System for reducing or optimizing the electrical consumption or production of a fluid machine having at least one rotating component

Abstract

1. A system for reducing or optimizing electrical consumption or production of a fluidic device having at least one rotating component, comprising: At least one electrical sensor (2) having electrodes (100) distributed around the body of the device, the ends of said electrodes being flush with the inner surface of the body and facing the component; an electronic circuit (12) for controlling the electrodes and for tomographic measurements by electrical impedance; a signal processing unit adapted to reconstruct an image of the fluid in the body from the matrix measurements; an electronic unit for automatically controlling a component for controlling the appliance, adapted to adjust the power of the appliance and thus modify the operating frequency of the appliance to adjust the flow:power ratio of the appliance; Including, the system.

Description

[Technical Field]

[0001] The present invention relates to the field of monitoring fluidic equipment, in particular intended to be implemented in fluidic circuits in industrial installations.

[0002] More particularly, the present invention relates to the detection of bubbles whose presence results from a phenomenon called cavitation in a fluid flowing in a fluid circuit, which can cause excessive electrical consumption or production by fluidic equipment having rotating components in the circuit.

[0003] Although described in relation to its application to monitoring pumps, the present invention may be applied to monitoring any type of fluid equipment that has rotating components and / or is likely to experience pressure drops that lead to cavitation, such as turbines, which are particularly likely to be present in fluid circuits within industrial facilities.

[0004] "Fluid equipment" is understood herein and in the context of the present invention to mean a set of at least one rotating or electromechanical component, likely implemented in a fluid circuit, adapted to be powered by electricity or to produce electricity. This includes active devices in which at least one rotating component moves a volume of fluid continuously and / or discontinuously (pumps, marine propulsion) or uses fluid power (turbines). [Background technology]

[0005] Pumps are a vital component of industrial equipment and are currently the second most manufactured device in the world after electric motors.

[0006] Pumps transport fluids required for human activity, especially industrial activity, such as most raw materials, water, and fluids used in the agri-food, chemical, pharmaceutical, construction, paper, electronics, mining, and fossil fuel industries.

[0007] The phenomenon of cavitation, i.e. the presence of vapor bubbles generated by excessive suction force or by the absence of fluid at the suction point of the pump, can result in excessive power consumption or even damage to the pump.

[0008] To address this issue, in the context of scheduled maintenance, the pump can be disassembled and parts replaced or cleaned, but this can lead to unnecessary expense as, to be safe, the pump must be inspected more frequently than actually necessary.

[0009] Many systems exist for monitoring fluid circuits that incorporate one or more pumps.

[0010] Those systems are mainly based on pressure differential, vibration, infrared or ultrasonic measurement measurements, as described in patent applications / patents FR 3026443 A1, CN 111197581 A and EP 1297331 B1, respectively.

[0011] These existing systems do not allow an overconsumption of electricity, or conversely an underconsumption of electricity, or even a breakdown of the pump, to be effectively predicted.

[0012] In particular, some of the commercial solutions that have been implemented can detect high degrees of cavitation, but can be complex to implement and are specific to particular types of pumps. [Prior art documents] [Patent documents]

[0013] [Patent Document 1] FR 3026443 A1 [Patent Document 2] CN 111197581 A [Patent Document 3] EP 1297331 B1 Summary of the Invention

[0014] There is therefore a need for a pump monitoring system in a fluid circuit that overcomes the drawbacks of known systems, in particular to enable cavitation to be easily detected for all types of pumps in order to optimize the pump's electrical consumption and in any case prevent the pump from being damaged due to cavitation.

[0015] More generally, there is a need for a system for monitoring fluidic equipment having at least one rotating component implemented in a fluid circuit that can easily detect cavitation in order to optimize the equipment's electricity consumption or production and, in any case, prevent the equipment from being damaged due to cavitation.

[0016] It is an object of the present invention to at least partially address these needs.

[0017] To this end, the object of the present invention is, according to one of its aspects, a system for reducing or optimizing the consumption or production of electricity of a fluid machine having at least one rotating component adapted to be electrically powered or to produce electricity, comprising: at least one electrical sensor including a plurality of electrodes distributed around the body of the fluidic device, the ends of the electrodes being flush with the inner surface of the body and facing the rotating component; an electronic circuit for controlling the electrodes and for tomographic measurements by electrical impedance, the electronic circuit being adapted to simultaneously excite the electrodes and, if applicable, measure the electrical impedance matrix of the fluid flow containing the cavitation bubbles in the body; a signal processing unit adapted to reconstruct an image of the fluid flow in the body from measurements of the impedance matrix of the electronic circuit; an electronic unit for automatically controlling a component for controlling a fluidic device, the electronic unit being adapted to adjust the operating power of the device and thus modify the operating frequency of the device to adjust the flow rate:power ratio of the device; The system includes:

[0018] According to an alternative embodiment, the fluid device is a pump or turbine, the end of the electrode faces or is integrated with the free end of a blade of the pump or turbine, and the control component is a frequency variator.

[0019] Advantageously, the operation of the electronic unit for automatically controlling the fluidic device is placed under the control of the operation of the signal processing unit.

[0020] According to an advantageous form of construction, the system includes a casing fixed around the body of the fluidic device, which houses the electrical sensor with the electrodes individually and sealably housed and fixed in the through holes of the body.

[0021] Preferably, the casing houses a power port for the electrode.

[0022] According to an advantageous alternative embodiment, the signal processing unit is adapted to implement a neural network for reconstructing the image.

[0023] According to an advantageous embodiment, the control circuit performs the following steps: a / A step of exciting the electrodes, each electrode being energized to a potential V n exc is excited by a potential V n exc but in the following format: [Formula 2]

[0024]

number

[0025] where A is the amplitude of the signal and n e is the number of electrodes, and θ n is the angular position of electrode n, and f m = m * f0 is the vibration frequency, and f0 is the frequency f for any m. m is the fundamental frequency chosen to be less than the Nyquist frequency of the system,

[0026]

number

[0027] is the set of odd natural numbers,

[0028]

number

[0029] is a set of even natural numbers, or the potential V n exc but in the following format: [Formula 5]

[0030]

number

[0031] and by convention, if the value of the start index is greater than the value of the end index, the sum is also zero, [Formula 6] Ψ i (t) = A sin(2πf i t), [Formula 7]

[0032]

number

[0033] and [Formula 8]

[0034]

number

[0035] and [V j (t)] n-1 is the voltage V j In identities such as the identity defining (t), the term Ψ i voltages V, following the convention that j represents the (n-1)th element of the identity defining (t), and excitation is performed either simultaneously for all electrodes according to [Equation 5] or sequentially for one or more subsets of electrodes; b / Electrical characteristics of fluid flow at electrodes V n meas measuring the c / a step of processing the data derived from the measurement step, step b / , comprising the following sub-steps: c1 / each electrode E n Regarding [Formula 10]

[0036]

number

[0037] The data points M defined by n the sub-step of calculating n meas is the value of the resistor used to measure V at the resistor terminals. n meas = RI n and P is the current I n is the number of points in the discrete sequence of measurements of e -1), and β p = (2πp / P), the substep, c2 / Data points M for all n and all k n (k) to the data matrix D as follows, i.e., if the excitation format [Equation 2] is implemented: [Formula 13]

[0038]

number

[0039] Or, if the excitation format [Equation 5] is implemented, [Formula 14]

[0040]

number

[0041] forming a sub-step according to c3 / forming a matrix of signed data, the elements of which represent the phase shift Φ between the excitation potential at electrode l and the measured current at electrode n; n,l When (k) is less than π / 2, the following equation is satisfied: [Formula 20]

[0042]

number

[0043] where the elements of the matrix are the phase shift Φ between the excitation potential at electrode l and the measured current at electrode n. n,l When (k) is equal to or greater than π / 2, the following equation is satisfied: [Formula 22]

[0044]

number

[0045] and Σ is defined by When the excitation format [Equation 2] is implemented, the i-th element of the j-th row of Σ is given by cosine ([2π / ([j+1] / 2)]*(i-1) / n for odd j. e ), and for even j it is the sine ([2π / (j / 2)]*(i-1) / n e ) is the sign of When the excitation format [Equation 5] is implemented, especially for measurement electrodes at equal distances between the two excitation electrodes, the amplitude is experimentally measured to be of the order of O(10-7) A, with the nearest excitation electrode being assigned an opposite sign, corresponding to a negligible contribution to the data. The substep is a matrix of signs defined as Including steps The method is adapted to perform the following steps:

[0046] Preferably, the control circuit controls all potentials V n exc The following conditions are met: [Formula 4]

[0047]

number

[0048] The method is adapted to perform step a / by verifying that:

[0049] According to an advantageous configuration, the electrodes of the electrical sensor are distributed at equal angles around the body of the fluidic device.

[0050] A further object of the present invention is the use of the optimized system to measure cavitation, bubbles, the absence of fluid, and the presence of gas.

[0051] A further object of the invention is an industrial installation comprising at least one fluid circuit and an optimization system as described above.

[0052] Generally, the invention can be implemented in any fluid circuit, especially in the fields of agri-food, pharmaceutical and cosmetic, chemical and petrochemical, water distribution and treatment, especially in factories or industrial production sites.

[0053] Thus, the present invention basically comprises a system for detecting cavitation that is likely to cause excessive electrical consumption or excessive electrical production, or even damage to fluidic equipment having rotating components installed in the fluid circuit.

[0054] The system includes an electrical sensor having electrodes preferably evenly distributed around the body of the device, with the ends of said electrodes flush with the inner wall of the body, preferably as close as possible to the blades of the rotating component.

[0055] Electrical Impedance Tomography (EIT) measurements are performed using either simultaneous trigonometric or paired electrode signals to excite the electrodes.

[0056] This non-invasive and non-destructive measurement allows for a continuous, real-time view of the inside of the body of a fluidic device, and thus the fluid flowing therethrough, by measuring electrical properties (electric potential and current).

[0057] By solving the inverse problem, an electrical impedance map within the body is reconstructed.

[0058] The acquisition rate of the images reconstructed by the processing unit can be very high, typically up to 31,250 images / second, which means that fluids flowing at speeds of up to 300 meters / second can be observed.

[0059] In response to signals from the fluid flow indicative of cavitation, an electronic unit adjusts the operating power of the device, which in turn automatically modifies the operating frequency of the device to adjust the flow:power ratio of the device.

[0060] As a result, the risk of cavitation is eliminated or at least reduced and the electrical consumption or production of the equipment is appropriately adapted.

[0061] The above-described invention has many advantages, including the following: - Direct measurement of cavitation, which can lead to excessive electricity consumption or even pump failure - Fast detection and possible preventive measures thanks to the possibility of collecting measurements / images at a very high rate of up to 31,250 images / second - Robust system as it is reliable regardless of the fluid used, even under very high pressures, typically up to 300 bar and / or at very high temperatures, typically up to 600°C and above [Brief explanation of the drawings]

[0062] [Figure 1] FIG. 1 shows a fluid circuit including a pump capable of generating cavitation in the fluid flowing through the pump, which cavitation can be detected by a system for optimizing the consumption of electricity according to the present invention, which system includes an electrical sensor having electrodes for electrical impedance tomography measurements. [Figure 2] 1 shows a schematic diagram of the hardware and software means of an optimization system according to the invention; [Figure 3] FIG. 1 shows a pump body incorporating an electrical sensor of a system according to the invention. [Figure 3A] 4 is a cross-sectional view of the pump body of FIG. 3 in the vicinity of the electrodes of the electric sensor. [Figure 4] FIG. 1 illustrates a spatial cosine pattern. [Figure 5] FIG. 1 shows part of the electronic circuit for exciting the electrodes. [Figure 6] FIG. 2 illustrates a method for generating excitation signals for electrodes of an electrical sensor according to a first alternative embodiment of the present invention. [Figure 7] FIG. 1 illustrates a method for measuring a signal generated by an electrode. [Figure 8] FIG. 1 illustrates a graphical representation of some of the excitation signals and their characteristics. [Figure 9] FIG. 1 shows a code matrix for a 16-electrode electrical sensor. [Figure 10] FIG. 1 shows a code matrix for a 32-electrode electrical transducer. [Figure 11] 1A and 1B show an image reconstructed by a conventional technique, and an image experimentally reconstructed in a system according to the present invention and an image simulated by a neural network, respectively. DETAILED DESCRIPTION OF THE INVENTION

[0063] 1 illustrates an embodiment of a system 1 for optimizing the electrical consumption of a pump 20 that moves a fluid in a circuit 2 that includes the pump 20. The system can detect air bubbles caused by cavitation, which can lead to excessive electrical consumption or even damage to the pump 20. The system can also use impedance measurements to measure dry running, foreign objects, blockages, viscosity changes, or other types of faults that can reduce the pump's performance or cause it to block. The system can also measure internal wear of the pump in real time and diagnose the hydraulic performance capability of fluid equipment.

[0064] The system 1 first includes an electrical sensor 10 disposed within the body 21 of the pump 20. The electrical sensor 10 enables the flow of fluid through the body 21 to be measured using electrical impedance tomography.

[0065] A unit 11 is also provided for controlling the operation of the pump's frequency variator according to a representative signal of the fluid flow and according to real-time measurements of any disturbances so as to prevent cavitation of the pump 20, as will be explained hereinafter.

[0066] More specifically, the electrical sensor 10 includes sixteen electrodes 100 distributed around the body 21, preferably at equal angles, with the ends of the electrodes being flush with the inner surface of the body 21 and preferably as close as possible to the ends of the pump blades.

[0067] A synoptic of the hardware and software means of the system 1 is shown in FIG.

[0068] The electrodes 100 are connected to a printed circuit 12, which is an electronic circuit for controlling the electrodes 100 and for tomographic measurements by electrical impedance, the circuit being adapted to simultaneously excite the electrodes respectively and to measure the electrical impedance matrix of the fluid flow containing cavitation bubbles, if applicable, within the body 21.

[0069] A signal processing unit 13 is used to reconstruct an image of the fluid flow within the body 21 from the impedance matrix measurements of the electronic circuit 12 .

[0070] An electronic automatic control unit 14 is used to control the frequency variator of the pump, preferably by digital communication, based on risks 13 that may or may not be specified for the pump 20, and more generally to monitor the industrial equipment in which the fluid circuit 2 is installed.

[0071] By modifying the operating frequency of the pump 20, the operating power of the pump 20 can be adjusted, and thus the flow:power ratio of the pump 20 can be adjusted.

[0072] 3 and 3A show an advantageous form of integration in the form of a casing 22 that houses the electrical sensor 10 within the fluid circuit.

[0073] A casing 22 fixed around the pump body 21 houses the electrical sensor 10 with the electrodes 100 individually and sealably received and fixed in the through holes 23 in the pipe.

[0074] The casing 22 may house a power port 24 for the electrodes.

[0075] A control circuit 12 may be connected to the data acquisition system. A screen 11 may be used to display the data and images generated from this data. The data acquisition system includes a Linux operating system (HOST), which controls an FPGA programmable logic array also included in the data acquisition system.

[0076] The acquisition system is used to generate an analog excitation signal and to measure an analog measurement signal resulting from the electrode 100 .

[0077] The acquisition system may incorporate, for example, a cRIO-9039 controller manufactured by National Instruments, which includes a programmable logic array, an NI-9262 module manufactured by National Instruments for generating analog excitation signals, and an NI-9223 module manufactured by National Instruments for measuring analog signals resulting from the electrodes 100.

[0078] Next, a method for measuring and processing signals implemented by a system for detecting faults and preventing failures in pumps according to the present invention will be described.

[0079] Note that the electrical sensor 10 is pre-installed in the fluid circuit with the electrodes 100 positioned as shown above.

[0080] Electrode excitation The first step involves simultaneously exciting all electrodes 100 with a potential of appropriate shape.

[0081] The electrodes 100 form a set of linearly independent electrodes that are used to generate electrical excitation on the surface of a body and to measure electrical properties.

[0082] The excitation according to the trigonometric pattern transformation [Equation 2] is as follows: n e For electrodes, (n e −1) linearly independent excitation patterns exist, as follows: [Formula 1]

[0083]

number

[0084] Fourier basis functions according to are a natural choice to describe these linearly independent patterns.

[0085] According to a first alternative, all electrodes are excited simultaneously with a triangularly shaped excitation.

[0086] This set of simultaneous excitations can be separated into spatial and temporal oscillations according to a Fourier basis.

[0087] In order to distinguish between the various triangular signals in frequency multiplexing, different frequencies are imposed.

[0088] For each trigonometric excitation pattern, each electrode E n is the static voltage V n sta is associated with.

[0089] n e quiescent voltage V n sta form a set of sine and cosine functions with different spatial frequencies m.

[0090] Figure 4 shows the spatial cosine patterns for m ranging from 1 to 5. The sine patterns are not shown.

[0091] n e The electrodes are positioned around the body ∂Ω, as indicated by the dashed lines in Figure 4. The solid lines represent the excitation potentials imposed on the electrodes.

[0092] Each electrode E n The static potential V n,m sta is from 1 to n e is defined by the following formula for n in the range [Formula 2]

[0093]

number

[0094] A is the amplitude of the signal, m∈1,...,(n e -1) represents the spatial frequency, and n e is the number of electrodes, and θ n is the angular position of electrode n, and f m = m * f0 is the vibration frequency, and f0 is the frequency of f for any m. m is the fundamental frequency chosen to be less than the Nyquist frequency of the system,

[0095]

number

[0096] is the set of odd natural numbers,

[0097]

number

[0098] is the set of even natural numbers.

[0099] n e For a given set of electrodes, all independent excitation patterns are e -1) distinct spatial frequencies. n = 2π n / n e For certain cases, the electrodes are evenly spaced around the body.

[0100] Each spatial frequency m corresponds to a temporal frequency f m and is imposed simultaneously on each of the electrodes.

[0101] Therefore, each simultaneous excitation potential V n exc is (n e -1) trigonometric functions, each function at a particular frequency f m It vibrates.

[0102] The excitation signal for electrode n is V, defined by the following equation: n exc is. [Formula 3]

[0103]

number

[0104] Each potential V defined in this way n exc (t) is the voltage of each electrode E n n e The sum of the excitation voltages of the electrodes is checked to ensure that it is zero independent of time t. This results in the following condition: [Formula 4]

[0105]

number

[0106] According to a second alternative of the invention, the excitation format is as follows: [Formula 5]

[0107]

number

[0108] By convention, if the value of the start index is greater than the value of the end index, the sum is also zero, [Formula 6] Ψ i (t) = A sin(2πf i t), [Formula 7]

[0109]

number

[0110] and [Formula 8]

[0111]

number

[0112] and [V j (t)] n-1 is the voltage V j In identities such as the identity defining (t), the term Ψ i voltages V, following the convention that j represents the (n-1)th element of the identity defining (t). Excitation can be performed simultaneously on all electrodes or sequentially on one or more subsets of electrodes.

[0113] Electrical property measurements The electrical properties of the fluid flowing through section 21 are then measured using electrodes 100 .

[0114] Unit 12 controls the programmable logic array of the acquisition system to generate 16 excitation signals with the described characteristics. These 16 digital signals are converted to analog signals using an NI-9262 module and sent to electrode 100 via a coaxial cable.

[0115] The printed circuit 12 includes an excitation circuit for each electrode 100, as shown in Figure 5, and each of these circuits includes a resistor R. As can be seen in this figure, the potential V n exc is imposed on one side of the resistor R, and the other side is the electrode E n is connected to.

[0116] Electrode E n The Neumann boundary condition at n flows through the excitation circuit. This current generates a voltage V at the terminals of the resistor. n meas = RI n It is obtained by measuring V n exc Similarly, this signal is a sum of trigonometric functions.

[0117] Data Processing In the fourth step, the data measured during the second step is processed to either directly feed information into a processing algorithm or to obtain a signed data matrix representing the image.

[0118] Data point M n Generation of In the first substep of the fourth step of the measurement method, for each electrode n, data points M n is calculated.

[0119] Measurement signal V n meas The Fourier transform of is n(p) calculated from the current measurement sequence, where p is a discrete time and verifies 0≦p≦P, i.e., [Formula 9]

[0120]

number

[0121] and

[0122]

number

[0123] ,

[0124]

number

[0125] , and the normalization factor

[0126]

number

[0127] is.

[0128] The Fourier transform may be calculated at frequency f1, which corresponds to the frequency at which the P Fourier coefficients are calculated.

[0129] Voltage V n exc frequency f m is chosen to be a harmonic of f1. This allows the measured signals to be distinguished. Thus, each coefficient k is used to determine the frequency of a particular frequency f m is associated with.

[0130] Then the data is generated at frequency f1 and the resolution in Fourier space is Δf = f m+1 -f m= f1. The highest frequency is the Nyquist frequency of the system, f Nyq Note that the time is chosen to be less than Δp = ½ Δp, where Δp is the sampling time.

[0131] Data point M n (k) is the modulus of each Fourier coefficient k for each electrode n, [Formula 10]

[0132]

number

[0133] R is V n meas is the value of the resistor used to measure V at the resistor terminals. n meas = RI n and P is the current I n is the number of points in the discrete sequence of measurements, p is the discrete time, and k ranges from 1 to (n e -1), and β p = (2πp / P).

[0134] Each data point defines a given triangular pattern of current for a given electrode. Data points M for all n and all k n The set (k) forms the measurement data.

[0135] The excitation frequency is determined by the sampling frequency f of the data acquisition system. DAQ is the voltage V n exc The maximum frequency f m and limit the Nyquist frequency f Nyq = f DAQ / 2 forms the upper limit.

[0136] f DAQ For a data acquisition system where = 1 MS / s, the Nyquist frequency is 500 kHz.

[0137] To take advantage of the small residual voltage error caused by the energy stored in the electrode-electrolyte contact impedance, a continuous signal must be applied. To generate continuous signals at different frequencies, the signals are chosen to be harmonics of the lowest generated frequency f1.

[0138] When the potential is no longer imposed on the electrode, part of the electrical energy is stored for a few tens of microseconds at the interface between the electrode and the medium. This contact impedance phenomenon leads to measurement errors and means that a dead time must be introduced between two successive excitations to wait for this energy to dissipate. The advantage of generating a continuous signal is that the imposed voltage is never de-excited, thus avoiding the errors associated with the contact impedance and the need to introduce a dead time.

[0139] Using 16 electrodes, a set of excitation signals is generated at 15 different frequencies (according to Equation 2) and 120 different frequencies (according to Equation 5). Considering a sampling rate of the acquisition system, e.g., 1 MS / s, the frequencies are f i = i * f0, where f0 is the fundamental frequency and i ranges between 1 and 15 or 1 and 120, respectively.

[0140] Furthermore, for the 15 frequencies, only positive results are considered, so the discrete Fourier transform can be chosen to be performed with P = 32 points, which is 1 * 10 6 This results in an image data acquisition rate of 31,250 images / s. This choice is made because the lowest sinusoidal signal frequency, f, is equal to the computation frequency of the discrete Fourier transform, and the highest frequency, f 15 = 15 * f0 = 468.875 kHz, i.e., below the Nyquist limit of 500 kHz for the considered system.

[0141] The excitation amplitude is determined as follows:

[0142] The voltage generation and acquisition modules operate within a range of ±10 V. n exc Considering this, the amplitude A of the sine must be much smaller than the sum of the generated sine waves due to constructive interference. However, to minimize the signal-to-noise ratio, the amplitude A of the signal must be as large as possible.

[0143] Another limit to consider is the maximum permissible variation between two successively generated potentials. Real-time control in the acquisition system allows a satisfactory value of A = 0.15 V to be selected, resulting in a resonant peak of ±2.25 V. Rapid transitions between positive and negative signal values ​​prevent the appearance of electrolysis effects. For example, the phenomenon of electrolysis in water occurs when DC voltages above 1.2 V are applied. This phenomenon does not occur with AC voltages above 1.2 V if these voltages change quickly enough.

[0144] Obtaining the data matrix D In the second substep, data point M n The data matrix D is obtained from

[0145] For the considered system with 16 electrodes using the NI-9223 module, a fixed-point data format with 20 bits allocated to the numbers, including 5 bits for precision digits, can be used. The electrode index n, ranging from 1 to 16, and the Fourier coefficient k, ranging from 1 to 15, can be described by a 4-bit coded binary number.

[0146] For a system with 32 electrodes, each data point module M n (k) is coded using the numbers n and k in the following format: [Formula 11]

[0147]

number

[0148] Fixed-Point Format<s, b, p> is used, where s means signed / unsigned, b is the number of bits allocated, and p is the number of bits for precision. n (k) is encoded in U32 format.

[0149] For a given Fourier coefficient k, i.e., for a given frequency f m Regarding e n measured at electrodes e The data points result in the following data vector: [Formula 12]

[0150]

number

[0151] M n (k) is an integer encoded in U32 format.

[0152] n e -1 vector can be concatenated into the data matrix D, and if the excitation format [Equation 2] is implemented, [Formula 13]

[0153]

number

[0154] and when the excitation format [Equation 5] is implemented, [Formula 14]

[0155]

number

[0156] is.

[0157] Then, the data size is S = n e (n e -1).

[0158] Only the absolute value of the Fourier transform forms part of the data.

[0159] For one image, the data size is S * 32 bits = 4 kB. In comparison, the methods described in publications [2], [3], [4], without any additional information about the boundary conditions, result in 127 kB of data for one image.

[0160] The measurement method implemented by the system according to the invention therefore allows to provide a higher image acquisition rate, with data sizes of n compared to the methods described in publications [2], [3], [4]. e / It can also be reduced by half.

[0161] Obtaining a Signed Data Matrix In a third sub-step, a signed data matrix representing the image is obtained.

[0162] The Fourier transform provides the magnitude and phase. The sign of each data point is deduced from the phase.

[0163] Therefore, the frequency f m At each electrode E n Considering the excitation signal imposed on [Formula 15]

[0164]

number

[0165] The phase of the signal is expressed as follows: [Formula 16]

[0166]

number

[0167] frequency f m Electrode E l The current I measured at l meas The phase of (t) is [Formula 17]

[0168]

number

[0169] is.

[0170] Assuming synchronous sampling between the analog signal input AI and the sampled signal output AO, the phase shift between the excitation potential and the measured current is [Formula 18]

[0171]

number

[0172] is.

[0173] The phase shift depends on the design of the EIT sensor and the nature of the flow within the body. If the phase shift is significant, wrap-around effects may make it impossible to reconstruct the sign of the data. In fact, the phase is symmetric with respect to a transformation of 2πN, where N is an integer. If the phase is greater than 2π, it will wrap around on itself.

[0174] The following two cases were identified: [Formula 19]

[0175]

number

[0176] In the first case, the sign of the data point is calculated from the above equation. Then, the element of the signed data matrix corresponding to the k-th Fourier coefficient and the n-th electrode is [Formula 20]

[0177]

number

[0178] is.

[0179] In the second case, the wraparound effect is n k This prevents the sign of σ from being estimated. Then, a sign matrix Σ is introduced to assign arbitrary signs to the data.

[0180] The sign matrix Σ is estimated from the sign of the excitation signal at t = 0 for a given harmonic of a given electrode by introducing the following sign function: [Formula 21]

[0181]

number

[0182] V n meas is as defined above.

[0183] More specifically, the sign matrix Σ is defined such that its rows alternate between cosine and sine signs, with each row having an integer number of periods: the first two rows have one period, and each subsequent pair of rows increases the number of periods by one unit.

[0184] In other words, when the excitation format [Equation 2] is implemented, the rows of the code matrix Σ are such that the ith element of the jth row is cosine ([2π / ([j+1] / 2)]*(i-1) / n for odd j. e), and for even j it is the sine ([2π / (j / 2)]*(i-1) / n e ) is defined to be the sign of

[0185] For example, the first element of the first row of the sign matrix is ​​the sign of cosine (0), i.e., +. The number of electrodes, n e If is equal to 16, then the sign of the fifth element in the first row is the sign of cosine (2π*[4 / 16]), i.e., 0.

[0186] Thus, the first row of the sign matrix is ​​the sign of the period of the cosine function, i.e., for the i-th element of the row, the cosine (2π*(i-1) / n e ) The second row represents the sign of one period of the sine function, i.e., the sine (2π*(i-1) / n e ) The third line represents the sign of two periods of the cosine function, i.e., the cosine ([2π / 2]*(i-1) / n e ) The fourth row represents the sign of two periods of the sine function, i.e., the sine ([2π / 2]*(i-1) / n e ) The fifth line represents the sign of the three periods of the cosine function, i.e., the cosine ([2π / 3]*(i-1) / n e ) sign, and (n e -1) and so on.

[0187] For example, for a device with 16 electrodes, the code matrix will have the format shown in Figure 9. For a device with 32 electrodes, the code matrix will have the format shown in Figure 10.

[0188] When the excitation format [Equation 5] is implemented, the closest excitation electrode is assigned an opposite sign, especially for measurement electrodes at equal distances between the two excitation electrodes. The amplitude is experimentally measured to be of the order of O(10-7) A, corresponding to a negligible contribution to the data.

[0189] The use of such a code matrix optimizes the processing of the data to form an image, allowing the code of each data point to be estimated and the image to be reconstructed.

[0190] For significant phase shifts, i.e., phase shifts of π / 2 or more, n e n of electrodes e The arbitrarily signed amplitude of one excitation pattern, in other words the element of the signed data matrix corresponding to the k-th Fourier coefficient and the n-th electrode, is given by [Formula 22]

[0191]

number

[0192] is given by

[0193] Algorithm implementation The HOST portion of the acquisition system continuously sends frequency and amplitude parameters to the FPGA of the acquisition system.

[0194] FIG. 6 shows the algorithm for generating excitation signals for the 16 electrodes.

[0195] In the considered system, the FPGA receives 16x16 data points in a loop defined as 1 MS / s to create 16 analog signals.

[0196] In the first step, the system is initialized.

[0197] Initially, the FPGA is empty. The HOST loads the FPGA and the NI-9262 module is reset.

[0198] In the second step, the interrupt request is sent and received.

[0199] A hardware interrupt is used to notify the HOST when the FPGA is ready to start collecting data. The FPGA waits for confirmation from the HOST before starting collection.

[0200] In the third step, a sampling check is performed.

[0201] The Generate Sample Pulse function is called to start generating data points. The frequency with which the function is called determines the sampling rate for generating data points. At the same time, the Write I / O Status function is called with the same frequency to check the status of each generated sample.

[0202] In the fourth step, a digital excitation signal function is generated.

[0203] The HOST commands the FPGA to start generating the excitation signal function.

[0204] In the fifth step, the analog excitation signals are generated: 16 excitation signals are sent to the electrodes.

[0205] In the sixth step, the HOST verifies that a signal has been generated, indicating any errors in the HOST or FPGA.

[0206] Steps 1 and 2 are performed once when the algorithm is started. Steps 3 through 6 are repeated for each output point at the sampling frequency.

[0207] The sampling frequency can range between 10 kHz and 500 MHz, preferably between 500 kHz and 50 MHz.

[0208] FIG. 7 shows an algorithm for processing the data received from the electrode 100.

[0209] By measuring the voltage at the terminals of resistor R, the Neumann boundary conditions for implementing the image reconstruction algorithm can be inferred. An acquisition rate of 1 MS / s for 16 channels corresponds to a data transfer rate of 320 MB / s.

[0210] The use of a Fast Fourier Transform, which only considers the Fourier coefficients linked to the generated signal, allows the size of the data to be reduced without affecting its quality. It also acts as an effective bandpass filter. However, calculating 16 Fast Fourier Transforms in real time requires high computational power. FPGAs, which allow signals across several channels to be transformed simultaneously in real time into their Fourier components, are a suitable tool to perform this task.

[0211] In the first step A, the system is initialized.

[0212] The FPGA resets the NI-9223 analog signal acquisition module.

[0213] In a second step B, the memory is configured.

[0214] The HOST configures and initiates direct access to the FPGA memory. The FPGA configures and initiates 16 first-in-first-out queues to ensure that the 16 measurement channels are connected with their fast Fourier transform calculations.

[0215] In a third step C, an interrupt request is sent or received.

[0216] A hardware interrupt ensures that the queue and direct access to memory are ready.

[0217] In the fourth step D, the sampling is verified.

[0218] The sample pulse generation function is called to control the sampling rate, and the I / O status read function is called at the same frequency to check the status of each sample and notify the HOST of any errors.

[0219] In a fifth step E, analog measurement signals are acquired.

[0220] The I / O Read function is configured to read one sample from each channel of each NI-9223 module. This function is called at 1 MHz and is regulated by the Sample Pulse Generation function.

[0221] In the sixth step F, the fast Fourier transform of each channel is calculated in a loop at 1 MHz. The calculation time is determined by the number of points P considered for the Fourier transform. Once P measured data points have been transferred for the Fourier transform calculation, the function recovers P Fourier coefficients one by one for each iteration of the Fourier transform loop. In the second phase, the amplitudes of the Fourier coefficients are calculated at a frequency of 1 MHz.

[0222] In a seventh step G, the data is addressed.

[0223] The amplitude data points in U32 format, together with the corresponding Fourier coefficients (in U16 format) and the corresponding channels (in U16 format), form data elements in U64 format. At each iteration of the Fourier transform loop, 16 elements for the 16 channels are written to direct access memory for transmission to the HOST.

[0224] In the eighth step H, a data matrix is ​​constructed.

[0225] The HOST waits for the direct access memory to collect at least 240 elements representing the complete data image. The addresses of the nth electrodes and Fourier coefficients associated with the amplitudes are used to form the data matrix D.

[0226] In the ninth step I, the data matrix is ​​stored.

[0227] The data is used to perform or store real-time image reconstruction, which is based on a one-step iterative least squares reconstruction algorithm, such as that described in publication [5].

[0228] Real-time image reconstruction can produce approximately 100 images per second.

[0229] In a tenth step J, signal acquisition is verified and error checking is performed.

[0230] The synchronization of the module for generating analog signals and the module for measuring analog signals is checked and any errors are reported.

[0231] Steps A through C are executed once when the algorithm is started.

[0232] Steps D through G are repeated for each output point at the sampling rate.

[0233] n e *(n e Once a complete data matrix containing −1) data points has been collected, the algorithm transitions to step H. Steps H through J are repeated at the image collection rate.

[0234] The sampling frequency can range between 10 kHz and 500 MHz, preferably between 500 kHz and 50 MHz.

[0235] Figure 8 shows in the left graph the excitation signals for 6 of the 16 electrodes, each signal consisting of a sum of 15 sinusoidal functions.

[0236] The solid line in the right graph of Figure 8 represents in equivalent Fourier space the measured voltage V across resistor R shown in Figure 2. meas where R = 200 Ω. The dashed line represents the Fourier transform of the voltage of the generated signal.

[0237] 11 shows an experimental image of a bubbly water flow obtained by neural network reconstruction based on the measurement matrix described above according to the present invention, and a comparative experimental image according to the prior art. It is clear that the detection according to the present invention is much more accurate than that according to the prior art, and corresponds almost perfectly to the experimental situation.

[0238] In response to signals from the fluid flow indicative of one or more cavitations, the electronic automatic control unit 14 may or may not modify the operating frequency of the pump 20, or even interrupt it, so as to avoid any excessive consumption of electricity and, if appropriate, prevent the pump 20 from being damaged.

[0239] The invention is not limited to the examples described above, and in particular it is possible to combine features of the examples shown in alternative embodiments not shown.

[0240] Other alternative embodiments and modifications may be envisaged without departing from the scope of the invention, in particular the methods performed by the system according to the invention may use collection systems other than those described.

[0241] In the examples shown, the number of sensor electrodes is equal to 16 or 32, although a smaller number, in particular 4 or 12 electrodes, or a number greater than 32 may be considered. (References) TIFF2025539692000040.tif112170 [Explanation of symbols]

[0242] 1 System 2 circuits 10 Electrical Sensors 11 units, screens 12 Printed circuits, control circuits, units 13 Signal Processing Unit, Risk 14 Electronic Automatic Control Unit 20 Pump 21 Main body, section 22 Casing 23 Through hole 24 power ports 100 electrodes

Claims

1. A system (1) for optimizing the consumption or production of electricity in a fluid machine having at least one rotating component adapted to be electrically powered or to produce electricity, comprising: at least one electrical sensor (2) comprising a plurality of electrodes (100) distributed around the body of the fluidic device, the ends of the electrodes being flush with the inner surface of the body and facing the rotating component; an electronic circuit (12) for controlling the electrodes and for tomographic measurements by electrical impedance, the electronic circuit (12) being adapted to simultaneously excite each of the electrodes and, if applicable, to measure the electrical impedance matrix of the fluid flow containing cavitation bubbles in the body; a signal processing unit (13) adapted to reconstruct an image of the fluid flow in the body from measurements of the impedance matrix of the electronic circuit; an electronic unit (14) for automatically controlling components for controlling said fluidic equipment, adapted to adjust the operating power of said equipment and thus modify the operating frequency of said equipment to adjust the flow:power ratio of said equipment; A system (1) comprising:

2. The optimization system of claim 1, wherein the fluid equipment is a pump or a turbine, the end of the electrode faces a free end of a blade of the pump or the turbine or is integrated with the free end, and the control component is a frequency variator.

3. 3. The optimization system of claim 1, wherein the operation of the electronic unit for automatically controlling the fluidic device is under the control of the operation of the signal processing unit.

4. An optimization system as described in any one of claims 1 to 3, comprising a casing fixed around the main body of the fluid device that houses the electrical sensors such that the electrodes are individually and sealably housed and fixed in the through holes of the main body.

5. The optimization system of claim 4 , wherein the casing houses a power port for the electrode.

6. 6. The optimization system of claim 1, wherein the signal processing unit is adapted to implement a neural network for reconstructing an image.

7. The control circuit performs the following steps: a / energizing the electrodes, wherein each electrode is energized to a potential V n exc and the potential V n exc but in the following format: [Formula 2] [Equation 1] where A is the amplitude of the signal and m∈1,...,(n e -1) represents the spatial frequency, and n e is the number of electrodes, and θ n is the angular position of electrode n, and f m = m * f 0 is the vibration frequency, and f 0 But for any m, f m is a fundamental frequency selected to be less than the Nyquist frequency of the system; [Equation 2] is the set of odd natural numbers, [Equation 3] is the set of even natural numbers, or the potential V n exc but in the following format: [Formula 5] [Equation 4] and by convention, if the value of the start index is greater than the value of the end index, the sum is also zero, [Formula 6] P i (t) = A sin(2πf i t)、 [Formula 7] [Equation 5] and [Formula 8] [Equation 6] and [V j (t)] n-1 is the voltage V j In identities such as the identity defining (t), the term Ψ i The voltages V are always arranged in ascending order of index i. j represents the (n-1)th element of said identity defining (t), and excitation is performed either simultaneously for all said electrodes according to [Equation 5] or sequentially for one or more subsets of electrodes; b / the electrical characteristic V of the flow of fluid at the electrodes n meas measuring the c / a step of processing the data derived from the measurement step, step b / , comprising the following sub-steps: c1 / each electrode E n Regarding [Formula 10] [Equation 7] The data points M defined by n the sub-step of calculating n meas is the value of the resistor used to measure V at the resistor terminals. n meas = RI n and P is the current I n is the number of points in the discrete sequence of measurements of e -1), and β p = (2πp / P), the substep, c2 / the data points M for all n and all k n (k) to the data matrix D as follows, i.e., if the excitation format [Equation 2] is implemented: [Formula 13] [Equation 8] Or, if the excitation format [Equation 5] is implemented, [Formula 14] [Equation 9] forming a substep according to c3 / forming a matrix of signed data, the elements of which represent the phase shift Φ between the excitation potential at electrode l and the measured current at electrode n n,l When (k) is less than π / 2, the following equation is satisfied: [Formula 20] [Equation 10] and the elements of the matrix are the phase shift Φ between the excitation potential at the electrode l and the current measured at the electrode n. n,l When (k) is equal to or greater than π / 2, the following equation is satisfied: [Formula 22] [0011] and Σ is defined by When the excitation format [Equation 2] is implemented, the i-th element of the j-th row of Σ is given by cosine ([2π / ([j+1] / 2)]*(i-1) / n for odd j. e ), and for even j it is the sine ([2π / (j / 2)]*(i-1) / n e ) is the sign of When the excitation format [Equation 5] is implemented, especially for measurement electrodes at equal distances between the two excitation electrodes, the amplitude is experimentally measured to be of the order of O(10-7) A, which corresponds to a negligible contribution to the data, with the nearest excitation electrode being assigned an opposite sign. The substep is a matrix of signs defined as Including steps 7. The optimization system of claim 1, adapted to perform the following:

8. The control circuit controls all of the potentials V n exc The following conditions are met: [Formula 4] [0012] 8. The optimization system of claim 7, adapted to perform step a / by verifying:

9. 9. The optimization system of claim 1, wherein the electrodes of the electrical sensor are distributed at equal angles around the body of the fluidic device.

10. 10. Use of the optimization system according to any one of claims 1 to 9 for measuring cavitation, bubbles, absence of fluid and presence of gas.

11. An industrial installation comprising at least one fluid circuit and an optimization system according to any one of claims 1 to 9.

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