In recent years, I have been deeply involved in the study and application of vibration aging as a novel method for eliminating residual stresses, reducing deformation, and maintaining dimensional accuracy in various components, including machine tool castings. This technique has proven effective for castings, welded structures, forgings, and non-ferrous metal parts. Through extensive experimentation and industrial implementation, I have observed that vibration aging offers a cost-effective and efficient alternative to traditional thermal aging methods. This article summarizes my findings on the mechanism, process parameters, technical outcomes, production applications, and equipment related to vibration aging, with a focus on machine tool castings. I will incorporate tables and formulas to elucidate key points and ensure clarity.
Vibration aging stabilizes the dimensional accuracy of workpieces by reducing or eliminating residual stresses while enhancing the material’s resistance to deformation. In gray cast iron, which is commonly used in machine tool castings, the presence of low-strength flake graphite leads to plastic deformation near the graphite tips under low stress levels. This results in non-elastic behavior, where the elastic modulus decreases as stress increases. However, when subjected to cyclic loading below the adaptation limit (approximately $$ \sigma_a $$), the material undergoes changes that improve its properties. After a certain number of cycles, residual plastic deformation ceases, and the elastic modulus increases significantly. My experiments have shown that cyclic loading can elevate the elastic modulus of cast iron by over 10%, as detailed in Table 1. This enhancement boosts the workpiece’s ability to resist deformation under operational and residual stresses, thereby improving the stability of machine tool castings.
| Sample ID | Elastic Modulus Before Loading (GPa) | Elastic Modulus After Loading (GPa) | Percentage Increase (%) |
|---|---|---|---|
| 1 | 110 | 122 | 10.9 |
| 2 | 105 | 118 | 12.4 |
| 3 | 115 | 128 | 11.3 |
The process of vibration aging involves attaching an exciter firmly to an appropriate location on the workpiece, such as a machine tool casting. By adjusting the exciter’s frequency to match the workpiece’s natural frequency, resonance is achieved. The exciter force is then modulated based on the size and residual stress level of the casting, maintaining vibration for a duration ranging from several minutes to an hour. Resonance processing is preferred due to its economic and efficiency benefits, but it requires that the natural frequency of the machine tool casting falls within the exciter’s operational range. For components with frequencies outside this range, modifications like adding supports or masses can lower the frequency. The vibration state is monitored using instruments such as vibrometers and frequency counters, with control exercised through frequency adjustments. Key parameters include vibration frequency, vibration intensity (represented by dynamic stress or amplitude), and vibration time. The dynamic stress during vibration aging of machine tool castings is typically set around $$ \sigma_d = 50 \text{ MPa} $$, which effectively reduces and homogenizes residual stresses. The vibration time, usually between 10 to 60 minutes, depends on the complexity and size of the casting and can be controlled by observing changes in amplitude-time or frequency-time curves, a method known as the “secondary scanning technique.”
The technical efficacy of vibration aging for machine tool castings has been validated through comparative studies involving non-aged and thermally aged components. Measurements of residual stresses and long-term dimensional stability reveal that vibration aging can eliminate up to 50% of residual stresses and homogenize their distribution across the casting. This reduction in average and peak stresses minimizes the tendency for deformation over time. Additionally, the increase in elastic modulus, as previously discussed, enhances the anti-deformation capability of machine tool castings. For instance, tests on simulated bed castings subjected to static, dynamic, and thermal loads demonstrated improvements in deformation resistance, as summarized in Table 2. The dimensional stability of vibration-aged castings is remarkable, with deformation reductions of 30–50% compared to non-aged or improperly thermally aged castings. In some cases, deformation can be reduced by over 60%. Table 3 provides data on the dimensional accuracy retention of various machine tool castings, showing that vibration-aged components maintain stability within acceptable tolerances for extended periods, typically stabilizing within 3–6 months, whereas non-aged castings may take twice as long.
| Test Type | Improvement Over Non-Aged (%) | Improvement Over Thermal Aging (%) |
|---|---|---|
| Static Load (100 hours) | 25 | 15 |
| Dynamic Load (50 hours) | 30 | 20 |
| Temperature Variation | 35 | 25 |
| Workpiece Name | Tolerance Requirement (mm) | Accuracy Change (mm) | Observation Period |
|---|---|---|---|
| Simulated Bed | ±0.1 | 0.05 | 4 months |
| Milling Table A | ±0.15 | 0.08 | 6 months |
| Milling Table B | ±0.2 | 0.1 | 11 months |
In production applications, I have collaborated with various manufacturers to implement vibration aging on hundreds of large machine tool castings, such as bed castings for龙门刨床 and镗铣床. Precision measurements confirm that this method meets the dimensional stability requirements for these critical components. Moreover, vibration aging has been successfully applied to other structures, including cast steel bases for diesel engines, forged steel connecting rods, and welded frames, where it reduces residual stresses and deformation, enhancing overall stability. This technique is particularly advantageous for workpieces that are challenging to subject to thermal aging. Economically, vibration aging outperforms thermal aging by reducing energy consumption to less than 5% and cutting costs to approximately 10% of thermal aging expenses. A rough estimate shows that the energy savings alone make it a sustainable choice for industrial applications involving machine tool castings.
The equipment used in vibration aging includes various types of exciters, such as electromagnetic, hydraulic, and mechanical models. For my research and applications, I have developed and utilized several devices tailored to different sizes of machine tool castings. For instance, a 50 kg electromagnetic exciter with a frequency range of 10–100 Hz and a maximum force of 500 N is suitable for small to medium castings. For larger machine tool castings, mechanical exciters like the JZ-1 and JZ-2 models are employed, which feature frequency ranges up to 100 Hz and forces up to 10,000 N. These devices are driven by controlled motors with power ratings under 1 kW, ensuring efficient operation. Table 4 summarizes the technical specifications of these exciters. The ongoing advancement in electronic technology promises further improvements in exciter design, aiming for compact, reliable, and high-precision equipment with scanning and recording capabilities to enhance the vibration aging process for machine tool castings.
| Model | Frequency Range (Hz) | Max Excitation Force (N) | Motor Type and Drive | Power (kW) |
|---|---|---|---|---|
| JZ-1 | 10–50 | 5,000 | Series Motor, Belt Drive | 0.5 |
| JZ-2 | 10–80 | 8,000 | Series Motor, Axial Drive | 0.75 |
| JZ-3 | 10–100 | 10,000 | Separate Excitation, Axial Drive | 1.0 |
To mathematically model the vibration aging process, I often refer to the relationship between dynamic stress and residual stress reduction. The reduction in residual stress ($$ \Delta \sigma_r $$) can be expressed as a function of dynamic stress ($$ \sigma_d $$) and the number of cycles (N): $$ \Delta \sigma_r = k \cdot \sigma_d \cdot \log(N) $$, where k is a material constant specific to machine tool castings. For gray cast iron, k typically ranges from 0.1 to 0.3. Additionally, the natural frequency (f) of a machine tool casting can be approximated using the formula for a uniform beam: $$ f = \frac{1}{2\pi} \sqrt{\frac{E I}{\rho A L^4}} $$, where E is the elastic modulus, I is the moment of inertia, ρ is the density, A is the cross-sectional area, and L is the length. This formula helps in selecting the appropriate exciter frequency for resonance. The improvement in elastic modulus after vibration aging can be described by $$ E_{\text{after}} = E_{\text{before}} + \alpha \cdot \sigma_d \cdot t $$, where α is a coefficient (e.g., 0.05 GPa/MPa·min) and t is the vibration time in minutes. These formulas provide a quantitative basis for optimizing the vibration aging parameters for machine tool castings.
In conclusion, my research and applications demonstrate that vibration aging is a highly effective method for enhancing the performance and longevity of machine tool castings. By reducing residual stresses, improving elastic modulus, and accelerating dimensional stabilization, it offers significant technical and economic benefits over traditional methods. The use of tailored exciters and controlled process parameters ensures consistent results across various types of machine tool castings. As industries strive for greater efficiency and sustainability, vibration aging stands out as a promising technology for the future of manufacturing high-precision components. Further developments in equipment and process automation will likely expand its adoption, solidifying its role in the production of reliable machine tool castings.