Diagnostic method for judging loose part of rotating equipment

Abstract

The invention relates to a diagnosis method for judging a loose part of rotating equipment. The diagnosis method comprises the following steps: (1) collecting vibration data; (2) spectrum characteristic analysis; (3) differential vibration testing; (4) positioning a loose part; and (5) dynamic verification and optimization. The device has the advantages that through multi-dimensional vibration data acquisition, vibration sensors are arranged at key parts such as motor feet, a bedplate and foundation bolts, vibration displacement values in the horizontal direction, the vertical direction and the axial direction are measured, multiple test points are divided to synchronously acquire data, and vibration information of rotating equipment can be comprehensively acquired. And combining frequency spectrum characteristic analysis and differential vibration comparison, comparing vibration displacement value differences of different hierarchical structures of the same part, and calculating a difference threshold value, so that the specific loose part of the A-type machine is accurately positioned, the limitation that accurate positioning is difficult to realize by traditional experience-dependent judgment or single vibration amplitude analysis is broken through, the blindness of maintenance is reduced, and the working efficiency is improved. The maintenance efficiency is improved.

Description

Technical Field

[0001] The invention relates to a diagnostic method for determining a loose part of a rotating device, and belongs to the technical field of mechanical fault diagnosis. Background Art

[0002] Rotating equipment such as steam turbines, generators, pumps, fans, coal mills, and air compressors are key equipment in manufacturing industries such as electricity, petrochemicals, and metallurgy. Failure of these equipment can lead to serious economic losses. Vibration is an important indicator for evaluating equipment reliability. Excessive vibration accounts for a large proportion of rotating equipment failures and is an important factor affecting the safe and stable operation of equipment. Its hazards are mainly manifested in three aspects: (1) Excessive vibration will cause bearing fatigue damage; (2) Excessive vibration will cause friction between the moving and static parts; (3) Excessive vibration will also cause equipment components to undergo large alternating stresses, causing damage to components such as rotors, connecting bolts, pipelines, and foundations.

[0003] During operation, rotating equipment often experiences excessive vibrations due to mechanical looseness, leading to equipment damage or shutdown. Type A mechanical looseness specifically refers to looseness caused by insufficient foundation stiffness or structural connection defects, such as insufficient table support stiffness, loose connections between components, etc. Traditional diagnostic methods mostly rely on empirical judgment or single vibration amplitude analysis, which makes it difficult to accurately locate the specific part of the looseness, resulting in multiple ineffective repairs. In the existing technology, although vibration spectrum analysis can identify loose frequency characteristics (such as 1X speed frequency), it lacks a systematic data comparison and positioning method. Therefore, there is an urgent need for a diagnostic method that combines multi-position vibration measurement, spectrum analysis and differential vibration comparison to improve the positioning accuracy of Type A mechanical looseness. Summary of the Invention

[0004] In order to overcome the defects of the prior art, the present invention provides a diagnostic method for determining the loose parts of rotating equipment. The technical solution of the present invention is:

[0005] A diagnostic method for determining a loose part of a rotating device comprises the following steps:

[0006] (1) Collect vibration data: Vibration sensors are placed at key locations on rotating equipment to simultaneously collect vibration signals in the horizontal, vertical, and axial directions.

[0007] (2) Spectral feature analysis: Perform spectrum analysis on the collected vibration signal to extract the vibration frequency components. If the 1X speed frequency dominates the spectrum and the vertical vibration amplitude is greater than the horizontal vibration amplitude, it is determined that there is mechanical looseness;

[0008] (3) Differential vibration test: Compare the difference in vibration displacement values ​​of different hierarchical structures at the same part. If the difference exceeds the preset threshold, it is determined that the connection has poor contact or insufficient stiffness;

[0009] (4) Locating loose parts: Through data comparison and tactile detection at multiple test points, identify the area with the largest vibration difference, and determine the specific loose parts based on the equipment structure drawings;

[0010] (5) Dynamic verification and optimization: Re-measure the vibration data after maintenance to verify whether the loose parts have been eliminated. If they reappear, use three-dimensional modeling or finite element analysis to optimize the structural design to ensure that the stiffness meets the requirements.

[0011] In the step (1), the key parts include the motor base, the platform and the anchor bolt positions, and the measurement area is divided into several test points, and data is collected synchronously at the several test points.

[0012] In the step (3), the preset threshold is: for two connecting parts with an elevation difference of less than 100 mm between the upper and lower measuring points, the difference in vibration displacement value is less than 20 μm.

[0013] In the step (4), the tactile detection is to sense the looseness of the connection part through tactile perception.

[0014] In the step (5), the structural optimization includes three-dimensional modeling or finite element analysis to modify the equipment design and ensure that the support stiffness meets the requirements.

[0015] In step (5), the specific steps of the three-dimensional modeling and stiffness analysis are as follows:

[0016] 5.1 Model construction

[0017] Data sources include:

[0018] Based on the original equipment design drawings; if the drawings are missing or incomplete, use 3D laser scanning or measurement tools to obtain the actual equipment geometry data;

[0019] Modeling tools: Use CAD software to create high-precision 3D models to restore the following areas: the contact surface between the table and the equipment footing; the distribution of anchor bolts and the area where preload forces act; and the connection structure between the frame and the concrete foundation.

[0020] Error control: The measurement data is filtered and calibrated to ensure that the error between the model and the actual object is less than ±1mm.

[0021] 5.2 Stiffness analysis

[0022] Static stiffness assessment: The equipment's deadweight and operating loads are simulated in the model, and the deformation of each connection is calculated. The displacement distribution of the table support area is monitored. If the displacement at any location exceeds 50 μm, the stiffness is determined to be insufficient.

[0023] Dynamic stiffness matching:

[0024] Combined with vibration test data, verify whether the model's natural frequency matches the measured spectrum; if the model's natural frequency deviation exceeds 5%, the material properties or boundary conditions need to be adjusted.

[0025] In step (5), the specific steps of the finite element analysis and parametric optimization are as follows:

[0026] 5.3 Load and boundary condition setting

[0027] Dynamic load: Input the actual operating parameters of the equipment and convert them into periodic force load;

[0028] Constraint conditions: The contact surface between the bottom of the platform and the concrete foundation is set as a fixed constraint; a pre-tightening force is applied to the anchor bolts to simulate the actual tightening state.

[0029] 5.4 Key simulation analysis types Modal analysis: Extract the first six natural frequencies and vibration modes of the structure to ensure that the separation degree from the equipment operating frequency is ≥20%;

[0030] If there is a risk of resonance, the structural stiffness needs to be adjusted;

[0031] Static analysis: Evaluate the stress distribution of the optimized structure under maximum load, requiring the maximum stress to be ≤ 60% of the material's yield strength. If the stress concentration area exceeds the threshold, add fillets or reinforced plates.

[0032] Transient dynamic analysis: Simulates the transient response of vibration amplitude during equipment startup / shutdown, requiring peak displacement ≤ 30μm; if the vibration exceeds the standard, optimize the damping structure.

[0033] 5.4 Parameterized Optimization Process

[0034] Optimization goal: Minimize the vibration displacement of key measuring points;

[0035] Design variables: number and spacing of anchor bolts; thickness of deck or addition of reinforcement ribs; cross-sectional shape of support frame;

[0036] Constraints: Total mass increase not exceeding 10%; manufacturing cost increase ≤ 15%;

[0037] Optimization algorithm: Use ANSYS Design Xplorer or Altair HyperStudy to perform multi-objective iterations and generate Pareto front solution sets.

[0038] The rotating equipment includes a steam turbine, a generator, a pump, a fan, a coal mill or an air compressor. The advantages of the present invention are:

[0039] 1. Accurately locate the fault location: Through multi-dimensional vibration data collection, including the placement of vibration sensors at key locations such as the motor foot, platform, and anchor bolts to measure vibration displacement in the horizontal, vertical, and axial directions, and the simultaneous data collection at multiple test points, comprehensive vibration information of the rotating equipment can be obtained. Combined with spectral feature analysis and differential vibration comparison, the vibration displacement values ​​of different hierarchical structures at the same location are compared, and the difference threshold is calculated to accurately locate the specific location of Type A mechanical looseness. This overcomes the limitations of traditional reliance on empirical judgment or single vibration amplitude analysis, reduces blindness in maintenance, and improves maintenance efficiency.

[0040] 2. Improve diagnostic reliability: Combining spectrum feature analysis with physical contact detection (the "hand-biting" phenomenon) allows for preliminary confirmation of Type A mechanical looseness based on spectrum analysis through tactile sensation. This makes diagnostic results more reliable, reduces the risk of misjudgment, and provides a more accurate basis for equipment maintenance and repair.

[0041] 3. Form a complete closed-loop process: Dynamic verification and optimization are introduced. Vibration data is remeasured after maintenance to verify that loose parts have been eliminated. If looseness recurs, 3D modeling or finite element analysis is used to optimize the structural design to ensure that stiffness meets requirements. This forms a closed-loop process of "diagnosis, treatment, and verification." This not only detects and locates faults, but also verifies and optimizes the treatment results, ensuring that the problem is completely resolved and effectively ensuring the long-term stable operation of the rotating equipment.

[0042] 4. Strong versatility in multiple industries: The present invention is suitable for locating mechanical loosening faults of rotating equipment in the electric power, chemical, metallurgical and other industries, covering a variety of key equipment such as steam turbines, generators, pumps, fans, coal mills, air compressors, etc. It has wide applicability and versatility, and can play an important role in the maintenance of rotating equipment in different industrial fields, providing strong support for equipment management in various industries.

[0043] 5. Combined with equipment structure analysis: After determining the specific loose location, analyze the root cause of the looseness in combination with the equipment structure drawings. In-depth exploration of the causes of mechanical looseness from the perspective of equipment design and structure will help to fundamentally solve the problem of mechanical looseness and prevent the recurrence of similar faults. It also provides a reference for equipment design improvement and optimization, and improves the overall reliability and stability of rotating equipment. DETAILED DESCRIPTION

[0044] The present invention will be further described below with reference to specific embodiments, and the advantages and features of the present invention will become clearer as the description proceeds. However, these embodiments are merely exemplary and do not constitute any limitation to the scope of the present invention. It should be understood by those skilled in the art that the details and forms of the technical solutions of the present invention may be modified or replaced without departing from the spirit and scope of the present invention, and such modifications and replacements fall within the scope of protection of the present invention.

[0045] The present invention relates to a diagnostic method for determining a loose part of a rotating device, comprising the following steps:

[0046] (1) Collect vibration data: Vibration sensors are placed at key locations on rotating equipment to simultaneously collect vibration signals in the horizontal, vertical, and axial directions.

[0047] (2) Spectral feature analysis: Perform spectrum analysis on the collected vibration signal to extract the vibration frequency components. If the 1X speed frequency dominates the spectrum and the vertical vibration amplitude is greater than the horizontal vibration amplitude, it is determined that there is mechanical looseness;

[0048] (3) Differential vibration test: Compare the difference in vibration displacement values ​​of different hierarchical structures at the same part. If the difference exceeds the preset threshold, it is determined that the connection has poor contact or insufficient stiffness;

[0049] (4) Locating loose parts: Through data comparison and tactile detection at multiple test points, identify the area with the largest vibration difference, and determine the specific loose parts based on the equipment structure drawings;

[0050] (5) Dynamic verification and optimization: Re-measure the vibration data after maintenance to verify whether the loose parts have been eliminated. If they reappear, use three-dimensional modeling or finite element analysis to optimize the structural design to ensure that the stiffness meets the requirements.

[0051] Based on the settings in the above steps, the following advantages are achieved:

[0052] Step (1) Collecting Vibration Data: Vibration sensors are placed at key locations on the rotating equipment to synchronously collect vibration signals in the horizontal, vertical, and axial directions. This allows for comprehensive acquisition of the equipment's vibration information, avoiding incomplete fault diagnosis caused by collecting vibration signals in only one direction. Data Reliability: High-precision vibration measurement tools are used to synchronously collect data to ensure that the collected vibration data is accurate and reliable, providing a solid foundation for subsequent analysis.

[0053] Step (2) Spectral Feature Analysis: By performing spectral analysis on the collected vibration signal and extracting the vibration frequency components, it is possible to quickly determine whether there is mechanical looseness. If the 1X speed frequency dominates the spectrum and the vertical vibration amplitude is greater than the horizontal vibration amplitude, it can be preliminarily determined that there is mechanical looseness, improving diagnostic efficiency.

[0054] Step (3) Differential vibration test: Compare the vibration displacement values ​​of different hierarchical structures in the same part (such as the equipment base and the table, the table and the frame, and the frame and the concrete), calculate the difference threshold, and accurately locate whether there is a problem of poor contact or insufficient rigidity at the connection. Generally speaking, if the elevation difference between two connecting parts is within 100mm above and below the measuring point, the vibration difference should be less than 20μm when the connection is tight. If the difference exceeds the threshold, it can be determined that there is poor contact or insufficient rigidity at the connection, which helps to further narrow the scope of the fault.

[0055] Step (4) Locating the loose parts: Combining the data comparison of multiple test points and tactile detection ("biting hand" phenomenon), not only can the area with the largest vibration difference be identified, but also the specific loose parts can be determined in combination with the equipment structure drawings, making the fault location more accurate and reducing the blindness of maintenance.

[0056] Step (5) Dynamic Verification and Optimization: After the inspection, re-measure the vibration data to verify whether the loose parts have been eliminated, forming a closed loop of "diagnosis-treatment-verification" to ensure that the problem is completely solved. If the looseness recurs, use 3D modeling or finite element analysis to optimize the structural design to ensure that the stiffness meets the requirements and prevent the fault from recurring at the root.

[0057] In the step (1), the key parts include the motor base, the platform and the anchor bolt positions, and the measurement area is divided into several test points, and data is collected synchronously at the several test points.

[0058] This step (1) pays attention to the motor base, platform and anchor bolt positions, which are key locations where rotating equipment is prone to loosening. By collecting vibration data from these key locations, the main support and connection points of the equipment can be effectively monitored, thereby improving the pertinence of fault diagnosis.

[0059] By dividing the measurement area into several test points and collecting data simultaneously, we can obtain vibration information from different parts of the equipment at the same time. This helps to more comprehensively understand the vibration status of the equipment, avoiding misjudgments caused by single-point measurement. It also enables more accurate analysis of the propagation and differences of vibration in different parts of the equipment, providing a richer and more accurate data foundation for subsequent fault location.

[0060] In the step (3), the preset threshold is: for two connecting parts with an elevation difference of less than 100 mm between the upper and lower measuring points, the difference in vibration displacement value is less than 20 μm.

[0061] A preset threshold of less than 20μm difference in vibration displacement between two connected components within a 100mm elevation difference at the measuring point provides a clear, quantitative standard for determining whether the connected components have poor contact or insufficient rigidity. This makes fault diagnosis more objective and accurate, reduces the subjectivity and uncertainty of human experience, and improves the reliability of diagnostic results.

[0062] In step (4), the tactile detection is to sense the looseness of the connection part through tactile perception. Combining tactile detection (sensing the looseness of the connection part through tactile perception) with multi-test point data comparison, traditional experience and modern vibration data analysis are combined. Tactile detection can provide an intuitive on-site experience, which can be verified with vibration data, further improving the accuracy and reliability of locating the loose part. In particular, for some minor looseness or situations that are difficult to directly judge through vibration data, tactile detection can provide additional diagnostic information.

[0063] In step (5), the structural optimization includes three-dimensional modeling or finite element analysis to correct the equipment design and ensure that the support stiffness meets the requirements; through structural optimization methods such as three-dimensional modeling or finite element analysis, the problem is corrected from the perspective of equipment design and structure to ensure that the support stiffness meets the requirements. This can not only solve the current loosening fault, but also prevent similar faults from happening again, improve the long-term stability and reliability of the equipment, and reduce repeated repairs and downtime caused by equipment loosening, which is of great significance to the long-term operation and maintenance of the equipment.

[0064] In step (5), the specific steps of the three-dimensional modeling and stiffness analysis are as follows:

[0065] 5.1 Model construction

[0066] Data sources include: Based on the original equipment design drawings (including the platform, anchor bolt layout, frame structure, etc.); if the drawings are missing or incomplete, use 3D laser scanning or measurement tools to obtain the actual equipment geometry data;

[0067] Modeling tools: Use CAD software to create high-precision 3D models to restore the following areas: the contact surface between the tabletop and the equipment footing; the distribution of anchor bolts and the area where preload forces act; and the connection structure between the frame and the concrete foundation.

[0068] Error control: The measurement data is filtered and calibrated to ensure that the error between the model and the actual object is less than ±1mm.

[0069] 5.2 Stiffness analysis

[0070] Static stiffness assessment: The equipment's own weight and operating loads (such as rotor weight and centrifugal force) are simulated in the model to calculate the deformation of each connection. The displacement distribution of the platen support area is monitored. If the displacement at any location exceeds 50 μm, the stiffness is determined to be insufficient.

[0071] Dynamic stiffness matching: Combined with vibration test data (such as 1X speed frequency amplitude), verify whether the model's natural frequency matches the measured spectrum. If the model's natural frequency deviation exceeds 5%, adjust the material properties or boundary conditions.

[0072] In step (5), the specific steps of the finite element analysis and parametric optimization are as follows:

[0073] 5.3 Load and boundary condition setting

[0074] Dynamic load: Input the actual operating parameters of the equipment (such as speed 3000 rpm, vibration amplitude 124 μm) and convert them into periodic force load;

[0075] Constraint conditions: The contact surface between the bottom of the platform and the concrete foundation is set as a fixed constraint; a pre-tightening force (e.g., 30 kN) is applied to the anchor bolts to simulate the actual tightening state.

[0076] 5.4 Key simulation analysis types Modal analysis: Extract the first six natural frequencies and vibration modes of the structure to ensure that the separation from the equipment operating frequency (e.g., 50 Hz) is ≥ 20%;

[0077] If there is a risk of resonance (e.g., the third-order frequency is 48 Hz), the structural stiffness needs to be adjusted;

[0078] Statics analysis:

[0079] Evaluate the stress distribution of the optimized structure under maximum load, requiring the maximum stress to be ≤ 60% of the material yield strength (e.g., for Q235 steel, the safety stress is ≤ 140 MPa);

[0080] If the stress concentration area (such as around the bolt hole) exceeds the threshold, add fillets or reinforcement plates;

[0081] Transient dynamics analysis:

[0082] Simulate the transient response of vibration amplitude during equipment startup / shutdown, requiring peak displacement ≤ 30μm;

[0083] If the vibration exceeds the standard, optimize the damping structure (such as adding rubber pads or hydraulic shock absorbers).

[0084] 5.4 Parameterized Optimization Process

[0085] Optimization goal: Minimize the vibration displacement of key measuring points (such as the vertical displacement of the southwest corner footing);

[0086] Design variables: number and spacing of anchor bolts (e.g., increasing from 4 to 6, and adjusting the spacing from 200 mm to 150 mm);

[0087] The thickness of the table top (such as increasing from 20mm to 25mm) or adding reinforcing ribs (10mm in height and 100mm in spacing); the cross-sectional shape of the supporting frame (such as changing the rectangular cross-section to an I-beam).

[0088] Constraints: Total mass increase not exceeding 10%; manufacturing cost increase ≤ 15%;

[0089] Optimization algorithm: Use ANSYS Design Xplorer or Altair HyperStudy to perform multi-objective iterations and generate Pareto front solution sets.

[0090] The rotating equipment includes a steam turbine, a generator, a pump, a fan, a coal mill or an air compressor. The working principle of the present invention is as follows:

[0091] This diagnostic method first arranges vibration sensors at the key parts of the rotating equipment (motor base, table, anchor bolts), and simultaneously collects horizontal, vertical, and axial vibration signals to fully obtain equipment vibration information. Perform spectrum analysis on the collected signals. If the 1X speed frequency dominates the spectrum and the vertical vibration amplitude is greater than the horizontal direction, it is preliminarily determined that there is mechanical looseness. Further compare the difference in vibration displacement values ​​of different hierarchical structures in the same part. If the difference exceeds the preset threshold (the difference in the upper and lower elevations of the measuring point is within 100mm, and the difference in vibration displacement values ​​is less than 20μm), it is determined that the connection has poor contact or insufficient stiffness. Combined with multi-test point data comparison and tactile detection, the area with the largest vibration difference is identified, and then the specific loose location is determined based on the equipment structure drawing. After maintenance, re-measure the vibration data to verify whether the looseness has been eliminated. If it recurs, optimize the structural design through three-dimensional modeling or finite element analysis to ensure that the stiffness meets the requirements, and finally form a complete closed loop to completely solve the problem of equipment looseness.

[0092] Based on the arrangement of the present invention, the following are achieved as a whole:

[0093] 1. Accurately locate faults: Integrating multi-dimensional vibration data collection, spectrum analysis, and differential vibration comparison, the system precisely pinpoints loose parts of machinery. This eliminates the limitations of traditional empirical judgment or single vibration amplitude analysis, reduces blind inspections, improves efficiency, and reduces labor and time costs.

[0094] 2. Efficient diagnostic process: Spectral feature analysis enables quick preliminary judgment, differential vibration testing accurately locates the fault point, and loose parts are located by combining multi-test point data comparison and tactile detection to determine the specific location. Dynamic verification and optimization form a closed loop to ensure diagnostic and processing efficiency, shorten equipment downtime, and reduce economic losses.

[0095] 3. Reliable optimized design: Dynamic verification and optimization uses 3D modeling or finite element analysis to verify and optimize the structural design, prevent recurrence of faults from the root, ensure long-term stable operation of the equipment, reduce maintenance costs, and extend equipment service life.

[0096] 4. Wide applicability: It is applicable to a variety of rotating equipment such as steam turbines, generators, pumps, fans, coal mills, air compressors, etc., covering multiple industries such as electricity, chemical industry, metallurgy, etc. It has strong versatility and provides strong support for the maintenance of rotating equipment in various industries.

[0097] 5. Data-driven decision-making: Collect a large amount of vibration data, combine spectrum feature analysis with differential vibration comparison, and provide reliable data support for equipment maintenance decisions, avoid blind decision-making, optimize maintenance processes, and improve equipment maintenance management level.

[0098] The above description is only a preferred specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with the technical field, within the technical scope disclosed by the present invention, who makes equivalent replacements or changes based on the technical solution and inventive concept of the present invention, should be covered by the scope of protection of the present invention.

Claims

1. A diagnostic method for determining the loose parts of rotating equipment, characterized in that: The following steps are involved: (1) Collect vibration data: Vibration sensors are placed at key locations on rotating equipment to simultaneously collect vibration signals in the horizontal, vertical, and axial directions. (2) Spectral feature analysis: Perform spectrum analysis on the collected vibration signal to extract the vibration frequency components. If the 1X speed frequency dominates the spectrum and the vertical vibration amplitude is greater than the horizontal vibration amplitude, it is determined that there is mechanical looseness; (3) Differential vibration test: Compare the difference in vibration displacement values ​​of different hierarchical structures at the same part. If the difference exceeds the preset threshold, it is determined that the connection has poor contact or insufficient stiffness; (4) Locating loose parts: Through data comparison and tactile detection at multiple test points, identify the area with the largest vibration difference, and determine the specific loose parts based on the equipment structure drawings; (5) Dynamic verification and optimization: Re-measure the vibration data after maintenance to verify whether the loose parts have been eliminated. If they reappear, use three-dimensional modeling or finite element analysis to optimize the structural design to ensure that the stiffness meets the requirements.

2. The diagnostic method for determining the loose part of rotating equipment according to claim 1, characterized in that: In the step (1), the key parts include the motor base, the platform and the anchor bolt positions, and the measurement area is divided into several test points, and data is collected synchronously at the several test points.

3. The diagnostic method for determining the loose part of a rotating device according to claim 1, characterized in that: In the step (3), the preset threshold is: for two connecting parts with an elevation difference of less than 100 mm between the upper and lower measuring points, the difference in vibration displacement value is less than 20 μm.

4. The diagnostic method for determining the loose position of rotating equipment according to claim 1, characterized in that: In the step (4), the tactile detection is to sense the looseness of the connection part through tactile perception.

5. The diagnostic method for determining the loose part of a rotating device according to claim 1, characterized in that: In the step (5), the structural optimization includes three-dimensional modeling or finite element analysis to modify the equipment design and ensure that the support stiffness meets the requirements.

6. The diagnostic method for determining the loose part of a rotating device according to claim 5, characterized in that: In step (5), the specific steps of the three-dimensional modeling and stiffness analysis are as follows: 5.1 Model construction Data sources include: Based on the original equipment design drawings; if the drawings are missing or incomplete, use 3D laser scanning or measurement tools to obtain the actual equipment geometry data; Modeling tools: Use CAD software to create high-precision 3D models to restore the following areas: the contact surface between the table and the equipment footing; the distribution of anchor bolts and the area where preload forces act; and the connection structure between the frame and the concrete foundation. Error control: The measurement data is filtered and calibrated to ensure that the error between the model and the actual object is less than ±1mm. 5.2 Stiffness analysis Static stiffness assessment: Simulate the equipment's deadweight and operating load in the model and calculate the deformation of each connection part; Pay attention to the displacement distribution of the platen support area. If the displacement at a certain point exceeds 50μm, it is judged as insufficient stiffness. Dynamic stiffness matching: Combined with vibration test data, verify whether the model's natural frequency matches the measured spectrum; If the natural frequency deviation of the model exceeds 5%, the material properties or boundary conditions need to be adjusted.

7. The diagnostic method for determining the loose position of rotating equipment according to claim 5, characterized in that: In step (5), the specific steps of the finite element analysis and parametric optimization are as follows: 5.3 Load and boundary condition setting Dynamic load: Input the actual operating parameters of the equipment and convert them into periodic force load; Constraint conditions: The contact surface between the bottom of the platform and the concrete foundation is set as a fixed constraint; a pre-tightening force is applied to the anchor bolts to simulate the actual tightening state. 5.4 Key simulation analysis types Modal analysis: Extract the first six natural frequencies and vibration modes of the structure to ensure that the separation from the equipment operating frequency is ≥20%; If there is a risk of resonance, the structural stiffness needs to be adjusted; Statics analysis: Evaluate the stress distribution of the optimized structure under maximum load, requiring the maximum stress to be ≤ 60% of the material yield strength; If the stress concentration area exceeds the threshold, add fillets or reinforcement plates; Transient dynamics analysis: Simulate the transient response of vibration amplitude during equipment startup / shutdown, requiring peak displacement ≤ 30μm; If the vibration exceeds the standard, optimize the damping structure. 5.4 Parameterized Optimization Process Optimization goal: Minimize the vibration displacement of key measuring points; Design variables: number and spacing of anchor bolts; thickness of deck or addition of reinforcement ribs; cross-sectional shape of support frame; Constraints: Total mass increase not exceeding 10%; manufacturing cost increase ≤ 15%; Optimization algorithm: Use ANSYS Design Xplorer or Altair HyperStudy to perform multi-objective iterations and generate Pareto front solution sets.

8. The diagnostic method for determining the loose position of rotating equipment according to claim 1, characterized in that: The rotating equipment includes a steam turbine, a generator, a pump, a fan, a coal mill or an air compressor.