illustrating the actual load estimation and comparative evaluation provided for embodiments of this application. Detailed Implementation

[0055] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. Of course, the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0056] Please see Figure 1 , Figure 2 , Figure 3 as well as Figure 4 , Figure 1 A flowchart of a dynamic evaluation method for the degradation of drum cutting performance provided in an embodiment of this application; Figure 2 A flowchart illustrating the establishment of the mechanical model for the drum cutting load provided in the embodiments of this application. Figure 3 The intent of constructing an ideal truncated load feature database for embodiments of this application is illustrated. Figure 4 A flowchart illustrating the actual load estimation and comparative evaluation provided for embodiments of this application. The method includes the following steps:

[0057] Step S1, benchmark calibration: Multiple diamond cutting teeth with embedded strain gauges are evenly installed on each spiral blade of the coal mining machine drum. Through signal calibration, temperature drift compensation and error correction, the true coal and rock cutting impedance benchmark value is obtained.

[0058] The calibration of the actual coal and rock cutting resistance benchmark value includes the following steps:

[0059] Step S11: Embed a high-precision impact-resistant strain gauge inside the diamond cutting tooth holder, construct a conversion circuit using a Wheatstone circuit full-bridge differential connection, and use the characteristic of mutual cancellation of temperature drift between adjacent bridge arms to achieve hardware-level temperature drift compensation, converting the mechanical strain signal collected by the strain gauge into an electrical signal that can be wirelessly transmitted.

[0060] Step S12: Through signal calibration and error correction, the wirelessly transmitted electrical signal is equivalently converted into the actual cutting load borne by the cutting teeth, ensuring that the cutting teeth always remain sharp and avoiding distortion of the cutting load due to wear of the cutting teeth.

[0061] Step S13: Calculate the cutting impedance of the coal and rock, and use the obtained cutting impedance as the reference value of the actual coal and rock cutting impedance. The formula for calculating the cutting impedance is as follows:

[0062]

[0063] in, Coal and rock cutting resistance; The average cutting load; For the cutting thickness.

[0064] In this way, hardware-level temperature drift compensation is achieved by embedding strain gauges in the cutting teeth and using a full-bridge differential connection of the Wheatstone circuit. Combined with signal calibration and error correction, the true reference value of coal and rock cutting impedance is accurately obtained, effectively avoiding cutting load distortion caused by cutting tooth wear, solving the problem of load back calculation failure in existing technologies, and providing a reliable data foundation for subsequent evaluation.

[0065] Step S2, Database Construction: Combining the structural parameters and motion parameters of the coal mining machine drum with the real coal and rock cutting impedance benchmark value obtained in step S1, establish a drum cutting load mechanical model, simulate the drum cutting process under different working conditions, construct an ideal cutting load characteristic database, and clarify the characteristic threshold of ideal cutting performance under different working conditions.

[0066] Constructing an ideal truncated load feature database involves the following steps:

[0067] Step S21: Obtain the structural and kinematic parameters of the coal mining machine drum. The structural parameters include drum diameter, number of cutting teeth, cutting pitch, helix angle, circumferential position angle of cutting teeth, and axial lever arm. The kinematic parameters include drum speed, traction speed, instantaneous cutting thickness, cutting width of cutting teeth, and friction coefficient. Combine the actual coal and rock cutting resistance benchmark value to establish a drum cutting load mechanical model.

[0068] Establishing a mechanical model for the load of drum cutting includes the following steps:

[0069] Step S211: Define the coordinate system and basic parameters: Establish a global coordinate system with the geometric center of the drum as the origin, the drum axis as the Z-axis, the horizontal direction perpendicular to the Z-axis as the X-axis, and the vertical direction perpendicular to the XZ plane as the Y-axis. The direction pointing towards the coal face is the positive direction of the Z-axis. Determine the drum diameter D, the total number of cutting teeth N, the cutting tooth pitch t, ​​and the helix angle. , No. The position of each cutting tooth is determined by the circumferential position angle. With axial lever arm Sure;

[0070] Step S212, Calculate the force on a single tooth: When the drum is working, the force on the cutting tooth is mainly divided into feed resistance. Cutting resistance Lateral force The calculation method is as follows:

[0071] Feed resistance: ,in, The coefficient of friction;

[0072] Cutting resistance: ,in The thickness is the instantaneous cutting thickness of the cutting teeth. This refers to the cutting width of the cutting teeth. The correction coefficient was obtained through a single-tooth cutting experiment. and in combination with formula Calculated;

[0073] Lateral force: , The lateral force coefficient varies with the arrangement of the cutting teeth, the helix angle α, and the coal-rock brittleness coefficient λ. The value range is generally 0.1-0.3;

[0074] Step S213: Obtain the dynamic component force of the cutting tooth: based on the circumferential position angle of the cutting tooth. By applying the principles of force composition and decomposition, the feed resistance, cutting resistance, and lateral force are decomposed into directions in the global coordinate system, thereby obtaining the dynamic force components of the cutting tooth. , , The specific formula is as follows:

[0075]

[0076] in, For feed resistance, To cut off resistance, It is a lateral force; The dynamic component of the cutting tooth in the X direction of the global coordinate system is given by... and Shared contribution; The dynamic component of the cutting tooth in the Y direction of the global coordinate system is given by... and Shared contribution; The dynamic component of the cutting tooth in the Z direction of the global coordinate system is equivalent to the lateral force. .

[0077] Step S214: Based on the coordinate system defined in step S211, the first... The coordinates of each cutting tooth are From step S213, we can know that the first The force vector on each cutting tooth is Then the first The torque generated by the force vector on each cutting tooth about the origin. (in, The total dynamic torque of the drum can be obtained by summing the values ​​of all the cutting teeth on the drum (using cross product), which is the mechanical model of the drum cutting load, as follows:

[0078]

[0079] in, This represents the total dynamic torque component of the drum around the X-axis; This represents the total dynamic torque component of the roller around the Y-axis; The total dynamic torque component of the roller around the Z-axis; This refers to the diameter of the roller.

[0080] In this way, by accurately defining the coordinate system, calculating the force and dynamic component of a single tooth, and summing the total dynamic torque, the accuracy of the mechanical model is improved, ensuring the accuracy of the cutting process simulation under multiple working conditions, providing reliable support for the construction of an ideal cutting load characteristic database, and further improving the accuracy of the evaluation.

[0081] Step S22: Set up various working conditions in the simulated thin coal seam mining process, including different coal and rock hardness grades, different cutting speeds, different traction speeds and different roof and floor undulations, and use the drum cutting load mechanical model to simulate and calculate the drum cutting process under each working condition.

[0082] Step S23: Extract the characteristic parameter set representing the ideal cutting load under each working condition from the simulation calculation results of each working condition, including the load mean, load peak, load fluctuation coefficient and load impact frequency; associate and store different working conditions with the corresponding ideal cutting load characteristic parameter set to construct a standardized ideal cutting load characteristic database, and define the characteristic threshold range of the ideal cutting performance for each working condition.

[0083] In this way, by constructing an ideal cutting load characteristic database, and combining the drum structure and motion parameters to establish a mechanical model, the cutting process under multiple working conditions is simulated and characteristic parameters are extracted. This solves the shortcomings of existing technologies that cannot cover complex working conditions in thin coal seams and lack quantifiable ideal reference benchmarks, and provides a standardized basis for determining the actual cutting state.

[0084] Step S3, Actual Load Inversion: Synchronously acquire the current signal of the cutting motor, and calculate the characteristic quantities of the actual cutting load of the drum through time domain analysis and frequency domain analysis.

[0085] The calculation of the actual cutting load characteristics includes the following steps:

[0086] Step S31. Synchronous signal acquisition: Install current sensors and voltage sensors at the output end of the coal mining machine drum cutting motor to acquire the three-phase current and three-phase voltage of the motor in real time. At the same time, install photoelectric encoders at the non-load end shaft extension of the motor to obtain the rotor position angle in real time.

[0087] Step S32: After transforming the collected three-phase current and three-phase voltage using coordinate transformation, the back electromotive force is integrated using the voltage model method to obtain the stator flux linkage component. The real-time electromagnetic torque of the motor is then calculated based on the electromagnetic torque formula, as follows:

[0088]

[0089] in, This represents the number of pole pairs of the motor. , For stator flux linkage components, , It is the current component;

[0090] Step S33: Based on the transmission ratio and transmission efficiency between the motor output torque and the drum cutting load, convert the motor electromagnetic torque calculated in step S32 into the drum cutting torque; perform time-domain statistical analysis on the converted drum cutting torque, and extract the mean torque, peak torque, and torque fluctuation coefficient as cutting load characteristic parameters; perform frequency-domain analysis on the converted drum cutting torque, extract the spectral amplitude at the cutting tooth passing frequency and its harmonics, and determine the main impact frequency as the impact characteristic parameter based on the spectral amplitude; combine the extracted load characteristic parameters and impact characteristic parameters into a four-dimensional feature vector, which serves as the actual cutting load characteristic quantity of the drum, and the feature dimensions of the actual characteristic quantity correspond one-to-one with the feature dimensions in the ideal cutting load characteristic database.

[0091] This approach optimizes the actual load inversion process by simultaneously acquiring multiple types of signals, converting electromagnetic torque, and extracting multi-dimensional features through time-domain and frequency-domain analysis. This addresses the issue of large errors in indirectly inferring cutting loads using existing technologies, ensuring that the actual cutting load features correspond to the ideal feature parameters and providing accurate data for subsequent degradation grading assessments.

[0092] Step S4: Calculate the load deviation: Compare the actual cutting load characteristic quantity in step S3 with the characteristic parameters of the corresponding working condition in the ideal cutting load characteristic database in step S2, and calculate the comprehensive load characteristic deviation rate.

[0093] Calculating load deviations involves the following steps:

[0094] Step S41: Determine the current working conditions based on the actual operating parameters of the coal mining machine, extract the set of ideal cutting load characteristic parameters corresponding to the current working conditions from the ideal cutting load characteristic database, and obtain the actual cutting load characteristic quantity calculated in step S3.

[0095] Step S42: Compare the actual cutting load characteristic quantity with the corresponding characteristic parameter in the ideal cutting load characteristic parameter set item by item, and calculate the single deviation rate of each characteristic parameter:

[0096]

[0097] in, These are the actual cut-off load characteristic parameters. To determine the ideal cut-off load characteristic parameters, the maximum value among all individual deviation rates is taken as the comprehensive deviation rate. ;

[0098] Step S5, Degradation Standard Classification: Based on the comprehensive deviation rate obtained in S4, classify the threshold ranges for three evaluation levels: health, early warning, and shutdown, and formulate corresponding response strategies.

[0099] The degradation criteria classification includes the following steps:

[0100] Step S51: Set the degradation level. Based on the magnitude of the overall deviation rate, set the threshold ranges for the three evaluation levels: health, warning, and shutdown, as follows:

[0101] ≤20% is considered a healthy state, and the equipment is operating normally; The system is deemed to be in a warning state, and a minor warning signal is issued to remind staff to strengthen patrols. If the system reaches >40%, an immediate shutdown warning will be issued to prevent equipment damage.

[0102] Step S52: While calculating the overall deviation rate, monitor whether the actual cutting load characteristics show any preset abnormal operating conditions. Abnormal operating conditions include one or more of the following: load peak exceeding the preset safety threshold, abnormal spectral peaks in vibration frequency components, and instantaneous surge in impact energy. When any abnormal operating condition is detected, the machine is directly determined to be in a shutdown state, regardless of the overall deviation rate determination result.

[0103] In this way, by matching operating conditions and calculating deviation rates to divide the evaluation thresholds into three levels, combined with abnormal operating condition monitoring, the shortcomings of existing technologies, such as fixed thresholds that are prone to false alarms and missed alarms and lack of fine-grained classification, are solved. This enables a progressive assessment of the deterioration of cutting performance, provides a scientific basis for equipment maintenance decisions, and avoids major equipment failures.

[0104] The evaluation method provided in the embodiments of this application constructs a complete dynamic evaluation process for the deterioration of drum cutting performance, which sequentially realizes benchmark calibration, ideal database construction, actual load inversion and graded evaluation. It comprehensively solves the problems of lack of cutting load perception benchmark, lack of standard basis for ideal cutting characteristics, and lack of dynamic comparison mechanism for deterioration evaluation in the existing technology, realizes accurate dynamic monitoring and graded early warning of cutting performance, ensures the continuity of thin coal seam mining, and improves the intelligence level of coal mining equipment.

[0105] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for dynamic evaluation of the deterioration of drum cutting performance, characterized in that, Includes the following steps: Step S1, benchmark calibration: Multiple diamond cutting teeth with embedded strain gauges are evenly installed on each spiral blade of the coal mining machine drum. The real coal and rock cutting impedance benchmark value is obtained through signal calibration, temperature drift compensation and error correction. Step S2, Database Construction: Combining the structural parameters and motion parameters of the coal mining machine drum with the real coal and rock cutting impedance benchmark value obtained in step S1, establish a drum cutting load mechanical model, simulate the drum cutting process under different working conditions, construct an ideal cutting load characteristic database, and clarify the characteristic threshold of ideal cutting performance under different working conditions. Step S3, Actual Load Inversion: Synchronously acquire the current signal of the cutting motor, and calculate the characteristic quantities of the actual cutting load of the drum through time domain analysis and frequency domain analysis; Step S4: Calculate the load deviation: Compare the actual cutting load characteristic quantity in step S3 with the characteristic parameters of the corresponding working condition in the ideal cutting load characteristic database in step S2, and calculate the comprehensive load characteristic deviation rate. Step S5, Deterioration Grading Assessment: Based on the comprehensive deviation rate obtained in Step S4, divide the threshold ranges of the three evaluation levels of health, early warning, and shutdown, and formulate corresponding response strategies.

2. The method for dynamic evaluation of the deterioration of drum cutting performance according to claim 1, characterized in that, In step S1, calibrating the reference value of actual coal and rock cutting impedance includes the following steps: Step S11: Embed a high-precision impact-resistant strain gauge inside the diamond cutting tooth holder, construct a conversion circuit using a Wheatstone circuit full-bridge differential connection, and use the characteristic of mutual cancellation of temperature drift between adjacent bridge arms to achieve hardware-level temperature drift compensation, converting the mechanical strain signal collected by the strain gauge into an electrical signal that can be wirelessly transmitted. Step S12: Through signal calibration and error correction, the wirelessly transmitted electrical signal is equivalently converted into the actual cutting load borne by the cutting teeth, ensuring that the cutting teeth always remain sharp and avoiding distortion of the cutting load due to wear of the cutting teeth. Step S13: Calculate the cutting impedance of the coal and rock, and use the obtained cutting impedance as the reference value of the actual coal and rock cutting impedance. The formula for calculating the cutting impedance is as follows: in, For coal and rock cutting resistance; The average cutting load; For the cutting thickness.

3. The method for dynamic evaluation of the deterioration of drum cutting performance according to claim 1, characterized in that, In step S2, constructing the ideal cut-off load feature database includes the following steps: Step S21: Obtain the structural and kinematic parameters of the coal mining machine drum. The structural parameters include drum diameter, number of cutting teeth, cut pitch, helix angle, circumferential position angle of cutting teeth, and axial lever arm. The kinematic parameters include drum rotation speed, traction speed, instantaneous cutting thickness, cutting width of cutting teeth, and friction coefficient. Combined with the actual coal and rock cutting resistance benchmark value, establish a drum cutting load mechanical model. Step S22: Set up various working conditions in the simulated thin coal seam mining process, including different coal and rock hardness grades, different cutting speeds, different traction speeds and different roof and floor undulations, and use the drum cutting load mechanical model to simulate and calculate the drum cutting process under each working condition. Step S23: Extract the characteristic parameter set representing the ideal cutting load under each working condition from the simulation calculation results of each working condition, including the load mean, load peak, load fluctuation coefficient and load impact frequency; associate and store different working conditions with the corresponding ideal cutting load characteristic parameter set to construct a standardized ideal cutting load characteristic database, and define the characteristic threshold range of the ideal cutting performance for each working condition.

4. The method for dynamic evaluation of the deterioration of drum cutting performance according to claim 3, characterized in that, In step S21, establishing the mechanical model of the drum cutting load specifically includes the following steps: Step S211: Define the coordinate system and basic parameters: Establish a global coordinate system with the geometric center of the drum as the origin, the drum axis as the Z-axis, the horizontal direction perpendicular to the Z-axis as the X-axis, and the vertical direction perpendicular to the XZ plane as the Y-axis. The direction pointing towards the coal face is the positive direction of the Z-axis. Determine the drum diameter D, the total number of cutting teeth N, the cutting tooth pitch t, ​​and the helix angle. , No. The position of each cutting tooth is determined by the circumferential position angle. With axial lever arm Sure; Step S212, Calculate the force on a single tooth: When the drum is working, the force on the cutting tooth is mainly divided into feed resistance. Cutting resistance Lateral force The calculation method is as follows: Feed resistance: ;in, The coefficient of friction; Cutting resistance: ;in, For coal and rock cutting resistance, The thickness is the instantaneous cutting thickness of the cutting teeth. This refers to the cutting width of the cutting teeth. The correction coefficient was obtained through a single-tooth cutting experiment. and in combination with formula Calculated; Lateral force: ;in, Depending on the arrangement of the cutting teeth and the helix angle Lateral force coefficients reflecting the variation of the coal and rock brittleness coefficient λ. The value range is 0.1-0.3; Step S213: Obtain the dynamic component force of the cutting tooth: based on the circumferential position angle of the cutting tooth. By applying the principles of force composition and decomposition, the feed resistance, cutting resistance, and lateral force are decomposed into directions in the global coordinate system, thereby obtaining the dynamic force components of the cutting tooth. , , The specific formula is as follows: in, For feed resistance, To cut off resistance, It is a lateral force; The dynamic component of the cutting tooth in the X direction of the global coordinate system is given by... and Shared contribution; The dynamic component of the cutting tooth in the Y direction of the global coordinate system is given by... and Shared contribution; The dynamic component of the cutting tooth in the Z direction of the global coordinate system is equivalent to the lateral force; Step S214: Based on the coordinate system defined in S211, the first... The coordinates of each cutting tooth are From S213, we can know that the first... The force vector on each cutting tooth is Then the first The torque generated by the force vector on each cutting tooth about the origin. The total dynamic torque of the drum can be obtained by summing the values ​​of all the cutting teeth on the drum, which is the mechanical model of the drum cutting load, as follows: in, This represents the total dynamic torque component of the drum around the X-axis; This represents the total dynamic torque component of the roller around the Y-axis; The total dynamic torque component of the roller around the Z-axis; This refers to the diameter of the roller.

5. The method for dynamic evaluation of the deterioration of drum cutting performance according to claim 1, characterized in that, In step S3, calculating the actual cutting load characteristic includes the following steps: Step S31, Signal Synchronous Acquisition: Install current sensors and voltage sensors at the output end of the coal mining machine drum cutting motor to collect the three-phase current and three-phase voltage of the motor in real time. At the same time, install photoelectric encoders at the non-load end shaft extension of the motor to obtain the rotor position angle in real time. Step S32: After transforming the collected three-phase current and three-phase voltage using coordinate transformation, the back electromotive force is integrated using the voltage model method to obtain the stator flux linkage component. The real-time electromagnetic torque of the motor is then calculated based on the electromagnetic torque formula. The formula is as follows: in, This represents the number of pole pairs of the motor. , For stator flux linkage components, , It is the current component; Step S33: Based on the transmission ratio and transmission efficiency between the motor output torque and the drum cutting load, the motor electromagnetic torque calculated in step S32 is converted into the drum cutting torque; time-domain statistical analysis is performed on the converted drum cutting torque to extract the mean torque, peak torque, and torque fluctuation coefficient as cutting load characteristic parameters; frequency-domain analysis is performed on the converted drum cutting torque to extract the spectral amplitude at the cutting tooth passing frequency and its harmonics, and the main impact frequency is determined as the impact characteristic parameter based on the spectral amplitude; the extracted load characteristic parameters and impact characteristic parameters are combined into a four-dimensional feature vector as the actual drum cutting load characteristic quantity, and the feature dimension of the actual characteristic quantity corresponds one-to-one with the feature dimension in the ideal cutting load characteristic database.

6. The method for dynamic evaluation of the deterioration of drum cutting performance according to claim 1, characterized in that, In step S4, calculating the load deviation includes the following steps: Step S41: Determine the current working conditions based on the actual operating parameters of the coal mining machine, extract the set of ideal cutting load characteristic parameters corresponding to the current working conditions from the ideal cutting load characteristic database, and obtain the actual cutting load characteristic quantity calculated in step S3. Step S42: Compare the actual cutting load characteristic quantity with the corresponding characteristic parameter in the ideal cutting load characteristic parameter set item by item, and calculate the single deviation rate of each characteristic parameter. : in, These are the actual cut-off load characteristic parameters. To determine the ideal truncated load characteristic parameters, take all individual deviation rates. The maximum value in the range is used as the overall deviation rate. .

7. The method for dynamic evaluation of the deterioration of drum cutting performance according to claim 1, characterized in that, In step S5, the degradation criteria classification includes the following steps: Step S51: Set the degradation level. Based on the magnitude of the overall deviation rate, set the threshold ranges for the three evaluation levels: health, warning, and shutdown, as follows: ≤20% is considered a healthy state, and the equipment is operating normally; The system is deemed to be in a warning state, and a minor warning signal is issued to remind staff to strengthen patrols. If the system reaches >40%, an immediate shutdown warning will be issued to prevent equipment damage. Step S52: While calculating the overall deviation rate, monitor whether the actual cutting load characteristics show preset abnormal operating conditions. The abnormal operating conditions include one or more of the following: load peak exceeding a preset safety threshold, abnormal spectral peaks in vibration frequency components, and instantaneous surge in impact energy. When any abnormal operating condition is detected, the machine is directly determined to be in a shutdown state, without being limited by the overall deviation rate determination result.

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