Impact performance optimization for hydraulic rock drill based on stroke and flow compensation factors

Abstract

In response to the issues of overheating of the shell and insufficient impact energy of the hydraulic rock drill, this paper focuses on the hydraulic rock drill with alternating front and rear return chambers. By establishing nonlinear and linear dynamic models, the influence of stroke amount and flow compensation on the hydraulic system is investigated, and an optimization method for impact characteristics is proposed. Considering factors such as hydraulic clamping force, fluid leakage, and rock properties, a feedback control numerical model is established for the impact system. This model is based on principles drawn from wave dynamics and fluid dynamics theories. It elucidates the dynamic characteristics of the impact piston, reversing valve, and high-pressure accumulator. Combining three linear models, this study investigates the influence of the advance amount of the return signal chamber and the gas pre-charge pressure of the high-pressure accumulator on the impact characteristics. A thorough laser experiment has been created to evaluate the actual rock drilling capabilities of the impact system. Proposed optimal parameters are tested experimentally to compare the impact performance before and after the enhancement. The results indicate an increase in impact power, validating the effectiveness of the proposed improvement method.

Keywords

Fluid power and control hydraulic rock drill signal advance amount gas pre-charge pressure impact characteristics

Introduction

Hydraulic rock drills, known for their cost-effectiveness, rapid operation, and strong adaptability, play a vital role in tunnel excavation, mining operations, and piercing through iron mouths.^1–3 The development of new hydraulic rock drills is characterized by high frequency, high power, and intelligent features. The hydraulic rock drill features alternating front and rear return chambers, ensuring a continuous oil discharge, minimal pressure fluctuations, and excellent drilling efficiency. In the new era of rapid artificial intelligence development, the concept of intelligent mines has placed higher demands on hydraulic rock drills. Therefore, investigating the structural factors influencing the impact characteristics of hydraulic rock drills with alternating front and rear return chambers holds significant importance.^4,5

As the reliability of hydraulic rock drills continues to improve, there is increasing research on the factors affecting their impact characteristics, but the research tends to focus on external operating parameters. Yang et al.⁶ scrutinize the response characteristics of impact pistons and reversing valves, with a specific emphasis on the impact performance influenced by factors such as piston chamber pressure, oil pump flow rate, relief valve pressure, and the gas pre-charge pressure of the accumulator. The rock drill impact system is optimized using the orthogonal test method, resulting in an improvement in drilling efficiency of over 17.7%. Yong et al.⁷ explore the impact performance of a sleeve valve rock drill, considering the effects of supply flow, the gas pre-charge pressure in the high-pressure accumulator, and the set pressure. The rock drill exhibits instability under low-pressure and low-flow conditions. Under normal working conditions, a higher accumulator charging pressure results in better impact performance. However, this study does not consider the factor of the pre-charge pressure more than the impact pressure. Cui et al.⁸ analyze how the volumetric motor’s fluid pulsation affects the hydraulic impactor’s performance. They find that chamber length and diameter are critical factors in generating pulsations. After optimization, drilling efficiency increased by 25%. Li et al.⁹ conduct comprehensive investigations on compressive strength, Brazilian splitting, and orthogonal rock drilling. They analyze drilling efficiency factors through an extreme difference analysis of drilling speed and specific energy. Subsequently, they propose a regression orthogonal design method. The interaction between impact power and rotational speed exhibits significant influence on the results. This method predominantly concentrates on the examination of rotational and thrust parameters. Geng et al.¹⁰ construct a numerical model for a double damping hydraulic rock drill, investigating the impact of damping valves and pipeline configurations on cavitation phenomena. Their findings indicate that damping valves effectively mitigate cavitation occurrences, whereas extended and slender pipelines are susceptible to cavitation, and intersecting pipelines can induce pressure fluctuations.

Regarding the internal structural parameters of rock drills, research generally focuses on the study of reversing valves and piston diameters.¹¹ Song et al.¹² investigate how supply pressure, piston rod, and bore diameter influence the rock drill’s impact power. Using the Taguchi method for selecting optimal design parameters, they improve the signal-to-noise ratio by 3.11 dB. Shi et al.¹³ focus on the effects of piston mass, the down-the-hole hammer’s total mass, supply pressure, and lifting distance on drilling characteristics. This study validates the anti-jamming characteristics of the bi-directional pneumatic submerged hammer and finds that the total weight of the submerged hammer does not exert a significant impact on drilling performance. Ma et al.¹⁴ incorporate factors like oil compressibility, impact leakage, and pressure loss to develop a coupled dynamics model for the impact system. They investigate the impact of spool valve damping clearance and pipeline diameter on impact performance.

The working environment of hydraulic rock drills is complex, with rock properties, ambient temperature, and mechanical vibration all affecting drilling effectiveness. Most nonlinear numerical models only consider the study of rock drilling under empty percussion conditions. Stosiak et al.¹⁵ investigate methods for reducing external mechanical vibrations of hydraulic valves in hydraulic systems. They introduce rubber cushion pads between the valve casing and the vibrating surface, and place elastic pads inside the valve casing between the casing and the centering spring to mitigate vibrations. Kim et al.¹⁶ integrate the flow dynamics of compressed air, the impact hole opening area, and the air tube valve into a numerical model describing the down-the-hole hammer impact system. Nonetheless, this approach faces limitations as it fails to replicate the rotary system. Hu et al.¹⁷ formulate a vibration model with a single degree of freedom for hydraulic rock drills, featuring alternating front and rear return chambers. This model utilizes quasi-steady-state and finite difference theories. While neural networks excel in capturing the intricate nonlinear relationships inherent in rock drills, they lack the ability to elucidate the internal decision-making processes. Iphar¹⁸ establishes artificial neural networks and adaptive neuro-fuzzy inference systems to forecast the crushing efficiency of hydraulic impact hammers. This involves acquiring data on rock rebound characteristics and rock evaluation indices. The demanding characteristics of hydraulic rock drills, marked by high-frequency and high-pressure attributes in alternating front and rear return chambers, necessitate advanced testing methods.¹⁹ He et al.²⁰ develop a hydro-hammer testing system using eddy current sensors to acquire pressure parameters and permeability data. However, the complexity of this method and its susceptibility to external environmental factors limit its applicability. Li^21,22 performs stress wave testing to plot the relationship between varying piston lengths and the coefficient of restitution, suffering from low detection accuracy.

Based on the analysis above, previous research on the influencing factors of impact performance has often overlooked piston stroke amount and flow compensation, focusing more on the study of working parameter matching, reversing valve, and accumulator structure. Nonlinear models typically neglect hydraulic jamming and load factors, and the testing methods for rock drills are complex, lacking appropriate means to validate research findings. This paper considers hydraulic jamming factors, establishes a dynamic model of rock drills under load, investigates the influence of the advance amount of the piston return signal chamber and the gas pre-charge pressure of the high-pressure accumulator, and validates the effectiveness of improved impact performance based on laser testing method.

The subsequent segments of this manuscript are structured in the following manner. Section “Working principle and model establishment of the impact system” investigates the numerical model of the impact system and simulation results. Section “Analysis of the influence of structural parameters” studies the influence of different factors on the impact performance. In section “Experiment engineering and improvement verification,” the impact system rock drilling test curves are analyzed, and an optimization method is proposed. Finally, section “Conclusion” summarizes the entire paper.

Working principle and model establishment of the impact system

Operating principle of the hydraulic rock drill

The hydraulic rock drill featuring alternating front and rear return chambers comprises the impact system, rotary system, and flushing system, as illustrated in Figure 1. The impact system includes the cylinder body, impact piston, reversing valve, high and low-pressure accumulators, guide sleeve, and sealing rings. Notably, the oil pressure propels the impact piston to execute high-velocity strikes on the shank. The shank, functioning as an elastic element, generates stress waves upon impact.²³ These stress waves propagate from the shank’s tail to its head, exerting the desired drilling and rock-breaking effect. The reversing valve controls the high and ow pressure switching of the piston, regulating its return and impact movements. In operation, the high-pressure accumulator absorbs and releases fluid during the return and impact strokes, respectively, amplifying the rock drill’s response velocity. Moreover, the high-pressure accumulator mitigates fluid fluctuations and casing vibrations.²⁴

Figure 1.

Schematic diagram of the hydraulic rock drill.

The rotary system consists of transmission gears, clutch sleeves, sealing devices, and motors, etc. The hydraulic motor outputs torque through the transmission gears, causing the drill bit to rotate to a new position after each impact, while separating the surface portion of the rock that has already cracked, preparing for the next impact. The flushing system consists of flushing heads, copper sleeves, and drill tails, etc. Pressurized water from the auxiliary water pump reaches the drill bit at the end of the drill rod through the flushing head, flushing the rock debris inside the drill hole during drilling.

Dynamics model of impact piston

When the piston collides with the brazing rod at a high velocity, a stress wave is generated and propagates the energy to the rock, accomplishing the objective of rock fragmentation.²⁵ Taking the external cylinder as the reference frame, based on Newton’s classical mechanics theory, we consider factors such as frictional resistance, hydraulic clamping force, and liquid leakage. The simulation model of the impacting piston is formulated, as depicted by equations (1) and (2). The friction resistance formula of the impact system is established using the Stribeck friction model. The Stribeck friction model suggests that the variation of frictional force with velocity can be divided into four stages: static friction stage, boundary lubrication stage, mixed lubrication stage, and full fluid lubrication stage. Employing principles from fluid dynamics theory and considering the compressibility of hydraulic fluid, equations describing the flow rate and pressure drop of the impacting piston are derived, as outlined in equations (3) and (4). The structural model of the impact system is illustrated in Figure 2.

m_{p} a_{p} = P_{h} A_{4} - P_{q} A_{3} - \frac{| v_{p} |}{v_{p}} F_{s} - \frac{| v_{p} |}{v_{p}} F_{f} - \frac{| v_{p} |}{v_{p}} F_{l}

(1)

where, m_p is the piston mass; a_p is the piston acceleration; P_q and P_h are the front and rear chambers pressure, respectively; A₃ and A₄ are the front and rear chambers annular areas, respectively; v_p is the piston velocity; F_s is the viscous frictional resistance; F_f is the seal friction resistance; F_l is the hydraulic clamping force.

Figure 2.

Structure model of the impact piston and reversing valve.

Among them,

{\begin{matrix} F_{s} = \frac{π μ}{\sqrt{1 - ε^{2}}} (\frac{l_{1} d_{1} | v_{p} |}{h_{1}} + \frac{l_{2} d_{2} | v_{p} |}{h_{2}} + \frac{l_{3} d_{3} | v_{p} |}{h_{3}} + \frac{l_{4} d_{4} | v_{p} |}{h_{4}}) \\ F_{f} = π \cdot d_{2} \cdot f \cdot P_{q} \cdot l_{5} + π \cdot d_{4} \cdot f \cdot P_{h} \cdot l_{5} + 2 π (d_{2} + d_{4}) ζ \\ F_{l} = Δ p_{1} \cdot τ_{1} \cdot l_{1} \cdot d_{1} + Δ p_{2} \cdot τ_{1} \cdot l_{2} \cdot d_{2} + Δ p_{3} \cdot τ_{1} \cdot l_{3} \cdot d_{3} \\ + Δ p_{4} \cdot τ_{1} \cdot l_{4} \cdot d_{4} \end{matrix}

(2)

where, μ is the kinematic viscosity; ε is the eccentricity; d_i is the diameter matching between the piston and guide sleeve, cylinder body; l_i (i = 1, 2, 3, 4) is the length of matching between the piston and guide sleeve, cylinder body; h_i is the clearance between the piston and guide sleeve, cylinder body; l₅ is the seal width; f is the coefficient of friction between the seal and the impact piston, f = 0.05; ζ is the O-ring compression amount coefficient, ζ = 0.1; Δp_i is the pressure difference; τ₁ is the hydraulic clamping force coefficient of the piston.

{\begin{matrix} \frac{V_{10} + A_{3} x_{p}}{K_{iig}} \cdot \frac{d P_{q}}{dt} = C_{1} Q_{q} + A_{3} v_{p} - Q_{l 1} - Q_{l 2} \\ \frac{V_{20} - A_{4} x_{p}}{K_{iig}} \cdot \frac{d P_{h}}{dt} = C_{2} Q_{h} - A_{4} v_{p} - Q_{l 3} - Q_{l 4} \end{matrix}

(3)

where V_i (i = 10, 20) is the initial volume of the chamber; x_p is the piston displacement; K_iig is the elastic modulus of the oil, K_iig = 1700 MPa; C_i is the state judgment amount; Q_q and Q_h are the flow rates of the front and the rear chamber; Q_li is the leakage flow rate.

Among them,

{\begin{matrix} Q_{q} = \frac{| P_{4} - P_{q} | π d^{4}}{128 μ l} \\ Q_{h} = \frac{| P_{2} - P_{h} | π d^{4}}{128 μ l} \\ Q_{li} = \frac{π d_{i} h_{i}^{3} (1 + 1.5 ε^{2})}{12 μ l_{i}} Δ p_{i} \end{matrix}

(4)

where P₄ is the pressure of the right valve chamber; d is the orifice diameter; l is the orifice length; P₂ is the pressure of the left valve chamber.

Dynamics model of reversing valve

Under the rock drill’s high-frequency, high-pressure, and high-temperature conditions, the reversing valve must ensure rapid response, low energy consumption, and minimal pressure pulsation. As the spool moves, trapped oil area absorbs the deceleration energy. Therefore, numerical modeling of the opening amount is critical. Incorporating factors like frictional resistance, hydraulic clamping force and fluid leakage, as detailed in equations (5) and (6). Flow rate and pressure drop equations of the reversing valve have been established, as indicated in equations (7) and (8).

m_{v} a_{v} = P_{1} A_{6} + P_{2} A_{6} - P_{1} A_{7} - P_{4} A_{7} - P_{3} A_{1} - F_{sv} - \frac{| v_{v} |}{v_{v}} F_{lv}

(5)

where m_v is the reversing valve mass; a_v is the reversing valve acceleration; A₆ is the left pushing valve area of the normal chamber in the reversing valve; A₇ is the right pushing valve area of the normal chamber in the reversing valve; A₁ is the pushing valve area of the control chamber in the reversing valve; P₁ is the pressure of the normal chamber in the reversing valve; P₃ is the pressure of the control chamber in the reversing valve; F_sv is the viscous frictional resistance of the reversing valve; v_v is the reversing valve velocity; F_lv is the hydraulic clamping force of the reversing valve.

Among them,

{\begin{matrix} F_{sv} = \frac{π \cdot μ \cdot l_{6} \cdot d_{6} \cdot v_{v}}{\sqrt{1 - ε^{2}} \cdot h_{5}} + \frac{π \cdot μ \cdot l_{7} \cdot d_{7} \cdot v_{v}}{\sqrt{1 - ε^{2}} \cdot h_{5}} \\ F_{lv} = Δ p_{5} \cdot τ_{2} \cdot l_{6} \cdot d_{6} + Δ p_{6} \cdot τ_{2} \cdot l_{7} \cdot d_{7} \end{matrix}

(6)

where l_i is reversing spool and body mating length; d_i is reversing spool and body mating diameter; h₅ is the reversing spool and body unilateral clearance.

{\begin{matrix} \frac{V_{30} + A_{6} x_{v}}{K_{iig}} \cdot \frac{d P_{1}}{dt} = Q_{1} - A_{6} v_{v} - Q_{l 5} - Q_{u 1} - Q_{2} - Q_{4} \\ \frac{V_{50} - A_{6} x_{v}}{K_{iig}} \cdot \frac{d P_{2}}{dt} = C_{8} Q_{h} + A_{6} v_{v} - Q_{l 5} - Q_{3} - Q_{2} \\ \frac{V_{40} - A_{1} x_{v}}{K_{ig}} \cdot \frac{d P_{3}}{dt} = Q_{u 2} + A_{1} v_{v} - Q_{l 5} \\ \frac{V_{60} - A_{7} x_{v}}{K_{iig}} \cdot \frac{d P_{4}}{dt} = C_{11} Q_{q} + A_{7} v_{v} + Q_{4} - Q_{5} - Q_{l 5} \end{matrix}

(7)

where x_v is the reversing valve displacement; Q₁ is the flow rate of the normal chamber in the reversing valve; Q_u₁ is the flow rate of the normal chamber between the reversing valve and the cylinder body; Q₂ is the valve port flow rate between normal chamber and left valve chamber in the reversing valve; Q₄ is the valve port flow rate between the normal chamber and right valve chamber in the reversing valve; Q₃ is the valve port flow rate between the left valve chamber and left return chamber in the reversing valve; Q_u₂ is the flow rate of the control chamber between the cylinder body and the reversing valve; Q₅ is the valve port flow rate between the right valve chamber and right return chamber in the reversing valve.

Among them,

Q_{i} = C_{d} π D_{i} B \sqrt{\frac{2 Δ p}{ρ}}

(8)

where Q_i (i = 2, 3, 4, 5) is the valve port flow rate; C_d is the valve port flow coefficient; D_i is the spool outer diameter; B is the spool movement distance; ρ is the hydraulic oil density.

Dynamics model of high-pressure accumulator

Gas pressure fluctuations and high-pressure oil fluctuations in the high-pressure accumulator coexist in dynamic equilibrium. Given the brief duration of hydraulic fluid inflow and outflow caused by the impact piston, the gas pressure energy conversion within the high-pressure accumulator can be approximated as an adiabatic, isentropic process. As a result, a gas state equation specific to the high-pressure accumulator has been formulated, as demonstrated in equations (9) and (10).

P_{x} V_{a}^{1.4} = P_{H} V_{H}^{1.4}

(9)

Among them,

V_{a} = V_{H} - \int_{0}^{t} Q_{H} dt

(10)

where P_x is the gas chamber pressure; V_a is the gas chamber volume; P_H is the gas pre-charge pressure; V_H is the initial volume; Q_H is the flow rate of the connecting pipe.

Dynamics model of collision rebound

After the piston impacts the shank, it does not come to a stop, but rebounds directly. The characteristics of the piston, shank, and rock affect the impact rebound velocity. When the displacement at the interface of the piston and shank collision induced by the reflected wave exceeds 0, the piston undergoes a rebound. When certain conditions are met, the piston rebounds. Generally, one-dimensional wave theory is used for analysis, as shown in equation (11). When the displacement at the interface of the piston and shank collision caused by the reflected wave is greater than 0, the piston rebounds. The rebound criterion is shown in equations (12) and (13), and the formula for rebound velocity is shown in equation (14).

Q = {\begin{matrix} \frac{1}{2} m v_{0} (1 - 2 e^{- β t}), 0 < t \leq τ \\ m v_{0} (1 - e^{- 2 / γ}) e^{α β (t - τ)}, t > τ \end{matrix}

(11)

2 / γ + 2 (1 - 1 / α) (e^{- 2 / γ} - 1) > 0

(12)

γ = \frac{m^{2}}{m_{p} K}

(13)

\begin{matrix} v_{e} = \\ {\begin{matrix} \frac{v_{0} γ}{2 α} [(\frac{2}{γ} - 1.6) α + 4 α (e^{- \frac{2}{γ}} - e^{- 1.6}) + 2 (1 - e^{- \frac{2}{γ}}) (1 - e^{- 1.6 α})], γ \leq 1.25 \\ \frac{v_{0} γ}{2 α} (e^{- \frac{2 α}{γ}} - 1) [2 (e^{- \frac{2}{α}} - 1) (1 - α) - \frac{2 α}{γ}], γ > 1.25 \end{matrix} \end{matrix}

(14)

where Q is the force value of the reflected wave; m is the wave impedance of the piston and shank; α is the loading stiffness of the rock; K is the loading stiffness of the rock; t is the time; τ is the duration; γ is the characteristic quantity related to the rebound velocity; β is the ratio of piston mass to rock stiffness; m_p is the piston mass; v₀ is the impact velocity; v_e is the rebound velocity.

Analysis of Simulink simulation results

The Simulink tool is utilized to solve the dynamic model, employing the Runge-Kutta algorithm, with a simulation time of 3 s. The simulation input parameters are listed in Table 4 in the appendix. The Simulink model diagram is depicted in Figure 3. Figure 4(a) illustrates the displacement and velocity curves of the piston and reversing valve, while Figure 4(b) displays the pressure curves of the front and rear chambers, and the signal chamber. The analysis unveils the following:

The motion of the piston encompasses three phases: retrograde acceleration, retrograde deceleration, and impulsive stroke acceleration. After the piston first impacts the chisel tail, it rebounds for a duration of 0.00025 ms. At this moment, the impact stroke switching is not yet complete, resulting in a secondary impact of the piston. The piston has a certain penetration depth, so the impact point is not at the maximum stroke.

The impact time of the piston occurs earlier than the directional balance point. After rebounding, it impacts the rear chamber, reaching a peak pressure of 7 MPa. Owing to the clearance fit existing between the piston and the cylinder, there is a consequential leakage of oil in the signal chamber, thereby complicating the maintenance of pressure. During the return stroke switching, a pressure shock ensues, characterized by a peak value of 13 MPa.

Hydraulic rock drills with alternating front and rear return chambers exhibit fast response characteristics, with the piston returning within 0.7 ms of impact. The reversing valve accomplishes the impact stroke switching in 2.7 ms and the return stroke switching in 2.5 ms.

Figure 3.

The diagram of the Simulink model.

Figure 4.

Simulation results of the impact system: (a) displacement, velocity curves of the piston and reversing valve; (b) pressure curves of the front and rear chambers.

Analysis of the influence of structural parameters

The effect of the advance amount of the return signal chamber

Following an examination of the motion characteristics of the impact piston, it has been determined that the impact performance is below the specified design parameters.¹⁹ The piston stroke exceeds the maximum design stroke and the impact point is ahead of the pressure balance point during impact stroke. The advance amount of the return signal chamber is the key factor for evaluating the stroke amount. Taking into account factors such as the reversal time of the spool and the propagation speed of the oil in the channel, we establish a model for the advance amount of the return signal chamber based on the three-stage method, as illustrated in equations (15) and (16). The maximum design stroke of the piston is shown in equation (17). Through numerical calculations, the maximum design stroke is set at 57 mm, and the advance amount of the return signal chamber is set between 26.5 and 30.5 mm.

The velocity, displacement and pressure curves of the impact piston are obtained through simulation, as shown in Figure 5. When the advance amounts are 26.5, 28.5, and 30.5 mm respectively, the impact point velocities are 7.507, 7.740, and 7.705 m/s, the impact frequencies are 43, 41, and 37 Hz, and the impact powers are 13.933, 14.123, and 12.630 kW, respectively. As the advance amount rises, there is a notable elevation in the return acceleration stroke, impact point velocity, and a decrease in impact frequency. However, an excessive stroke leads to insufficient flow replenishment, causing decreased pressure and reducing piston acceleration. Considering multiple factors, an advance amount of 28.5 mm is identified as the optimal parameter for achieving the desired impact power.

S_{R} = \frac{a_{r} {(t_{r 1} - t_{v})}^{2}}{2} = \frac{a_{r} {(1 - k_{v})}^{2} t_{r 1}^{2}}{2} = (1 - k_{v})^{2} S_{r 1}

(15)

k_{v} = t_{v} / t_{r 1}

(16)

S_{max} = \frac{1}{4} v_{p} T

(17)

where S_R is the advance amount of the return signal chamber; a_r is the return acceleration; t_r₁ is the accelerated return time of the piston; t_v is the time for the reversing valve to switch direction during return; k_v is the directional switching coefficient of the reversing valve during return, 0.12–0.18; S_r₁ is the accelerated return distance; S_max is the maximum stroke; v_p is the impact velocity; T is the period of the motion.

Figure 5.

Simulation results of the impact system with different S_R values: (a) displacement and velocity curves of the impact piston; (b) pressure curves of the front-chamber and rear-chamber.

The effect of the gas pre-charge pressure of the high-pressure accumulator

With the gas pre-charge pressure, the high-pressure accumulator oil chamber accumulates oil energy when the power system supply can fulfill the high-frequency movement requirements of the impact system. When there is no flow in the shock system, the accumulator releases oil to replenish the energy, preventing the stroke amount from being too large and causing insufficient flow compensation. This improves the response speed of directional changes, thereby eliminating the impact gap phenomenon. Within the same cycle, the gas pressure in the accumulator undergoes steady changes, while the pressure in the impact system experiences sharp fluctuations.^26–28 Numerical model of the diaphragm accumulator is established based on Boyle’s Law to analyze its dynamic characteristics, as shown in equation (18). The transfer function between oil pressure and gas chamber pressure is shown in equation (19).

After the rock drill is started, the diaphragm in the accumulator undergoes an overturning motion as the impact pressure rises. This results in an augmentation of the oil chamber space and a reduction in the gas chamber space, continuing until the rock drill attains its maximum pressure. Therefore, the minimum pressure in the impact system should not be lower than the gas pre-charge pressure. For hydraulic rock drills, the gas pre-charge pressure should be between 35% and 45% of the impact pressure. Through numerical calculations, the gas pre-charge pressure is set at 6–8 MPa.

Figure 6 presents velocity curves of the piston and flow rate curves of the accumulator connecting pipe under different P_H values. Figure 7 illustrates pressure curves of the front and rear chambers corresponding to varying P_H values. When the charging pressures are 6, 7, and 8 MPa, the impact point velocities are 6.996, 7.040, and 7.140 m/s, and the total strokes are 55.731, 55.986, and 56.423 mm, respectively. Elevated pre-charge pressure simultaneously increases impact velocity, impact frequency and piston stroke. This results in a shortened time to peak pressure of the front and rear chambers, an augmented peak flow in the connecting pipe, and a faster response from the accumulator. However, excessively high P_H values induce a significant hydraulic impact effect, elevating the resonant frequency and causing intense vibration. Considering all factors, a P_H value of 8MPa is determined as providing the optimal impact power.

\frac{dp}{dt} = - \frac{1}{ε_{c} V_{H}} \cdot \frac{d (Δ V)}{dt} = - \frac{Q_{H}}{ε_{c} V_{H}}

(18)

G (j ω) = \frac{2 p_{0}}{Q_{H}} \frac{ω_{a}^{2} + 2 ζ_{1} (j ω) - ω^{2}}{ω_{a}^{2} + 2 ζ_{2} (j ω) - ω^{2}}

(19)

where ε_c is the compressibility coefficient; ΔV is the volume compression of the oil; p is the connected pipe pressure; V_H is the initial volume; Q_H is the flow rate of connecting pipe; p₀ is the oil pressure; ω_a is the natural frequency of the accumulator; ζ₁ is the damping ratio of the differential component; ζ₂ is the damping ratio of the oscillatory component; ω is angular frequency of flow pulsations in the connected pipe.

Figure 6.

Simulation results of the impact system with different P_H values: (a) velocity curves of the piston; (b) flow rate curves of the accumulator connecting pipe.

Figure 7.

Simulation results of the impact system with different P_H values: (a) pressure curves of the front chamber; (b) pressure curves of the rear chamber.

Experiment engineering and improvement verification

Comprehensive laser experiment setting

Owing to the limited accuracy and measurement challenges of traditional rock drill testing methods like the stress wave method, a high-precision, non-contact system for testing impact performance, specifically designed for rock drills, has been developed.²⁹ The core of this system features a laser displacement sensor. The purity of the sensor is 100,000 times greater than traditional monochromatic light sources such as Krypton-86 lamps, making it a high-brightness, directional light source. The laser sensor’s high measurement accuracy is derived from its working principle, which is based on the geometric principle of similar triangles. It captures motion signals of objects, enabling the measurement of high-frequency, high-speed piston movements with up to 0.02% precision. The sensor’s internal components include a laser diode, a photosensitive plate, lenses, and filters. A converging lens helps the laser diode project a light spot onto the surface of the object under measurement. A light spot reflected from the object surface is captured by a light-sensitive plate through a precise receiving lens, and the data is then transmitted to a computer.

As depicted in Figure 8, the laser testing system is composed of a laser sensor, a hydraulic rock drill, pressure sensors, an impact cylinder, a hydraulic pump station, an LMS SCADAS Mobile data acquisition instrument, and a computer. The laser displacement sensor is employed for measuring the displacement of the impact piston. An impact cylinder is utilized to simulate the stiffness and hardness of rock. The hydraulic rock drill is connected to the piston rod of the impacted hydraulic cylinder by the drill bit sleeve, which ensures axial alignment. Pressure sensors are responsible for monitoring pressures in the front, rear, and signal chambers of the rock drill, and the rock drilling site is illustrated in Figure 9.

Figure 8.

Schematic diagram of laser test system.

Figure 9.

Scene diagram of the rock drilling test.

Data analysis

Table 1 exhibits the experimental conditions for the laser method. Table 2 provides a comparison between the design parameters and experimental results of the hydraulic rock drill. Figure 10 illustrates the velocity and pressure curves of the impact piston in the front and rear chambers. Figure 11 depicts the displacement of the impact piston and the pressure curves of the signal chamber. The following observations can be made:

As shown in Figure 10, the piston undergoes a rebound upon impacting the tail of the drill bit, as the impact transpires ahead of the equilibrium point between the front and rear chamber pressures prior to its directional change. Subsequently, the piston decelerates upon encountering the oil cushion in the rear chamber. Upon completing the directional change, it accelerates during its return stroke.

During the initial phase of return acceleration, the oil produces a violent shock between the front and rear chambers. This directional impact induces pressure fluctuations in the front chamber, reaching a peak of 23 MPa. When the return signal hole opens in the front chamber, the volume of the front chamber increases and the inlet port becomes smaller resulting in a drop in pressure. The piston squeezes the rear chamber causing the pressure to rise up to 7 MPa.

Upon the opening of the stroke signal hole, the rear chamber’s volume increases, and its pressure decreases due to the narrowing of the inlet, resulting in a spike in the front chamber pressure, peaking at 5 MPa. Following this, the piston rebounds from striking the drill bit’s tail, compressing the rear chamber and causing a pressure increase to approximately 25 MPa. The increase in the front chamber’s volume leads to a pressure trough, approximately 0 MPa.

In Figure 11, it is observed that during the return acceleration, the piston’s accelerated movement compresses the signal hole, causing substantial fluctuations peaking at 40 MPa. The piston advances to 22.3 mm, resulting in a sharp decrease in the pressure within the signal chamber. Although the design stipulates that the signal hole should open at 26.5 mm during the return stroke, high-pressure oil leakage causes premature oil return in the signal chamber. The duration of the directional change in the return stroke is 3.2 ms.

During the stroke acceleration phase, the stroke signal orifice attains the high-pressure oil at a distance of 2 mm. Although the design prescribes an oil intake of 8 mm, the temporal delay in hydraulic fluid ingress into the chamber results in a lag in oil uptake. The directional change time of the impact stroke is 2.2 ms. Following the piston’s strike and rebound from the drill bit’s tail, the normal pressure oil chamber closes, leading to a rapid decrease in the signal chamber pressure to 9 MPa.

Table 1.

Experimental condition setting.

Condition name	Set value
Supply flow rate/(L/min)	140
Gas pre-charge pressure of high-pressure accumulator/MPa	6
Relief valve set pressure/MPa	18
Laser sensor position/mm	286
Pipe diameter/mm	26
Sampling frequency/kHz	10
Piston weight/kg	11.5

Table 2.

Comparison table of design and experimental values for impact performance.

Parameter name	Design value	Experimental value
Stroke/mm	47	47.8
Impact velocity/(m/s)	8.3	7.2
Impact energy/J	400	298.1
Impact frequency/Hz	40	38
Impact power/kW	16	11.3

Figure 10.

Pressure and velocity curves by experiment: (a) pressure curves of the front and rear chambers and velocity curves; (b) enlarged curves from panel (a).

Figure 11.

Displacement, velocity and pressure of the signal chamber curves by experiment.

Verification of improvement effects

Based on the analysis of influencing factors, the optimal enhancement approach determines the maximum design stroke of the piston at 57 mm, the advance amount of the return signal chamber at 28.5 mm, and the gas pre-charge pressure of the high-pressure accumulator at 8 MPa, as detailed in Table 3. Displacement and velocity curves pre-enhancement and post-enhancement are acquired through laser experimentation, as depicted in Figure 12. Post-improvements, there is an augmentation in impact energy, a reduction in impact frequency, and an elevation in impact power. The piston remains within its prescribed maximum design stroke, successfully addressing the issue of insufficient impact power. Pressure fluctuations in both the front and rear chambers diminish, and the responsiveness to oil replenishment improves. The volume and pressure in the rear chamber increase, leading to amplified return braking and stroke acceleration. During piston rebound, compression by high-pressure oil in the rear chamber results in a lower rebound velocity compared to the pre-improvement state. In conclusion, the impact energy and power align with the nominal data, affirming the further improvement of the rock drill.

Table 3.

Structural parameters before and after improvement.

Parameters	S_max/mm	S_R/mm	P _H/MPa
Before improvement	47	26.5	6
After improvement	57	28.5	8

Figure 12.

Velocity and displacement curves before and after improvement by experiment.

Conclusion

This research establishes a dynamic numerical model for the hydraulic rock drill under load, investigating the impact of stroke amount and flow compensation factors on its performance. By integrating experimental data acquired through laser techniques, the high frequency characteristics of the impact system are evaluated. Optimal parameters are chosen to validate the enhanced impact performance. The primary conclusions derived from this investigation are as follows:

(1) Considering factors such as hydraulic clamping force, fluid leakage, and rock properties, an impact system dynamics model is established. The research reveals that a secondary impact phenomenon occurs when the piston switches direction prematurely, and the piston has a certain degree of penetration displacement. The trapped oil zone contributes to the instant deceleration of the reversing valve without causing it to rebound.

(2) The influencing factors include the advance amount of the return signal chamber and the gas pre-charge pressure of the high-pressure accumulator. The study determines that as the advance amount increases, there is a corresponding increase in the impact point velocity. However, excessive stroke leads to insufficient flow replenishment, reducing piston acceleration and impact frequency. As the charging pressure increases, the impact velocity and impact frequency increase. With the total stroke increases, the time for the front and rear chamber pressures to rise to peak values is shortened, and the response of the accumulator is faster.

(3) A non-contact rock drilling experiment using lasers is designed, which has strong anti-interference capabilities and high testing accuracy. Synchronous sampling acquires data pertaining to the piston displacement, pressures within the anterior and posterior chambers, as well as the signal chamber. It is found that the impact point occurs before the balance point of the pressure during stroke. The piston exceeds the total stroke, impacts the shell during the return, and rebounds after impacting the drill tail during the stroke, resulting in peak pressures up to 25 MPa in the front and rear chambers. Due to fluid leakage, the pressure in the signal chamber fluctuates significantly. By considering various factors, the optimal improvement method is determined with S_max at 57 mm, S_R at 28.5 mm, and P_H at 8 MPa. The results indicate that the piston satisfies the prescribed total stroke amount, resulting in a 39.3% increase in impact energy and a corresponding enhancement of 28.3% in impact power.

Footnotes

Appendix

Table 4.

Structural parameters of the impact system in simulation.

Parameters	Value	Parameters	Value
Q/(L/min)	140	l/mm	100
P _H/MPa	6	l ₁/mm	47.5
V _H/mL	208	l ₂/mm	27
P _L/MPa	1.5	l ₃/mm	81
V _L/mL	208	l ₄/mm	43
m _p/kg	11.5	l ₅/mm	6.1
m _v/kg	0.5	l ₆/mm	8
d ₀/mm	3	l ₇ /mm	5
d ₁/mm	83	h ₁, h₂, h₃, h₄/mm	0.01
d ₂/mm	78	h ₅/mm	0.05
d ₃/mm	81	d/mm	10
d ₄/mm	75	ρ/(kg/m³)	0.85 × 10³
d ₆/mm	37	v/(m²/s)	4.58 × 10⁻⁵
d ₇/mm	35	μ/kg·(m·s)⁻¹	3.893 × 10⁻²
C _d	0.6	τ ₁	0.209
τ ₂	0.261	ε	0.9
K_iig/MPa	700	Λ	0.1
f	0.05	ζ	1

Acknowledgements

First and foremost, we would like to express our heartfelt gratitude to all those who have contributed to the successful completion of this journal. Furthermore, we are also extremely grateful to our esteemed reviewers for their thorough evaluation, constructive feedback, and expert guidance throughout the peer review process. Last but not least, we thank all the editors for their dedication, hard work, and commitment to advancing knowledge in our field.

Handling Editor: Tianshou Ma

Author contributions

Siyuan Chang: Conceptualization, Methodology, Software, Validation, Writing – original draft. Min Ye: Funding support and Review and Editing. Daqing Zhang: Funding support and Review. Yuchuan Ma: Investigation, Data curation. Jiale Zhang: Review.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by Key Research and Development Program of Shaanxi Province (2023-YBSF-104).

ORCID iDs

Siyuan Chang

Min Ye

References

Hashiba

Fukui

. Review of theoretical, experimental, and numerical studies on rotary percussive rock drilling. Int J Mining Reclam Environ 2024; 38: 167–191.

Liu

Zhao

Zhu

, et al. Review, classification and structural analysis of downhole robots: core technology and prospects for application. Robot Autonom Syst 2019, 115: 104–120.

Wang

Sun

, et al. Field application of non-blasting mechanized mining using high-frequency impact hammer in deep hard rock mine. Trans Nonferrous Met Soc China 2022; 32: 3051–3064.

Wang

, et al. Development of rockburst research: a comprehensive review. Appl Sci 2022; 12: 974.

Tao

Pan

Tang

, et al. Current status and geological conditions for the applicability of CBM drilling technologies in China: a review. Int J Coal Geol 2019; 202: 95–108.

Yang

Guo

, et al. Analysis and optimization of the working parameters of the impact mechanism of hydraulic rock drill based on a numerical simulation. Int J Prec Eng Manuf 2017; 18: 971–977.

Yong

Deshun

Shuyi

, et al. Hydraulic–mechanical coupling modeling by bond graph for impact system of a high frequency rock drill drifter with sleeve distributor. Autom Constr 2016; 63: 88–99.

Cui

Xiao

, et al. Study on the Influence of fluid pulsation on hydraulic impactor performance in drilling engineering. Processes 2023; 11: 2392.

Liu

Chang

. Experimental research on the influence of working parameters on the drilling efficiency. Tunnel Undergr Space Technol 2020; 95: 103174.

10.

Geng

, et al. Cavitation erosion of the damping piston in double damping system of hydraulic rock drill and its influencing factors. AIP Adv 2018; 8: 115025.

11.

Lundberg

Okrouhlik

. Influence of 3D effects on the efficiency of percussive rock drilling. Int J Impact Eng 2001; 25: 345–360.

12.

Song

Chung

Kim

, et al. Design optimization of a drifter using the Taguchi method for efficient percussion drilling. J Mech Sci Technol 2017; 31: 1797–1803.

13.

Shi

. Impact characteristics of a bidirectional pneumatic DTH hammer for unconsolidated formations. Appl Sci 2023; 13: 11797.

14.

Geng

Jia

, et al. Percussion characteristic analysis for hydraulic rock drill with no constant-pressurized chamber through numerical simulation and experiment. Adv Mech Eng 2019; 11: 1687814019841486.

15.

Stosiak

Karpenko

Prentkovskis

, et al. Research of vibrations effect on hydraulic valves in military vehicles. Defence Technol 2023; 30: 111–125.

16.

Kim

Cho

, et al. Design study of impact performance of a DTH hammer using PQRSM and numerical simulation. J Mech Sci Technol 2019; 33: 5589–5602.

17.

Yang

Zheng

, et al. Dynamic simulation and test research of impact performance of hydraulic rock drill with no constant-pressurized chamber. Autom Constr 2014; 37: 211–216.

18.

Iphar

. ANN and ANFIS performance prediction models for hydraulic impact hammers. Tunnel Undergr Space Technol 2012; 27: 23–29.

19.

Liu

Chang

. Drilling performance of rock drill by high-pressure water jet under different configuration modes. Shock Vibr 2017; 2017: 5413823.

20.

Liang

, et al. Theoretical analysis and design of hydro-hammer with a jet actuator: an engineering application to improve the penetration rate of directional well drilling in hard rock formations. PLoS One 2018; 13: e0196234.

21.

. Research on the matching of impact performance and collision coefficient of hydraulic rock drill. Shock Vibr 2021; 2021: 1–13.

22.

Luo

. Fault diagnosis research on impact system of hydraulic rock drill based on internal mechanism testing method. Shock Vibr 2018; 2018: 4928438.

23.

Yin

Xia

Han

. Leakage simulation of the impactor of hydraulic rock drill. Adv Mater Res 2013; 744: 113–117.

24.

Seo

Noh

Lee

, et al. A percussion performance analysis for rock-drill drifter through simulation modeling and experimental validation. Int J Prec Eng Manuf 2016; 17: 163–170.

25.

Zhang

Jiang

, et al. Analysis and testing of load characteristics for rotary-percussive drilling of lunar rock simulant with a lunar regolith coring bit. Shock Vibr 2017; 2017; 3012749.

26.

Ahn

. Modeling and simulation of hydrostatic transmission system with energy regeneration using hydraulic accumulator. J Mech Sci Technol 2010; 24: 1163–1175.

27.

Mamèic

Bogdevièius

. Simulation of dynamic processes in hydraulic accumulators. Transport 2010; 25: 215–221.

28.

Pourmovahed

Baum

Fronczak

, et al. Experimental evaluation of hydraulic accumulator efficiency with and without elastomeric foam. J Propul Power 1988; 4: 185–192.

29.

Wen

, et al. Using an acoustic sensor and accelerometer to measure the downhole impact frequency of a hydraulic impactor. J Nat Gas Sci Eng 2015; 27: 1296–1303.