Who has the electronic version of the book \"Equipment Fault Diagnosis\" by Shen Qinggen?

98 Summary of Key Points in “Equipment Fault Diagnosis – Shen Qinggen” 1.1. The meaning of equipment fault diagnosis； Equipment fault diagnosis refers to the application of modern testing and analysis methods as well as diagnostic theories ； 1.2. The process of equipment fault diagnosis ； Signal acquisition → Signal processing → Fault diagnosis → Diagnostic decision-making → Fault prevention and control ； 1.3. Characteristics of equipment fault diagnosis ； Diversity, hierarchy, multi-factor correlation, latency, uncertainty ； 1.4. Three maintenance systems ； After-maintenance (fault repair), regular maintenance (planned maintenance), condition ； 1.5 What are the types of equipment failures? ； ①Structural damage faults (cracks, wear). 1.1. The meaning of equipment fault diagnosis: Equipment fault diagnosis refers to the use of modern testing and analysis techniques as well as diagnostic theories to identify and determine the mechanism, causes, location, and severity of faults in operating mechanical equipment. Based on these diagnostic findings, repair plans and preventive measures for the equipment are determined. 1.2. The process of equipment fault diagnosis: Signal acquisition → Signal processing → Fault diagnosis → Diagnostic decision-making → Fault prevention and control 1.3. Characteristics of equipment fault diagnosis: Diversity, hierarchy, multi-factor correlation, latency, uncertainty 1.4. Three maintenance systems: Reactive maintenance (fault-based maintenance), preventive maintenance (planned maintenance), condition monitoring maintenance (predictive maintenance) 1.5. What are the types of equipment faults? ① Structural damage faults (cracks, wear, corrosion, deformation, fracture, spalling, and burns) ② Degradation faults related to motion conditions (poor mechanical positioning, insufficient rigidity, friction, fluid-induced vibrations, nonlinear harmonic resonance) 1.6. Functions of equipment fault diagnosis: ① Detection without shutting down the equipment or removing it; ② Predicting the reliability of the equipment; ③ Identifying the source of the fault and proposing corrective measures. 1.7. Technologies and methods for equipment condition monitoring and fault diagnosis: Vibration signal monitoring and diagnosis techniques (universal applicability, rich information content, easy to process and analyze); Acoustic signal monitoring and diagnosis techniques (sound monitoring method, spectrum analysis method, sound intensity method); Temperature signal monitoring and diagnosis techniques; Lubricant analysis and diagnosis techniques; Other non-destructive testing and diagnosis techniques. 1.8. Methods for identifying equipment fault conditions: Information comparison diagnosis method, parameter change diagnosis method, simulation test diagnosis method, function diagnosis method, fault tree analysis diagnosis method, fuzzy diagnosis method, neural network diagnosis method, expert system. 2.1. Meaning and classification of signals: Signals are carriers of information that describe the state or behavior of objective entities. Classification: Deterministic signals and stochastic signals ； Continuous signals and discrete signals ； Energy signals and power signals ； Time-limited and frequency-limited signals 2.2. Signal time domain decomposition DC component and AC component pulse component real component and imaginary component orthogonal function component 2.3. Time domain statistics of signal mean mean square value variance 2.4. Time domain correlation analysis correlation coefficient: 2.5. Spectral analysis method uses the Fourier transform method to decompose the vibration signal and expand it in frequency order to make it a function of frequency. Then, it is a process of studying and processing the signal in the frequency domain, which is called spectrum analysis. 2.6. The basic parameters of vibration monitoring: amplitude, frequency, and phase. 2.7. Axis trajectory of vibration signal processing graphics commonly used in rotating machinery.: The movement path of the journal center relative to the bearing seat in the vertical plane of the axis. The rotor mode shape.: The position of the journal whirl center of a space curve formed by the vibration displacement of each point on the rotor axis.: In sliding bearings, the center of the journal moves around a certain center point under the action of the disturbing force.: The relationship curve describing the change of rotor amplitude and phase with rotational speed. The ordinate is the amplitude and phase, and the abscissa is the rotor's rotational speed or rotational frequency polar coordinate diagram.: Express the relationship between the amplitude and phase of the rotor with the rotation speed in the form of polar coordinates (intuitive, convenient, clear, and anti-interference) three-dimensional coordinate diagram (cascade diagram, waterfall diagram): As the rotational speed increases, the basic amplitude index of mechanical vibration increases and the order ratio spectrum analysis: Divide each frequency value on the abscissa on the spectrogram by a certain reference frequency value (clear reading, periodic sampling, high accuracy) 3.1 What are the types of faults in rotating machinery? ① Rotary imbalance ② Rotor misalignment ③ Sliding bearing failure ④ Rotor friction ⑤ Floating ring seal failure 3.2 The concept of rotor imbalance The rotor is affected by various factors such as material quality, processing, assembly and operation. Due to the influence of factors, there is a certain amount of eccentricity between the center of mass and the center line of rotation, which causes periodic centrifugal force interference when the rotor is working, generating dynamic loads on the bearings, thereby causing machine vibration. The unbalanced centrifugal force is large. Small 3.3 Fault characteristics of unbalanced vibration of the rotor ① Unbalanced fault mainly causes radial vibration of the rotor or bearing. In the spectrum diagram obtained at the radial measuring point of the rotor, the speed frequency component has a prominent peak value ② For simple unbalanced vibration, the speed frequency The amplitude of high-order harmonics is very low, so the waveform in the time domain is a sine wave. ③ The shape of the axis trajectory of the rotor is basically a circle or ellipse, which means that the signal phase difference of two probes placed perpendicular to each other on the same section of the rotating shaft is close to 90°. ④ The precession direction of the rotor is synchronous positive precession ⑤ Except for the cantilever rotor, for ordinary rotors supported at both ends, the amplitude of unbalance in the axial direction is generally not obvious ⑥ The rotor amplitude is very sensitive to changes in rotational speed. As the rotational speed decreases, the amplitude will decrease significantly 3.4 Causes of unbalanced vibration of the rotor ① Inherent mass imbalance (design errors, material defects, processing and assembly errors, incorrect dynamic balancing methods) ②Unbalance during rotor operation (rotor bending, rotor balance state destruction) 3.5 How to distinguish rotor bending imbalance and mass imbalance ①Changes in amplitude with rotation speed: The mass imbalance and rotational speed change according to a fixed relationship. There is no fixed ② phase change with rotational speed for bending.: The phase of the mass is changing, and the bending is basically unchanged ③The amplitude changes with the load: The vibration of the mass does not change with the load, and it will bend. 3.6 Characteristics of rotor misalignment faults ① Changes the oil film pressure in the bearing ② The vibration amplitude of the bearing increases with the increase of the rotor load ③ Parallel misalignment mainly causes radial vibration ④ Misalignment causes a phase difference in the rotor vibration on both sides of the rigid coupling ⑤ Analysis from the vibration frequency, The vibration frequencies caused by different types of rotors and different forms of misalignment are different. ⑥ Misalignment of multi-span rotors on large turbomachinery is generally accompanied by other failure factors, so the vibration situation is more complicated. ⑦ Misalignment between rotors, due to a preload in the direction of bearing misalignment, the axis center of the journal movement The trajectory shape is elliptical. As the preload increases, the trajectory shape will change into a banana shape, a "8" shape, or an inner ring in the outer ring. 3.7 Reasons for rotor misalignment faults ① The initial installation alignment is out of tolerance ② The thermal rise of each rotor centerline is not correctly estimated during cold alignment, and the active rotor and the centerline appear during operation. Poor dynamic alignment of the driven rotor ③ Uneven thermal expansion of the bearing frame ④ Pipe force ⑤ Deformation or displacement of the casing ⑥ Uneven subsidence of the foundation ⑦ Foundation deformation ⑧ Rotor bending, resulting in unbalance and misalignment faults at the same time 3.8 Monitoring methods for misalignment faults ① Static detection method (beating table, laser alignment method, coupling surface condition detection method) ②Dynamic monitoring method (vibration diagnosis method, laser alignment method, Dodd rod measurement method, eddy current absolute value measurement method, bearing oil film pressure measurement method) 3.9 Causes and preventive measures for common failures of sliding bearings ①Babbitt alloy loosening (re-pouring) ②Abnormal bearing wear, scratches, roughening (bearing assembly defects, bearing processing errors, large rotor vibration, thrust bearing design errors, oil supply system problems) ③Bearing fatigue (appropriate bearing pressure, appropriate bearing clearance, use thin Babbitt alloy, control bearing temperature) ④ Bearing corrosion ⑤ Bearing cavitation ⑥ Bearing shell looseness ⑦ Bearing clearance inappropriate ⑧ Bearing temperature too high 3.10 Overview of oil film oscillation is a unique fault of high-speed sliding bearings. The self-excited vibration caused by the oil film force. When the rotor oil film oscillates, the input energy is large enough to cause damage to the components of the rotor bearing system. The mechanism and characteristics of the bad 3.11 oil film oscillation is a large-amplitude resonance phenomenon that occurs when the whirling motion of the journal coincides with the natural frequency of the rotor. It is often characterized by a very strong momentum, a sudden increase in amplitude in an instant, and a local oil film rupture will soon occur, causing friction between the journal and the bearing bush, emitting a strong roar, and seriously damaging the oil film. Bad bearings and rotors 3.12 Failure characteristics of oil film oscillation in bearings ① Oil film oscillation is a self-excited vibration. The energy to maintain the vibration is generated by the shaft itself during rotation, and it is not affected by external excitation forces. ② In high-speed and lightly loaded rotors, the speed at which oil film oscillation occurs is always more than twice the first-order critical speed of the rotor system. ③Oil film oscillation is a nonlinear oil film resonance ④The shape of the axis trajectory is disordered and divergent, and many irregular trajectories are superimposed into a petal shape ⑤Due to intense self-excited vibration of the rotor, the bearing oil film ruptures, resulting in simultaneous collision and friction between the journal and the bearing bush, and sometimes a huge roar occurs ⑥Inertia phenomenon: Once the rotor speed enters the oil film resonance zone, increase the speed, the oscillation frequency remains unchanged, and the amplitude does not decrease. 3.13 Preventive measures for oil film instability ① Avoid the oil film resonance zone ② Increase bearing specific pressure ③ Reduce bearing clearance ④ Control appropriate bearing pre-conditioning Load ⑤ Select bearings with good vibration resistance ⑥ Adjust oil temperature 4.1 Fault types and causes of reciprocating compressors ① Abnormal compressor thermal parameters (reduced exhaust volume, abnormal suction and exhaust pressure, abnormal temperature, changes in working conditions, oil circuit failure) ② Mechanical failure of the main components of the compressor (valve failure, piston rod breakage, connecting rod bolt breakage, crankshaft breakage, piston stuck, biting or cracked) ③ Compressor failure vibration/dynamic failure (motion inertia force of the crank connecting rod mechanism, compressor failure vibration (cylinder, body and basic vibration) and abnormal sound (motion mechanism, cylinder, suction valve, exhaust valve failure) 4.2 Forms of valve failure ① The valve plate is damaged ② The spring is broken ③ The air valve is leaking 4.3 Methods for monitoring and diagnosing air valve failures ① Install the sensor on the valve cover to obtain the vibration signal or noise signal ② Install the displacement sensor in the valve chamber to monitor the movement pattern signal of the valve plate ③ Monitor with PV power indicator diagram ④ Measure Pulsating pressure and temperature changes in the suction and exhaust chambers 4.4 What adverse effects does pressure pulsation bring to the compressor? ① It may increase the indicated power of the compressor ② Reduce the service life of the air valve ③ Increase or decrease the exhaust volume ④ Destroy the tightness of the safety valve ⑤ Cause vibration of pipelines and equipment 4.5 Prevention and control measures for pipeline pressure pulsation ① Adopt a reasonable suction and exhaust sequence ② Install a buffer ③ Install an acoustic filter ④ Install an orifice plate ⑤ Configure a suitable gas collecting pipe ⑦ Avoid sudden changes in the direction and flow rate of air flow in the pipeline 4.6 Causes of mechanical resonance of pipelines Caused by air flow pressure pulsation Column resonance and any kind of excitation force 4.7 Diagnosis method of pipeline mechanical resonance ① Test method ② Calculation method 4.8 Prevention and control measures of pipeline mechanical resonance ① Change the support conditions ② Use dynamic shock absorbers 5.1 Common faults of gears ① Teeth fracture (fatigue fracture and overload fracture) ② Tooth wear (adhesive wear, abrasive wear, corrosion wear) ③ Tooth surface fatigue (pitting, spalling) ④ Tooth surface scratches and scratches 5.2 Main conventional excitations and fault excitations of gears ① Stiffness excitation ② Transmission error (manufacturing error, assembly error, gear tooth damage error, external excitation error) ③Meshing impact ④Pitch line impact 5.3 Characteristics of gear faults ①Meshing frequency and its harmonic components ②Sidebands formed by amplitude modulation and frequency modulation ③Additional pulses composed of low-order harmonics of gear speed frequency ④Implicit components formed by gear machining errors 5.4 The meaning of cepstrum The power spectrum of the logarithm of the power spectrum (inverse Fourier transform), that is, the time signal x The power spectrum function G(f) of (t) takes the logarithm, and then performs Fourier transform, and its expression is 5.5 Advantages of cepstrum ① Effective extraction and identification of periodic components on the spectrum ② Little influence on the transmission path 5.6 Diagnostic methods of gear faults ① Refined spectrum analysis method ② Cepstrum analysis method ③ Time domain synchronous averaging method ④ Adaptive denoising technology (vibration signal diagnosis) ⑤Noise Diagnosis 6.1 Why is it said that rolling bearings are the most vulnerable to damage? They have poor ability to withstand impacts and are prone to failure under impact loads. The load distribution of rolling bearings on the rolling elements is uneven. The rolling element under the load line is the most stressed. The stress and stress cycle times of each point on the inner ring and outer ring are different. 6.2 Failure forms of rolling bearings. Speed n10r/min - fatigue spalling (pitting corrosion), abrasive wear, cracks and fractures, indentation, corrosion, electric corrosion, Gluing (adhesion), fretting wear, and burning 6.3 Detection methods of rolling bearing faults Detection based on the vibration and sound of the bearing Detection based on the temperature of the bearing or the temperature of the lubricating oil Detection based on the wear particles of the bearing Detection based on the change of the gap in the bearing Detection based on the change of oil film resistance in the bearing 6.4 Causes of vibration of rolling bearings External excitation factors: Internal causes of vibration transmission such as rotor imbalance, misalignment, fluid excitation, and structural resonance: Ⅰ Vibration caused by the bearing structure itself ① Vibration caused by the rolling element passing through the load direction ② Natural vibration of the ring ③ Vibration caused by the elastic characteristics of the bearing Ⅱ Vibration caused by bearing shape and accuracy issues ① Vibration caused by the waviness of the ring, raceway and rolling element ② Vibration caused by uneven size of the rolling elements and eccentricity of the inner and outer rings Ⅲ Vibration caused by improper use or incorrect assembly of the bearing ① Vibration caused by local defects on the raceway contact surface ② Vibration caused by poor lubrication and friction ③ Vibration caused by incorrect assembly and journal deflection

98 Summary of Key Points from “Equipment Fault Diagnosis – Shen Qinggen”-2 6.5 What are the excitation forces caused by bearing failures?； ①The waveform is random and disordered. ② The driving force is a pulse wave in the form of a spike. ③ Excitation ； 6.6 Characteristics in the frequency domain of bearing vibration signals ； ①The spectrum has wide-band characteristics, and these characteristics vary depending on the type and shape of the defects ； 20~60kHz, natural frequencies of other bearing components ； Above 60 kHz, it falls within the range of acoustic emission (poor lubrication, bonding, ； 6.7 Vibration detection techniques and diagnosis methods for bearing failures ； ①Low-frequency signal reception method ② Impulse pulse method (SPM) ③ Resonant demodulation ； 7.1 Oil sample analysis 6.5 What are the excitation forces caused by bearing failures? ① The waveform is random and disordered. ② The excitation force takes the form of spike-shaped pulse waves. ③ The excitation is steady-state and in the form of sine waves. 6.6 Characteristics of the frequency domain in bearing vibration signals ① The spectrum exhibits a wide frequency range, and it varies depending on the type and shape of defects, as well as the bearing size and rotation speed. Three frequency bands: 0–20 kHz, corresponding to the failure-related frequencies of the rotor and bearings (misalignment, imbalance); 20–60 kHz, corresponding to the natural frequencies of other components in the bearing; above 60 kHz, falling within the range of acoustic emission (poor lubrication, adhesion, delamination cracks). 6.7 Techniques and methods for detecting and diagnosing bearing failure vibrations ① Low-frequency signal reception method. ② Shock pulse method (SPM). ③ Resonance demodulation method. ④ Fiber optic sensor technology. ⑤ Eddy current sensor technology. 7.1 Overview of oil sample analysis techniques By sampling and analyzing the oil, information regarding the wear condition of various friction pairs in the equipment can be obtained, thereby allowing for a scientific assessment of the equipment’s operating status. 7.2 Common Oil Sample Analysis Techniques ① Spectral analysis (SOA): Atomic absorption spectroscopy, atomic emission spectroscopy, X-ray fluorescence spectroscopy ② Ferrography ③ Particle counters ④ Magnetic plugs 7.3 Overview of Acoustic Emission: The phenomenon in which materials release strain energy in the form of elastic waves under external loads (such as force, heat, electricity, magnetism, etc.) or internal forces. 7.4 Process of Acoustic Emission Signal Transmission: Acoustic emission source → Propagation within the material → Sensor coupling interface → Sensor → Acoustic emission instrument receives the signal → Signal processing → Data display. 7.5 Characteristic Parameters of Acoustic Emission Signals ① Count and count rate ② Amplitude and amplitude distribution ③ Location determination of the acoustic emission source. 7.6 Functions of Acoustic Emission Detection Instruments ① Receiving acoustic emission signals ② Processing signals ③ Displaying acoustic emission data. 7.7 Classification of Acoustic Emission Instruments: Number of channels for receiving signals: single-channel, dual-channel, multi-channel. 7.8 Research and Application Areas of Acoustic Emission Detection ① Petrochemical industry ② Power industry ③ Material testing ④ Civil engineering ⑤ Aerospace industry ⑥ Metal processing ⑦ Transportation industry ⑧ Others. 8.1 Overview of Expert Systems: Expert systems are a branch of artificial intelligence; they are computer-based systems equipped with a large amount of specialized programs. By utilizing artificial intelligence techniques, they can make deductions and judgments based on knowledge provided by experts, simulating the decision-making process of human experts to solve complex problems that only human experts can handle. 8.2 Structure of Expert Systems: Core components, human-computer interface. 8.3 Basic Issues Involved in Expert Systems: Expert systems are knowledge-processing systems that involve three basic issues: knowledge acquisition, representation (core), and utilization. 8.4 Common Knowledge Representation Methods: Production rule representation, frame representation, predicate logic representation, process representation. 8.5 Format of Production Rule Representation: IFTHEN. 8.6 Components of a Production Rule System: Rule base, knowledge database, inference engine (control strategies and inference methods). 8.7 Advantages and Disadvantages of Production Rule Representation: Advantages: Modularity, consistency, naturalness. Disadvantages: Low inference efficiency. 8.8 Inference Methods in Expert Systems: Rule-based inference (forward, backward, and hybrid inference); disadvantages: Difficulty in knowledge acquisition and vulnerability in inference. Model-based inference; disadvantages: Low inference efficiency and difficulty in establishing system models. Case-based inference; advantages: Easy knowledge acquisition, learning capability, strong adaptability, ease of acceptance ； Disadvantages: difficult to search, no guarantee of obtaining the best solution)

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