A sensor network layout method for monitoring damage of solid rocket motor casing

Abstract

This invention discloses a sensor network deployment method for solid rocket motor case damage monitoring, specifically targeting the barrel section of a solid rocket motor case. The monitoring experiment uses a piezoelectric (PZT) sensor as the excitation and a fiber optic (FBG) sensor as the receiver. Post-processing employs a probabilistic imaging method to locate damage. This method achieves blind-spot monitoring of the barrel section of a solid rocket motor case, and can locate delamination damage greater than 40 mm in diameter using a probabilistic imaging method based on guided waves.

Description

Technical Field

[0001] The present invention belongs to the technical field of health detection, and in particular relates to a method for distributing a sensor network for monitoring damage of a solid rocket engine casing. Background Art

[0002] Solid rocket motor casings operate in complex environments and have unique failure modes, which places high demands on their damage monitoring technology: the monitoring system should be able to promptly identify damage in the casing, have strong anti-electromagnetic interference capabilities and measurement stability and reliability, and the number of sensors and demodulators should be as small as possible and the size should be as small as possible to avoid affecting the normal operation of the casing.

[0003] Ultrasonic guided wave technology offers the advantage of detecting minute damage, and it can generate ultrasonic waves using low-cost piezoelectric sensors and minimal energy. Furthermore, guided waves can propagate over long distances with minimal attenuation, enabling coverage of large areas with relatively few sensors. Ultrasonic guided wave technology has attracted widespread attention from researchers due to its high sensitivity, wide monitoring range, and relatively high positioning accuracy.

[0004] Researchers at home and abroad have conducted extensive research on composite structural health monitoring methods based on ultrasonic guided waves. Castaings et al. (France) investigated the influence of impact damage size on S0 mode guided wave signals in composite flat plates and found that ultrasonic guided waves can quantitatively detect the size of delamination damage in composites. Luca et al. (Italy) studied the interaction between low-velocity impact damage characteristics and guided waves in composites. They concluded that the damage patterns of composites caused by impact are complex, and guided waves can lead to inaccurate or inaccurate damage localization. The mechanism of this interaction requires further investigation. Based on these studies, Fenza et al. (Italy) determined the location and extent of damage in composite laminates and established a correlation between guided wave characteristics and laminate damage index. Harb et al. (France) used a non-contact air probe and a laser ultrasonic generator to excite Lamb waves dominated by the A0 mode in composite laminates. They then used guided waves in this mode to detect damage in the laminates. The results demonstrated that both excitation methods offer high sensitivity and efficiency. Based on this research, Ramadas et al. and Schaal et al. investigated Lamb wave propagation in composite T-joints and variable-thickness composite plates, respectively, and discussed in detail the mechanisms by which interfacial delamination and thickness variations in T-joints influence ultrasonic guided waves. Using three-dimensional finite element simulations and experimental techniques, Yang et al. investigated the influence of composite bolted joint configuration, number of connection holes, and load on guided wave propagation, establishing a correlation between guided wave signatures and joint failure modes.

[0005] As can be seen, extensive research has been conducted on damage monitoring of composite structures using ultrasonic guided waves. However, most of this research has focused on simple structures such as flat or stiffened panels. There is less research on structural damage in solid rocket motor casings, and the corresponding sensor network layout method remains to be studied. Summary of the Invention

[0006] To overcome the shortcomings of existing technologies, the present invention provides a sensor network deployment method for solid rocket motor case damage monitoring, specifically targeting the barrel section of a solid rocket motor case. The monitoring experiment uses a piezoelectric (PZT) sensor as the excitation and a fiber optic (FBG) sensor as the receiver. Probabilistic imaging is employed in post-processing to locate damage. This method achieves blind-spot monitoring of the barrel section of a solid rocket motor case and can locate delamination damage greater than 40 mm in diameter using a waveguide-based probabilistic imaging method.

[0007] The technical solutions adopted by the present invention to solve the technical problems are as follows:

[0008] Step 1: Select the piezoelectric plate size and fiber grating length;

[0009] Step 2: Attach a piezoelectric patch to the solid rocket motor casing and attach fiber optic sensors at different distances from the piezoelectric patch along the circumference of the casing. Perform a set of experiments using the same excitation signal frequency and amplitude, monitoring the amplitude and signal quality of each received signal to determine the range of the circumferential length of the sensing path.

[0010] Step 3: Make the axial distance between sensors equal to the distance between sensor groups to determine the number of sensors in each group;

[0011] Step 4: Measure the circumference and axial length of the shell monitoring area and determine that the distance between sensor groups is 1 / 2 of the circumferential length of the sensing path; divide the circumference of the shell monitoring area equally while meeting the circumferential length range measured in step 2, and determine the number of sensors in each group and arrange them evenly according to the method in step 3;

[0012] Step 5: Take the shell specimen to be tested and arrange the sensor network on the specimen according to the designed network distance; evenly arrange PZT sensors as excitation and FBG sensors as reception around the circumference of the shell, alternating between two groups of PZTs and two groups of FBGs in the circumferential direction, that is, there are four groups of sensors in one cycle. In the experiment, PZTs and FBGs separated by one sensor are used for damage monitoring experiments.

[0013] Step 6: Paste all sensors and cure them at room temperature for about 8 hours to ensure that the PZT sensor, FBG sensor grid area and the shell are firmly attached; connect the experimental system and check whether the signal can be stimulated and received normally;

[0014] Step 7: Select the monitoring area and adjust the wavelength of each FBG sensor within the monitoring area. Use the NI signal generator to output a Hanning window modulated sinusoidal signal to excite the PZT. Simultaneously, use the FBG sensor to receive the signal. Collect the signal of each excitation-sensing path in the monitoring area as a reference signal and save the signal data file.

[0015] Step 8: Apply coupling agent and place a simulated damage anywhere in the specimen monitoring area. Record the location of the simulated damage. Using the same experimental conditions as step 7, collect the signal of each excitation-receiving path under the damage state and save the signal data file.

[0016] Step 9: For each stimulus-receive path, use the measured reference signal and impairment signal to calculate the impairment index SDC as the reference impairment index, denoted as DI. The SDC index is determined by the following formula:

[0017]

[0018] Among them, b i represents the reference signal of path i, c i represents the monitoring signal of path i, and N represents the number of waveguide signal data points; represents the average value of the reference signal of path i, represents the average value of the monitoring signal of path i;

[0019] Step 10: Assume that the sensor network has n excitation-receiving sensing paths. Divide the rectangular monitoring area into several discrete pixels. Use the following formula to calculate the distance R from any pixel position (x, y) to the nth sensing path: n (x,y):

[0020]

[0021] Where: D n is the distance between the actuator and the receiver in the nth sensing path, that is, the distance between the PZT and the FBG; D an (x,y) and D sn (x, y) are the distances from the pixel point (x, y) to the PZT and FBG respectively;

[0022] Step 11: According to the distance R from the pixel point (x, y) to the nth sensing path n (x, y), calculate the weight factor W of this point relative to the nth sensing path n , as shown below:

[0023]

[0024] Where: β is a parameter that controls the size of the damage factor impact area of ​​a single path. It is an elliptical area with the sensor FBG and the actuator PZT as the focus, indicating the maximum range of damage impact. The damage probability beyond this range is zero.

[0025] Step 12: Calculate the probability of damage at each pixel (x, y), which can be expressed as follows:

[0026]

[0027] Where DI is the damage factor on the nth sensor path, W n [R n (x, y)] is the damage probability weighted distribution function that maps the damage factor value to the pixel point (x, y); p n (x,y) represents the damage probability value brought to point (x,y) by the nth sensing path;

[0028] Step 13: Display the damage probability of each pixel in the monitoring area in the form of an image. The point with the maximum probability is the monitored simulated damage location. Adjust the threshold to display the maximum damage location.

[0029] Step 14: Perform the monitoring process from step 2 to step 8 on each monitoring area of ​​the shell to conduct comprehensive damage monitoring on the shell.

[0030] Preferably, the diameter of the piezoelectric sheet is 10 mm.

[0031] Preferably, the fiber grating length is 10 mm.

[0032] Preferably, in step 6, epoxy structural adhesive is used to adhere all sensors.

[0033] The beneficial effects of the present invention are as follows:

[0034] The present invention uses a sensor networking method with two groups of excitation and two groups of reception interleaved. The blind spots in the sensor axis area are covered by the interleaving of monitoring areas, thereby realizing blind-spot-free monitoring of the barrel section of the solid rocket motor casing. The probabilistic imaging method based on guided waves can be used to locate delamination damage with a diameter greater than 40 mm. Most monitoring areas can be covered twice by a sensor network composed of different sensors, making the networking scheme tolerant to sensor damage. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 A physical diagram of the experimental system used in the present invention;

[0036] Figure 2 This is a schematic diagram of the sensor network solution of the present invention;

[0037] Figure 3 This is a physical map of the monitoring area in the embodiment of the present invention;

[0038] Figure 4 This is the imaging result of the damage localization according to the embodiment of the present invention. DETAILED DESCRIPTION

[0039] The present invention will be further described below with reference to the accompanying drawings and examples.

[0040] The purpose of the present invention is to propose a sensor networking method for monitoring damage to solid rocket engine casings. This method solves the current problem of lack of a sensor networking method for monitoring damage to solid rocket engine casings. The proposed networking method has comprehensive monitoring range and fault tolerance to sensor damage, and realizes accurate positioning of simulated damage.

[0041] The purpose of the present invention is solved by the following technical solutions:

[0042] The barrel section of a solid rocket motor casing is often a vulnerable area for damage. Therefore, this study investigates damage monitoring for this section. The monitoring experiment uses a piezoelectric transistor (PZT) as the excitation and a fiber optic (FBG) sensor as the receiver. Post-processing employs probabilistic imaging to locate damage.

[0043] Step 1: Select the piezoelectric disc size and fiber grating length. While ensuring a good fit between the piezoelectric disc and the housing, select a piezoelectric disc with the largest possible diameter. Select a fiber optic sensor with a larger grating length (around 10 mm). Fibers with larger grating lengths receive larger amplitudes of guided wave signals when sensing the same guided wave strain field.

[0044] Step 2: Paste a piezoelectric plate on the shell, and paste optical fiber sensors at different distances from the piezoelectric plate along the circumferential direction. Perform a set of experiments using the same excitation signal frequency and amplitude, observe the amplitude and signal quality of each received signal, and thus determine the range of the circumferential length of the sensing path.

[0045] Step 3: Determine the axial distance between sensors, that is, determine how many sensors a group contains. The axial distance between sensors should be roughly the same as the distance between sensor groups.

[0046] Step 4: Measure the circumference and axial length of the shell monitoring area, and specifically determine the distance between sensor groups (1 / 2 of the circumferential length of the sensing path in step 2). Divide the circumference equally while meeting the circumferential length range measured in step 2. Use the same method to determine the number of sensors in each group and arrange them evenly.

[0047] Step 5: Take the shell specimen to be tested and arrange the sensor grid around it according to the designed grid spacing. PZT sensors (for excitation) and FBG sensors (for reception) are evenly arranged around the circumference of the shell, alternating between two PZT groups and two FBG groups, resulting in four sensor groups per cycle. The damage monitoring experiment uses PZTs and FBGs separated by one sensor.

[0048] Step 6: Use epoxy structural adhesive to stick all sensors together and cure them at room temperature for about 8 hours to ensure that the PZT sensor and FBG sensor grid area are firmly attached to the shell; connect the experimental system and check whether the signal can be stimulated and received normally.

[0049] Step 7: Select the monitoring area and adjust the wavelength of each FBG sensor within the area. Use the NI signal generator to output a Hanning window modulated sinusoidal signal to excite the PZT. Simultaneously, use the FBG sensor to receive the signal. Collect the signal of each excitation-sensing path in the monitoring area as a reference signal and save the signal data file.

[0050] Step 8: Apply coupling agent and place a simulated damage anywhere within the specimen monitoring area. Record the location of the simulated damage. Using the same experimental conditions as step 7, collect the signal of each excitation-receiving path under the damage state and save the signal data file.

[0051] Step 9: For each stimulus-receive path, use the measured reference signal and impairment signal to calculate the impairment index SDC as the reference impairment index, denoted as DI. The SDC index is determined by the following formula:

[0052]

[0053] Step 10: Assume that the sensor network has n excitation-receiving sensing paths. Divide the rectangular monitoring area into several discrete pixels. Use the following formula to calculate the distance R from any pixel position (x, y) to the nth sensing path: n (x,y):

[0054]

[0055] Step 11: According to the distance R from the pixel point (x, y) to the nth sensing path n (x, y), calculate the weight factor Wn of this point relative to the nth sensing path, as shown in the following formula:

[0056]

[0057] Where: β is a parameter that controls the size of the area affected by the damage factor of a single path. It is an elliptical area with the sensor FBG and the actuator PZT as the focus, indicating the maximum range of the damage impact. The probability of damage beyond this range is zero, and its value is based on certain experience.

[0058] Step 12: Calculate the probability of damage at each pixel (x, y), which can be expressed as follows:

[0059]

[0060] Step 13: Display the damage probability of each pixel in the monitoring area in the form of an image. The point with the maximum probability is the monitored simulated damage location. Adjust the threshold to display the maximum damage location.

[0061] Step 14: Perform the monitoring process from step 2 to step 8 on each monitoring area of ​​the shell to conduct comprehensive damage monitoring on the shell.

[0062] Example:

[0063] At a reduced ratio Taking a wound composite shell test piece as an example, the monitoring method of the present invention is further described in detail:

[0064] Step 1: Select the piezoelectric disc size and fiber grating length. To ensure a good fit between the piezoelectric disc and the housing, a piezoelectric disc with a diameter of 10 mm and a fiber optic sensor with a grating length of 10 mm were selected.

[0065] Step 2: Paste a piezoelectric plate on the shell, and paste optical fiber sensors at positions 100 mm, 150 mm, and 200 mm away from the piezoelectric plate along the circumferential direction. Use a 70 kHz Hanning window modulated sinusoidal signal as the excitation signal, observe the amplitude and signal quality of each received signal, and thus determine that the circumferential length of the sensing path ranges from 100 to 150 mm.

[0066] Step 3: Determine the axial distance between sensors, that is, determine the number of sensors in a group. The axial distance between sensors should be roughly equivalent to the distance between sensor groups (1 / 2 of the circumferential length of the path), approximately 50-75mm, to ensure the minimum number of sensors and the densest sensor network.

[0067] Step 4: Measure the circumference of the shell monitoring area to be 680mm and the axial length to be 200mm. Specifically, determine the inter-group distance of the sensors to be 56mm. This results in a circumferential length of the sensing path of 112mm, meeting the circumferential length range requirements measured in Step 2. Use the same method to determine the number of sensors per group to be three, evenly spaced.

[0068] Step 5: Take the shell specimen to be tested and arrange the sensor network on the specimen. Arrange PZT sensors and FBG sensors around the circumference of the shell, and alternately arrange two groups of PZT and two groups of FBG in the circumferential direction, that is, one cycle includes four groups of sensors. In the experiment, the damage monitoring experiment is carried out using PZT and FBG separated by one group of sensors. For example, in the monitoring Figure 2 For damage in the overlapping area of ​​the blue and red dashed lines, monitoring can be performed using either PZT group 1 and FBG group 1, or PZT group 2 and FBG group 2. For damage occurring along the sensor axis, monitoring experiments can also be performed using adjacent PZT-FBG sensor groups. The axial distance between each sensor group is 65 mm, and the circumferential spacing between sensor groups is 56 mm.

[0069] Step 6: Use epoxy structural adhesive to stick all sensors together and cure them at room temperature for about 8 hours to ensure that the PZT sensor, FBG sensor grid area and the housing are firmly attached; connect the experimental system and check whether the signal can be stimulated and received normally;

[0070] Step 7: Select the monitoring area and adjust the wavelength of each FBG sensor within the area. Use the NI signal generator to output a 3.5-cycle Hanning window modulated sinusoidal signal with a gain of 1.8 to excite the PZT. Simultaneously, use the FBG sensor to receive the signal. Collect the signal from each excitation-sensing path in the monitoring area as the reference signal. Take 128 averages of each signal and save the signal data file.

[0071] Step 8: Apply coupling agent to the axis of the FBG group in the middle of the monitoring area, 30 mm away from the edge FBGs, and place a 20 mm diameter weight block as a simulated damage. The simulated damage coordinates are (70, 40). Using the same experimental conditions as step 7, collect the signal of each excitation-receiving path in the damaged state. Similarly, average each signal 128 times and save the signal data file.

[0072] Step 9: For each of the nine stimulus-receive paths, use the measured reference signal and the impairment signal to calculate the impairment index SDC as the reference impairment index, denoted as DI. The SDC index is determined by the following formula:

[0073]

[0074] Step 10: The sensor network in the experiment has 9 excitation-receiving sensing paths. The rectangular monitoring area is divided into several discrete pixels. The distance R from any pixel position (x, y) to the nth sensing path is calculated using the following formula: n (x,y):

[0075]

[0076] Step 11: According to the distance R from the pixel point (x, y) to the nth sensing path n (x, y), calculate the weight factor Wn of this point relative to the nth sensing path, as shown in the following formula:

[0077]

[0078] Where β is a parameter that controls the size of the damage factor impact area of ​​a single path. It is an elliptical area with the sensor FBG and the actuator PZT as the focus, indicating the maximum range of the damage impact. The probability of damage beyond this range is zero. Its value is empirical and is taken as 0.097 here.

[0079] Step 12: Calculate the probability of damage at each pixel (x, y), which can be expressed as follows:

[0080]

[0081] Step 13: Display the damage probability of each pixel in the monitoring area in the form of an image. The point with the maximum probability is the monitored simulated damage location. Adjust the threshold to display the maximum damage location.

[0082] Step 14: Perform the monitoring process from step 2 to step 8 on each monitoring area of ​​the shell to conduct comprehensive damage monitoring on the shell.

Claims

1. A method for laying out a sensor network for monitoring damage to a solid rocket motor casing, characterized in that: The steps include: Step 1: Select the piezoelectric plate size and fiber grating length; Step 2: Attach a piezoelectric patch to the solid rocket motor casing and attach fiber optic sensors at different distances from the piezoelectric patch along the circumference of the casing. Perform a set of experiments using the same excitation signal frequency and amplitude, monitoring the amplitude and signal quality of each received signal to determine the range of the circumferential length of the sensing path. Step 3: Make the axial distance between sensors equal to the distance between sensor groups to determine the number of sensors in each group; Step 4: Measure the circumference and axial length of the shell monitoring area and determine that the distance between sensor groups is 1 / 2 of the circumferential length of the sensing path; divide the circumference of the shell monitoring area equally while meeting the circumferential length range measured in step 2, and determine the number of sensors in each group and arrange them evenly according to the method in step 3; Step 5: Take the shell specimen to be tested and arrange the sensor network on the specimen according to the designed network distance; evenly arrange PZT sensors as excitation and FBG sensors as reception around the circumference of the shell, alternating between two groups of PZTs and two groups of FBGs in the circumferential direction, that is, there are four groups of sensors in one cycle. In the experiment, the PZT and FBG sensors are separated by one sensor for damage monitoring. Step 6: Paste all sensors and cure them at room temperature for about 8 hours to ensure that the PZT sensor, FBG sensor grid area and the shell are firmly attached; connect the experimental system and check whether the signal can be stimulated and received normally; Step 7: Select the monitoring area and debug the wavelength of each FBG sensor in the monitoring area; Use the NI signal generator to output a Hanning window modulated sinusoidal signal to excite the PZT, and use the FBG sensor to receive the signal. Collect the signal of each excitation-sensing path in the monitoring area as the reference signal and save the signal data file. Step 8: Apply coupling agent and place a simulated damage anywhere in the specimen monitoring area. Record the location of the simulated damage. Using the same experimental conditions as step 7, collect the signal of each excitation-receiving path under the damage state and save the signal data file. Step 9: For each stimulus-receive path, use the measured reference signal and impairment signal to calculate the impairment index SDC as the reference impairment index, denoted as DI. The SDC index is determined by the following formula: Among them, b i represents the reference signal of path i, c i represents the monitoring signal of path i, and N represents the number of waveguide signal data points; represents the average value of the reference signal of path i, represents the average value of the monitoring signal of path i; Step 10: Assume that the sensor network has n excitation-receiving sensing paths. Divide the rectangular monitoring area into several discrete pixels. Use the following formula to calculate the distance R from any pixel position (x, y) to the nth sensing path: n (x,y): Where: D n is the distance between the actuator and the receiver in the nth sensing path, that is, the distance between the PZT and the FBG; D an (x,y) and D sn (x, y) are the distances from the pixel point (x, y) to the PZT and FBG respectively; Step 11: According to the distance R from the pixel point (x, y) to the nth sensing path n (x, y), calculate the weight factor W of this point relative to the nth sensing path n , as shown below: Where: β is a parameter that controls the size of the damage factor impact area of ​​a single path. It is an elliptical area with the sensor FBG and the actuator PZT as the focus, indicating the maximum range of damage impact. The damage probability beyond this range is zero. Step 12: Calculate the probability of damage at each pixel (x, y), which can be expressed as follows: Where DI is the damage factor on the nth sensor path, W n [R n (x, y)] is the damage probability weighted distribution function that maps the damage factor value to the pixel point (x, y); p n (x,y) represents the damage probability value brought to point (x,y) by the nth sensing path; Step 13: Display the damage probability of each pixel in the monitoring area in the form of an image. The point with the maximum probability is the monitored simulated damage location. Adjust the threshold to display the maximum damage location. Step 14: Perform the monitoring process from step 2 to step 8 on each monitoring area of ​​the shell to conduct comprehensive damage monitoring on the shell.

2. A solid rocket motor casing damage monitoring sensor network layout method according to claim 1, characterized in that: The diameter of the piezoelectric piece is 10 mm.

3. A solid rocket motor casing damage monitoring sensor network layout method according to claim 1, characterized in that: The length of the fiber grating is 10 mm.

4. A solid rocket motor casing damage monitoring sensor network layout method according to claim 1, characterized in that: In step 6, epoxy structural adhesive is used to stick all sensors together.

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