Design manufacturing and service full life cycle management method oriented to equipment intrinsic safety

Abstract

The invention relates to the technical field of mechanical engineering and structural safety, and provides a design manufacturing and service full life cycle management method oriented to equipment intrinsic safety, and the method comprises the steps: reducing the damage accumulation from the source through introducing a damage mode in a design stage; in the manufacturing stage, the interlayer temperature in the welding process is controlled by regulating and controlling welding heat input parameters and the forming technology, then the expected grain size is obtained, and welding manufacturing with the strength-toughness collaborative improvement of a welded joint and the service life reliability as the benchmark is achieved; in the service stage, reliable detection of micro-damage and micro-defects is achieved through nonlinear ultrasonic micro-damage detection; according to the method, the defects of regular design, empirical manufacturing and passive operation and maintenance in the whole life cycle of traditional equipment are overcome, an intrinsically safe guarantee mechanism is formed, the equipment is promoted to achieve conversion from passive maintenance to active prevention, the reliability of the whole life cycle of the equipment is improved, and therefore long-period continuous production of the equipment is guaranteed.

Description

Technical Field

[0001] This invention relates to the technical field of mechanical engineering and structural safety, and in particular to a design, manufacturing, and service life-cycle management method for equipment with inherent safety. Background Technology

[0002] Industries such as petrochemicals, aerospace, shipbuilding, and nuclear / thermal power widely rely on various engineering equipment to support their core processes or achieve critical functions. As applications evolve towards high-speed, heavy-load, extreme-temperature, and long-life service conditions, the operating conditions of equipment are becoming increasingly complex and demanding, placing higher requirements on structural safety and reliability. Furthermore, welding, a common joining method in industry, inevitably introduces welding defects during manufacturing, creating localized structural weaknesses. In the event of a destructive accident, this often leads to significant economic losses. Therefore, fundamentally improving the inherent safety and reliability of the structure remains crucial for engineering equipment.

[0003] Currently, mainstream engineering practices still rely on static strength theory for equipment design, manufacturing, and maintenance, employing empirical analogies and reactive maintenance. This approach fails to fully reveal the complex damage evolution mechanisms and diverse failure modes during equipment service. This passive safety approach, based on planned maintenance and reactive remediation, coupled with traditional technical systems, leads to excessive or insufficient safety margins in the design process, low lifespan reliability of welded structures during manufacturing, and difficulty in detecting early damage and micro-defects during inspection and maintenance. The interaction of these factors not only makes it difficult to substantially control potential risks but also results in overly redundant design and high maintenance costs, hindering the development of larger, longer-lasting, and more reliable equipment. The inherent lack of safety has become a bottleneck restricting the improvement of engineering equipment quality and reliability.

[0004] To address the aforementioned issues, it is imperative for those skilled in the art to design a lifecycle management method that spans the entire design, manufacturing, and service life, comprehensively considering the impact of damage and complex failure modes, thus providing a new solution for ensuring the inherent safety of large-scale engineering equipment. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention provides a method for the design, manufacturing, and service life-cycle management of equipment with inherent safety as its core objective. The management method includes:

[0006] Design phase:

[0007] (11) Identify the damage modes of key components of mechanical equipment based on the operating conditions and material types of the equipment. For example, if the steady-state operating temperature of the mechanical equipment exceeds the creep initiation temperature, creep damage is considered to exist; if the mechanical equipment is subjected to cyclic loads, fatigue damage is considered to exist; if it is used in special environments such as hydrogen, high-temperature steam, or irradiation, hydrogen embrittlement, stress corrosion, or irradiation embrittlement damage is considered to exist. In the actual service process of equipment, damage modes often exhibit the characteristics of multiple mechanisms coexisting and coupled. Therefore, it is necessary to comprehensively consider the operating status of the equipment and systematically identify various possible damage modes.

[0008] Operating conditions include operating temperature, presence of cyclic loads, and characteristics of the medium environment;

[0009] (12) Based on the determined damage mode, establish a constitutive model that incorporates the damage mode, and on this basis set the corresponding failure criteria and derive the allowable lifetime value.

[0010] (13) Based on damage mode and failure criteria, establish a composite design curve with multiple criteria;

[0011] (14) Based on the composite design curve, the equipment designed according to the rules is optimized and evaluated to obtain the final design scheme of the mechanical equipment.

[0012] Manufacturing stage:

[0013] (21) Based on the relationship between microstructure and properties, welding process parameters were determined through numerical simulation; welding process parameters include heat input Q (unit kJ / mm) and preheating temperature T. pre Interlayer temperature T inter / Welding speed (mm / s), shielding gas flow rate (L / min), welding current (A), welding voltage (V);

[0014] Service phase:

[0015] (31) Quantitative damage D is obtained using nonlinear ultrasound;

[0016] (32) Based on the obtained quantized damage D and critical damage D C Comparison: If the quantified damage D is less than the critical damage D C If it is not in normal service, it will continue to serve normally; otherwise, an early warning will be issued and maintenance or replacement will be arranged immediately.

[0017] During the operation phase:

[0018] (41) Record the operating data and failure information of mechanical equipment, and correct the constitutive model and composite design curve by feeding it back to the design stage. Improve the organizational and performance relationship model in the manufacturing stage to form a closed loop.

[0019] Further, the specific steps of step (12) are as follows: select a constitutive model that can reflect the material degradation behavior, determine the relevant parameters in the constitutive model, establish a constitutive model that considers damage evolution, fit the constitutive model parameters through experimental data, set the failure criterion, and infer the theoretical lifetime by combining the constitutive model, thereby obtaining the allowable lifetime value. If creep damage is identified, time-related creep constitutive relations, such as the Norton-Bailey model, can be used to describe the strain evolution behavior of the material under long-term high-temperature loads.

[0020] If fatigue damage is identified, SN curves and ε-N curves under cyclic loading can be used for life assessment.

[0021] Failure criteria include creep life end point and fatigue life limit; failure criteria vary depending on the damage mode.

[0022] Furthermore, the specific steps of step (13) are as follows:

[0023] First, determine the design parameter coordinate system. Based on the constitutive model and failure criterion of each damage mode, draw the limit curve in the selected coordinate system. Take the most stringent limit value as the design constraint of the point, forming a region that meets the safety requirements under all damage modes. This region is the multi-criteria composite safety zone.

[0024] Based on damage modes and failure criteria, design curves corresponding to single criteria are established, and the physical quantity dimensions of each criterion are normalized to unify them to a common scale. The design curves of each criterion are superimposed or enveloped in the same design parameter coordinate system, and the area enclosed by the envelope curves is taken as the design safety zone that satisfies multiple criterion constraints, thus forming a composite design curve.

[0025] Furthermore, based on the envelope, linear matching technology is used to perform linear interpolation or weighted combination of two or more failure mode constraint functions in a certain region or transition zone to ensure the continuity of the curve or to make its transition smooth.

[0026] Furthermore, the specific steps of step (14) are as follows:

[0027] The working parameters of key components in the preliminary design are mapped to the coordinate system corresponding to the composite design curve. It is determined whether the design point falls within the envelope curve. If it falls within the envelope curve, it means that the design meets the safety requirements for all damage modes under the current working conditions. Otherwise, the over-limit parts are optimized and adjusted. After modifying the relevant parameters, iterative verification is performed until the design points corresponding to all dominant risk modes fall into the composite safety zone, and the final design scheme of the equipment is obtained.

[0028] Furthermore, the specific steps of step (21) are as follows:

[0029] Welded specimens were prepared using representative materials, and the quantitative microstructure parameters and corresponding performance indicators were summarized using specimen testing techniques. The quantitative microstructure parameters included grain size, precipitates, grain boundary angles, dislocation density, phase composition, inclusion size / location, texture, and hardness. The performance indicators included yield strength, tensile strength, elongation after fracture, impact energy, and reduction of area.

[0030] A microstructure-property relationship model is established using regression analysis, data fitting, or machine learning techniques to support the optimization design. The temperature-dependent thermophysical properties and phase transformation kinetic parameters of the material are imported into simulation software. Welding heat input parameters are set to simulate the temperature field during weld progression, and a finite element model is established. Grain growth is simulated under a set temperature history to obtain microstructure information of the weld zone and heat-affected zone. A creep subroutine is used to calculate the stress and strain evolution during welding and cooling stages to obtain the residual stress field, acquiring microstructure information and residual stress distribution results corresponding to each welding process parameter. Based on the microstructure-property relationship and the process-microstructure and residual stress distribution relationship, the process parameters are iteratively optimized with the goal of synergistic regulation of welded structure strength and toughness and control of residual stress to determine the welding process parameters.

[0031] Furthermore, the specific steps of step (31) are as follows:

[0032] Nonlinear ultrasonic nondestructive testing (NDT) technology is employed to periodically inspect key areas (weld zone, stress concentration zone, and heat-affected zone) to achieve early identification and quantitative assessment of micro-damage. This allows for predictive maintenance guidance through damage evolution trend analysis. High-frequency ultrasonic transducers are deployed in relevant areas of the structure under test to receive returned ultrasonic excitation signals. Analog-to-digital conversion (ADC) is used to obtain time-domain signal data. A fast Fourier transform (FFT) of the signal in the time domain is then performed to obtain the amplitude-frequency response curve in the frequency domain. From this curve, the amplitude A1 at the fundamental frequency f and the amplitude A2 at the second harmonic 2f are identified. Damage quantification is then performed using the nonlinear coefficient β = A2 / A1. Before testing, baseline calibration is performed on the test area, and the acquired baseline signal is used... As a signal reference; data is acquired under the same coupling conditions during each detection. Record the nonlinear coefficient β curr and through β corr =β curr -β base Eliminate baseline bias; reduce the change in nonlinear coefficient β corr Substitute into the pre-established damage variable mapping relationship D = f nl (β corr ), thus obtaining the change in nonlinear coefficient β corr The corresponding quantized damage D, where, β baseThese are the fundamental amplitude, second harmonic amplitude, and nonlinear coefficients acquired under non-destructive conditions. β curr These are the fundamental amplitude, second harmonic amplitude, and nonlinear coefficient collected during testing in service.

[0033] The mapping relationship can be established through statistical analysis or machine learning methods on experimental or simulation results, and this patent does not limit this.

[0034] Furthermore, the specific steps of step (41) are as follows:

[0035] Through sensors and operation logs, environmental data and operating conditions are recorded during equipment operation, forming multi-source time-series data during service. The operating data and maintenance / failure logs are written into the database according to a preset format for management, and fed back to the design and manufacturing stages for model and process correction. Among them, environmental data includes temperature, humidity, and pressure; operating conditions include load spectrum and number of start-stop cycles.

[0036] During the design phase, the allowable lifetime value corresponding to the damage mode derived from step (12) is compared with the actual failure cycle, and the corresponding criteria are selected according to different damage modes. If the predicted value deviates significantly from the measured value, the model parameters in the constitutive model are adjusted by Bayesian correction and other methods. Based on the corrected constitutive model, the composite design curve is updated.

[0037] During the manufacturing stage, the microstructure information of the field-failed samples and their corresponding process parameters are used as inputs to perform a weighted correction on the microstructure-property relationship model. This correction is applied to the original microstructure-property relationship model g. 0 Based on (x), a correction increment Δg(x) is introduced to construct a new tissue-performance relationship model g. (*) (x):

[0038] g (*) (x)=(1-ω)g (0) (x)+ω[g (0) (x)+Δg(x)]

[0039] Where ω is the update weight, ω∈[0,1];

[0040] The introduction of sample data drives the continuous correction and optimization of the model, which gradually converges to the actual organization-performance correlation. Through data feedback and model updates, the closed loop of each stage is completed.

[0041] The present invention has the following beneficial effects:

[0042] (1) In view of the inherent safety requirements of equipment, this invention adopts damage-based optimization design, reliability-based welding manufacturing, high-precision damage detection during service and data feedback communication at each stage to build a closed-loop technical system.

[0043] (2) This invention introduces damage modes during the design phase to slow down damage accumulation from the source, thus supplementing the traditional static strength-based design method.

[0044] (3) In the manufacturing stage, the present invention controls the interpass temperature during the welding process by adjusting the welding heat input parameters and forming process, thereby obtaining the desired grain size and realizing welding manufacturing based on the synergistic improvement of the strength and toughness of the welded joint and the reliability of its life.

[0045] (4) During the service phase, the present invention achieves reliable detection of micro-damage and micro-defects through nonlinear ultrasonic micro-damage detection, and provides timely early warning or prevention of cracks and damage in the early stage, thereby effectively preventing crack propagation.

[0046] (5) This invention improves the shortcomings of rule design, experience manufacturing and passive operation and maintenance in the entire life cycle of traditional equipment, forms an inherent safety guarantee mechanism, promotes the transformation of equipment from passive maintenance to active prevention, improves the reliability of equipment throughout its entire life cycle, and thus ensures long-term continuous production of equipment. Attached Figure Description

[0047] Figure 1 This is a flowchart of the management method in this invention.

[0048] Figure 2 It is a closed-loop diagram of the entire life cycle of design, manufacturing, and service. Detailed Implementation

[0049] The technical solution of the present invention will be further described in detail below with reference to specific embodiments. However, these embodiments are not intended to limit the present invention. Any similar structures and similar variations of the present invention should be included in the protection scope of the present invention. The commas in the present invention all indicate the relationship between and. The English letters in the present invention are case-sensitive.

[0050] like Figure 1-2 As shown, this invention provides a design, manufacturing, and service life-cycle management method for equipment with inherent safety, the management method comprising:

[0051] Design phase:

[0052] S11 identifies damage modes of key components of mechanical equipment based on operating conditions and material types. For example, if the steady-state operating temperature of the equipment exceeds the creep initiation temperature, creep damage is considered to exist; if the equipment is subjected to cyclic loads, fatigue damage is considered to exist; if it operates in special environments such as hydrogen, high-temperature steam, or irradiation, hydrogen embrittlement, stress corrosion, or irradiation embrittlement damage is considered to exist. During actual service, damage modes often exhibit the characteristics of multiple mechanisms coexisting and coupled, therefore, it is necessary to comprehensively consider the equipment's operating status and systematically identify all possible damage modes.

[0053] Operating conditions include operating temperature, presence of cyclic loads, and characteristics of the medium environment;

[0054] For example, common materials for petrochemical equipment include Cr-Mo steel and austenitic steel. By analyzing the service conditions they face, it is determined that the equipment suffers from creep-fatigue damage because the operating temperature is higher than the material's creep initiation temperature and there is cyclic load.

[0055] S12. Based on the determined damage modes, a constitutive model incorporating the damage modes is established. Based on this, corresponding failure criteria are set, and the allowable lifetime value is derived. A constitutive model that can reflect the material degradation behavior is selected, and relevant parameters in the constitutive model are determined. A constitutive model considering damage evolution is established. The parameters of the constitutive model are fitted using experimental data, failure criteria are set, and the theoretical lifetime is inferred from the constitutive model to obtain the allowable lifetime value. For example, a critical strain amplitude or critical damage Dc is set. Based on the constitutive equation, when the obtained damage is greater than the critical damage Dc, or the strain amplitude is greater than the critical strain amplitude, failure is determined, thus deriving the allowable lifetime value.

[0056] If creep damage is identified, time-dependent creep constitutive relations, such as the Norton-Bailey model, can be used to describe the strain evolution behavior of the material under long-term high-temperature loading. If fatigue damage is identified, SN curves and ε-N curves under cyclic loading can be introduced for life assessment. The constitutive model should be selected based on the identified damage mode, combined with specific service conditions, material behavior, and analysis requirements. Failure criteria include creep life endpoint and fatigue life limit; failure criteria vary depending on the damage mode.

[0057] Taking low-cycle fatigue damage as an example, the constitutive model chosen is the Coffin-Manson formula:

[0058]

[0059] In the formula, ε a ε is the total strain amplitude; e ε p These represent the elastic and plastic strain amplitudes, respectively; σ′ fIt is the fatigue strength coefficient, approximately equal to the true fracture stress under static tension of the material, in MPa; ε′ f It is the fatigue ductility coefficient, approximately equal to the true fracture strain of the material under static tension; E is the elastic modulus, in MPa; N f σ′ represents the allowable fatigue life, expressed in cycles; b is the fatigue strength index; and c is the fatigue ductility index. The model parameters σ′ are fitted using low-cycle fatigue experimental data. f ,ε′ f After b and c, the low-cycle fatigue failure strain amplitude ε is set. a,fail Substituting into the constitutive equation, we obtain the allowable fatigue life N. f Define low-cycle fatigue damage When low-cycle fatigue damage D f ≥D c Failure is determined to occur at that time. The critical damage D is among them. c The value is typically set to 1, but can be adjusted based on actual engineering conditions if necessary. By establishing constitutive models and failure criteria for different damage modes, support is provided for the subsequent development of composite design curves.

[0060] S13, Based on damage modes and failure criteria, establish a composite design curve with multiple criteria;

[0061] First, determine the design parameter coordinate system. Based on the constitutive model and failure criterion of each damage mode, draw the limit curve in the selected coordinate system. Take the most stringent limit value as the design constraint of the point, forming a region that meets the safety requirements under all damage modes. This region is the multi-criteria composite safety zone.

[0062] Based on damage modes and failure criteria, design curves corresponding to individual criteria are established. The physical quantities of each criterion are normalized to unify them to a common scale. The design curves of each criterion are superimposed or enveloped in the same design parameter coordinate system. The region enclosed by the envelope curves is taken as the design safety zone that satisfies multiple criterion constraints, thus forming a composite design curve. Based on the envelope, linear matching technology is used to perform linear interpolation or weighted combination of two or more failure mode constraint functions in a certain region or transition zone to ensure the continuity of the curve or to make its transition smooth.

[0063] S14, based on the composite design curve, optimize and evaluate the equipment designed according to the rules to obtain the final design scheme of the mechanical equipment;

[0064] The working parameters of key components in the preliminary design are mapped to the coordinate system corresponding to the composite design curve. It is determined whether the design point falls within the envelope curve. If it falls within the envelope curve, it means that the design meets the safety requirements for all damage modes under the current working conditions. Otherwise, the over-limit parts are optimized and adjusted. After modifying the relevant parameters, iterative verification is performed until the design points corresponding to all dominant risk modes fall into the composite safety zone, and the final design scheme of the equipment is obtained.

[0065] Manufacturing stage:

[0066] S21. Based on the relationship between microstructure and properties, welding process parameters were determined through numerical simulation. These parameters included heat input Q (unit: kJ / mm) and preheating temperature T. pre and interlayer temperature T inter / Welding speed (mm / s), shielding gas flow rate (L / min), welding current (A), welding voltage (V);

[0067] Welded specimens were prepared using representative materials, and the quantitative microstructure parameters and corresponding performance indicators were summarized using specimen testing techniques. The quantitative microstructure parameters included grain size, precipitates, grain boundary angles, dislocation density, phase composition, inclusion size / location, texture, and hardness. The performance indicators included yield strength, tensile strength, elongation after fracture, impact energy, and reduction of area.

[0068] A microstructure-property relationship model is established using regression analysis, data fitting, or machine learning techniques to support the optimization design. The temperature-dependent thermophysical properties and phase transformation kinetic parameters of the material are imported into simulation software. Welding heat input parameters are set to simulate the temperature field during weld progression, and a finite element model is established. Grain growth is simulated under a set temperature history to obtain microstructure information of the weld zone and heat-affected zone. A creep subroutine is used to calculate the stress and strain evolution during welding and cooling stages to obtain the residual stress field, acquiring microstructure information and residual stress distribution results corresponding to each welding process parameter. Based on the microstructure-property relationship and the process-microstructure and residual stress distribution relationship, the process parameters are iteratively optimized with the goal of synergistic regulation of welded structure strength and toughness and control of residual stress to determine the welding process parameters.

[0069] During the finite element simulation analysis, the data is continuously converted between the main program and subroutines of the ABAQUS software. The main program is responsible for providing the current values ​​to the subroutines, which then perform calculations based on the written constitutive equations. After iterating over the Jacobian matrix, stress tensor, and some state variables, the data is transmitted back to the main program. The main program then calculates the current values ​​based on the received data and outputs them, and so on.

[0070] Its specific workflow is as follows: in t nIn equilibrium, the main program transmits the total stress and total strain data of each element point of the current material to the subroutine and sets the time change Δt. The subroutine receives the data, calculates the magnitude of the total strain increment, solves for the magnitude of the total stress increment using the constitutive equation, and iteratively transmits the stress tensor back to the main program. The main program then updates the total strain and other parameters based on the returned variables. Finally, the process is repeated, but if the maximum number of iterations (16) of the ABAQUS software is exceeded, Δt will be halved and the loop will restart. During the execution, equilibrium checks are also performed repeatedly to determine whether the structure meets the equilibrium conditions. If it does, the current calculation ends; otherwise, the loop continues.

[0071] Service phase:

[0072] S31, using nonlinear ultrasound to obtain quantitative damage D;

[0073] Nonlinear ultrasonic nondestructive testing (NDT) technology is employed to periodically inspect key areas (weld zone, stress concentration zone, and heat-affected zone) to achieve early identification and quantitative assessment of micro-damage. This allows for predictive maintenance guidance through damage evolution trend analysis. High-frequency ultrasonic transducers are deployed in relevant areas of the structure under test to receive returned ultrasonic excitation signals. Analog-to-digital conversion (ADC) is used to obtain time-domain signal data. A fast Fourier transform (FFT) of the signal in the time domain is then performed to obtain the amplitude-frequency response curve in the frequency domain. From this curve, the amplitude A1 at the fundamental frequency f and the amplitude A2 at the second harmonic 2f are identified. Damage quantification is then performed using the nonlinear coefficient β = A2 / A1. Before testing, baseline calibration is performed on the test area, and the acquired baseline signal is used... As a signal reference; data is acquired under the same coupling conditions during each detection. Record the nonlinear coefficient β curr and through β corr =β curr -β base Eliminate baseline bias; reduce the change in nonlinear coefficient β corr Substitute into the pre-established damage variable mapping relationship D = f nl (β corr ), thus obtaining the change in nonlinear coefficient β corr The corresponding quantized damage D, where, β base These are the fundamental amplitude, second harmonic amplitude, and nonlinear coefficients acquired under non-destructive conditions. β curr These are the fundamental amplitude, second harmonic amplitude, and nonlinear coefficient collected during testing in service.

[0074] The mapping relationship can be established through statistical analysis or machine learning methods on experimental or simulation results, and this patent does not limit this.

[0075] S32, based on the obtained quantized damage D and critical damage D C Comparison: If the quantified damage D is less than the critical damage D C If it is not in normal service, it will continue to serve normally; otherwise, an early warning will be issued and maintenance or replacement will be arranged immediately.

[0076] During the operation phase:

[0077] S41 records the operating data and failure information of mechanical equipment, and feeds it back to the design stage to correct the constitutive model and composite design curve. In the manufacturing stage, it improves the organizational and performance relationship model to form a closed loop.

[0078] Through sensors and operation logs, environmental data and operating conditions are recorded during equipment operation, forming multi-source time-series data during service. The operating data and maintenance / failure logs are written into the database according to a preset format for management, and fed back to the design and manufacturing stages for model and process correction. Among them, environmental data includes temperature, humidity, and pressure; operating conditions include load spectrum and number of start-stop cycles.

[0079] During the design phase, the allowable lifetime value corresponding to the damage mode derived from step S12 is compared with the actual failure period, and the corresponding criteria are selected according to different damage modes. If the predicted value deviates significantly from the measured value, the model parameters in the constitutive model are adjusted using methods such as Bayesian correction, and the composite design curve is updated based on the corrected constitutive model.

[0080] During the manufacturing stage, the microstructure information of the field-failed samples and their corresponding process parameters are used as inputs to perform a weighted correction on the microstructure-property relationship model. This correction is applied to the original microstructure-property relationship model g. 0 Based on (x), a correction increment Δg(x) is introduced to construct a new tissue-performance relationship model g. (*) (x):

[0081] g (*) (x)=(1-ω)g (0) (x)+ω[g (0) (x)+Δg(x)]

[0082] Where ω is the update weight, ω∈[0,1];

[0083] The introduction of sample data drives the continuous correction and optimization of the model, which gradually converges to the actual organization-performance correlation. Through data feedback and model updates, the closed loop of each stage is completed.

[0084] Damage-based optimization design fully considers various damage modes in actual service, effectively controlling the problem of excessive or insufficient safety margins in the design. Reliability-based welding manufacturing optimizes the microstructure and residual stress in the joint area, achieving a synergistic improvement in strength and toughness, and enhancing structural reliability. During service, nonlinear ultrasonic testing technology enables effective identification and response to micro-damage and early defects. The feedback and integration of data from each stage construct a closed-loop technical system, mitigating damage accumulation from the source, strengthening the inherent safety of equipment, promoting the transformation of operation and maintenance mode from passive maintenance to proactive prevention, and ensuring the long-term stable operation of equipment.

[0085] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

Claims

1. A method for the design, manufacturing, and service life-cycle management of equipment oriented towards intrinsic safety, characterized in that, The management method includes: Design phase: (11) Identify the damage modes of key components of mechanical equipment based on the operating conditions and material types of the mechanical equipment. The operating conditions include operating temperature, presence of cyclic load, and characteristics of the medium environment. (12) Based on the determined damage mode, establish a constitutive model that incorporates the damage mode, and on this basis set the corresponding failure criteria and derive the allowable lifetime value. (13) Based on damage mode and failure criteria, establish a composite design curve with multiple criteria; (14) Based on the composite design curve, the equipment designed according to the rules is optimized and evaluated to obtain the final design scheme of the mechanical equipment. Manufacturing stage: (21) Based on the relationship between microstructure and properties, welding process parameters are determined through numerical simulation; welding process parameters include heat input Q and preheating temperature T. pre and interlayer temperature T inter Welding speed, shielding gas flow rate, welding current, and welding voltage; Service phase: (31) Quantitative damage D is obtained using nonlinear ultrasound; (32) Based on the obtained quantized damage D and critical damage D C Comparison: If the quantified damage D is less than the critical damage D C If it is not in normal service, it will continue to serve normally; otherwise, an early warning will be issued and maintenance or replacement will be arranged immediately. During the operation phase: (41) Record the operating data and failure information of mechanical equipment, and correct the constitutive model and composite design curve by feeding it back to the design stage. Improve the organizational and performance relationship model in the manufacturing stage to form a closed loop.

2. The method for design, manufacturing, and service life management of equipment oriented towards intrinsic safety according to claim 1, characterized in that, The specific steps of step (12) are as follows: select a constitutive model that corresponds to the energy to reflect the material degradation behavior, determine the relevant parameters in the constitutive model, establish a constitutive model that considers damage evolution, fit the parameters of the constitutive model through experimental data, set the failure criteria, and combine the constitutive model to infer the theoretical lifetime, thereby obtaining the allowable lifetime value.

3. The method for design, manufacturing, and service life management of equipment oriented towards intrinsic safety according to claim 1, characterized in that, The specific steps of step (13) are as follows: First, determine the design parameter coordinate system. Based on the constitutive model and failure criterion of each damage mode, draw the limit curve in the selected coordinate system. Take the most stringent limit value as the design constraint of the point, forming a region that meets the safety requirements under all damage modes. This region is the multi-criteria composite safety zone. Based on damage modes and failure criteria, design curves corresponding to single criteria are established, and the physical quantity dimensions of each criterion are normalized to unify them to a common scale. The design curves of each criterion are superimposed or enveloped in the same design parameter coordinate system. The area enclosed by the envelope curves is taken as the design safety zone that satisfies multiple criterion constraints, thus forming a composite design curve.

4. The method for design, manufacturing, and service life management of equipment oriented towards intrinsic safety according to claim 3, characterized in that, Based on the envelope, linear matching technology is used to perform linear interpolation or weighted combination of two or more failure mode constraint functions in a certain region or transition zone to ensure the continuity of the curve or to make its transition smooth.

5. A method for design, manufacturing, and service life management of equipment oriented towards intrinsic safety, as described in claim 1, is characterized in that... The specific steps of step (14) are as follows: The working parameters of key components in the preliminary design are mapped to the coordinate system corresponding to the composite design curve. It is determined whether the design point falls within the envelope curve. If it falls within the envelope curve, it means that the design meets the safety requirements for all damage modes under the current working conditions. Otherwise, the over-limit parts are optimized and adjusted. After modifying the relevant parameters, iterative verification is performed until the design points corresponding to all dominant risk modes fall into the composite safety zone, and the final design scheme of the equipment is obtained.

6. The method for design, manufacturing, and service life management of equipment oriented towards intrinsic safety according to claim 1, characterized in that, The specific steps of step (21) are as follows: Welded specimens were prepared using representative materials, and the quantitative microstructure parameters and corresponding performance indicators were summarized using specimen testing techniques. The quantitative microstructure parameters included grain size, precipitates, grain boundary angles, dislocation density, phase composition, inclusion size / location, texture, and hardness. The performance indicators included yield strength, tensile strength, elongation after fracture, impact energy, and reduction of area. A microstructure-property relationship model is established using regression analysis, data fitting, or machine learning. Temperature-dependent thermophysical properties and phase transformation kinetic parameters of the material are imported into simulation software. Welding thermal input parameters are set to simulate the temperature field during weld progression. A finite element model is established to simulate grain growth under a set temperature history, obtaining microstructure information of the weld zone and heat-affected zone. A creep subroutine is used to calculate stress and strain evolution during welding and cooling stages, obtaining the residual stress field and acquiring microstructure information and residual stress distribution results corresponding to each welding process parameter. Based on the microstructure-property relationship and the process-microstructure and residual stress distribution relationship, the process parameters are iteratively optimized with the goal of synergistic regulation of welded structure strength and toughness and control of residual stress, thus determining the welding process parameters.

7. The method for design, manufacturing, and service life management of equipment oriented towards intrinsic safety according to claim 1, characterized in that, The specific steps of step (31) are as follows: Nonlinear ultrasonic nondestructive testing (NDT) technology is used to periodically inspect key components. High-frequency ultrasonic transducers are placed in relevant areas of the structure under test to receive the returned ultrasonic excitation signals. Analog-to-digital conversion is performed to obtain time-domain signal data. After a fast Fourier transform of the signal in the time domain, the amplitude-frequency characteristic curve in the frequency domain is obtained. From the amplitude-frequency characteristic curve, the amplitude A1 at the fundamental frequency f and the amplitude A2 at the second harmonic 2f are identified. Damage quantification is performed using the nonlinear coefficient β = A2 / A1. Before testing, baseline calibration is performed on the test area, and the acquired baseline signal is used... As a signal reference; data is acquired under the same coupling conditions during each detection. Record the nonlinear coefficient β curr and through β corr =β curr -β base Eliminate baseline bias; reduce the change in nonlinear coefficient β corr Substitute into the pre-established damage variable mapping relationship D = f nl (β corr ), thus obtaining the change in nonlinear coefficient β corr The corresponding quantized damage D, where, β base These are the fundamental amplitude, second harmonic amplitude, and nonlinear coefficients acquired under non-destructive conditions. β curr These are the fundamental amplitude, second harmonic amplitude, and nonlinear coefficient collected during testing in service.

8. The method for design, manufacturing, and service life management of equipment oriented towards intrinsic safety according to claim 1, characterized in that, The specific steps of step (41) are as follows: Through sensors and operation logs, environmental data and operating conditions are recorded during equipment operation, forming multi-source time-series data during service. The operating data and maintenance / failure logs are written into the database according to a preset format for management, and fed back to the design and manufacturing stages for model and process correction. Among them, environmental data includes temperature, humidity, and pressure; operating conditions include load spectrum and number of start-stop cycles. During the design phase, the allowable lifetime value corresponding to the damage mode derived from step (12) is compared with the actual failure cycle, and the corresponding criteria are selected according to different damage modes. If the predicted value deviates significantly from the measured value, the model parameters in the constitutive model are adjusted by Bayesian correction and other methods. Based on the corrected constitutive model, the composite design curve is updated. During the manufacturing stage, the microstructure information of the field-failed samples and their corresponding process parameters are used as inputs to perform a weighted correction on the microstructure-property relationship model. This correction is applied to the original microstructure-property relationship model g. 0 Based on (x), a correction increment Δg(x) is introduced to construct a new tissue-performance relationship model g. (*) (x): g (*) (x)=(1-ω)g (0) (x)+ω[g (0) (x)+Δg(x)] Where ω is the update weight, ω∈[0,1].

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