Steel fiber vibrating process and temperature control synchronous optimization method for segment production

Abstract

A steel fiber vibration process and temperature control synchronous optimization method for segment production belongs to the technical field of steel fiber concrete processing, and the method comprises the following steps: vibration sensors and temperature sensors are arranged on the chute of the hopper and the vibration head of the vibration table respectively to construct a multi-point sensing network covering the chute conveying, the vibration output and the internal and external temperature of the concrete. Sensor signals from the multi-point sensing network are received, and the phase difference between different positions on the chute of the hopper is calculated based on the sensor signals to estimate the phase error. Based on the phase error, driving instructions are generated; the driving instructions are used to control the vibration phase advance, the vibration frequency adjustment and the vibration time length adjustment. The present application synchronizes or stagger peaks of the vibrator vibration phase and the chute vibration phase of the hopper through phase error locking, so that the two vibrations "resonate" or "cancel out", effectively avoiding the secondary sliding accumulation of the chute sidewall fibers.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of steel fiber reinforced concrete processing, and more particularly to a steel fiber vibration process and temperature control synchronous optimization method for segment production. BACKGROUND

[0002] At present, in the traditional steel fiber reinforced concrete processing process, for example, the first batch of steel fiber reinforced concrete transport hopper is transported from the mixing station to the pouring workshop at 13:59 in the afternoon, the concrete transport volume is 2.2m 3 , the steel fiber reinforced concrete is put into the segment mold at 14:04, the total time required from the mixing station to the concrete placing machine is 5 minutes, the concrete vibration time is 2 minutes, the concrete performance is good, and at the same time, the on-site laboratory technician detects the concrete slump, the measured value is 70mm, which meets the design requirements. During the concrete pouring process, professional technicians are arranged in time to check the performance of the concrete, and it is found that the steel fiber clumps block the concrete discharge, and the staff on site arranges to clean the steel fiber clumps in time, a total of 3 steel fiber clumps are picked out, the sizes of the steel fiber clumps are 10cm, 9cm and 14cm respectively, and a small amount of smaller steel fiber clumps are found to fall into the segment reinforcement cage during the clump cleaning process. Since the volume is small, it gradually blends with the surrounding normal steel fiber reinforced concrete with the flow of concrete vibration, and it is difficult to clean manually.

[0003] In the prior art, the steel fiber reinforced concrete is produced by adopting the scheme of the Mark Phillips steel fiber manufacturer, the coarse and fine aggregate feeding interval is 10s, the total coarse and fine aggregate feeding time is 40s, and the Mark Phillips steel fiber feeding time is 30s; the concrete mix ratio is not adjusted, and after adjustment by the manufacturer, the steel fiber feeding machine operates normally, the total coarse and fine aggregate feeding time is 40s, the Mark Phillips steel fiber feeding time is 30s, the steel fiber is all fed into the mixing equipment with the aggregate, the feeding is completed after 15s of pre-mixing, the concrete mixing time is 120s, the steel fiber reinforced concrete is transported to the pouring site with the hopper, and the steel fiber still has the clumping phenomenon.

[0004] For example, the second batch of steel fiber reinforced concrete transport hopper is transported from the mixing station to the pouring workshop at 14:39 in the afternoon, the concrete transport volume is 2.1m 3, the artificial installation hopper aviation plug time is 2 minutes, the hopper is hung to the pouring platform time is 2 minutes, the steel fiber concrete is put into the segment mold at 14:43, and the total time required from the mixing station to the concrete placing machine is 4 minutes, and the concrete vibrating time is 6 minutes;The technical personnel found that the steel fiber still had the phenomenon of clumping during the process of checking the performance state of the concrete, and the steel fiber after clumping was cleaned in time on the spot, and a total of 3 steel fibers after clumping were picked out, and the size of the steel fiber clumps was 11cm, 12cm and 14cm respectively, and a small amount of steel fiber after clumping was found to fall into the segment reinforcement cage during the clumping cleaning process, and since the volume is small, it gradually blends with the surrounding normal steel fiber concrete with the concrete vibrating flow, and manual cleaning work is still difficult.

[0005] Therefore, in the prefabrication plant, the steel fiber concrete hopper needs to be transported along the 5°-7° inclined ramp from the mixing station to the vibrating table. The ramp vibration (generated by the shock absorber of the conveying vehicle) and the vibrator work vibration often have phase superposition misalignment. This leads to: (1) Local clumping: when the hopper on the ramp rolls down, the fibers previously dispersed on the material surface will accumulate on the "side wall" of the ramp due to phase misalignment, forming small clumps with a diameter of 5-8 cm. (2) Guide instability: at the moment of landing, the vibrator and the material surface have a slight phase difference, causing the fibers on the material surface to slide and accumulate again. SUMMARY

[0006] To solve the problems in the prior art, the purpose of the present application is to solve the above-mentioned defects, and further to provide a steel fiber vibrating process and temperature control synchronous optimization method for segment production.

[0007] The present application adopts the following technical solutions.

[0008] The first aspect of the present application discloses a steel fiber vibrating process and temperature control synchronous optimization method for segment production, the method comprising:

[0009] Vibration sensors and temperature sensors are arranged on the hopper ramp and the vibrating head of the vibrating table respectively to build a multi-point sensing network covering the ramp conveying, vibrating output and the internal and external temperature of the concrete;

[0010] Receive sensor signals from the multi-point sensing network, and calculate the phase difference between different positions on the hopper ramp based on the sensor signals to estimate the phase error;

[0011] Based on the phase error, a driving instruction is generated; the driving instruction is used to control the vibrating phase advance, the vibration frequency adjustment and the vibration time adjustment.

[0012] Further, the vibration sensor and the temperature sensor are arranged on the chute and the vibration head of the vibrating platform respectively to construct a multi-point sensing network covering the chute conveying, the vibrating output and the temperature inside and outside the concrete, including:

[0013] Obtaining the geometric size of the chute, including the length and the inclination angle of the chute;

[0014] Marking the chute in the CAD model according to the geometric size, and segmenting the length of the chute to determine the two end points and the intermediate point of the chute;

[0015] Arranging the vibration sensor and the temperature sensor at the two ends and the intermediate point of the chute, and arranging the vibration sensor and the heat exchange temperature sensor inside the vibrating platform.

[0016] Further, the vibration sensor and the temperature sensor are arranged on the chute and the vibration head of the vibrating platform respectively to construct a multi-point sensing network covering the chute conveying, the vibrating output and the temperature inside and outside the concrete, including:

[0017] Obtaining the preset vibration frequency range and temperature measurement range, and selecting the MEMS vibration sensor and the K-type thermocouple with an error not more than a set range in the vibration frequency range and the temperature measurement range as the vibration sensor and the temperature sensor respectively;

[0018] Placing the selected vibration sensor and temperature sensor in a standard vibration table and a thermostat respectively, calibrating the vibration sensor and the temperature sensor according to the metrological regulation, and recording the calibration coefficient;

[0019] Physically installing the calibrated vibration sensor and temperature sensor, and electrically connecting the installed vibration sensor and temperature sensor with the control terminal to construct the multi-point sensing network.

[0020] Further, the vibration sensor and the temperature sensor are arranged on the chute and the vibration head of the vibrating platform respectively to construct a multi-point sensing network covering the chute conveying, the vibrating output and the temperature inside and outside the concrete, including:

[0021] Based on the vibration sensor, a plurality of direction acceleration signals are collected;

[0022] Based on the plurality of direction acceleration signals, an acceleration sequence is synthesized, and the acceleration sequence is band-pass filtered to remove low-frequency drift and high-frequency noise to obtain a filtered signal;

[0023] The filtered signal is processed by Hilbert transform to construct an analytical signal, and the instantaneous phase is calculated according to the analytical signal;

[0024] At the same time stamp, the difference between different instantaneous phases is calculated, and the difference is mapped to a preset angle range to obtain a measured phase difference between different positions on the chute.

[0025] Further, the sensor signal from the multi-point sensing network is received, and the phase difference between different positions on the chute is calculated based on the sensor signal to estimate the phase error, and further comprising:

[0026] The temperature normalized values of the chute and the segment center are obtained through the multi-point sensing network respectively; the temperature normalized value is obtained by linear normalization based on the original temperature of the temperature sensor;

[0027] The maximum temperature value in the temperature normalized values of the chute and the segment center is selected as the comprehensive normalized temperature, and an inverse proportional model is called to process the comprehensive normalized temperature to output a relative viscosity factor.

[0028] Further, the sensor signal from the multi-point sensing network is received, and the phase difference between different positions on the chute is calculated based on the sensor signal to estimate the phase error, and further comprising:

[0029] The concrete density and the material elastic modulus are obtained, and the ideal filtering under no temperature coupling is calculated based on the concrete density and the material elastic modulus;

[0030] The relative viscosity factor is calculated based on the relative viscosity factor, and the propagation time delay of each position on the chute is calculated according to the suppression wave speed combined with the length of the chute;

[0031] Based on the vibration main frequency of each position on the chute, the propagation time delay is converted into a theoretical phase difference between different positions on the chute;

[0032] The difference between the measured phase difference and the theoretical phase difference is calculated to obtain the phase error.

[0033] Further, the driving instruction is generated based on the phase error, comprising:

[0034] Based on the main peak of the vibrator frequency spectrum of the chute and the main peak of the vibration sensor at the vibration head of the vibrating table, the nominal frequency of the vibrator and the preset normalized parameter are combined to determine the vibration frequency;

[0035] According to the acceleration signal of the vibration sensor along the Z-axis direction, the vibration time length is determined;

[0036] Based on the phase error, the vibration frequency and the vibration time length are combined to generate the driving instruction, so as to control the vibration phase advance, the vibration frequency adjustment and the vibration time length adjustment in response to the driving instruction.

[0037] The second aspect of the present application discloses a steel fiber vibration process and temperature control synchronous optimization device for segment production, which is used to realize the steel fiber vibration process and temperature control synchronous optimization method for segment production.

[0038] A multi-point sensing network construction module is configured to arrange vibration sensors and temperature sensors on the hopper chute and the vibration head of the vibrating table respectively to construct a multi-point sensing network covering the chute conveying, the vibration output and the internal and external temperature of the concrete.

[0039] A phase error estimation module is configured to receive sensor signals from the multi-point sensing network and calculate the phase difference between different positions on the hopper chute based on the sensor signals to estimate the phase error.

[0040] A driving instruction generation module is configured to generate driving instructions based on the phase error, wherein the driving instructions are used to control the vibration phase advance, the vibration frequency adjustment and the vibration duration adjustment.

[0041] The third aspect of the present application discloses a terminal comprising a processor and a storage medium.

[0042] The storage medium is configured to store instructions.

[0043] The processor is configured to operate according to the instructions to perform the steps of the method of the first aspect.

[0044] The fourth aspect of the present application discloses a computer readable storage medium having a computer program stored thereon, wherein the program is executed by a processor to implement the steps of the method of the first aspect.

[0045] The present application has the following advantages compared with the prior art.

[0046] (1) The present application arranges vibration sensors and temperature sensors on the hopper chute and the vibration head of the vibrating table respectively to form a multi-point sensing network covering the chute conveying, the vibration output and the internal and external temperature of the concrete, which can monitor and calculate the temperature, the relative viscosity and the vibration frequency of the steel fiber concrete at different positions in real time, and provide a basis for the generation of driving instructions for the vibration phase advance, the vibration frequency adjustment and the vibration duration adjustment.

[0047] (2) The application adopts a phase synchronization acceleration control system to arrange three-axis acceleration sensors at the chute ramp section and the vibrating table, to collect the ramp vibration and vibrating vibration waveforms in real time; through phase error locking, the vibrating phase and the ramp vibration phase are synchronized or staggered, so that the two vibrations "resonate" or "cancel out", avoiding the secondary sliding accumulation of the chute ramp sidewall fibers. BRIEF DESCRIPTION OF DRAWINGS

[0048] Figure 1 is a flowchart of the steel fiber vibrating process and temperature control synchronization optimization method provided by the application for segment production.

[0049] Figure 2 is a schematic diagram of the steel fiber vibrating process and temperature control synchronization optimization system provided by the application for segment production. DETAILED DESCRIPTION

[0050] The application will be further described below in conjunction with the drawings. The following examples are only used to more clearly illustrate the technical solutions of the application, and cannot be used to limit the protection scope of the application.

[0051] As Figure 1 shown, in one embodiment, a steel fiber vibrating process and temperature control synchronization optimization method for segment production includes the following steps:

[0052] Step S110, vibration sensors and temperature sensors are arranged at the chute ramp and the vibrating table vibration head respectively to construct a multi-point sensing network covering the chute conveying, vibrating output and internal and external temperature of the concrete.

[0053] In some embodiments, the steel fiber vibrating process and temperature control synchronization optimization method provided by the application for segment production, step S110 specifically includes the following steps:

[0054] Step S111, the geometric size of the chute ramp is obtained; the geometric size includes the length and inclination angle of the chute ramp.

[0055] Step S112, the chute ramp is labeled according to the geometric size in the CAD model, and the length of the chute ramp is segmented to determine the two end points and the intermediate point of the chute ramp.

[0056] Step S113, vibration sensors and temperature sensors are arranged at the two ends and the intermediate point of the chute ramp, and vibration sensors and heat temperature sensors are arranged inside the vibrating table.

[0057] In some embodiments, the steel fiber vibrating process and temperature control synchronization optimization method provided by the application for segment production, step S110 specifically further includes the following steps:

[0058] Step S114, a preset vibration frequency range and temperature measurement range are obtained, and a MEMS vibration sensor and a K-type thermocouple with an error of the vibration frequency range and the temperature measurement range not exceeding a set range are selected as a vibration sensor and a temperature sensor, respectively.

[0059] Step S115, the selected vibration sensor and temperature sensor are respectively placed in a standard vibration table and a thermostat, and the vibration sensor and the temperature sensor are calibrated according to a measurement regulation, and a calibration coefficient is recorded.

[0060] Step S116, the calibrated vibration sensor and temperature sensor are physically installed, and the installed vibration sensor and temperature sensor are electrically connected with a control terminal to construct a multi-point sensing network.

[0061] In specific embodiments, the steel fiber vibration process for segment production and temperature control synchronous optimization method provided by the present application comprises steps 1-3:

[0062] Step 1, a multi-point sensor network is laid out.

[0063] Vibration sensors and temperature sensors are respectively laid out at the hopper chute and the vibration head of the vibration table to form a multi-point sensing network covering the chute conveying, vibration output and the internal and external temperature of the concrete.

[0064] It should be noted that the highest point of the hopper chute is connected to the discharge port of the mixing station, which is the place where the concrete first enters the chute; the lowest point of the chute is just at the outlet of the hopper, and is closely connected with the inlet of the segment mold; the discharge port of the vibration table is located below the lowest point of the chute, and coincides with the normal position of the inlet of the segment mold. That is, the vibration table can directly push the vibrated concrete into the inlet side of the mold without any intermediate collection or transfer device.

[0065] In actual application, the concrete is produced and fed in the following order: sand 1→polypropylene fiber→steel fiber material→gravel 1→polypropylene fiber→steel fiber→gravel 2→polypropylene fiber→steel fiber material→sand 2→polypropylene fiber→steel fiber material→powder→water reducing agent, rust inhibitor, water; and then fed into the intermediate bin. The steel fiber material used should be a row of bonded steel fibers. Then it enters the mixing tank from the intermediate bin, and after stirring for 120s, it is transported to the construction site by the hopper.

[0066] In the process of concrete pouring, the performance state of the concrete needs to be checked. If it is found that the steel fibers are blocked by the concrete, the steel fibers after being blocked should be cleaned. In order to reduce the blocking, cement, fly ash, mineral powder and other powder materials can be added into the mixing tank for pre-mixing for 15s before the concrete is added into the mixing tank, then the water reducing agent, the rust inhibitor, the water are added together with the concrete for mixing for 120s, and then the concrete is transported to the construction site through the hopper. Among them, the measurement deviation of the raw materials of the concrete is: cement, water, additive, admixture ≤1%, coarse and fine aggregate ≤2%.

[0067] The construction proportioning of the segment concrete can be as follows: cement: 317; fly ash: 97; mineral powder: 73; sand: 732; gravel: 1111; steel fiber: 40; polypropylene fiber: 1.5; rust inhibitor: 19; water reducing agent: 5.11; water: 105; and the water content of the concrete sand is ensured to be about 4.0%.

[0068] The method comprises the following steps:

[0069] Step 1.1, determining the sensor installation points.

[0070] Specifically, first, the full length of the inclined channel is marked in the CAD model, and the inclined channel is divided into two sections at equal intervals, and the highest point, the middle point and the lowest point of the hopper inclined channel are taken as the installation points of the vibration sensors (D0, D1, D2), and a vibration sensor D3 is also arranged inside the vibrating table, forming a vibration sensor set {D0, D1, D2, D3}.

[0071] Similarly, at the middle point and the lowest point of the hopper inclined channel, the temperature sensor (position) corresponds to the vibration sensor one by one, forming a temperature sensor set {T1, T2}.

[0072] Step 1.2, selecting and calibrating the sensor.

[0073] Specifically, first, according to the preset vibration frequency range interval [20Hz, 200Hz] and the temperature measurement range interval [5℃, 80℃], a MEMS vibration sensor with a range of ±50g and a bandwidth of 20Hz-500Hz is selected, and a K-type thermocouple with a response time of <1s and a temperature resistance of -40℃-150℃ is selected as the vibration sensor and the temperature sensor in this example. Secondly, the selected vibration sensor and temperature sensor are respectively placed in the standard vibration table and the constant temperature box, and the calibration sensitivity and zero point drift are calibrated according to the national measurement regulations, and the calibration coefficient is recorded, so as to complete the calibration of the temperature sensor and the vibration sensor, and obtain the calibrated vibration sensor and temperature sensor.

[0074] Step 1.3, physically installed in the system connection.

[0075] Specifically, the selected and calibrated vibration sensor and temperature sensor in step 1.2 are installed on the corresponding positions of the chute and the vibration head of the vibrating table, and the installed vibration sensor and temperature sensor are electrically connected with the terminal system to transmit monitoring data to the terminal system in real time.

[0076] In step S120, sensor signals from the multi-point sensing network are received, and phase differences between different positions on the chute are calculated based on the sensor signals to estimate phase errors.

[0077] In some embodiments, the steel fiber vibrating process for segment production and the temperature control synchronous optimization method provided by the present application specifically include the following steps in step S120:

[0078] In step S121, acceleration signals in multiple directions are collected based on the vibration sensor.

[0079] In step S122, acceleration sequences are synthesized based on the acceleration signals in multiple directions, and band-pass filtering is performed on the acceleration sequences to remove low-frequency drift and high-frequency noise to obtain filtered signals.

[0080] In step S123, the filtered signals are processed by Hilbert transform to construct analytic signals, and instantaneous phases are calculated based on the analytic signals.

[0081] In step S124, differences between different instantaneous phases are calculated at the same timestamp, and the differences are mapped to a preset angle range to obtain measured phase differences between different positions on the chute.

[0082] In some embodiments, the steel fiber vibrating process for segment production and the temperature control synchronous optimization method provided by the present application specifically include the following steps in step S120:

[0083] In step S125, temperature normalized values of the chute and the segment center are obtained through the multi-point sensing network; the temperature normalized values are obtained by linear normalization of the original temperature based on the temperature sensor.

[0084] In step S126, the maximum temperature value of the temperature normalized values of the chute and the segment center is selected as a comprehensive normalized temperature, and a reciprocal model is called to process the comprehensive normalized temperature to output a relative viscosity factor.

[0085] In some embodiments, the steel fiber vibrating process for segment production and the temperature control synchronous optimization method provided by the present application specifically include the following steps in step S120:

[0086] In step S127, the concrete density and the material elastic modulus are obtained, and ideal filtering without temperature coupling is calculated based on the concrete density and the material elastic modulus.

[0087] Step S128, based on the relative viscosity factor, calculate the inhibitory wave velocity, and according to the inhibitory wave velocity and the length of the hopper chute, calculate the propagation time delay of each position on the hopper chute.

[0088] Step S129, based on the vibration main frequency of each position of the hopper chute, convert the propagation time delay into the theoretical phase difference between different positions on the hopper chute.

[0089] Step S1210, calculate the phase error by subtracting the measured phase difference from the theoretical phase difference.

[0090] In a specific embodiment, the steel fiber vibration process for segment production and the temperature control synchronous optimization method provided by the present application, step 2, phase difference locking and temperature warning generation.

[0091] It should be noted that the phase difference refers to the phase difference of the data signals of the vibration sensor at the middle point of the chute or the lowest point of the chute and the vibration sensor at the highest point of the chute.

[0092] Comprising the following steps:

[0093] Step 2.1, signal preprocessing and measured phase difference calculation.

[0094] Specifically, first, based on the vibration sensor, collect the acceleration signals in three directions (X, Y, Z axes) at the corresponding installation position, respectively represented as a x , a y , a z , and then take the combined acceleration sequence of the acceleration signals in three directions (the sum of the squares of the accelerations in the X, Y, Z axis directions at multiple times is taken to the power of 1 / 2), represented as:

[0095]

[0096] In the formula, t represents the time, a(t) represents the combined acceleration at time t, and a(t) is the result of taking the sum of the squares of the accelerations in the X, Y, Z axis directions at time t to the power of 1 / 2.

[0097] Then, the combined acceleration a(t) is subjected to a 5-200Hz band-pass filter to remove low-frequency drift and high-frequency noise, and a filtered signal is obtained. Then, the Hilbert transform is applied to the filtered signal to construct an analytical signal, expressed as:

[0098] z(t)=a f (t)+jH[a f (t)]

[0099] In the formula, z(t) is the analytical signal at time t, a f(t) is the filtered signal at time t, j is the Hilbert transform coefficient, and H[·] is the Hilbert transform function.

[0100] Subsequently, the instantaneous phase is calculated according to the constructed analytic signal, and the expression is:

[0101] φ(t) = atan2(H[a f (t)], a f (t))

[0102] In the formula, φ(t) represents the instantaneous phase at time t, and atan is a function for calculating the instantaneous phase.

[0103] Finally, the phase difference is calculated at the same time point (or averaged for a stable signal interval at one end), that is, the difference between the instantaneous phases at different positions on the chute, and the calculated phase difference is mapped to [-180°, 180°], and the measured phase difference is obtained, which is used for comparison with the theoretical phase lag to evaluate the comprehensive effect of temperature coupling and actual phase displacement.

[0104] Δφ i,meas = φ i (t0) - φ top (t0)i∈{edge, mid}

[0105] wherein φ top (t0), φ mid (t0), and φ edge (t0) represent the instantaneous phases corresponding to the highest point, the middle point, and the lowest point of the chute, respectively, and Δφ i,meas represents the phase difference.

[0106] Step 2.2, temperature coupling phase error estimation.

[0107] Specifically, first, the temperature normalized values of the chute and the pipe piece center are obtained by linear normalization of the original temperature of the temperature sensor, and second, the maximum value of the two temperature normalized values is selected as the comprehensive normalized temperature to ensure that the viscosity estimation is based on the extreme highest temperature. In the case of multiple sensors in parallel, using the highest normalized temperature can reflect the influence of the most severe environment on the viscosity, so as to avoid missing the key point.

[0108] In order to ensure the high viscosity of the concrete, the mix proportion design of the concrete should meet the requirements of JGJ 55, the durability design should meet the relevant provisions of GB 50010 and CCES 01, the chloride ion content should not be greater than 0.06% of the total amount of cementitious materials, and the total alkali content of the concrete should be ≤3.0 kg / m 3 , and the total alkali content of the concrete is tested according to CECS 53:1993.

[0109] Then, the relative viscosity factor is calculated based on the comprehensive normalized temperature using an inverse proportional model, and the expression is:

[0110]

[0111] In the formula, k μ is the relative viscosity factor, ∈ is the saturation fine-tuning constant to avoid division by zero, and T represents the comprehensive normalized temperature. In this example, when T approaches 0, it indicates that the current environment is a low temperature environment, and the current concrete is determined to be high viscosity based on the relative viscosity factor. When T approaches 1, it indicates that the current environment is a high temperature environment, and the current concrete is determined to be low viscosity based on the relative viscosity factor.

[0112] Step 2.2 maps the normalized temperature value to the viscosity factor. The higher the temperature, the lower the viscosity, and the lower the temperature, the higher the viscosity, which is consistent with the physical law of concrete rheology.

[0113] Step 2.3, Calculation of propagation delay and theoretical phase lag.

[0114] It should be noted that the relative viscosity factor is a quantity that varies with location (essentially with temperature). Therefore, each element in the location viscosity vector (composed of relative viscosity factors at multiple locations) is actually the relative viscosity factor at the temperature sensor location corresponding to that element multiplied by the reference viscosity. Here, the reference viscosity (unit: Pa·s) represents the concrete viscosity at the corresponding reference temperature (25℃). Therefore, the elements in the location propagation delay vector represent the propagation delay of the temperature sensor corresponding to that element, and the elements in the location theoretical phase lag vector represent the theoretical relative lag of the temperature sensor corresponding to that element.

[0115] Specifically, firstly, the ideal wave velocity under no temperature coupling (reference viscosity) is calculated based on the elastic modulus and density of concrete. The expression is:

[0116]

[0117] In the formula, v0 is the ideal wave velocity, E is the elastic modulus of concrete, usually taken as 20-30 GPa, and ρ is the density of concrete, approximately 2400 kg / m³. 3 .

[0118] Then, by the relative viscosity factor k μ Calculate the suppressed wave velocity v based on the ideal wave velocity v0 i Its expression is:

[0119]

[0120] Calculate the corresponding propagation delay Δt i The expression is:

[0121]

[0122] wherein L represents the length of the hopper chute.

[0123] Finally, the above propagation time delay Δt is converted into the theoretical phase lag at the corresponding position in combination with the vibration main frequency f on the hopper chute i The expression is:

[0124] Δφ i = 2π x f x Δt i

[0125] wherein Δφ i represents the theoretical phase lag at the position.

[0126] Step 2.4, phase error calculation.

[0127] Specifically, the phase error is calculated according to the measured phase difference obtained in step 2.1 and the theoretical phase lag at the corresponding position obtained in step 2.2.

[0128] Step S130, generating a driving instruction based on the phase error; the driving instruction is used to control the vibration phase advance, vibration frequency adjustment, and vibration duration adjustment.

[0129] In some embodiments, the steel fiber vibration process for segment production and temperature control synchronous optimization method provided by the application specifically comprises the following steps:

[0130] Step S131, determining the vibration frequency based on the main peak of the vibrator spectrum of the hopper chute and the main peak of the vibration sensor at the vibration head of the vibrating table, in combination with the nominal frequency of the vibrator and the preset normalization parameter.

[0131] Step S132, determining the vibration duration according to the acceleration signal of the vibration sensor along the Z-axis direction.

[0132] Step S133, generating a driving instruction based on the phase error, in combination with the vibration frequency and the vibration duration, to control the vibration phase advance, vibration frequency adjustment, and vibration duration adjustment in response to the driving instruction.

[0133] In specific embodiments, the steel fiber vibration process for segment production and temperature control synchronous optimization method provided by the application, step 3, generates a driving instruction. The generated driving instruction is used to control: the vibration phase advance δ φ , vibration frequency f adj adjustment, and vibration duration t adj adjustment.

[0134] Specifically, the vibration phase advance is: δφ = ε φ × ∈ edge , ∈ edge is the residual error of the middle point of the chute.

[0135] The residual error is determined by the following equation:

[0136] ∈ i = Δφ i,meas - Δφ i i ∈ {edge, mid}

[0137] Based on the spectrum peak f mid , f edge of the vibrator at the middle point and the lowest point of the chute, and the spectrum peak f v of the vibration sensor at the vibrating table, the vibration frequency f adj is determined, and the expression is as follows:

[0138]

[0139] In the expression, f n is the nominal frequency, which is determined by the inherent properties of the vibrator and is preset at the early stage of the process design, u mid , u edge are normalized parameters of the middle point and the lowest point of the chute respectively, and satisfy the following constraint condition:

[0140] u mid + u edge = 1

[0141]

[0142] In this embodiment, the vibration duration can be determined based on the acceleration signals of the vibration sensor along the Z-axis direction, and the expression is as follows:

[0143]

[0144] In the expression, a z_mid (t), a z_edge (t), a z_v (t) are the acceleration signals of the vibration sensor along the Z-axis direction at time t at the middle point of the chute, the lowest point of the chute, and the vibrating table respectively, wherein the Z-axis should be set as the axis direction from the highest point to the lowest point of the chute; t n is the nominal duration, which is determined in advance by the segment thickness and the volume.

[0145] It should be noted that ∈ mid is the residual error of the middle point of the chute, ∈ φ , ∈ f , ∈ t are the parameters to be adjusted, and the parameters to be adjusted ∈φ , ε f , ε t should be initialized to 1.

[0146] vibration phase advance δ φ Relationship with slump:

[0147] Physical mechanism: vibration phase advance δ φ The phase alignment of the vibrator starting time relative to the hopper delivery is controlled. If the vibrator head is started synchronously (phase alignment) when the hopper just starts to discharge, the vibration force can be immediately applied at the earliest material layer, making the aggregate-slurry interface quickly loose and flow, thereby improving the overall slump. This is because before the concrete is poured, its slump needs to be detected, and the cohesive and water-retaining properties of the concrete are visually inspected. The test method for the performance of the concrete mixture shall comply with the provisions of GB / T 50080-2002.

[0148] Forward mapping: δ φ > 0 (vibrator starts relatively in advance) can increase the time window of the vibration force acting on the freshly mixed concrete, increasing the slump; on the contrary, δ φ < 0 (vibrator starts lagging) will reduce the loosening time and reduce the fluidity, thereby reducing the slump; but at this time, the problem of insufficient vibration needs to be considered.

[0149] Experiments have found that generally, every increase of ±1° phase advance can bring about a change of 0.5-1 mm in slump, so ε φ can be fine-tuned based on the slump.

[0150] Vibration frequency f adj and vibration duration t adj Effect on fiber dispersion:

[0151] Since the vibration frequency and the vibration duration jointly determine the vibration moment, there are two cases:

[0152] (1) High vibration frequency and short vibration duration: under the same duration, the higher the frequency, the greater the energy of a single vibration cycle, but the duration is short, which can easily make the steel fibers rapidly cut and disperse in local intense vibration, suitable for breaking up large clumps in the early stage.

[0153] (2) Low vibration frequency and long vibration duration: the energy is relatively concentrated for a longer time, suitable for promoting the flow of concrete in detail and assisting the uniform deployment of fibers in a larger volume, avoiding local over-segregation.

[0154] In summary, according to the feedback of the fiber dispersion on site, the ratio of ε f and ε t can be fine-tuned, for example, increasing ε f while shortening ε tTo break the group in priority, or reduce epsilon f At the same time, extend epsilon t To optimize the overall dispersion.

[0155] The steel fiber vibrating process for segment production and the temperature control synchronization optimization device provided by the present application are described below. The steel fiber vibrating process for segment production and the temperature control synchronization optimization device described below can be mutually corresponding and referred to with the steel fiber vibrating process for segment production and the temperature control synchronization optimization method described above.

[0156] In one embodiment, a steel fiber vibrating process for segment production and temperature control synchronization optimization device includes a multi-point sensing network construction module, a phase error estimation module, and a driving instruction generation module.

[0157] The multi-point sensing network construction module is used to arrange vibration sensors and temperature sensors on the hopper chute and the vibrating head of the vibrating table respectively to construct a multi-point sensing network covering the chute conveying, vibrating output, and the internal and external temperature of the concrete.

[0158] The phase error estimation module is used to receive sensor signals from the multi-point sensing network and calculate the phase difference between different positions on the hopper chute based on the sensor signals to estimate the phase error.

[0159] The driving instruction generation module is used to generate driving instructions based on the phase error; the driving instructions are used to instruct the vibrating phase advance, the vibration frequency adjustment, and the vibration duration adjustment.

[0160] The present disclosure can be a system, a method, and / or a computer program product. The computer program product can include a computer readable storage medium having computer readable program instructions embodied therewith, which cause a processor to implement various aspects of the present disclosure.

[0161] Computer readable storage media can be tangible storage media which can retain and store instructions for use by an instruction execution device. Computer readable storage media can be, for example, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of computer readable storage media include the following: a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanically encoded device such as punch-cards or raised structures in a groove having instructions recorded thereon, and any suitable combination of the foregoing. A computer readable storage medium, as used herein, is not to be construed as being transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media (e.g., light pulses passing through a fiber-optic cable), or electrical signals transmitted through a wire.

[0162] Computer readable program instructions described herein can be downloaded to respective computing / processing devices from a computer readable storage medium or to an external computer or external storage device via a network, for example, the Internet, a local area network, a wide area network and / or a wireless network. The network can comprise copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and / or edge servers. A network adapter card or network interface in each computing / processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium within the respective computing / processing device.

[0163] Computer readable program instructions for carrying out operations of the present disclosure can be assembler instructions, instruction-set-architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state-setting data, or either source code or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The computer readable program instructions can execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computer (for example, through the Internet using an Internet Service Provider). In some embodiments, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate array (FPGA), or programmable logic array (PLA) can execute the computer readable program instructions by utilizing state information of the computer readable program instructions to personalize the electronic circuitry, in order to perform aspects of the present disclosure.

[0164] The computer readable program instructions can also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other device to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0165] These computer readable program instructions can be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks. These computer readable program instructions can also be stored in a computer readable storage medium that can include random access memory (RAM), read only memory (ROM), electrically erasable programmable read only memory (EEPROM), flash memory or other data storage device. When the computer readable program instructions are loaded into the computer and other programmable data processing apparatus, a series of operational steps are implemented that provide processes such that the computer or other programmable apparatus provide processes for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0166] The computer readable program instructions can also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus or other device to produce a computer implemented process such that the instructions which execute on the computer, other programmable data processing apparatus, or other device implement the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0167] The computer readable program instructions can also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus or other device to produce a computer implemented process such that the instructions which execute on the computer, other programmable data processing apparatus, or other device implement the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0168] Finally, it should be noted that the above-mentioned embodiments are merely used to illustrate the technical solutions of the present application, rather than limiting the present application, and although the present application has been described in detail with reference to the above-mentioned embodiments, it should be understood by those skilled in the art that the specific embodiments of the present application can be modified or equivalent replacements without departing from the spirit and scope of the present application, and any modifications or equivalent replacements shall be covered within the protection scope of the claims of the present application.

Claims

1. A method for simultaneously optimizing the steel fiber vibration process and temperature control in tunnel segment production, characterized in that, The method includes: Vibration sensors are installed on the hopper chute and the vibrating head of the vibrating table, and temperature sensors are installed on the hopper chute to build a multi-point sensing network covering the hopper chute conveying, vibration output and the internal and external temperature of the concrete. The system receives sensor signals from a multi-point sensing network and calculates the phase difference between different positions on the hopper chute based on the sensor signals to estimate the phase error. Based on the phase error, a driving command is generated; the driving command is used to control the advance of the vibration phase, the adjustment of the vibration frequency, and the adjustment of the vibration duration.

2. The method for simultaneous optimization of steel fiber vibration process and temperature control in segment production according to claim 1, characterized in that, Vibration sensors are installed on the hopper chute and the vibrating head of the vibrating table, and temperature sensors are installed on the hopper chute to construct a multi-point sensing network covering the hopper chute conveying, vibration output, and internal and external temperatures of the concrete, including: Obtain the geometric dimensions of the hopper ramp; the geometric dimensions include the length and inclination angle of the hopper ramp; In the CAD model, the hopper ramp is marked according to the geometric dimensions, and the length of the hopper ramp is segmented to determine the two endpoints and the midpoint of the hopper ramp; Vibration sensors are installed at both ends and the middle point of the hopper ramp and at the vibrating head of the vibrating table. Temperature sensors are installed at the lowest point of the two ends and at the middle point.

3. The method for simultaneous optimization of steel fiber vibration process and temperature control in segment production according to claim 2, characterized in that, The method of installing vibration sensors on the hopper chute and the vibrating head of the vibrating table, and simultaneously installing temperature sensors on the hopper chute to construct a multi-point sensing network covering the hopper chute conveying, vibration output, and internal and external temperatures of the concrete, further includes: Obtain the preset vibration frequency range and temperature measurement range, and select a MEMS vibration sensor and a K-type thermocouple whose errors with the vibration frequency range and temperature measurement range do not exceed the set range as the vibration sensor and temperature sensor, respectively. The selected vibration sensor and temperature sensor were placed in a standard vibration table and a constant temperature chamber, respectively. The vibration sensor and temperature sensor were calibrated according to the metrological procedure, and the calibration coefficients were recorded. The calibrated vibration and temperature sensors are physically installed, and then electrically connected to the control terminal to construct the multi-point sensing network.

4. The method for simultaneous optimization of steel fiber vibration process and temperature control in segment production according to claim 3, characterized in that, The process of receiving sensor signals from a multi-point sensing network and calculating the phase difference between different positions on the hopper chute based on the sensor signals to estimate the phase error includes: Based on vibration sensors, acceleration signals in multiple directions are collected; An acceleration sequence is synthesized based on the acceleration signals from the multiple directions, and the acceleration sequence is bandpass filtered to remove low-frequency drift and high-frequency noise, resulting in a filtered signal. The filtered signal is processed by Hilbert transform to construct an analytical signal, and the instantaneous phase is calculated based on the analytical signal. The difference between different instantaneous phases is calculated at the same timestamp, and the difference is mapped to a preset angle range to obtain the measured phase difference between different positions on the hopper ramp.

5. The method for simultaneous optimization of steel fiber vibration process and temperature control in segment production according to claim 4, characterized in that, The step of receiving sensor signals from a multi-point sensing network and calculating the phase difference between different positions on the hopper chute based on the sensor signals to estimate the phase error further includes: The normalized temperature values ​​of the hopper ramp and the center of the tube segment are obtained through the multi-point sensing network; the normalized temperature values ​​are obtained by linear normalization of the original temperature of the temperature sensor. The maximum temperature among the normalized temperatures of the hopper ramp and the center of the tube is selected as the comprehensive normalized temperature, and the comprehensive normalized temperature is processed by the inverse proportional model to output the relative viscosity factor.

6. The method for simultaneous optimization of steel fiber vibration process and temperature control in segment production according to claim 5, characterized in that, The step of receiving sensor signals from a multi-point sensing network and calculating the phase difference between different positions on the hopper chute based on the sensor signals to estimate the phase error further includes: Obtain the concrete density and material elastic modulus, and calculate the ideal filter under no-temperature coupling based on the concrete density and material elastic modulus; The suppressed wave velocity is calculated based on the relative viscosity factor, and the propagation delay at each position on the hopper ramp is calculated based on the suppressed wave velocity and the length of the hopper ramp. Based on the dominant vibration frequency at each position of the hopper chute, the propagation delay is converted into the theoretical phase difference between different positions on the hopper chute. The phase error is obtained by calculating the difference between the measured phase difference and the theoretical phase difference.

7. The method for simultaneous optimization of steel fiber vibration process and temperature control in segment production according to claim 6, characterized in that, The step of generating drive commands based on the phase error includes: Based on the main peak of the vibrator spectrum of the hopper inclined channel and the main peak of the vibration sensor at the vibrating head of the vibrating table, combined with the nominal frequency of the vibrator and the preset normalized parameters, the vibration frequency is determined. The vibration duration is determined based on the acceleration signal from the vibration sensor along the Z-axis. Based on the phase error, combined with the vibration frequency and vibration duration, the driving command is generated to control the vibration phase advance, vibration frequency adjustment, and vibration duration adjustment in response to the driving command.

8. A device for simultaneously optimizing steel fiber vibration process and temperature control in segment production, characterized in that, The apparatus for implementing the method for simultaneous optimization of steel fiber vibration process and temperature control in segment production as described in any one of claims 1 to 7, comprises: The multi-point sensing network construction module is used to deploy vibration sensors on the hopper chute and the vibrating head of the vibrating table, and at the same time deploy temperature sensors on the hopper chute to build a multi-point sensing network covering the hopper chute conveying, vibration output and the internal and external temperature of concrete. The phase error estimation module is used to receive sensor signals from the multi-point sensing network and calculate the phase difference between different positions on the hopper ramp based on the sensor signals in order to estimate the phase error. The drive command generation module is used to generate drive commands based on the phase error; the drive commands are used to control the vibration phase advance, vibration frequency adjustment, and vibration duration adjustment.

9. A terminal, comprising a processor and a storage medium; characterized in that: The storage medium is used to store instructions; The processor is configured to operate according to the instructions to perform the steps of the method according to any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the program implements the steps of the method according to any one of claims 1-7.

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