A fault detection method and system based on a transfer tool holder

Abstract

The application provides a kind of based on the fault detection method and system of adapter holder, it is related to mechanical equipment fault diagnosis technical field, method includes: obtaining the displacement signal of adapter holder;According to displacement signal, determine feed rate;According to feed rate, establish cutting force model;Based on cutting force model, establish disturbance model;Establish observer model;According to disturbance model and observer model, determine cutting force error;Based on observer model, determine the wear rate of adapter holder;Combining cutting force error and wear rate carries out fault detection;According to fault detection result, judge whether adapter holder fails;If yes, then using genetic algorithm to carry out parameter adjustment to adapter holder, otherwise, return to reacquire displacement signal.The application improves the efficiency of fault diagnosis, reduces maintenance cost, improves production efficiency.

Description

Technical Field

[0001] This invention relates to the field of mechanical equipment fault diagnosis technology, and in particular to a fault detection method and system based on a tool holder adapter. Background Technology

[0002] The fault detection method based on the adapter tool holder is a technology that monitors the dynamic behavior and state changes of the adapter tool holder to detect and diagnose potential faults or anomalies in a mechanical system in real time. By using sensors installed on the adapter tool holder to monitor its displacement, temperature, vibration and other signals, characteristic data related to the fault can be obtained. By analyzing these sensor data, the fault type and degree of the adapter tool holder can be identified, and timely alarms or preventive maintenance can be performed, thereby improving the stability of the machining process and production efficiency.

[0003] The adapter tool holder plays a crucial role in connecting the cutting tool and the spindle during machining. Its working condition directly affects the machining quality and accuracy. With prolonged use, the adapter tool holder may experience wear, deformation, or other malfunctions. These problems often lead to inaccurate tool positioning, unstable cutting forces, and even equipment damage. Therefore, a method is needed that can capture potential fault information in real time, issue timely warnings, and prevent the fault from worsening, thereby reducing production downtime, lowering maintenance costs, and ensuring high production efficiency and equipment safety.

[0004] However, traditional fault detection techniques typically rely on periodic monitoring or manual inspection, which cannot respond to changes in system status in real time. This may cause downtime or more extensive damage. In the fault detection process, the main reliance is on human experience and manual intervention to determine the occurrence of faults. This is highly subjective and easily influenced by the operator's experience, causing some minor but important fault signs to be missed, resulting in low accuracy and speed of fault detection. Summary of the Invention

[0005] To address the shortcomings of traditional fault detection technologies, which typically rely on periodic monitoring or manual inspection and cannot respond to changes in system status in real time, potentially causing downtime or wider damage, and which depend heavily on human experience and manual intervention to determine fault occurrence during the fault detection process, this invention provides a fault detection method and system based on a tool holder adapter.

[0006] The technical solutions provided by the embodiments of the present invention are as follows:

[0007] First aspect:

[0008] This invention provides a fault detection method based on an adapter tool holder, comprising:

[0009] S1: Obtain the displacement signal of the adapter tool holder;

[0010] S2: Determine the feed rate based on the displacement signal;

[0011] S3: Establish a cutting force model based on the feed rate;

[0012] S4: Based on the cutting force model, establish a disturbance model;

[0013] S5: Establish an observer model;

[0014] S6: Determine the cutting force error based on the disturbance model and the observer model;

[0015] S7: Determine the wear rate of the adapter tool holder based on the observer model;

[0016] S8: Perform fault detection by combining the cutting force error and the wear rate;

[0017] S9: Based on the fault detection results, determine whether the adapter tool holder has malfunctioned; if so, use a genetic algorithm to adjust the parameters of the adapter tool holder; otherwise, return to step S1.

[0018] The second aspect:

[0019] This invention provides a fault detection system based on an adapter tool holder, comprising:

[0020] processor;

[0021] A memory storing computer-readable instructions, which, when executed by the processor, implement the fault detection method based on the adapter tool holder as described in the first aspect.

[0022] Third aspect:

[0023] The present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the fault detection method based on the adapter tool holder as described in the first aspect.

[0024] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following:

[0025] In the embodiments of the invention, by establishing a cutting force model and a disturbance model, the influence of feed rate on cutting force is accurately described, and fluctuations in the actual machining environment are simulated, thereby better capturing subtle changes in the equipment, enhancing the adaptability and reliability of fault detection, and enabling it to cope with changing machining environments. By establishing an observer model to estimate the system state, relevant key parameters can be accurately inferred even without directly measuring certain variables, improving the efficiency of fault diagnosis. Combined with the comprehensive analysis of cutting force error and wear rate, equipment faults can be identified more accurately, enhancing the robustness and accuracy of fault detection, reducing the risk of false alarms and missed alarms. When a fault occurs, the equipment parameters are automatically adjusted through a genetic algorithm, avoiding further damage to the equipment, reducing maintenance costs, and improving production efficiency. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 A flowchart illustrating a fault detection method based on an adapter tool holder provided in an embodiment of the present invention;

[0028] Figure 2 This is a schematic diagram of a fault detection system based on an adapter tool holder provided in an embodiment of the present invention. Detailed Implementation

[0029] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0030] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0031] In the embodiments of this invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, their intended meanings are consistent. Similarly, the terms "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, their intended meanings are consistent.

[0032] In this embodiment of the invention, sometimes a subscript such as W1 may be written in a non-subscript form such as W1. When the difference is not emphasized, the meaning they express is the same.

[0033] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0034] Reference manual attached Figure 1 The diagram shows a flowchart of a fault detection method based on an adapter tool holder provided by an embodiment of the present invention.

[0035] This invention provides a fault detection method based on an adapter tool holder. This method can be implemented by a fault detection device based on the adapter tool holder, which can be a terminal or a server. The processing flow of the fault detection method based on the adapter tool holder may include the following steps:

[0036] S1: Obtain the displacement signal of the adapter tool holder.

[0037] An adapter tool holder is a device used to connect a cutting tool to a machine tool spindle, ensuring that the tool is stably fixed on the spindle during machining. Its performance directly affects machining accuracy and tool life. A displacement signal refers to the displacement data of the adapter tool holder during machining, acquired by a sensor (such as an eddy current displacement sensor). The displacement signal reflects the actual motion state of the adapter tool holder, and thus indirectly reflects information such as changes in cutting force during machining.

[0038] It should be noted that acquiring the displacement signal of the adapter tool holder can monitor the operating status of the equipment in real time, accurately understand the displacement of the adapter tool holder, promptly detect abnormalities and minor faults, ensure the stability of the machining process, obtain dynamic feedback without interrupting production, and effectively improve fault early warning and maintenance efficiency.

[0039] In one possible implementation, S1 specifically refers to:

[0040] Displacement signals are acquired using multiple eddy current displacement sensors.

[0041] Among them, the eddy current displacement sensor is a sensor that measures the position or displacement of an object through the eddy current effect. It changes the induced current by the interaction between the electromagnetic field emitted by the sensor and the object being measured, thereby measuring the displacement of the object.

[0042] S2: Determine the feed rate based on the displacement signal.

[0043] The feed rate refers to the speed at which the tool or workpiece moves in a given direction. During machining, the feed rate determines the cutting speed and the material removal rate.

[0044] It should be noted that by determining the feed rate through displacement signals, the movement of the tool or adapter can be tracked accurately in real time, avoiding the delay and errors of traditional methods. The feed rate can be dynamically adjusted to cope with changes that may occur during the machining process, thereby improving machining accuracy and reducing equipment wear.

[0045] In one possible implementation, S2 specifically includes:

[0046] S201: Establish a displacement signal model based on the displacement signal:

[0047] S1(θ)=G[R1-r(θ)-Δx]

[0048] S²(θ) = G[R² - r(θ + π) + Δx]

[0049] Wherein, S1 and S2 both represent sensors on the radial side of the adapter tool holder, S1(θ) represents the displacement signal of displacement sensor S1 when the adapter tool holder rotates by θ, S2(θ) represents the displacement signal of displacement sensor S2 when the adapter tool holder rotates by θ, G represents the sensitivity of the sensor, R1 represents the distance from sensor S1 to the center of the adapter tool holder, R2 represents the distance from sensor S2 to the center of the adapter tool holder, r() represents the radial change, π represents pi, and Δx represents the displacement of the adapter tool holder.

[0050] The sensitivity of a sensor represents the change in output caused by a unit input quantity, usually expressed as the ratio of voltage change to displacement change.

[0051] S202: Determine the radial displacement signal of the adapter tool holder based on the displacement signal model:

[0052]

[0053] Among them, S x (θ) represents the radial displacement signal when the adapter tool holder rotates by θ.

[0054] S203: When the displacement of the adapter tool holder is zero, the radial displacement signal is determined as the reference displacement signal.

[0055] S204: Combine the radial displacement signal and the reference displacement signal to determine the displacement of the adapter tool holder:

[0056]

[0057] Among them, S x0 (θ) represents the reference displacement signal when the adapter tool holder rotates by θ.

[0058] S205: Determine the feed rate based on the displacement of the adapter tool holder:

[0059]

[0060] Among them, f r Δt represents the feed rate, and Δt represents the duration of the tool holder displacement Δx.

[0061] It should be noted that by calculating the radial displacement signal of the adapter tool holder, key information can be accurately extracted from the displacement signal to effectively determine the feed rate. By comparing it with the reference displacement signal, external interference or errors are eliminated, ensuring the accuracy and reliability of the feed rate. This process has high precision in real-time monitoring and control, which can improve the stability and efficiency of the machining process and avoid the lag and errors that may exist in traditional methods.

[0062] S3: Establish a cutting force model based on the feed rate.

[0063] Among them, establishing a cutting force model based on the feed rate can accurately simulate and predict the changes in cutting force during the machining process. Cutting force is an important factor affecting machining quality, tool wear and machining accuracy. An accurate cutting force model can provide an important basis for subsequent fault detection, wear monitoring and machining optimization.

[0064] In one possible implementation, the cutting force model is specifically as follows:

[0065]

[0066] Where F represents the cutting force, Indicates the rate of change of cutting force. ξ represents the acceleration due to the cutting force, ω represents the damping coefficient. n K represents the natural frequency. s f represents the cutting gain. r This indicates the feed rate.

[0067] S4: Based on the cutting force model, establish a disturbance model.

[0068] The disturbance model is used to describe the deviations or fluctuations caused by external uncertainties, environmental changes or equipment problems in the system. In the actual machining process, in addition to the expected cutting force, the system may also be subject to various disturbances. These disturbances need to be modeled and compensated by the disturbance model. Here, the system refers to the machinery and control process in the entire machining process.

[0069] It should be noted that by establishing a disturbance model, the influence of external factors and system uncertainties on the cutting force can be taken into account, thereby improving the accuracy and robustness of the model. It can monitor and compensate for the dynamic changes of the equipment in real time, ensure the stability of the machining process, reduce errors caused by disturbances, and improve the accuracy of fault detection and early warning.

[0070] In one possible implementation, S4 specifically includes:

[0071] S401: Transform the cutting force model into a state-space form:

[0072]

[0073] y = C T x

[0074]

[0075] u = f r

[0076]

[0077] C = [1 0] T

[0078] in, Let A represent the rate of change of the system's state, x represent the system's state, b represent the input matrix, u represent the input vector, y represent the system output, and C represent the output matrix. T This indicates the transpose operation.

[0079] Specifically, x represents the system's state variables, which typically include key parameters describing the system's behavior, such as cutting force and wear. The input matrix b represents the influence of the system input on the state variables, describing how the input signal (such as the feed rate) affects the system state. The output matrix C represents the relationship between the system state and the output as a linear mapping.

[0080] S402: Based on the state-space form of the cutting force model, establish the disturbance model:

[0081]

[0082] y = C T x

[0083]

[0084] Where ΔA represents the system matrix perturbation, Δb represents the input matrix perturbation, d represents the bounded perturbation, Δa1(t) and Δa2(t) both represent perturbation parameters related to the cutting time t, and Δb1(t) represents the perturbation term of the input matrix. ΔA reflects the changes in the system dynamics caused by external or internal uncertainties.

[0085] It should be noted that by transforming the cutting force model into a state-space form, the dynamic behavior of the system can be expressed more clearly, facilitating mathematical analysis and control design. By establishing a disturbance model, the impact of uncertainties and external disturbances on the system can be taken into account, ensuring that the system can effectively detect and prevent faults under complex and variable working conditions. This process can better simulate the actual situation, enhance the system's robustness to external disturbances, and improve the accuracy and reliability of fault diagnosis.

[0086] S5: Establish an observer model.

[0087] Specifically, the observer model is a method that infers the internal state of a system by measuring its output and combining it with a mathematical model of the system. Even if some states cannot be directly measured, the observer model can estimate the system's state based on other available output information. Establishing an observer model enables the estimation of the system's internal state. By using the system's input and output information, the system's behavior can be monitored and predicted in real time, improving the accuracy and timeliness of fault diagnosis. The introduction of the observer model makes the fault detection process more reliable and comprehensive, reduces reliance on expensive or complex sensors, lowers costs, and improves system stability.

[0088] In one possible implementation, the observer model is specifically as follows:

[0089]

[0090] K = [k1, k2, ..., k n ] T

[0091] in, This represents the rate of change of the estimated system state. This represents the system state estimate, and K represents the observer gain matrix. k represents the output estimate of the system. j The elements of the observer gain matrix are represented by j = 1, 2, ..., n, where n represents the total number of elements in the observer gain matrix.

[0092] S6: Determine the cutting force error based on the disturbance model and the observer model.

[0093] Among them, cutting force error refers to the difference between the cutting force estimated by the observer model and the actual cutting force, reflecting the deviation in the cutting process, and is usually used to evaluate the performance and failure of the system.

[0094] It should be noted that by combining the perturbation model and the observer model to calculate the cutting force error, the changes in cutting force during the machining process can be monitored and accurately judged in real time. This avoids the problem that traditional methods cannot effectively capture minute changes, improves the sensitivity of fault detection, and promptly detects equipment deviations or abnormalities. As a result, machining parameters can be optimized, machining errors and tool wear can be reduced, thereby improving production efficiency and equipment stability.

[0095] In one possible implementation, the cutting force error is specifically:

[0096]

[0097] Where e represents the cutting force error.

[0098] In this invention, the state estimation error is defined as... The output estimation error is The error dynamic equation is then:

[0099]

[0100] in, This indicates the output estimation error. This represents the state estimation error. This represents the rate of change of the state estimation error.

[0101] S7: Determine the wear rate of the adapter tool holder based on the observer model.

[0102] The wear rate of the adapter tool holder refers to the rate of wear change that occurs during machining due to prolonged use and cutting forces. Wear rate is a key indicator for evaluating tool performance and preventing malfunctions.

[0103] It should be noted that determining the wear rate of the adapter tool holder based on the observer model can estimate the tool wear in real time and avoid the technical difficulties caused by directly measuring wear. By monitoring the wear rate in real time, potential faults can be identified in advance, and machining parameters can be adjusted or tools can be replaced in a timely manner, thereby optimizing production efficiency and extending tool life.

[0104] In one possible implementation, S7 specifically includes:

[0105] S701: Establishing a model relating wear rate and cutting force change rate:

[0106] F = F0 + Lw

[0107]

[0108] Where F represents the cutting force, F0 represents the initial cutting force (i.e., the cutting force when the tool holder is not worn), L represents parameters related to cutting conditions, w represents tool wear, w0 represents initial wear, and t represents the duration of the cutting process. ΔF represents the wear rate, ΔF represents the change in cutting force, and Δt represents the change in time. This represents the rate of change of cutting force.

[0109] S702: Determine the rate of change of cutting force based on the observer model.

[0110] S703: Determine the wear rate of the adapter tool holder based on the relationship model and the rate of change of cutting force.

[0111] It should be noted that by establishing a model relating the wear rate to the rate of change of cutting force, the wear condition of the adapter tool holder can be estimated more accurately. By calculating the rate of change of cutting force in real time using the observer model and combining it with mathematical relationships to extrapolate the wear rate, tool wear problems can be detected at an early stage.

[0112] In this invention, the observer can estimate the rate of change of the cutting force. Wear rate With the rate of change of cutting force There is a direct relationship between the two factors; therefore, by combining the observer model and the rate of change of the cutting force, the wear rate of the adapter tool holder can be determined. This is because the cutting force F and its rate of change... It is part of the system state, and the rate of change of cutting force can be accurately estimated through the observer model.

[0113] S8: Fault detection is performed by combining cutting force error and wear rate.

[0114] It should be noted that combining cutting force error and wear rate for fault detection can comprehensively analyze abnormal situations in the machining process, identify potential faults or equipment malfunctions in advance, avoid false alarms or missed alarms caused by a single parameter, improve the accuracy and robustness of fault detection, help optimize the machining process in real time, improve equipment stability, and reduce downtime and maintenance costs.

[0115] In one possible implementation, S8 specifically includes:

[0116] S801: Set the cutting force error threshold and wear rate threshold.

[0117] The wear rate threshold is specifically:

[0118]

[0119] Among them, F T C1 represents the wear rate threshold, and C1 represents the proportionality coefficient. Indicates the average wear rate. Let i represent the wear rate measured in the i-th measurement, where i = 1, 2, ..., N, and N represents the total number of measurements.

[0120] The specific cutting force error threshold is as follows:

[0121]

[0122] Among them, E T C1 represents the cutting force error threshold, C2 represents the proportionality coefficient, and e(i) represents the cutting force error of the i-th measurement.

[0123] S802: Determine whether the cutting force error exceeds the cutting force error threshold and whether the wear rate exceeds the wear rate threshold; if so, the adapter tool holder has malfunctioned; otherwise, the adapter tool holder has not malfunctioned.

[0124] It should be noted that by setting thresholds for cutting force error and wear rate and making judgments, the working status of the adapter tool holder can be accurately monitored, the system performance can be evaluated in real time, and fault warnings can be issued in a timely manner when the cutting force or wear rate is abnormal. By setting thresholds, fault judgments that are too early or too late can be avoided, thereby improving the sensitivity and stability of the system, effectively reducing the equipment failure rate and extending the equipment life.

[0125] S9: Based on the fault detection results, determine whether the adapter tool holder has malfunctioned; if so, use a genetic algorithm to adjust the parameters of the adapter tool holder; otherwise, return to step S1.

[0126] It should be noted that the system automatically determines whether the adapter tool holder is malfunctioning based on the fault detection results, and adjusts the parameters through a genetic algorithm when a fault occurs. This enables the equipment to self-repair and optimize itself. The genetic algorithm can effectively optimize control parameters, improve machining accuracy and efficiency, and avoid the shortcomings of manual intervention.

[0127] In one possible implementation, the use of a genetic algorithm to adjust the parameters of the adapter tool holder specifically includes:

[0128] Define the fitness function:

[0129] Fitness(x)=w1·error(x)+w2·wear(x)

[0130] Where Fitness() represents the fitness function, w1 and w2 both represent weight coefficients, error() represents the error of the cutting force, and wear() represents the wear rate.

[0131] Initialize the population.

[0132] Each individual's genetic code represents the control parameters of the tool holder (such as feed rate, cutting force coefficient, etc.).

[0133] Based on the fitness function, the optimal individual in the initial population is selected using a roulette wheel selection method.

[0134] Forced mutation judgment is performed on the optimal individual.

[0135] Forced mutation determination specifically includes:

[0136] Calculate the average fitness value of all individuals in the entire population:

[0137]

[0138] Among them, f avg f represents the average fitness value. i Let i represent the i-th individual in the initial population, where i = 1, 2, ..., N, and N represents the total number of individuals in the initial population.

[0139] Calculate fitness gap:

[0140]

[0141] Where Δf represents the fitness gap, f max This represents the fitness value of the individual with the highest fitness value in the initial population.

[0142] Set a fitness threshold.

[0143] Determine if the fitness gap is greater than the fitness threshold; if so, no mutation operation is needed; otherwise, no mutation operation is needed.

[0144] Based on the results of the forced mutation assessment, determine whether the optimal individual needs to undergo mutation; if so, proceed to the next step; otherwise, re-initialize the population.

[0145] Perform crossover and mutation operations on the best individual to obtain the mutated individual.

[0146] The mutation operation is as follows:

[0147] Perform Gaussian-uniform mutation on the best individual:

[0148]

[0149] Δx U =u(-δ,δ)

[0150] Δx=Δx G +Δx U

[0151] x′=x+Δx

[0152] Where, Δx G Denotes the Gaussian variation, Δx U Let N() represent the uniformly distributed variance, N() represent the Gaussian distribution function, u() represent the uniform distribution function, and σ represent the uniform distribution function. G δ represents the magnitude of the Gaussian perturbation, e represents the exponential function, β represents the decay parameter, δ represents the magnitude of the uniform perturbation, Δx represents the overall variability, and x′ represents the mutated individual.

[0153] The mutated individuals are merged with the initial population to obtain the merged population.

[0154] Calculate the fitness value of individuals in the merged population.

[0155] Determine if the maximum number of iterations has been reached. If so, output the individual with the highest fitness value; otherwise, return to continue iterating.

[0156] It should be noted that by introducing forced mutation and multiple mutation strategies, genetic algorithms can effectively avoid early convergence, improve global search capabilities, and accurately optimize control parameters. This not only improves system stability but also effectively reduces failure risks and maintenance costs.

[0157] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following:

[0158] In the embodiments of the invention, by establishing a cutting force model and a disturbance model, the influence of feed rate on cutting force is accurately described, and fluctuations in the actual machining environment are simulated, thereby better capturing subtle changes in the equipment, enhancing the adaptability and reliability of fault detection, and enabling it to cope with changing machining environments. By establishing an observer model to estimate the system state, relevant key parameters can be accurately inferred even without directly measuring certain variables, improving the efficiency of fault diagnosis. Combined with the comprehensive analysis of cutting force error and wear rate, equipment faults can be identified more accurately, enhancing the robustness and accuracy of fault detection, reducing the risk of false alarms and missed alarms. When a fault occurs, the equipment parameters are automatically adjusted through a genetic algorithm, avoiding further damage to the equipment, reducing maintenance costs, and improving production efficiency.

[0159] Reference manual attached Figure 2 The diagram shows a structural schematic of a fault detection system based on an adapter tool holder provided by the present invention.

[0160] The present invention also provides a fault detection system 20 based on an adapter tool holder, applied to the above-mentioned fault detection method based on an adapter tool holder, comprising:

[0161] Processor 201.

[0162] The memory 202 stores computer-readable instructions, which, when executed by the processor 201, implement the fault detection method based on the adapter tool holder as described in the method embodiment.

[0163] The fault detection system 20 based on the adapter tool holder provided by the present invention can execute the above-mentioned fault detection method based on the adapter tool holder and achieve the same or similar technical effects. To avoid repetition, the present invention will not elaborate further.

[0164] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following:

[0165] In the embodiments of the invention, by establishing a cutting force model and a disturbance model, the influence of feed rate on cutting force is accurately described, and fluctuations in the actual machining environment are simulated, thereby better capturing subtle changes in the equipment, enhancing the adaptability and reliability of fault detection, and enabling it to cope with changing machining environments. By establishing an observer model to estimate the system state, relevant key parameters can be accurately inferred even without directly measuring certain variables, improving the efficiency of fault diagnosis. Combined with the comprehensive analysis of cutting force error and wear rate, equipment faults can be identified more accurately, enhancing the robustness and accuracy of fault detection, reducing the risk of false alarms and missed alarms. When a fault occurs, the equipment parameters are automatically adjusted through a genetic algorithm, avoiding further damage to the equipment, reducing maintenance costs, and improving production efficiency.

[0166] It should be understood that the processor in the embodiments of the present invention can be a central processing unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0167] It should also be understood that the memory in the embodiments of the present invention can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate synchronous DRAM (DDR SDRAM), enhanced synchronous DRAM (ESDRAM), synchronous linked DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0168] The above embodiments can be implemented, in whole or in part, by software, hardware (such as circuits), firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. A computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the flow or function according to the embodiments of the present invention is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. Computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., infrared, wireless, microwave, etc.) means. A computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. Available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media. Semiconductor media can be solid-state drives.

[0169] It should be understood that the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. A and B can be singular or plural. Additionally, the character " / " in this article generally indicates an "or" relationship between the preceding and following related objects, but it can also represent an "and / or" relationship. Please refer to the context for a more accurate understanding.

[0170] In this invention, "at least one" means one or more, and "more than one" means two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of a single item or a plurality of items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be a single item or multiple items.

[0171] It should be understood that, in various embodiments of the present invention, the sequence number of each process does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0172] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0173] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the devices, apparatuses, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0174] In the embodiments provided by this invention, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0175] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0176] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0177] If the functionality is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0178] This invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the fault detection method based on a tool holder as described in the method embodiment.

[0179] The present invention provides a computer-readable storage medium that can implement the steps and effects of the fault detection method based on the adapter tool holder described in the above method embodiments. To avoid repetition, the present invention will not repeat the details.

[0180] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following:

[0181] In the embodiments of the invention, by establishing a cutting force model and a disturbance model, the influence of feed rate on cutting force is accurately described, and fluctuations in the actual machining environment are simulated, thereby better capturing subtle changes in the equipment, enhancing the adaptability and reliability of fault detection, and enabling it to cope with changing machining environments. By establishing an observer model to estimate the system state, relevant key parameters can be accurately inferred even without directly measuring certain variables, improving the efficiency of fault diagnosis. Combined with the comprehensive analysis of cutting force error and wear rate, equipment faults can be identified more accurately, enhancing the robustness and accuracy of fault detection, reducing the risk of false alarms and missed alarms. When a fault occurs, the equipment parameters are automatically adjusted through a genetic algorithm, avoiding further damage to the equipment, reducing maintenance costs, and improving production efficiency.

[0182] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

[0183] The following points need to be explained:

[0184] (1) The accompanying drawings of the embodiments of the present invention only involve the structures involved in the embodiments of the present invention. Other structures can refer to the general design.

[0185] (2) For clarity, the thickness of layers or regions is enlarged or reduced in the drawings used to describe embodiments of the present invention; that is, these drawings are not drawn to actual scale. It is understood that when an element such as a layer, film, region, or substrate is referred to as being “above” or “below” another element, the element may be “directly” located “above” or “below” the other element, or there may be intermediate elements.

[0186] (3) Where there is no conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other to obtain new embodiments.

[0187] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. The scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A fault detection method based on an adapter tool holder, characterized in that, include: S1: Obtain the displacement signal of the adapter tool holder; S2: Determine the feed rate based on the displacement signal; S3: Establish a cutting force model based on the feed rate; S4: Based on the cutting force model, establish a disturbance model; S5: Establish an observer model; S6: Determine the cutting force error based on the disturbance model and the observer model; S7: Determine the wear rate of the adapter tool holder based on the observer model; S8: Perform fault detection by combining the cutting force error and the wear rate; S9: Based on the fault detection results, determine whether the adapter tool holder has malfunctioned; if so, use a genetic algorithm to adjust the parameters of the adapter tool holder; otherwise, return to step S1.

2. The fault detection method based on the adapter tool holder according to claim 1, characterized in that, Specifically, S1 is: The displacement signal is acquired by multiple eddy current displacement sensors.

3. The fault detection method based on the adapter tool holder according to claim 1, characterized in that, S2 specifically includes: S201: Based on the displacement signal, establish a displacement signal model: S1(θ)=G[R1-r(θ)-Δx] S²(θ) = G[R² - r(θ + π) + Δx] Where S1 and S2 both represent sensors on the radial side of the adapter tool holder, S1(θ) represents the displacement signal of displacement sensor S1 when the adapter tool holder rotates by θ, S2(θ) represents the displacement signal of displacement sensor S2 when the adapter tool holder rotates by θ, G represents the sensitivity of the sensor, R1 represents the distance from sensor S1 to the center of the adapter tool holder, R2 represents the distance from sensor S2 to the center of the adapter tool holder, r() represents the radial change, π represents pi, and Δx represents the displacement of the adapter tool holder; S202: Determine the radial displacement signal of the adapter tool holder based on the displacement signal model: Among them, S x (θ) represents the radial displacement signal when the adapter tool holder rotates by θ; S203: When the displacement of the adapter tool holder is zero, the radial displacement signal is determined to be the reference displacement signal; S204: Combine the radial displacement signal and the reference displacement signal to determine the displacement of the adapter tool holder: Among them, S x0 (θ) represents the reference displacement signal when the adapter tool holder rotates by θ; S205: Determine the feed rate based on the displacement of the adapter tool holder.

4. The fault detection method based on the adapter tool holder according to claim 1, characterized in that, The cutting force model is specifically as follows: Where F represents the cutting force, Indicates the rate of change of cutting force. ξ represents the acceleration due to the cutting force, ω represents the damping coefficient. n K represents the natural frequency. s f represents the cutting gain. r This indicates the feed rate.

5. The fault detection method based on the adapter tool holder according to claim 1, characterized in that, S4 specifically includes: S401: Transform the cutting force model into a state-space form; S402: Based on the state-space form of the cutting force model, establish the disturbance model: y=C T x in, Let A represent the system's rate of change of state, x represent the system's state, b represent the input matrix, u represent the input vector, y represent the system output, C represent the output matrix, T represent the transpose operation, ΔA represent the system matrix perturbation, Δb represent the input matrix perturbation, d represent the bounded perturbation, Δa1(t) and Δa2(t) both represent perturbation parameters related to the cutting time t, and Δb1(t) represent the perturbation term of the input matrix.

6. The fault detection method based on the adapter tool holder according to claim 1, characterized in that, The observer model is specifically as follows: K=[k1,k2,...,k n ] T in, This represents the rate of change of the estimated system state. This represents the system state estimate, and K represents the observer gain matrix. k represents the output estimate of the system. j Let j represent the j-th element of the observer gain matrix, where j = 1, 2, ..., n, and n represents the total number of elements in the observer gain matrix.

7. The fault detection method based on the adapter tool holder according to claim 1, characterized in that, The cutting force error is specifically: Where e represents the cutting force error.

8. The fault detection method based on the adapter tool holder according to claim 1, characterized in that, Specifically, S7 includes: S701: Establish a model relating the wear rate and the rate of change of cutting force; S702: Determine the rate of change of cutting force based on the observer model; S703: Determine the wear rate of the adapter tool holder based on the relationship model and the cutting force change rate.

9. The fault detection method based on the adapter tool holder according to claim 1, characterized in that, S8 specifically includes: S801: Set the cutting force error threshold and wear rate threshold; S802: Determine whether the cutting force error exceeds the cutting force error threshold and whether the wear rate exceeds the wear rate threshold; if so, the adapter tool holder has malfunctioned; otherwise, the adapter tool holder has not malfunctioned.

10. A fault detection system based on an adapter toolholder, characterized in that, include: processor; A memory storing computer-readable instructions, which, when executed by the processor, implement the fault detection method based on the adapter tool holder as described in any one of claims 1 to 9.

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