Equipment failure analysis method based on coupling mechanism of equipment function and hardware performance

Abstract

Embodiments of the present invention provide a device failure analysis method, apparatus, and storage medium based on a mechanism for coupling device functions with hardware performance. The method includes: performing structural and functional analysis on a target device to obtain a characteristic description, and determining the target device's coupling relationship units based on the characteristic description; establishing a FRAM model based on the upstream and downstream relationships of the coupling relationship units to determine the coupling relationship between the target device's functions and hardware performance; determining the unit variability of the coupling relationship units from two dimensions: hardware performance degradation and functional output accuracy, using the analytic hierarchy process; determining the coupling loss degree of the coupling relationship units based on the unit variability, structural entropy, and frequency entropy; and assessing the target device's failure risk based on the coupling loss degree. This method effectively assesses the failure risk of the device.

Description

Technical Field

[0001] The present invention relates to the field of equipment failure analysis methods, and in particular to an equipment failure analysis method based on a coupling mechanism between equipment functions and hardware performance. Background Art

[0002] Studying equipment failure modes, diagnosing the causes of malfunctions, and quantifying the risk of hardware performance degradation to device functionality are all crucial for improving equipment reliability. Hardware materials and structural connections degrade over time, leading to a decrease in hardware structural performance and, ultimately, hardware failures, ultimately causing system malfunctions. With the continuous development of manufacturing equipment and the increasing complexity of equipment systems, there is a coupled variation between device functionality and hardware performance, and faults are emergent.

[0003] Existing fault analysis tools mainly include fault tree analysis and failure mode and effects analysis. These fault analysis methods mainly use hardware analysis or functional analysis, which are out of touch with actual work and have low practicality. Summary of the Invention

[0004] The purpose of the embodiments of the present invention is to provide a device failure analysis method based on a device function and hardware performance coupling mechanism, which implements effective failure risk assessment for the device.

[0005] To achieve the above objectives, an embodiment of the present invention provides a device failure analysis method based on a device function and hardware performance coupling mechanism, the method comprising:

[0006] Performing structural analysis and functional analysis on the target device to obtain a feature description, and determining coupling relationship units of the target device based on the feature description;

[0007] Establishing a FRAM model according to the upstream and downstream relationships of the coupling relationship units, so as to determine the coupling relationship between the functions and hardware performance of the target device;

[0008] According to the hierarchical analysis method, the unit variability of the coupling relationship unit is determined from two dimensions: hardware performance degradation and function output accuracy;

[0009] Determining the coupling loss degree of the coupling relationship unit according to the unit variability, structural entropy and frequency entropy;

[0010] The failure risk of the target device is evaluated according to the coupling loss degree.

[0011] Optionally, the feature description includes input description, output description, premise description, resource description, time description and control description;

[0012] The input is described as the thing or condition that initiates the coupling relationship unit;

[0013] The output description is the output processing result of the operation of the coupling relationship unit;

[0014] The premise description is a necessary condition for the operation of the coupling relationship unit;

[0015] The resource description is the material or information required or consumed during the operation of the coupling relationship unit;

[0016] The time description is a time constraint for the operation of the coupling relationship units;

[0017] The control description is a method of monitoring and controlling the operation process of the coupling relationship units.

[0018] Optionally, establishing a FRAM model according to the upstream and downstream relationships of the coupling relationship units includes:

[0019] Determining a functional hexagon of the coupling relationship unit according to the feature description;

[0020] The functional hexagon connects the upstream unit and the downstream unit, and the output of the upstream unit serves as the feature description of the downstream unit;

[0021] A FRAM model is established based on the functional hexagons and their connected upstream and downstream units.

[0022] Optionally, the unit variability of the coupling relationship unit ,include:

[0023]

[0024] in, Score the change for degradation, ,

[0025] Score the change in accuracy, ,

[0026] is the relative weight of the degradation dimension,

[0027] is the relative weight of the precision dimension,

[0028] i is the i-th coupling relationship unit.

[0029] Optionally, the coupling loss degree of the coupling relationship unit is determined according to the unit variability, structural entropy and frequency entropy;

[0030]

[0031]

[0032] in, EC i is the entropy center, is the structural entropy, is the frequency entropy, i is the i-th coupling relationship unit,

[0033] is the first weight coefficient, is the second weight coefficient,

[0034] is the coupling loss, Unit variability.

[0035] Optionally, the structural entropy for:

[0036]

[0037] The frequency entropy

[0038]

[0039] Among them, M is the number of first-order neighbor nodes of the coupling relationship unit,

[0040] is the degree of the j-th node, is the degree of the kth node, is the influence of coupling relationship unit i on coupling relationship unit j, is the influence of coupling relationship unit i on coupling relationship unit k.

[0041] Optionally, the method further includes:

[0042] The degradation and precision discrete probabilities of the coupling relationship units in the FRAM model are corrected by using a hierarchical analysis method to determine the output changes of the coupling relationship units.

[0043] On the other hand, the present invention also proposes a device failure analysis device based on a device function and hardware performance coupling mechanism, the device comprising:

[0044] A first processing module is configured to perform structural analysis and functional analysis on a target device to obtain a feature description, and determine a coupling relationship unit of the target device according to the feature description;

[0045] A second processing module is used to establish a FRAM model according to the upstream and downstream relationships of the coupling relationship units, so as to determine the coupling relationship between the functions and hardware performance of the target device;

[0046] A third processing module is configured to determine the unit variability of the coupling relationship unit from two dimensions: hardware performance degradation and function output accuracy.

[0047] a fourth processing module, configured to determine a coupling loss degree of the coupling relationship unit according to the unit variability, structural entropy, and frequency entropy;

[0048] A fifth processing module is configured to evaluate the failure risk of the target device according to the coupling loss degree.

[0049] Optionally, establishing a FRAM model according to the upstream and downstream relationships of the coupling relationship units includes:

[0050] Determining a functional hexagon of the coupling relationship unit according to the feature description;

[0051] The functional hexagon connects the upstream unit and the downstream unit, and the output of the upstream unit serves as the feature description of the downstream unit;

[0052] A FRAM model is established based on the functional hexagons and their connected upstream and downstream units.

[0053] Optionally, the unit variability of the coupling relationship unit ,include:

[0054]

[0055] in, Score the change for degradation, ,

[0056] Score the change in accuracy, ,

[0057] is the relative weight of the degradation dimension,

[0058] is the relative weight of the precision dimension,

[0059] i is the i-th coupling relationship unit.

[0060] Optionally, the coupling loss degree of the coupling relationship unit is determined according to the unit variability, structural entropy and frequency entropy;

[0061]

[0062]

[0063] in, EC i is the entropy center, is the structural entropy, is the frequency entropy, i is the i-th coupling relationship unit,

[0064] is the first weight coefficient, is the second weight coefficient,

[0065] is the coupling loss, Unit variability.

[0066] On the other hand, the present invention also proposes a machine-readable storage medium, which stores instructions. When the instructions are executed by a processor, the processor is configured to execute the above-mentioned device failure analysis method based on the device function and hardware performance coupling mechanism.

[0067] The present invention's device failure analysis method, based on the coupling mechanism between device function and hardware performance, includes: performing structural and functional analysis on a target device to obtain a characteristic description, determining the target device's coupling relationship units based on the characteristic description; establishing a FRAM model based on the upstream and downstream relationships of the coupling relationship units to determine the coupling relationship between the target device's function and hardware performance; determining the unit variability of the coupling relationship units based on the two dimensions of hardware performance degradation and functional output accuracy using the analytic hierarchy process; determining the coupling loss degree of the coupling relationship units based on the unit variability, structural entropy, and frequency entropy; and assessing the failure risk of the target device based on the coupling loss degree. This method, based on the FRAM framework, considers the degradability of the device system, analyzes the coupling variation relationship between device function and hardware performance, establishes a relationship model between device function and hardware performance, and calculates the coupling loss degree based on information entropy, structural entropy, and frequency entropy, quantifying the impact of hardware performance degradation on device function. This method effectively assesses the failure risk of different devices.

[0068] Other features and advantages of the embodiments of the present invention will be described in detail in the subsequent detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] The accompanying drawings are used to provide a further understanding of the embodiments of the present invention and constitute a part of the specification. Together with the following detailed description, they are used to explain the embodiments of the present invention, but do not constitute a limitation of the embodiments of the present invention. In the accompanying drawings:

[0070] Figure 1 It is a flow chart of the device failure analysis method based on the device function and hardware performance coupling mechanism of the present invention;

[0071] Figure 2 Schematic diagram of the hexagonal characteristics of the coupling relationship unit of the present invention;

[0072] Figure 3 is a schematic diagram of a flow chart of embodiment 2 of the present invention;

[0073] Figure 4 1 is a schematic diagram of the probability of coupling relationship units changing according to the second embodiment of the present invention;

[0074] Figure 5 Schematic diagram of the relationship model between equipment functions and hardware performance of a steam turbine according to an embodiment of the present invention;

[0075] Figure 6 It is a schematic diagram of the device failure analysis device based on the device function and hardware performance coupling mechanism of the present invention.

[0076] Description of Reference Numerals

[0077] 100-Equipment failure analysis device based on the coupling mechanism of device function and hardware performance;

[0078] 200-first processing module;

[0079] 300-second processing module;

[0080] 400-third processing module;

[0081] 500-fourth processing module;

[0082] 600-Fifth processing module. DETAILED DESCRIPTION

[0083] The following describes the specific implementation of the embodiment of the present invention in detail with reference to the accompanying drawings. It should be understood that the specific implementation described herein is only used to illustrate and explain the embodiment of the present invention and is not used to limit the embodiment of the present invention.

[0084] It should be noted that the acquisition, transmission, storage, use, and processing of data in the technical solution of this application are in compliance with the relevant provisions of national laws and regulations. In the embodiments of this application, certain software, components, models, and other existing solutions in the industry may be mentioned. These should be considered as exemplary. Their purpose is only to illustrate the feasibility of implementing the technical solution of this application, but it does not mean that the applicant has or will necessarily use such solutions.

[0085] Example 1

[0086] Figure 1 FIG. 1 is a flow chart of a device failure analysis method based on the device function and hardware performance coupling mechanism of the present invention, as shown in FIG. Figure 1 As shown, a method for assessing equipment failure risk of the present invention includes:

[0087] Step S101 is to perform structural analysis and functional analysis on a target device to obtain a feature description, and determine coupling relationship units of the target device according to the feature description.

[0088] Specifically, the feature description includes input description, output description, premise description, resource description, time description and control description; the input description is the thing or condition that starts the coupling relationship unit; the output description is the output processing result of the coupling relationship unit; the premise description is the necessary condition for the operation of the coupling relationship unit; the resource description is the material or information required or consumed during the operation of the coupling relationship unit; the time description is the time sequence constraint of the operation of the coupling relationship unit; and the control description is the monitoring and control method of the operation process of the coupling relationship unit.

[0089] According to a specific implementation method, a structural and functional analysis of the target device is performed to determine all functions and supporting structures required for system operation. The structural and functional relationships between each device level are analyzed, the specific process of normal system operation is described, and coupling units are identified. Based on this, the coupling units are characterized from six aspects (i.e., input description, output description, premise description, resource description, time description, and control description) including input, output, premise, resource, time description, and control description. Input I represents the object or condition that activates the coupling unit; output O represents the output processing result of the coupling unit's operation; premise P represents the condition necessary for the coupling unit's operation, but does not directly activate the unit; resource R represents the materials or information required or consumed during the coupling unit's operation; time T represents the relevant temporal constraints of the coupling unit's operation; and control C represents the means of monitoring and controlling the coupling unit's operation.

[0090] Step S102 is to establish a FRAM model based on the upstream and downstream relationships of the coupling relationship units, so as to determine the coupling relationship between the function and hardware performance of the target device. The FRAM is a functional resonance analysis method.

[0091] The coupling relationship unit is the basis of the FRAM framework. The structural relationship and functional relationship of the target device give detailed transfer relationships of each hierarchical structure of the device to complete the given function. The hardware structure and system function of the device are defined as coupling relationship units, and the set of coupling relationship units is defined as F ={ f 1, f 2,…, f n}( F is a collection of coupling relationship units, f i is the coupling relationship unit, and n is the number of hardware and device functions).

[0092] According to a specific embodiment, establishing a FRAM model based on the upstream and downstream relationships of the coupling relationship units includes: determining a functional hexagon of the coupling relationship unit based on the feature description; the functional hexagon connects an upstream unit and a downstream unit, and the output of the upstream unit serves as a feature description of the downstream unit; and establishing a FRAM model based on the functional hexagon and the connected upstream and downstream units.

[0093] Based on the identification and description of the coupling relationship units, the FRAM method is used to consider the upstream and downstream relationships of the coupling relationship units, establish a FRAM framework, express the potential coupling relationship between the coupling relationship units, and complete the establishment of the coupling relationship between device functions and hardware performance.

[0094] Specifically, such as Figure 2 As shown, the coupling relationship unit uses a hexagonal graphical form to represent the six characteristics of the unit (capital letters represent the corresponding functional unit characteristics). After the unit identification and description are completed, the FRAM framework is established to represent the potential coupling relationship between the units. For any two units f i and f j The coupling relationship between them is defined as l ij , and define the coupling set as L ={ l ij |1≤ i ≤n,1≤ j ≤n}, where L is the set of coupling relationships between units, l ij For unit f i and f j The FRAM framework is based on the premise that each unit represents the hexagonal image. The output of the upstream unit can be used as the input, resource, control, premise or time feature description of the downstream unit and connect them. Assuming that the unit i and unit j Directly connected by edges, then l ij =1, otherwise l ij = 0. Then, the connection relationships between all units are constructed, and a model of the relationship between device functions and hardware performance based on FRAM is established. In the subsequent analysis process, the potential or actual coupling between each unit is determined by the specific description of the unit characteristics. The established model of the coupling relationship between device functions and hardware performance can be expressed as:

[0095]

[0096] in, Represented as a coupling relationship unit, Represented as any two units and The coupling relationship between Display unit Lead unit The weight of the failure.

[0097] Step S103 is to determine the unit variability of the coupling relationship unit from two dimensions of hardware performance degradation and function output accuracy according to the hierarchical analysis method.

[0098] According to a specific embodiment, the unit variability of the coupling relationship unit ,include:

[0099]

[0100] in, Score the change for degradation, , Score the change in accuracy ( Coupling relationship unit f i Deterioration change score, Coupling relationship unit f i Output accuracy change score), , is the relative weight of the degradation dimension, is the relative weight of the precision dimension, and i is the i-th coupling relationship unit.

[0101] Specifically, during the operation of the device, considering factors such as hardware performance degradation and functional stability, the present invention quantitatively describes the coupling relationship units from the aspects of time and accuracy, and uses the Analytic Hierarchy Process (AHP) to correct the discrete probability of changes in time and accuracy of each coupling relationship unit.

[0102] The FRAM framework identifies and describes the output changes of the unit from the perspectives of time and accuracy, including premature, timely, late, and non-occurrence in terms of time, and accurate, acceptable, and imprecise in terms of accuracy. During the operation of the equipment, the degradation of the hardware structure is a gradual process, including the state of good quality, the state of tolerance, the state of influence, and the state of failure, which can be respectively described as the changes of the coupling relationship unit in the time dimension. Coupling relationship unit f i Deterioration change scoring express, Indicates quality intact, acceptable, affected and faulty. Coupling relationship unit f i Output accuracy change express, Indicates precise, acceptable, and imprecise.

[0103] In order to give full play to the role of FRAM in equipment fault analysis and evaluation, make the fault analysis results more consistent with the actual operation of the equipment, and improve the pertinence and accuracy of equipment fault analysis and identification, the present invention adopts the Analytic Hierarchy Process (AHP) to correct the discrete probability of each FTAM unit in terms of degradation and accuracy, and characterize the possibility of different output changes in the coupling relationship unit. First, the importance of different factors is compared and assigned in the form of a judgment matrix. The scaling method of the judgment matrix is ​​shown in Table 1. Then calculate the relative weight, multiply each row element of the judgment matrix one by one, and calculate the nth root of the multiplication result according to the matrix order to obtain the corresponding eigenvector value. The eigenvector value of the degradation change dimension is expressed as :

[0104]

[0105] in, is the element in the tth row and jth column of the judgment matrix.

[0106] Table 1: Judgment Matrix Scaling Table

[0107]

[0108] Then the obtained eigenvector values ​​are normalized to obtain the relative weights of each change factor, which is expressed as:

[0109]

[0110] Finally, the variability of the coupling relationship unit is calculated , expressed as:

[0111]

[0112] in, is the relative weight of the degradation dimension, is the relative weight of the precision dimension. Coupling relationship unit f i variability.

[0113] Step S104 is to determine the coupling loss degree of the coupling relationship unit according to the unit variability, structural entropy and frequency entropy.

[0114] According to a specific embodiment, the coupling loss degree of the coupling relationship unit is determined based on the unit variability, structural entropy and frequency entropy;

[0115]

[0116]

[0117] in, EC i is the entropy center, is the structural entropy, is the frequency entropy, i is the i-th coupling relationship unit, is the first weight coefficient, is the second weight coefficient, is the coupling loss, Unit variability.

[0118] Specifically, the structural entropy for:

[0119]

[0120] The frequency entropy

[0121]

[0122] Among them, M is the number of first-order neighbor nodes of the coupling relationship unit,

[0123] is the degree of the j-th node, is the degree of the kth node, is the influence of coupling relationship unit i on coupling relationship unit j, is the influence of coupling relationship unit i on coupling relationship unit k.

[0124] According to a specific implementation method, the present invention defines the degree of the coupling relationship unit, and based on information entropy, evaluates the degree of the coupling relationship unit in the relationship model between device function and hardware performance from the two dimensions of structural entropy and frequency entropy, quantitatively describes the units that may have coupling effects during functional changes, and calculates the coupling loss degree of the coupling relationship unit. Based on the upstream and downstream relationship of the coupling relationship unit, the degree of the node is defined as DC i :

[0125]

[0126] in, l ij Represents coupling relationship unit fi Coupling relationship unit f j If the upstream coupling relationship unit is connected to the unit to be analyzed by a direct relationship, l ij is 1, otherwise l ij is 0.

[0127] According to the topological characteristics of the network, structural entropy is used Evaluate a given coupling relationship unit f i The influence or intensity of the position in the FRAM network on other coupling units or the entire network is expressed as:

[0128]

[0129] in, M Coupling relationship unit f i The number of first-order neighbor nodes.

[0130] Using the weight information contained between the coupling relationship units, the possibility Z Indicates the weight of the failure mode caused by the failure cause, To represent the set of weights, it indicates the influence of one coupling relationship unit on another coupling relationship unit. This paper uses frequency entropy Describes the effectiveness of the propagation of a given coupling relationship unit. That is, the larger the weight, the greater the probability of mutual influence between coupling relationship units, expressed as:

[0131]

[0132] Furthermore, the coupling relationship unit f i The entropy center is set to EC i , which can be expressed as:

[0133]

[0134] in, and is the weight coefficient of the equation, and ( is the first weight coefficient, is the second weight coefficient. According to experience, and is set to 0.4 and 0.6), under the condition of this particular parameter set, entropy-based centrality outperforms degree-based centrality and path-based centrality.

[0135] Finally, combine the coupling relationship unit f i Entropy Center EC i and coupling relationship units f i Unit variability , calculation coupling relationship unit f i The coupling loss , quantifying the relationship between device functionality and hardware performance:

[0136]

[0137] in, Coupling relationship unit f i The structural entropy of Coupling relationship unit f i The frequency entropy of .

[0138] Step S105 is to evaluate the failure risk of the target device according to the coupling loss degree.

[0139] By quantifying the changes in each unit during equipment operation and the transmission and coupling of changes between units, the possibility of unit coupling impact during equipment operation is analyzed, the equipment hardware structure or fault propagation link that is prone to unit coupling impact is identified and judged, and effective preventive measures are proposed.

[0140] This invention establishes a relationship model between device functions and hardware performance, and using FRAM as a framework, quantifies the variability of coupling relationship units and the coupling loss of coupling relationship units, completing the device fault analysis process that includes potential fault identification and risk quantification. Furthermore, this invention considers the degradability of the device system, analyzes the coupling variation relationship between device functions and hardware performance, and establishes a relationship model between device functions and hardware performance. Starting from information entropy, the coupling loss degree is calculated in combination with structural entropy and frequency entropy, quantifying the impact of hardware performance degradation on device functions. This invention has a certain degree of openness and practicality in practical applications, and is equally applicable to fault analysis entropies of different devices.

[0141] Example 2

[0142] This embodiment focuses on the typical functions and hardware structures of a steam turbine system, a water supply system, and a lubricating oil system of a steam turbine equipment, and performs fault analysis, as shown in Table 2.

[0143] Table 2: Failure Analysis

[0144]

[0145] like Figure 3 As shown, for this embodiment, the present invention performs the following steps to evaluate the fault:

[0146] Step 1: Identify and describe the coupling relationship units, conduct structural and functional analysis on the steam turbine equipment, and according to Table 2 above, determine that the function of the steam turbine body system is to convert the thermal energy of steam into mechanical energy, the function of the water supply system is to remove accumulated water, prevent water shock, and protect the blades, and the function of the lubricating oil system is lubrication, cooling, and cleaning. The typical hardware structure of the steam turbine body is the rotor, radial pads, thrust pads, bearings, and cylinders. The typical hardware structure of the water supply system is the drain manual valve and drain air control valve. The typical hardware structure of the lubrication system is the main oil tank, oil filter, and oil cooler. Define the coupling relationship unit f 1- f 13 Represent the turbine body, water supply system, lubrication system and typical hardware structures respectively. On this basis, each coupling relationship unit is characterized from six aspects: input I, output O, premise P, resource R, time T and control C (such as Figure 4 shown).

[0147] Step 2: Establish a relationship model between device functions and hardware performance: Figure 5 As shown, based on the identification and description of coupling relationship units, the FRAM method is used to consider the upstream and downstream relationships of the coupling relationship units, and a FRAM model is established to represent the potential coupling correlation between the coupling relationship units, thereby completing the relationship between device functions and hardware performance.

[0148] Step 3: Quantitative analysis of the variability of coupling relationship units: During the operation of the equipment, considering factors such as hardware performance degradation and functional stability, the coupling relationship units are quantitatively described from the two aspects of time and accuracy, and the hierarchical analysis method is used to correct the discrete probability of each coupling relationship unit changing in time and accuracy. Among them, considering that the hardware structure will deteriorate over time and the hardware performance will decrease accordingly, the probability of change in the time dimension of the coupling relationship unit is evaluated from the four stages of quality intact, tolerable, affected and faulty. The probability of change of the coupling relationship unit is shown in Table 3. Combined with the formula, the variability of the coupling relationship unit is obtained. f 4 and coupling relationship unit f 11 The high degree of variability indicates that attention should be paid to the hardware performance changes of the rotor and oil tank. When the system operates normally, the hardware structure corresponding to the above-mentioned coupling relationship unit is prone to failure, resulting in abnormal equipment function.

[0149] Table 3: Coupling relationship units

[0150]

[0151] Table 4: Coupling relationship unit variability

[0152]

[0153] Table 5: Coupling relationship unit loss

[0154]

[0155] Step 4: Quantitative analysis of coupling loss of coupling relationship units: Based on information entropy, the structural entropy and frequency entropy of each coupling relationship unit are calculated to quantitatively describe the units that may produce coupling effects during functional changes and calculate the coupling loss of coupling relationship units, as shown in Tables 3-5. f 4 and coupling relationship unit f 11 The coupling loss of the above units is much greater than that of other coupling relationship units, which means that the hardware structure corresponding to the above units is prone to coupling failure during the operation of the equipment, which has a great impact on the operation of the equipment and is likely to cause the function transmission link to be broken, affecting the function of the equipment.

[0156] Step 5: Analyze the risk of equipment failure: According to the quantitative changes of each unit and the transmission and coupling of changes between units during the operation of the equipment, find the coupling relationship units during the operation of the equipment. f 4 and coupling relationship unit f 11 Coupling effects are highly likely to occur. The rotor is prone to bending failure, which in turn causes the turbine bearings to vibrate with high intensity. Initially, this will increase wear on the turbine radial seal clearance and reduce the unit's economic efficiency. Further damage can lead to bearing wear and damage, cracks or even breakage in the shaft and blades, and serious accidents such as blade and partition damage and shaft bending. Ultimately, turbine vibration can reach tripping levels, causing malfunction. The frequency of rotor inspections and the accuracy of online monitoring should be increased, and preventive measures should be implemented to minimize the impact of hardware performance degradation on equipment function. The main oil tank is prone to oil leakage, which in turn makes it impossible to store lubricating oil, making it impossible to maintain a normal oil level in the main tank, triggering a low oil level alarm. In severe cases, this can cause bearing wear, oil shortages, and bearing burns, leading to malfunction of the turbine. The frequency of monitoring the main oil tank oil level should be increased, and preventive measures should be implemented promptly to minimize the impact of hardware performance degradation on equipment function.

[0157] Using this method, on-site personnel can comprehensively analyze equipment failures and accurately locate the hardware failures that lead to equipment malfunctions. Based on the quantitative analysis results provided by this method, appropriate preventative measures can be selected to address potential equipment malfunctions, ensuring safe and stable equipment operation.

[0158] Example 3

[0159] like Figure 6 As shown, the present invention also proposes a device failure analysis device 100 based on the device function and hardware performance coupling mechanism, which includes: a first processing module 200, used to perform structural analysis and functional analysis on the target device to obtain a feature description, and determine the coupling relationship unit of the target device according to the feature description; a second processing module 300, used to establish a FRAM model according to the upstream and downstream relationships of the coupling relationship unit, and used to determine the coupling relationship between the function and hardware performance of the target device; a third processing module 400, used to determine the unit variability of the coupling relationship unit from two dimensions of hardware performance degradation and functional output accuracy according to the hierarchical analysis method; a fourth processing module 500, used to determine the coupling loss degree of the coupling relationship unit according to the unit variability, structural entropy and frequency entropy; and a fifth processing module 600, used to evaluate the failure risk of the target device according to the coupling loss degree.

[0160] Specifically, establishing the FRAM model according to the upstream and downstream relationships of the coupling relationship units includes: determining a functional hexagon of the coupling relationship unit according to the feature description; the functional hexagon connects an upstream unit and a downstream unit, and the output of the upstream unit serves as a feature description of the downstream unit; and establishing the FRAM model according to the functional hexagon and the upstream and downstream units connected thereto.

[0161] Unit variability of the coupling relationship unit ,include:

[0162]

[0163] in, Score the change for degradation, , Score the change in accuracy, , is the relative weight of the degradation dimension, is the relative weight of the precision dimension, and i is the i-th coupling relationship unit.

[0164] Determining the coupling loss degree of the coupling relationship unit according to the unit variability, structural entropy and frequency entropy;

[0165]

[0166]

[0167] in, EC i is the entropy center, is the structural entropy, is the frequency entropy, i is the i-th coupling relationship unit, is the first weight coefficient, is the second weight coefficient, is the coupling loss, Unit variability.

[0168] This device, based on the FRAM framework, considers the degradation of device systems, analyzes the coupling variation between device functions and hardware performance, and establishes a relationship model between these two. Starting from information entropy, it combines structural entropy and frequency entropy to calculate the coupling loss degree, quantifying the impact of hardware performance degradation on device functions. This method enables effective failure risk assessment of different devices.

[0169] The present invention's device failure analysis method, based on the coupling mechanism between device function and hardware performance, includes: performing structural and functional analysis on a target device to obtain a characteristic description, determining the target device's coupling relationship units based on the characteristic description; establishing a FRAM model based on the upstream and downstream relationships of the coupling relationship units to determine the coupling relationship between the target device's function and hardware performance; determining the unit variability of the coupling relationship units based on the two dimensions of hardware performance degradation and functional output accuracy using the analytic hierarchy process; determining the coupling loss degree of the coupling relationship units based on the unit variability, structural entropy, and frequency entropy; and assessing the failure risk of the target device based on the coupling loss degree. This method, based on the FRAM framework, considers the degradability of the device system, analyzes the coupling variation relationship between device function and hardware performance, establishes a relationship model between device function and hardware performance, and calculates the coupling loss degree based on information entropy, structural entropy, and frequency entropy, quantifying the impact of hardware performance degradation on device function. This method effectively assesses the failure risk of different devices.

[0170] On the other hand, an embodiment of the present invention provides a storage medium having a program stored thereon, which, when executed by a processor, implements the device failure analysis method based on the device function and hardware performance coupling mechanism.

[0171] An embodiment of the present invention provides a processor, which is used to run a program, wherein the device failure analysis method based on the device function and hardware performance coupling mechanism is executed when the program is run.

[0172] An embodiment of the present invention provides a device comprising a processor, a memory, and a program stored in the memory and executable on the processor. When the processor executes the program, the following steps are implemented: structural and functional analysis of a target device is performed to obtain a characteristic description, and coupling relationship units of the target device are determined based on the characteristic description; a FRAM model is established based on the upstream and downstream relationships of the coupling relationship units to determine the coupling relationship between the functions and hardware performance of the target device; the unit variability of the coupling relationship units is determined based on the two dimensions of hardware performance degradation and functional output accuracy according to the hierarchical analysis method; the coupling loss degree of the coupling relationship units is determined based on the unit variability, structural entropy, and frequency entropy; and the failure risk of the target device is assessed based on the coupling loss degree. The device herein may be a server, PC, PAD, mobile phone, etc.

[0173] The present application also provides a computer program product, which, when executed on a data processing device, is suitable for executing an initialization program having the following method steps: performing structural analysis and functional analysis on a target device to obtain a feature description, and determining a coupling relationship unit of the target device based on the feature description; establishing a FRAM model based on the upstream and downstream relationship of the coupling relationship unit to determine the coupling relationship between the function and hardware performance of the target device; determining the unit variability of the coupling relationship unit from two dimensions of hardware performance degradation and functional output accuracy according to the hierarchical analysis method; determining the coupling loss degree of the coupling relationship unit based on the unit variability, structural entropy and frequency entropy; and evaluating the failure risk of the target device based on the coupling loss degree.

[0174] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0175] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0176] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0177] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0178] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0179] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0180] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can be implemented using any method or technology to store information. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change RAM (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices, or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media, such as modulated data signals and carrier waves.

[0181] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0182] The above are merely embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should all be included within the scope of the claims of the present application.

Claims

1. A device failure analysis method based on the coupling mechanism of device function and hardware performance, characterized in that: The method includes: Performing structural analysis and functional analysis on the target device to obtain a feature description, and determining coupling relationship units of the target device based on the feature description; Establishing a FRAM model according to the upstream and downstream relationships of the coupling relationship units, so as to determine the coupling relationship between the functions and hardware performance of the target device; According to the hierarchical analysis method, the unit variability of the coupling relationship unit is determined from two dimensions: hardware performance degradation and functional output accuracy. The degradation change score of the hardware performance degradation includes intact quality, tolerable, affected and faulty quality; Determining the coupling loss degree of the coupling relationship unit according to the unit variability, structural entropy and frequency entropy; evaluating a failure risk of the target device according to the coupling loss degree; Unit variability of the coupling relationship unit ,include: in, Score the change for degradation, , Score the change in accuracy, , is the relative weight of the degradation dimension, is the relative weight of the precision dimension, i is the i-th coupling relationship unit.

2. The method according to claim 1, characterized in that The feature description includes input description, output description, premise description, resource description, time description and control description; The input is described as the thing or condition that initiates the coupling relationship unit; The output description is the output processing result of the operation of the coupling relationship unit; The premise description is a necessary condition for the operation of the coupling relationship unit; The resource description is the material or information required or consumed during the operation of the coupling relationship unit; The time description is a time constraint for the operation of the coupling relationship units; The control description is a method of monitoring and controlling the operation process of the coupling relationship units.

3. The method according to claim 1, characterized in that The establishing of the FRAM model according to the upstream and downstream relationships of the coupling relationship units includes: Determining a functional hexagon of the coupling relationship unit according to the feature description; The functional hexagon connects the upstream unit and the downstream unit, and the output of the upstream unit serves as the feature description of the downstream unit; A FRAM model is established based on the functional hexagons and their connected upstream and downstream units.

4. The method according to claim 1, wherein Determining the coupling loss degree of the coupling relationship unit according to the unit variability, structural entropy and frequency entropy; in, EC i is the entropy center, is the structural entropy, is the frequency entropy, i is the i-th coupling relationship unit, is the first weight coefficient, is the second weight coefficient, is the coupling loss, Unit variability.

5. The method according to claim 4, characterized in that The structural entropy for: The frequency entropy Among them, M is the number of first-order neighbor nodes of the coupling relationship unit, is the degree of the j-th node, is the degree of the kth node, is the influence of coupling relationship unit i on coupling relationship unit j, is the influence of coupling relationship unit i on coupling relationship unit k.

6. The method according to claim 1, characterized in that The method further includes: The degradation and precision discrete probabilities of the coupling relationship units in the FRAM model are corrected by using a hierarchical analysis method to determine the output changes of the coupling relationship units.

7. A device failure analysis device based on the coupling mechanism of device function and hardware performance, characterized in that: The device includes: A first processing module is configured to perform structural analysis and functional analysis on a target device to obtain a feature description, and determine a coupling relationship unit of the target device according to the feature description; A second processing module is used to establish a FRAM model according to the upstream and downstream relationships of the coupling relationship units, so as to determine the coupling relationship between the functions and hardware performance of the target device; a third processing module, configured to determine, based on a hierarchical analysis method, the unit variability of the coupling relationship unit from two dimensions: hardware performance degradation and function output accuracy, wherein the degradation change score of the hardware performance degradation includes intact quality, tolerable quality, affected quality, and failure; Unit variability of the coupling relationship unit ,include: in, Score the change for degradation, , Score the change in accuracy, , is the relative weight of the degradation dimension, is the relative weight of the accuracy dimension, i is the i-th coupling relationship unit; a fourth processing module, configured to determine a coupling loss degree of the coupling relationship unit according to the unit variability, structural entropy, and frequency entropy; A fifth processing module is configured to evaluate the failure risk of the target device according to the coupling loss degree.

8. The device according to claim 7, characterized in that The establishing of the FRAM model according to the upstream and downstream relationships of the coupling relationship units includes: Determining a functional hexagon of the coupling relationship unit according to the feature description; The functional hexagon connects the upstream unit and the downstream unit, and the output of the upstream unit serves as the feature description of the downstream unit; A FRAM model is established based on the functional hexagons and their connected upstream and downstream units.

9. The device according to claim 7, characterized in that Determining the coupling loss degree of the coupling relationship unit according to the unit variability, structural entropy and frequency entropy; in, EC i is the entropy center, is the structural entropy, is the frequency entropy, i is the i-th coupling relationship unit, is the first weight coefficient, is the second weight coefficient, is the coupling loss, Unit variability.

10. A machine-readable storage medium having instructions stored thereon, characterized in that: When the instruction is executed by a processor, the processor is configured to execute the device failure analysis method based on the device function and hardware performance coupling mechanism according to any one of claims 1 to 6.

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