Absolute hollow encoder performance evaluation method and system based on real-time feedback

Abstract

The present invention relates to the technical field of encoder monitoring, and in particular to a method and system for evaluating the performance of an absolute value hollow encoder based on real-time feedback, which can improve the accuracy and practicality of encoder performance evaluation; the method comprises: dividing the absolute value hollow encoder into a plurality of collaborative operation units based on the structural function of the absolute value hollow encoder; determining a key performance parameter set of each collaborative operation unit according to the working type of each collaborative operation unit; performing real-time monitoring of the absolute value hollow encoder in the same measurement operation according to a preset monitoring frequency and key performance parameter set to obtain a real-time key performance parameter set; utilizing a pre-constructed unit performance evaluation model to perform multi-dimensional comprehensive calculations on each real-time key performance parameter set to obtain a multi-dimensional performance index; and considering the service life of the absolute value hollow encoder and the working environment status of the location where the absolute value hollow encoder is located.

Description

Technical Field

[0001] The present invention relates to the technical field of encoder monitoring, and in particular to a method and system for evaluating the performance of an absolute value hollow encoder based on real-time feedback. Background Art

[0002] In modern industrial automation and precision machinery systems, absolute hollow encoders are widely used because they can provide precise position feedback. Absolute hollow encoders are usually installed on motor shafts or other rotating equipment to monitor and control key parameters such as position, speed, and direction. With the development of Industry 4.0 and smart manufacturing, the requirements for encoder performance are increasing. Not only must they ensure high accuracy and reliability, but they must also have the ability to monitor and self-evaluate in real time to achieve predictive maintenance and optimize overall production efficiency.

[0003] Existing evaluation methods often only focus on some basic performance indicators of the encoder, such as resolution and accuracy, but ignore the synergy between the internal units of the encoder as a complex system and the impact of the external environment on the encoder performance. As a result, the evaluation results are not precise enough and it is difficult to accurately reflect the actual working status of the encoder. Summary of the Invention

[0004] In order to solve the above technical problems, the present invention provides an absolute value hollow encoder performance evaluation method and system based on real-time feedback, which can improve the accuracy and practicality of encoder performance evaluation.

[0005] In a first aspect, the present invention provides a method for evaluating the performance of an absolute value hollow encoder based on real-time feedback, the method comprising:

[0006] Based on the structural function of the absolute value hollow encoder, the absolute value hollow encoder is divided into multiple collaborative operation units;

[0007] Determining a key performance parameter set of each of the collaborative operation units according to the working type of each of the collaborative operation units;

[0008] According to the preset monitoring frequency and the key performance parameter set, in the same measurement operation, the absolute hollow encoder is monitored in real time to obtain the real-time key performance parameter set;

[0009] Using the pre-built unit performance evaluation model, multi-dimensional comprehensive calculations are performed on each set of real-time key performance parameters to obtain a multi-dimensional performance index;

[0010] Taking into account the service life of the absolute value hollow encoder and the working environment conditions of the location, each of the multidimensional performance indices is corrected to obtain multiple multidimensional performance correction indices;

[0011] Based on the preset weight coefficients, each multidimensional performance correction index is weighted to obtain a multidimensional performance comprehensive index;

[0012] According to the multi-dimensional performance comprehensive index, the corresponding absolute value hollow encoder performance evaluation result is mapped in the pre-built encoder performance comparison space.

[0013] Furthermore, considering the service life of the absolute hollow encoder and the working environment conditions of the location, each of the multi-dimensional performance indices is calibrated separately, including:

[0014] Obtain the service life of the absolute hollow encoder and the working environment parameter information of its location;

[0015] Identifying parameters exceeding the standard on the working environment parameter information, and calculating the exceeding range, to obtain a working environment exceeding standard parameter set; the working environment exceeding standard parameter set includes the exceeding ranges of all exceeding standard parameters;

[0016] Performing comprehensive calculation on the set of parameters exceeding the working environment standard to obtain a working environment impact coefficient;

[0017] Perform statistical analysis on the service life of the absolute hollow encoder and the pre-set standard working time to obtain the service life influence coefficient;

[0018] The working environment influence coefficient and the service time influence coefficient are used to simultaneously correct the multidimensional performance index and obtain the multidimensional performance correction index.

[0019] Furthermore, the multidimensional performance index is corrected and calculated, and the calculation formula for the multidimensional performance correction index is obtained as follows:

[0020] P t =P i ×(1+α·(EIC-1))×(1+β·(LIF-1))

[0021] Among them, P t represents the multidimensional performance correction index; P i represents the multidimensional performance index; EIC represents the working environment influence coefficient; LIF represents the service time influence coefficient; α and β represent adjustment coefficients, which are used to control the degree of influence of working environment and service time on the performance index.

[0022] Furthermore, the coordinated operation unit includes a signal processing unit, a position detection unit and a communication interface unit.

[0023] Furthermore, the key performance parameter set of the signal processing unit includes signal strength, signal-to-noise ratio, signal frequency, signal processing delay and error rate; the key performance parameter set of the position detection unit includes resolution, repeatability, zero offset error and position conversion accuracy; the key performance parameter set of the communication interface unit includes data transmission rate, bit error rate, connection stability, data communication delay and data transmission integrity.

[0024] Furthermore, factors influencing the setting of the preset weight coefficient include functional criticality, fault impact, parameter stability, parameter impact on overall performance, harshness of the working environment, service time, system requirements and maintenance strategy.

[0025] Furthermore, the method for constructing the encoder performance comparison space includes:

[0026] According to the structure, function and working principle of the absolute hollow encoder, the main dimensions that affect the encoder performance are determined, and for each dimension, the performance indicators are further refined;

[0027] Collect historical test, monitoring and maintenance record data for encoders;

[0028] Clean and organize the collected historical data, remove outliers and invalid data, and standardize the data;

[0029] Building an encoder performance mapping model based on the processed historical data;

[0030] Set performance thresholds for each dimension and indicator based on the encoder's application scenarios and performance requirements;

[0031] The encoder performance mapping model, performance thresholds and related performance indicators are integrated to form an encoder performance comparison space.

[0032] On the other hand, the present application also provides an absolute value hollow encoder performance evaluation system based on real-time feedback, the system comprising:

[0033] A unit division module, based on the structural function of the absolute value hollow encoder, divides the absolute value hollow encoder into multiple cooperative operation units; the cooperative operation units include a signal processing unit, a position detection unit and a communication interface unit;

[0034] a performance parameter definition module, for determining a key performance parameter set of each of the collaborative operation units based on the working type of each of the collaborative operation units; the key performance parameter set of the signal processing unit includes signal strength, signal-to-noise ratio, signal frequency, signal processing delay, and error rate; the key performance parameter set of the position detection unit includes resolution, repeatability, zero offset error, and position conversion accuracy; the key performance parameter set of the communication interface unit includes data transmission rate, bit error rate, connection stability, data communication delay, and data transmission integrity;

[0035] A real-time monitoring module, which monitors the absolute hollow encoder in real time during a same measurement operation according to a preset monitoring frequency and the key performance parameter set, and obtains a real-time key performance parameter set of each of the collaborative operation units;

[0036] The unit performance evaluation module uses a pre-built unit performance evaluation model to perform multi-dimensional comprehensive calculations on each set of real-time key performance parameters to obtain a multi-dimensional performance index for each of the collaborative operation units;

[0037] a performance correction module, which takes into account the service life of the absolute value hollow encoder and the working environment status of the location, and performs correction processing on the multidimensional performance index of each of the collaborative operation units to obtain the multidimensional performance correction index of each of the collaborative operation units;

[0038] A weight calculation module performs weight calculation on the multidimensional performance correction index of each of the collaborative operation units based on a preset weight coefficient to obtain a comprehensive multidimensional performance index of the absolute value hollow encoder;

[0039] The performance evaluation result mapping module maps the corresponding absolute value hollow encoder performance evaluation result in a pre-built encoder performance comparison space according to the multi-dimensional performance comprehensive index.

[0040] In a third aspect, the present application provides an electronic device comprising a bus, a transceiver, a memory, a processor, and a computer program stored in the memory and runnable on the processor, wherein the transceiver, the memory, and the processor are connected via the bus, and the computer program implements the steps of any one of the above methods when executed by the processor.

[0041] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, which implements the steps in any one of the above methods when executed by a processor.

[0042] Compared with the existing technology, the present invention has the following advantages: by meticulously dividing the absolute value hollow encoder into multiple collaborative operation units and determining a set of key performance parameters for each unit, this method achieves a refined evaluation of encoder performance. It not only covers traditional basic performance indicators, but also delves into the synergy between the various units within the encoder and the impact of the external environment on performance, thereby providing a more comprehensive and accurate evaluation result.

[0043] By using preset monitoring frequencies and real-time monitoring technology, this method can obtain a set of key encoder performance parameters in real time and immediately perform multi-dimensional comprehensive calculations. This helps to promptly identify changes in encoder performance and potential problems, providing strong support for predictive maintenance and optimizing production efficiency.

[0044] Using a pre-built unit performance evaluation model, this method performs a multi-dimensional comprehensive calculation of each set of real-time key performance parameters to obtain a multi-dimensional performance index for each collaboratively operated unit. This method can more comprehensively reflect the performance status of the encoder, avoid the one-sidedness of single-index evaluation, and improve the accuracy and reliability of the evaluation results.

[0045] This method takes into account the impact of the encoder's service life and the working environment conditions on its performance, and corrects the multi-dimensional performance index. This improves the adaptability and accuracy of the evaluation results, making them more reflective of the encoder's actual performance in the current working environment.

[0046] Through weight calculation based on preset weight coefficients, this method combines the multi-dimensional performance correction index of each collaboratively operating unit into a multi-dimensional performance comprehensive index of the absolute hollow encoder. This more accurately reflects the overall performance level of the encoder, providing a scientific basis for optimizing production efficiency and equipment maintenance. This method maps the corresponding performance evaluation results in a pre-established encoder performance comparison space, making the evaluation results more intuitive and easy to understand. This helps technicians quickly understand the performance status of the encoder and improve maintenance efficiency and accuracy.

[0047] In summary, the absolute value hollow encoder performance evaluation method based on real-time feedback not only solves the limitations of existing evaluation methods, but also improves the accuracy and practicality of encoder performance evaluation. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 is a flow chart of the present invention;

[0049] Figure 2 is a flow chart of a method for respectively correcting the multi-dimensional performance index of each of the collaborative operation units;

[0050] Figure 34 is a structural diagram of an absolute value hollow encoder performance evaluation system based on real-time feedback in an embodiment. DETAILED DESCRIPTION

[0051] In the description of this application, those skilled in the art should know that this application can be implemented as a method, an apparatus, an electronic device, and a computer-readable storage medium. Therefore, this application can be specifically implemented in the following forms: complete hardware, complete software (including firmware, resident software, microcode, etc.), or a combination of hardware and software. In addition, in some embodiments, this application can also be implemented in the form of a computer program product in one or more computer-readable storage media, wherein the computer-readable storage medium contains computer program code.

[0052] The computer-readable storage medium may be any combination of one or more computer-readable storage media. Computer-readable storage media include: electrical, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or components, or any combination thereof. More specific examples of computer-readable storage media include: portable computer disks, hard disks, random access memories, read-only memories, erasable programmable read-only memories, flash memory, optical fibers, optical disc read-only memories, optical storage devices, magnetic storage devices, or any combination thereof. In this application, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, device, or component.

[0053] The acquisition, storage, use, and processing of data in this application's technical solution comply with relevant national laws.

[0054] This application describes the provided methods, devices, and electronic devices through flowcharts and / or block diagrams.

[0055] It should be understood that each block in the flowchart and / or block diagram, as well as combinations of blocks in the flowchart and / or block diagram, can be implemented by computer-readable program instructions. These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, thereby producing a machine. These computer-readable program instructions are executed by the computer or other programmable data processing device to produce a device that implements the functions / operations specified in the blocks in the flowchart and / or block diagram.

[0056] These computer-readable program instructions may also be stored in a computer-readable storage medium that enables a computer or other programmable data processing device to operate in a specific manner. In this way, the instructions stored in the computer-readable storage medium produce an instruction device product that implements the functions / operations specified in the blocks in the flowchart and / or block diagram.

[0057] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device, so that a series of operational steps are performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby enabling the instructions executed on the computer or other programmable data processing apparatus to provide a process that implements the functions / operations specified by the blocks in the flowchart and / or block diagram.

[0058] The present application is described below in conjunction with the accompanying drawings.

[0059] Example 1: Figures 1 to 2 As shown, the absolute value hollow encoder performance evaluation method based on real-time feedback of the present invention specifically includes the following steps:

[0060] S1. Based on the structural function of the absolute value hollow encoder, the absolute value hollow encoder is divided into multiple collaborative operation units;

[0061] The collaborative operation unit includes a signal processing unit, a position detection unit and a communication interface unit;

[0062] The signal processing unit is used to receive the raw signal from the position detection unit and convert it into a digital signal or other form of data for further processing; it includes analog-to-digital conversion, filtering, amplification and other processes to ensure signal quality and accuracy; in addition, the signal processing unit also includes algorithms for calculating absolute position or angle, and processing communication protocols;

[0063] The position detection unit is composed of a grating, magnetic element, or other type of sensing technology to directly sense the position change of the rotating shaft. Depending on the technology used, it can be optical using an LED light source and photodetector, magnetic using a Hall effect sensor, or capacitive. When selecting, factors such as resolution, response speed, durability, and cost should be considered.

[0064] The communication interface unit enables data exchange between the encoder and the control system; it supports multiple industry standard communication protocols and ensures high-speed, low-latency and highly reliable data transmission; it involves hardware connection and software level protocol stack implementation and error checking mechanism;

[0065] The three collaborative operating units are not isolated, but interdependent and work together; the signal processing unit provides clear and accurate signal input to the position detection unit; the position detection unit calculates the position information based on these signals and passes it to the communication interface unit; the communication interface unit ensures that this information can be reliably transmitted to the external system.

[0066] In this step, the absolute value hollow encoder is divided into three collaborative operating units: a signal processing unit, a position detection unit, and a communication interface unit, thereby realizing a modular design of the encoder. Each unit can be independently developed, tested, and optimized, thereby improving the overall development efficiency and maintainability of the system. The signal processing unit is responsible for receiving the original signal and converting and processing it, ensuring the quality and accuracy of the signal. This helps to reduce errors and improve the accuracy and reliability of the encoder. The position detection unit adopts a variety of sensing technologies, and the most suitable technology can be selected according to the specific application scenario. This enables the encoder to adapt to different working environments and rotating shaft types, improving its versatility and applicability. The communication interface unit supports a variety of industrial standard communication protocols and ensures high-speed, low-latency, and highly reliable data transmission. This ensures that data exchange between the encoder and the external system can proceed smoothly, thereby improving the response speed and stability of the entire control system. The three collaborative operating units are interdependent and work together to form an efficient and stable encoder system. This not only improves the performance of the encoder, but also makes the system easier to integrate and expand, providing convenience for subsequent upgrades and maintenance.

[0067] S2. Determine a key performance parameter set of each collaborative operation unit according to the working type of each collaborative operation unit;

[0068] The key performance parameter set of the signal processing unit includes:

[0069] Signal strength: measures the strength of the original received signal. The stronger the signal strength, the better the signal transmission quality and the stronger the anti-interference ability.

[0070] Signal-to-noise ratio: the ratio between signal and noise. The higher the signal-to-noise ratio, the better the signal quality and the smaller the impact of noise on the signal.

[0071] Signal frequency: indicates how fast the signal changes;

[0072] Signal processing delay: refers to the time from receiving the original signal to outputting the processed signal. The smaller the delay, the faster the signal processing speed and the smaller the impact on the real-time performance of the system;

[0073] Error rate: measures the size of the error introduced during signal processing. The lower the error rate, the higher the accuracy of signal processing.

[0074] The key performance parameter set of the position detection unit includes:

[0075] Resolution: Indicates the minimum position change that the encoder can recognize. The higher the resolution, the more sensitive the encoder is to position changes and the higher the detection accuracy.

[0076] Repeatability: Measures the stability and consistency of the encoder's output when measuring the same position multiple times. The better the repeatability, the higher the reliability of the encoder.

[0077] Zero offset error: refers to the error of the encoder at the initial position. The smaller the zero offset error, the higher the initial positioning accuracy of the encoder.

[0078] Position conversion accuracy: measures the accuracy of the encoder in converting position changes into electrical signals. The higher the conversion accuracy, the stronger the encoder's position detection capability.

[0079] The key performance parameter set of the communication interface unit includes:

[0080] Data transmission rate: Indicates the speed of data exchange between the encoder and the external system. The higher the rate, the more efficient the data transmission.

[0081] Bit error rate: measures the probability of errors during data transmission. The lower the bit error rate, the higher the reliability of data transmission.

[0082] Connection stability: refers to whether the connection between the encoder and the external system is stable. The more stable the connection, the better the continuity of data transmission.

[0083] Data communication delay: refers to the time from when the encoder sends data to when the external system receives the data. The smaller the delay, the better the real-time performance of data transmission.

[0084] Data transmission integrity: measures whether data is lost or damaged during transmission. The higher the integrity, the better the data transmission quality.

[0085] In this step, by determining the key performance parameter set for each collaborative operation unit according to its working type, a refined evaluation of the absolute value hollow encoder performance is achieved; not only the basic performance indicators of the encoder are paid attention to, but also the working status and performance of each unit inside the encoder are deeply understood, so that the actual working status of the encoder can be reflected more comprehensively and accurately; the key performance parameter set of each collaborative operation unit can directly reflect the performance level and stability of the unit; therefore, in the process of real-time monitoring and evaluation, by measuring and analyzing these key performance parameters, the accuracy of the evaluation can be greatly improved, and the possibility of misjudgment and missed judgment can be reduced; by real-time monitoring and evaluation of the key performance parameters of each collaborative operation unit, potential performance problems or potential faults; it helps enterprises to formulate more scientific and reasonable maintenance strategies and carry out preventive maintenance in advance, thereby avoiding or reducing production interruptions and losses caused by encoder failures; through real-time monitoring and evaluation of encoder performance, enterprises can promptly discover and solve performance bottlenecks and problems, ensuring that the encoder is always in the best working condition; it helps to improve production efficiency, reduce production costs, and enhance the competitiveness and market position of enterprises; the key performance parameter set determined in this step not only provides a scientific basis for the performance evaluation of the encoder, but also provides an important reference for technological innovation and R&D; enterprises can continuously optimize and improve the design and manufacturing process of the encoder according to the requirements of these parameter sets, and promote the continuous progress and innovative development of technology.

[0086] S3. According to the preset monitoring frequency and the key performance parameter set, in the same measurement operation, the absolute value hollow encoder is monitored in real time to obtain the real-time key performance parameter set of each of the collaborative operation units;

[0087] The method for obtaining the real-time key performance parameter set includes:

[0088] Preset a monitoring frequency based on the actual application scenario and requirements of the encoder. The preset monitoring frequency should be high enough to capture performance changes of the encoder during operation, but not too high to avoid generating excessive data and increasing the difficulty of subsequent processing.

[0089] Monitor the encoder in real time according to the preset monitoring frequency. Use specialized monitoring equipment or systems to collect key performance parameters of each cooperating unit of the encoder in real time. These parameters include signal strength, signal-to-noise ratio, signal frequency, signal processing delay, error rate; resolution, repeatability, zero offset error, position conversion accuracy; data transmission rate, bit error rate, connection stability, data communication delay, and data transmission integrity.

[0090] During the monitoring process, the key performance parameters collected are recorded in real time and used for subsequent multi-dimensional comprehensive calculation and analysis to evaluate the overall performance of the encoder;

[0091] Since the encoder is monitored in real time during the same measurement operation, it is necessary to ensure the synchronization of data collection of each collaborative operation unit to ensure the accuracy and comparability of the data;

[0092] During real-time monitoring, an anomaly detection mechanism is set up; when a key performance parameter exceeds the preset threshold, the system will immediately issue an alarm, indicating that the encoder may have a problem or require maintenance.

[0093] In this step, by presetting a reasonable monitoring frequency, the performance changes of the absolute value hollow encoder during operation can be captured in real time, which helps to ensure the stable operation of the production line; during the monitoring process, special monitoring equipment or systems are used to collect the key performance parameters of each collaborative operation unit of the encoder in real time, ensuring the accuracy and reliability of the data, and providing a solid foundation for subsequent multi-dimensional comprehensive calculation and analysis; ensuring the synchronization of data collection of each collaborative operation unit, avoiding performance evaluation errors caused by data asynchrony; by setting an anomaly detection mechanism, when a key performance parameter exceeds the preset threshold, the system will immediately issue an alarm; it can timely detect possible problems or failures of the encoder, provide strong support for predictive maintenance, and help reduce production interruptions and losses caused by encoder failures; the real-time key performance parameter set obtained in this step is the basis for subsequent multi-dimensional comprehensive calculation and analysis; through the processing and analysis of these data, the overall performance of the encoder can be comprehensively evaluated, providing a scientific basis for optimizing production efficiency and formulating maintenance strategies.

[0094] S4. Using a pre-built unit performance evaluation model, perform multi-dimensional comprehensive calculations on each set of real-time key performance parameters to obtain a multi-dimensional performance index for each of the collaborative operation units;

[0095] The method for constructing the unit performance evaluation model includes:

[0096] Collect historical data of the encoder in actual operation, including the real-time key performance parameter set of each collaborative operation unit;

[0097] Preprocess the data to remove outliers and noise, ensure data quality, and perform normalization and standardization to ensure that all parameters are compared on the same scale;

[0098] Selecting a machine learning model as the basic architecture of the unit performance evaluation model. The machine learning model includes support vector machines, random forests, and neural networks, which can automatically learn the mapping relationship between input and output from a large amount of training data;

[0099] Divide the preprocessed historical data into training set and validation set;

[0100] Use the training set to train the unit performance evaluation model;

[0101] Validate the evaluation model using the validation set to assess its accuracy and reliability; repeat the validation and optimization process until the model meets the performance requirements;

[0102] Apply the constructed evaluation model to the actual encoder performance evaluation;

[0103] The mathematical formula for calculating the multidimensional performance index of the unit performance evaluation model is:

[0104]

[0105] Among them, P i represents the multidimensional performance index of the i-th collaborative operation unit, w ij represents the weight of the jth key performance parameter, x ij represents the jth KPP value after normalization, and n is the number of KPPs.

[0106] In this step, by constructing a unit performance evaluation model and performing multi-dimensional comprehensive calculations on the real-time key performance parameter sets of each collaborative operation unit, the performance of the absolute value hollow encoder can be evaluated more finely; not only the basic performance indicators of the encoder are considered, but also the synergy between its internal units and the impact of the external environment on the encoder performance are covered, thereby more accurately reflecting the actual working status of the encoder; when constructing the unit performance evaluation model, the quality and comparability of the data are ensured by collecting historical data of the encoder in actual operation and performing preprocessing, normalization and standardization; at the same time, the machine learning model is selected as the basic architecture of the evaluation model, which can be obtained from a large amount of training data. The mapping relationship between input and output is automatically learned from the data, which further improves the accuracy of the evaluation. When the actual encoder performance is evaluated using the constructed evaluation model, the key performance parameters of each collaborative operation unit can be monitored in real time, and a multi-dimensional performance index can be quickly calculated. This helps to promptly detect encoder performance anomalies and provide strong support for predictive maintenance and optimization of overall production efficiency. Through the training and optimization of the machine learning model, the unit performance evaluation model can adapt to the performance evaluation requirements of different working environments and encoder models. This step realizes the refinement, accuracy and real-time monitoring of the absolute value hollow encoder performance by constructing a unit performance evaluation model and performing multi-dimensional comprehensive calculations.

[0107] S5. Considering the service life of the absolute value hollow encoder and the working environment conditions of the location, respectively correct the multidimensional performance index of each of the collaborative operation units to obtain a multidimensional performance correction index of each of the collaborative operation units;

[0108] Accurately capture the encoder's service life, i.e., the time span since the encoder was put into use, using an internal timer or an external maintenance recording system. Utilize a sensor network or remote monitoring system to collect real-time operating environment parameters, such as temperature, humidity, vibration, and electromagnetic interference, at the encoder's location. These parameters can fully reflect the state of the encoder's operating environment.

[0109] The collected working environment parameters are compared with the preset thresholds to identify parameters that exceed the normal range, i.e., exceedance parameters. For each exceedance parameter, the degree to which it exceeds the threshold, i.e., exceedance amplitude, is calculated to accurately quantify the impact of the exceedance parameter on the encoder performance.

[0110] Performing comprehensive calculation on the set of parameters exceeding the working environment standard to obtain a working environment impact coefficient;

[0111] Conduct statistical analysis on the relationship between encoder service life and performance degradation to determine the extent to which service life affects encoder performance. Based on the statistical analysis results, determine the specific value of the service life impact coefficient; this coefficient should be able to reflect the performance degradation of the encoder caused by long-term use.

[0112] Construct a correction formula for the multidimensional performance index, which should be able to simultaneously consider the impact of the working environment influence coefficient and the service time influence coefficient on the multidimensional performance index; substitute the working environment influence coefficient and the service time influence coefficient into the correction formula, and perform correction calculations on the multidimensional performance index of each collaborative operation unit to obtain a multidimensional performance correction index;

[0113] The multidimensional performance index is corrected and calculated, and the calculation formula for the multidimensional performance correction index is obtained as follows:

[0114] P t =P i ×(1+α·(EIC-1))×(1+β·(LIF-1))

[0115] Among them, P t represents the multidimensional performance correction index; P i represents the multidimensional performance index; EIC represents the working environment influence coefficient; LIF represents the service time influence coefficient; α and β represent adjustment coefficients, which are used to control the degree of influence of working environment and service time on the performance index.

[0116] This step considers the encoder's service life and operating environment to more comprehensively evaluate the encoder's actual performance. Service life and operating environment are important factors affecting encoder performance. This step introduces the service life and operating environment impact coefficients to correct the multidimensional performance index, thereby improving the accuracy of the performance evaluation. Accurate performance evaluation results help to promptly identify potential encoder failure risks. By analyzing the multidimensional performance correction index, the encoder's remaining life and possible performance degradation trends can be predicted, allowing proactive maintenance or replacement measures to avoid unexpected failures and production losses. As a key component in industrial automation and precision machinery systems, the performance of the encoder directly affects the operating efficiency and stability of the entire system. By accurately evaluating the encoder's performance status, this step can guide system optimization and upgrades, improving production efficiency and quality. By real-time monitoring and correcting the encoder's performance index, potential performance issues can be promptly identified and resolved, thereby enhancing the reliability and stability of the entire system. The multidimensional performance correction index can provide decision support for equipment managers. Based on these indices, maintenance plans, procurement strategies, and system upgrade plans can be formulated to maximize the encoder's service life and optimize its performance.

[0117] S6. Based on a preset weight coefficient, weight calculation is performed on the multidimensional performance correction index of each of the collaborative operation units to obtain a multidimensional performance comprehensive index of the absolute value hollow encoder;

[0118] The factors affecting the setting of the preset weight coefficient include:

[0119] Functional criticality: Different cooperating units play different key roles in the overall function of the encoder. For example, the position detection unit directly determines the position feedback accuracy of the encoder, so its weight may be relatively high.

[0120] Fault impact: The impact of a failure in a cooperating unit on the entire encoder system is also a factor that needs to be considered when setting weights. The unit with the greater fault impact usually has a higher weight.

[0121] Parameter stability: Some performance parameters are more susceptible to fluctuations due to external environmental or internal factors. The weights of the collaborative operation units corresponding to sensitive parameters need to be appropriately adjusted to reflect their instability in actual operation.

[0122] Impact of parameters on overall performance: The degree to which a change in a performance parameter affects the overall performance of the encoder. The greater the impact of a parameter, the higher the weight of the corresponding collaborative operation unit.

[0123] Harshness of the working environment: The harsher the working environment of the encoder, the higher the weight of certain collaborative operation units needs to be to reflect their importance in this environment;

[0124] Service life: As service time increases, some performance parameters of the encoder will gradually degrade. Therefore, when setting weights, it is necessary to consider the impact of service life on the performance of each collaborative operation unit and adjust the weights accordingly.

[0125] System requirements: The specific requirements of the system in which the encoder is located will affect the weighting of different collaborative operation units. In systems that require high-precision position feedback, the weight of the position detection unit will be higher.

[0126] Maintenance strategy: Different maintenance strategies will also affect the setting of weight coefficients; preventive maintenance focuses more on the early detection and treatment of potential faults, so the weight of collaborative operation units related to fault prediction and diagnosis will be higher.

[0127] In this step, by introducing preset weight coefficients, this step can comprehensively consider multiple factors such as the key role of different collaborative operation units in the overall function realization of the encoder, the impact of faults, parameter stability, the impact of parameters on overall performance, the severity of the working environment, service time, system requirements and maintenance strategies, so as to achieve a comprehensive and integrated evaluation of the encoder performance; it helps to more accurately reflect the actual working status and performance level of the encoder; the multi-dimensional performance comprehensive index as the output result of this step provides equipment management personnel with a more intuitive and quantitative performance evaluation indicator; based on this indicator, managers can more scientifically formulate maintenance plans, procurement strategies and system upgrade plans, etc., to maximize the service life of the encoder and optimize its performance; through the comprehensive evaluation of this step, potential fault risks of the encoder can be discovered in time, thereby providing Measures are taken for maintenance or replacement before the encoder fails; compared with traditional post-fault maintenance, it can significantly reduce production interruptions and losses caused by encoder failure, and improve maintenance efficiency and production efficiency; this step can timely discover the deficiencies and bottlenecks of existing technologies by comprehensively evaluating the multi-dimensional performance of the encoder, thereby promoting technological innovation and upgrading; through the comprehensive evaluation and optimization of this step, it can ensure that the encoder is always kept in the best working state, thereby enhancing the reliability and stability of the entire system; this step obtains the multi-dimensional performance comprehensive index of the absolute value hollow encoder by introducing a preset weight coefficient to perform weight calculation on the multi-dimensional performance correction index of each collaborative operation unit; this step not only improves the comprehensive evaluation capability of the encoder, but also brings significant beneficial effects in optimizing decision support, improving maintenance efficiency, promoting technological innovation and upgrading, and enhancing system reliability.

[0128] S7. Mapping the corresponding absolute value hollow encoder performance evaluation result in a pre-established encoder performance comparison space according to the multi-dimensional performance comprehensive index;

[0129] The method for constructing the encoder performance comparison space includes:

[0130] Based on the structure, function and working principle of the absolute value hollow encoder, the main dimensions that affect the encoder performance are determined. For each dimension, specific performance indicators are further refined. The dimensions that affect the encoder performance include accuracy, reliability, real-time performance, environmental adaptability, etc.

[0131] Collect historical test, monitoring, and maintenance records of encoders; ensure that the data covers encoder performance in different working environments, different service times, and different working conditions;

[0132] Clean and organize the collected historical data, remove outliers and invalid data, and standardize the data to ensure comparability between different dimensions;

[0133] Using statistics, machine learning, or data mining techniques, an encoder performance mapping model is constructed based on the processed historical data;

[0134] According to the application scenario and performance requirements of the encoder, set the performance threshold of each dimension and indicator. The threshold serves as the basis for judging whether the encoder performance is normal.

[0135] The encoder performance mapping model, performance thresholds and related performance indicators are integrated to form an encoder performance comparison space.

[0136] In this step, by constructing an encoder performance comparison space and mapping the multi-dimensional performance comprehensive index to the space, an accurate evaluation of the absolute value hollow encoder performance can be achieved; not only the basic performance indicators of the encoder are considered, but also the synergy between the various units inside the encoder and the impact of the external environment on the encoder performance are comprehensively considered, thereby improving the accuracy and comprehensiveness of the evaluation results; the encoder performance comparison space has a visual interface, which can intuitively display the performance status of the encoder in the form of charts, data points, etc.; this enables equipment managers or maintenance personnel to quickly understand the current performance level of the encoder, facilitate timely detection of performance anomalies or degradation trends, and take corresponding maintenance measures or optimization strategies; by setting performance thresholds for each dimension and indicator, the encoder performance comparison space can Real-time monitoring and early warning of encoder performance are achieved; when a performance indicator of the encoder approaches or exceeds the threshold, the system will issue an alarm in time to prompt the management personnel to perform maintenance or replacement; it can significantly reduce production interruptions and losses caused by encoder failures; in the process of constructing and applying the encoder performance comparison space, the performance data and maintenance experience of the encoder will be continuously accumulated; it can provide strong support for the continuous improvement of encoder technology; accurate encoder performance evaluation and predictive maintenance can ensure that the encoder is always kept in the best working condition, thereby improving production efficiency and product quality; this step realizes the accurate evaluation, intuitive display, predictive maintenance and continuous improvement of the absolute value hollow encoder performance by constructing the encoder performance comparison space and mapping the multi-dimensional performance comprehensive index, which can improve production efficiency and quality.

[0137] Example 2: Figure 3 As shown, the absolute value hollow encoder performance evaluation system based on real-time feedback of the present invention specifically includes the following modules;

[0138] A unit division module, based on the structural function of the absolute value hollow encoder, divides the absolute value hollow encoder into multiple cooperative operation units; the cooperative operation units include a signal processing unit, a position detection unit and a communication interface unit;

[0139] a performance parameter definition module, for determining a key performance parameter set of each of the collaborative operation units based on the working type of each of the collaborative operation units; the key performance parameter set of the signal processing unit includes signal strength, signal-to-noise ratio, signal frequency, signal processing delay, and error rate; the key performance parameter set of the position detection unit includes resolution, repeatability, zero offset error, and position conversion accuracy; the key performance parameter set of the communication interface unit includes data transmission rate, bit error rate, connection stability, data communication delay, and data transmission integrity;

[0140] A real-time monitoring module, which monitors the absolute hollow encoder in real time during a same measurement operation according to a preset monitoring frequency and the key performance parameter set, and obtains a real-time key performance parameter set of each of the collaborative operation units;

[0141] The unit performance evaluation module uses a pre-built unit performance evaluation model to perform multi-dimensional comprehensive calculations on each set of real-time key performance parameters to obtain a multi-dimensional performance index for each of the collaborative operation units;

[0142] a performance correction module, which takes into account the service life of the absolute value hollow encoder and the working environment status of the location, and performs correction processing on the multidimensional performance index of each of the collaborative operation units to obtain the multidimensional performance correction index of each of the collaborative operation units;

[0143] A weight calculation module performs weight calculation on the multidimensional performance correction index of each of the collaborative operation units based on a preset weight coefficient to obtain a comprehensive multidimensional performance index of the absolute value hollow encoder;

[0144] The performance evaluation result mapping module maps the corresponding absolute value hollow encoder performance evaluation result in a pre-built encoder performance comparison space according to the multi-dimensional performance comprehensive index.

[0145] The system divides the encoder into multiple collaborative operating units through the unit division module and defines a set of key performance parameters for each unit. It can penetrate into each component of the encoder to more accurately reflect its actual working status.

[0146] The real-time monitoring module can monitor the various collaborative operation units of the encoder in real time according to the preset monitoring frequency, and obtain key performance parameters in a timely manner. It helps to promptly discover possible problems with the encoder and take corresponding maintenance measures;

[0147] The unit performance evaluation module uses a multi-dimensional comprehensive calculation model to process each set of real-time key performance parameters to obtain a multi-dimensional performance index; it can more comprehensively reflect the performance status of the encoder and avoid the one-sidedness of single indicator evaluation;

[0148] The performance correction module takes into account the impact of the encoder's service life and working environment on performance, and corrects the multi-dimensional performance index. This improves the accuracy and adaptability of the evaluation results, making them more reflective of the encoder's actual performance in the current working environment.

[0149] The weight calculation module calculates the multi-dimensional performance correction index of each collaborative operation unit based on the preset weight coefficient to obtain a multi-dimensional performance comprehensive index. This can more accurately reflect the overall performance level of the encoder and provide strong support for optimizing overall production efficiency.

[0150] The performance evaluation result mapping module maps the corresponding performance evaluation results in the pre-built encoder performance comparison space, making the evaluation results more intuitive and easy to understand, allowing technicians to quickly judge and analyze the performance status of the encoder;

[0151] In summary, the absolute value hollow encoder performance evaluation system based on real-time feedback not only solves the limitations of existing evaluation methods, but also improves the accuracy and practicality of encoder performance evaluation.

[0152] The various variations and specific embodiments of the absolute value hollow encoder performance evaluation method based on real-time feedback in the aforementioned embodiment 1 are also applicable to the absolute value hollow encoder performance evaluation system based on real-time feedback in this embodiment. Through the aforementioned detailed description of the absolute value hollow encoder performance evaluation method based on real-time feedback, those skilled in the art can clearly understand the implementation method of the absolute value hollow encoder performance evaluation system based on real-time feedback in this embodiment, so for the sake of brevity of the specification, it will not be described in detail here.

[0153] In addition, the present application also provides an electronic device, including a bus, a transceiver, a memory, a processor, and a computer program stored in the memory and runnable on the processor. The transceiver, the memory, and the processor are respectively connected via a bus. When the computer program is executed by the processor, each process of the above-mentioned method embodiment for controlling output data is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be described here.

[0154] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for evaluating the performance of an absolute value hollow encoder based on real-time feedback, characterized in that: The method comprises: Based on the structural function of the absolute value hollow encoder, the absolute value hollow encoder is divided into multiple cooperative operation units; the cooperative operation units include a signal processing unit, a position detection unit and a communication interface unit; Determine the key performance parameter set of each collaborative operation unit based on the working type of each collaborative operation unit; the key performance parameter set of the signal processing unit includes signal strength, signal-to-noise ratio, signal frequency, signal processing delay, and error rate; the key performance parameter set of the position detection unit includes resolution, repeatability, zero offset error, and position conversion accuracy; the key performance parameter set of the communication interface unit includes data transmission rate, bit error rate, connection stability, data communication delay, and data transmission integrity; According to the preset monitoring frequency and the key performance parameter set, in the same measurement operation, the absolute hollow encoder is monitored in real time to obtain the real-time key performance parameter set; Using the pre-built unit performance evaluation model, multi-dimensional comprehensive calculations are performed on each set of real-time key performance parameters to obtain a multi-dimensional performance index; Taking into account the service life of the absolute value hollow encoder and the working environment conditions of the location, each of the multidimensional performance indices is corrected to obtain multiple multidimensional performance correction indices; Based on the preset weight coefficients, each multidimensional performance correction index is weighted to obtain a multidimensional performance comprehensive index; According to the multi-dimensional performance comprehensive index, the corresponding absolute value hollow encoder performance evaluation result is mapped in the pre-built encoder performance comparison space.

2. The absolute value hollow encoder performance evaluation method based on real-time feedback according to claim 1, characterized in that: Considering the service life of the absolute hollow encoder and the working environment conditions of the location, each of the multi-dimensional performance indices is calibrated separately, including: Obtain the service life of the absolute hollow encoder and the working environment parameter information of its location; Identifying parameters exceeding the standard on the working environment parameter information, and calculating the exceeding range, to obtain a working environment exceeding standard parameter set; the working environment exceeding standard parameter set includes the exceeding ranges of all exceeding standard parameters; Performing comprehensive calculation on the set of parameters exceeding the working environment standard to obtain a working environment impact coefficient; Statistically analyze the service life of the absolute hollow encoder and the pre-set standard working time to obtain the service life influence coefficient; The working environment influence coefficient and the service time influence coefficient are used to simultaneously correct the multidimensional performance index and obtain the multidimensional performance correction index.

3. The absolute value hollow encoder performance evaluation method based on real-time feedback according to claim 2, characterized in that: The multidimensional performance index is corrected and calculated, and the calculation formula for the multidimensional performance correction index is obtained as follows: ； Among them, P t represents the multidimensional performance correction index; P i represents the multidimensional performance index; EIC represents the working environment influence coefficient; LIF represents the service time influence coefficient; α and β represent adjustment coefficients, which are used to control the degree of influence of working environment and service time on the performance index.

4. The absolute value hollow encoder performance evaluation method based on real-time feedback according to claim 1, characterized in that: The factors affecting the setting of the preset weight coefficient include functional criticality, fault impact, parameter stability, parameter impact on overall performance, harshness of the working environment, service time, system requirements and maintenance strategy.

5. The absolute value hollow encoder performance evaluation method based on real-time feedback according to claim 1, characterized in that: The method for constructing the encoder performance comparison space includes: According to the structure, function and working principle of the absolute hollow encoder, the main dimensions that affect the encoder performance are determined, and for each dimension, the performance indicators are further refined; Collect historical test, monitoring and maintenance record data for encoders; Clean and organize the collected historical data, remove outliers and invalid data, and standardize the data; Building an encoder performance mapping model based on the processed historical data; Set performance thresholds for each dimension and indicator based on the encoder's application scenarios and performance requirements; The encoder performance mapping model, performance thresholds and related performance indicators are integrated to form an encoder performance comparison space.

6. A performance evaluation system for absolute hollow encoder based on real-time feedback, characterized in that: The system comprises: A unit division module, based on the structural function of the absolute value hollow encoder, divides the absolute value hollow encoder into multiple cooperative operation units; the cooperative operation units include a signal processing unit, a position detection unit and a communication interface unit; a performance parameter definition module, for determining a key performance parameter set of each of the collaborative operation units based on the working type of each of the collaborative operation units; the key performance parameter set of the signal processing unit includes signal strength, signal-to-noise ratio, signal frequency, signal processing delay, and error rate; the key performance parameter set of the position detection unit includes resolution, repeatability, zero offset error, and position conversion accuracy; the key performance parameter set of the communication interface unit includes data transmission rate, bit error rate, connection stability, data communication delay, and data transmission integrity; A real-time monitoring module, which monitors the absolute hollow encoder in real time during a same measurement operation according to a preset monitoring frequency and the key performance parameter set, and obtains a real-time key performance parameter set of each of the collaborative operation units; The unit performance evaluation module uses a pre-built unit performance evaluation model to perform multi-dimensional comprehensive calculations on each set of real-time key performance parameters to obtain a multi-dimensional performance index for each of the collaborative operation units; a performance correction module, which takes into account the service life of the absolute value hollow encoder and the working environment status of the location, and performs correction processing on the multidimensional performance index of each of the collaborative operation units to obtain the multidimensional performance correction index of each of the collaborative operation units; A weight calculation module performs weight calculation on the multidimensional performance correction index of each of the collaborative operation units based on a preset weight coefficient to obtain a multidimensional performance comprehensive index of the absolute value hollow encoder; The performance evaluation result mapping module maps the corresponding absolute value hollow encoder performance evaluation result in a pre-built encoder performance comparison space according to the multi-dimensional performance comprehensive index.

7. An electronic device for evaluating the performance of an absolute value hollow encoder based on real-time feedback, comprising a bus, a transceiver, a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the transceiver, the memory, and the processor are connected via the bus, and characterized in that: When the computer program is executed by the processor, the steps of the method according to any one of claims 1 to 5 are implemented.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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