System for reducing or optimizing the electrical consumption or production of fluidic equipment with at least one rotating component.

Abstract

A system for reducing or optimizing the electrical consumption or production of fluidic equipment with at least one rotating component. This system comprises: - at least one electrical sensor (2) with electrodes (100) distributed around a body of the equipment, with their ends flush with the inner surface of the body and facing the component; - an electronic circuit (12) for controlling the electrodes and for electrical impedance tomographic measurement; - a signal processing unit adapted to reconstruct images of the fluid in the body from matrix measurements; - an electronic unit for automatically controlling the equipment's control element, adapted to modify the equipment's operating frequency to adjust its electrical power and thus its flow / power ratio.Figure for the abridged version: fig.2.

Description

Title of the invention: System for reducing or optimizing the electrical consumption or production of a fluidic equipment with at least one rotating component. Technical field

[0001] The present invention relates to the field of monitoring fluidic equipment intended to be implemented in a fluidic circuit, particularly in an industrial installation.

[0002] The invention relates more particularly to the detection of air bubbles whose presence is due to a phenomenon called cavitation, in a fluid flowing in a fluidic circuit and capable of generating an overconsumption of electricity or an overproduction of electricity of a fluidic equipment with a rotating component in said circuit.

[0003] Although described with reference to a pump monitoring application, the invention can be applied to the monitoring of any type of fluidic equipment with a rotating component and / or capable of creating a pressure drop leading to cavitation, such as a turbine, which may be present in a fluidic circuit, particularly in an industrial installation.

[0004] For the purposes of this invention, "fluidic equipment" refers to at least one rotating component or set of electromechanical components that can be used in a fluidic circuit and is adapted to be electrically powered or to generate electricity. This refers to an active device in which at least one rotating component moves volumes of fluid continuously and / or discontinuously (pump, marine propulsion) or uses the force of a fluid (turbine). Previous technique

[0005] Pumps are a key element of industrial installations, and are today, after electric motors, the second most manufactured device in the world.

[0006] Pumps transport the fluids necessary for human activities, particularly industrial ones, such as most raw materials, water, fluids from the food processing, chemical, pharmaceutical, construction, paper, electronics, mining, fossil fuel industries, ...

[0007] The so-called cavitation phenomena, i.e. the presence of vapor bubbles created by too much suction power or by the absence of fluid at the suction of a pump, can generate overconsumption of electricity or even cause the pump to break down.

[0008] To solve this problem, the pumps can be disassembled and parts They are replaced or cleaned as part of scheduled maintenance. However, this can lead to unnecessary expenses because, to be safe, the pumps must be serviced more frequently than actually required.

[0009] There are a large number of fluidic circuit monitoring systems incorporating one or more pumps.

[0010] They are based mainly on measurements of pressure differences, vibrations, infrared or ultrasonic measurements, as respectively described in patent applications / patents FR3026443A1, CN111197581A and EP1297331B1.

[0011] These existing systems do not allow for the real anticipation of electrical overconsumption or, conversely, electrical underconsumption, or even pump failures.

[0012] In particular, while some commercial solutions implemented allow for the detection of a high degree of cavitation, they can be complex to implement and are specific to certain types of pumps.

[0013] There is therefore a need for a pump monitoring system in a fluidic circuit which overcomes the disadvantages of known systems, in particular to allow cavitation to be detected in a simple way for all types of pumps, in order to optimize the electrical consumption of the pump and in any case to prevent pump failure which would be due to cavitation.

[0014] More generally, there is a need for a monitoring system for fluidic equipment with at least one rotating component implemented in a fluidic circuit, which is capable of detecting cavitation in a simple way in order to optimize the electrical consumption or production of the equipment, and in any case, to prevent equipment failure due to cavitation.

[0015] The object of the invention is to meet at least partially these needs. Description of the invention

[0016] To this end, the invention relates, according to one of its aspects, to a system for reducing or optimizing the electrical consumption or electrical production of fluidic equipment with at least one rotating component, adapted to be electrically powered or to produce electricity, comprising:

[0017] - at least one electrical sensor comprising a plurality of distributed electrodes around a body of the fluidic equipment, with their end flush with the internal surface of the body and facing the rotating component;

[0018] - an electronic circuit for controlling the electrodes and for tomographic measurement by electrical impedance, the circuit being adapted to respectively excite the electrodes simultaneously, and measure electrical impedance matrices of the flowing fluid including where appropriate cavitation bubbles in the body;

[0019] - a signal processing unit, adapted for reconstructing fluid images flow in the body from impedance matrix measurements of the electronic circuit;

[0020] - an electronic automatic control unit for the control element of the fluidic equipment, adapted to modify the operating frequency of the equipment in order to adjust its electrical operating power and thus adjust its flow / power ratio.

[0021] According to one embodiment, the fluidic equipment is a pump or a turbine, the end of the electrodes facing the free end of the blades of the pump or turbine or being integrated into them, the control element being a frequency inverter.

[0022] Advantageously, the operation of the electronic automatic control unit of the fluidic equipment is controlled by that of the signal processing unit.

[0023] According to an advantageous construction method, the system comprises a housing fixed around the body of the fluidic equipment, housing the electrical sensor with the electrodes housed and fixed individually in a sealed manner in a hole opening from the body.

[0024] Preferably, the housing accommodates a power supply port for the electrodes.

[0025] According to an advantageous embodiment, the signal processing unit is adapted to implement a neural network for image reconstruction.

[0026] According to an advantageous embodiment, the control circuit is adapted to implement the following steps:

[0027] a / excitation of the electrodes, each electrode being excited by a potential Vnexc having either the form:

[0028] [Math.2] Vfc ( t ) =}cos ( Zrrfj ) [ ô^cos( mdn ) + ô®sin(^)]

[0029] where A is a signal amplitude, ne the number of electrodes, 0n is the angular position of electrode n, fm = m * f0 is an oscillation frequency, f0 is a fundamental frequency chosen such that fm is less than the Nyquist frequency of the system for all m, O the set of odd natural numbers, £ the set of even natural numbers,

[0030] i.e. the form:

[0031] [Math.5] tinOX

[0032] in which, by convention, a sum is identically zero if the value of the starting index is greater than that of the final index,

[0033] where:

[0034] [Math.6] ^i(t) -A sin(Irrf.t),

[0035] [Math.7] jmin / , \ n(wl) ln +

[0036] and

[0037] [Math. 8] ,max (ah-I) n L n = nn e - ——,

[0038] and with FV (?) 1 denoting the (n-1)th element of the identity defining the voltage Vsous the convention according to which the terms are always arranged in ascending order of the indices i in such an identity, the excitation being carried out either simultaneously on all the electrodes according to [Math 5], or sequentially on one or more subsets of electrodes;

[0039] b / measurement of the electrical properties Vnmeas of the fluid flow with electrodes,

[0040] c / processing of data from measurement step b, comprising the following sub-steps: cl / for each electrode En, calculation of the data points Mn defined by:

[0041] [Math. 10] M„(k) =

[0042] where R is the value of the resistance used for the measurement of Vnmeas with Vnmeas = R In across the resistor, P is the number of points in a discrete sequence of measurements of the current In, p is the discrete time, k is a Fourier coefficient between 1 and (ne - 1) and [3P = (2jrp / P),

[0043] c2 / constitution of a data matrix D from the data points Mn(k) for all n and for all k, according to the equation:

[0044] [Math. 13] M( 01 M(2)) { ».,(3)} '(«»(«,-1)1 '

[0045] if the excitation form [Math 2] is implemented,

[0046] or

[0047] [Math. 14] {-MO) !M„(2)} {«„(3))

[0048] if the excitation form [Math 5] is implemented,

[0049] c3 / constitution of a signed data matrix whose elements are defined by the following equation when the phase shift <bnj(k) entre le potentiel d’excitation à l’électrode 1 et le courant mesuré à l’électrode n est inférieur à ir / 2 :

[0050] [Math.20] _ sin(0;jZ(À.-) ) " - 1^(0)1 'P and whose elements are defined by the following equation when the phase shift <hn4(k) entre le potentiel d’excitation à l’électrode 1 et le courant mesuré à l’électrode n est supérieur ou égal à ir / 2 : [Math 22]

[0051] [Math.22] r)m _

[0052] where S is a sign matrix defined such that:

[0053] - if the excitation form [Math 2] is implemented, the i-th element of the j-th line S is the sign of cosine([2ir / ([j+l] / 2)]*(il) / ne) for odd j and the sign of sine([2jr / (j / 2)]*(il) / ne) for even j,

[0054] - if the excitation form [Math 5] is implemented, the opposite sign is assigned to the nearest excitation electrode, in particular for a measurement electrode located at an equal distance between two excitation electrodes, the amplitude is experimentally measured to be on the order of 0(10-7) A, corresponding to a negligible contribution to the data.

[0055] Preferably, the control circuit is adapted to implement step a / with all the potentials Vnexc satisfying the condition:

[0056] [Math.4] LO) =»•

[0057] According to an advantageous configuration, the electrodes of the electrical sensor are angularly distributed regularly around the body of the fluidic equipment.

[0058] The invention also relates to the use of the optimization system to measure cavitation, air bubbles, absence of fluid and presence of gas.

[0059] The invention also relates to an industrial installation, comprising at least one fluidic circuit and an optimization system as described above.

[0060] In general, the invention can be implemented in any fluidic circuit, in particular in a factory or industrial production site, especially in the fields of food processing, pharmaceuticals and cosmetics, chemicals and petrochemicals, water distribution and treatment.

[0061] The invention therefore essentially consists of a cavitation detection system likely to cause overconsumption of electricity or overproduction of electricity or even breakage of a fluidic equipment with a rotating component installed in a fluidic circuit.

[0062] The system includes an electrical sensor with distributed electrodes, preferably regularly around a body of the equipment and with their end flush with the inner wall of the body preferably as close as possible to the blades of the rotating component.

[0063] Electrical Impedance Tomography (EIT) measurements are performed using either trigonometric signals or electrode pair signals, implemented simultaneously for electrode excitation.

[0064] This measurement allows, in a non-invasive and non-destructive manner, to visualize, in real time and continuously, the inside of the body of the fluidic equipment and therefore of the fluid flowing within it, by measuring the electrical properties (potential and electric current).

[0065] The electrical impedance map inside the body is reconstructed by solving the inverse problem.

[0066] The acquisition speed of the images reconstructed by the processing unit can be very high, typically up to 31,250 images / second, which makes it possible to observe fluids flowing at a rate of up to 300 meters / second.

[0067] Depending on the signals from the flowing fluid that are representative of cavitation, an electronic unit will automatically modify the operating frequency of the equipment in order to adjust its electrical operating power and thus adjust its flow / power ratio.

[0068] By this means, the risk of cavitation is eliminated, or at least reduced, and the electrical consumption or electrical production of the equipment is adapted to just what is necessary.

[0069] The advantages of the invention just described are numerous, among which we can mention: - a direct measurement of cavitation causing excessive electrical consumption or even pump failure; - rapid detection and possible preventive action due to the possibility of acquiring measurements / images at a very high rate, up to 31,250 images / second; - a robust system because it is reliable regardless of the fluid used, even under very high pressure, typically up to 300 bars or even beyond, and / or at very high temperatures, typically up to 600°C or even beyond. Brief description of the drawings

[0070] [Fig-1] Fig. 1 illustrates a fluidic circuit comprising a pump, which can generate cavitation within the fluid flowing through the pump, this cavitation being detectable by an electrical consumption optimization system according to the invention, comprising an electrical electrode sensor for electrical impedance tomography measurement.

[0071] [Fig.2] Fig.2 schematically illustrates the hardware and software means of an optimization system according to the invention.

[0072] [Fig.3] Fig.3 illustrates a pump body incorporating an electrical sensor of a system according to the invention.

[0073] [Fig.3A] The [Fig.3A] is a cross-sectional view of a pump body according to the [Fig.3], at the level of the electrodes of the electrical sensor.

[0074] [Fig.4] Fig.4 illustrates spatial cosine patterns.

[0075] [Fig.5] The [Fig.5] represents a part of an electronic circuit allowing the excitation of an electrode.

[0076] [Fig.6] The [Fig.6] illustrates a method of generating the excitation signals of the electrodes of the electrical sensor according to a first variant of the invention.

[0077] [Fig.7] Fig.7 illustrates a method for measuring the signals generated by the electrodes.

[0078] [Fig.8] Fig.8 represents graphically excitation signals and some of their properties.

[0079] [Fig.9] The [Fig.9] illustrates a sign matrix for an electrical sensor with 16 electrodes.

[0080] [Fig. 10] The [Fig. 10] illustrates a sign matrix for an electrical sensor with 32 electrodes.

[0081] [Fig. 11] The [Fig. 11] illustrates images reconstructed respectively according to the state of the art and experimentally and simulated by neural network in a system according to the invention. Detailed description

[0082] An example of the implementation of a system 1 for optimizing the electrical consumption of a pump 20 moving a fluid in a circuit 2 comprising the pump 20 is illustrated in [Fig. 1]. This system makes it possible to detect air bubbles due to cavitation which cause excessive electrical consumption or even failure of the pump 20. This system also makes it possible, via impedance measurement, to measure the operation at Dryness, foreign matter, blockages, viscosity changes, or other types of defects can reduce pump performance or cause blockage. The system can also measure internal pump wear in real time and diagnose the hydraulic performance of the fluidic equipment.

[0083] The system 1 includes first of all an electrical sensor 10, arranged in a body 21 of the pump 2. This electrical sensor 10 allows measurements to be made by Electrical Impedance Tomography of the fluid flowing in this body 21.

[0084] An operational control unit 11 of the pump frequency inverter, according to real-time fault measurements so as to prevent the pump 20 from cavitation, depending on representative flow fluid signals, as detailed later.

[0085] More specifically, the electrical sensor 10 comprises a number of 16 electrodes 100 distributed, preferably angularly distributed regularly, around the body 21 with their end flush with the internal surface of the body 21, preferably as close as possible to the end of the pump blades.

[0086] The synoptic diagram of the hardware and software means of system 1 is illustrated in [Fig.2].

[0087] The electrodes 100 are connected to a printed circuit board 12 which is an electronic circuit of electrode control 100 and tomographic measurement by electrical impedance, the circuit being adapted to respectively excite the electrodes simultaneously, and measure electrical impedance matrices of the flowing fluid including where appropriate cavitation bubbles in the body 21.

[0088] A signal processing unit 13 allows images of the fluid flowing in the body 21 to be reconstructed from the impedance matrix measurements of the electronic circuit 12.

[0089] An electronic automatic control unit 14 allows, from a risk 13 identified or not for the pump 20, preferably by digital communication, to control the frequency inverter of the pump, and more generally to carry out the supervision of the industrial installation in which the fluidic circuit 2 is located.

[0090] By changing the operating frequency of the pump 20, it is possible to adjust its electrical operating power and thus adjust its flow / power ratio.

[0091] Figures 3 and 3A illustrate an advantageous mode of integration in the form of a housing 22 accommodating an electrical sensor 10 within a fluidic circuit.

[0092] A housing 22 fixed around the pump body 21 houses the electrical sensor 10 with the electrodes 100 housed and individually fixed in a sealed manner in a hole 23 opening from the conduit.

[0093] The housing 22 can accommodate a power supply port 24 for the electrodes.

[0094] The control circuit 12 can be connected to a data acquisition system. A screen 11 can be used to view the data and the images produced from that data. The data acquisition system contains a Linux operating system (HOST) which controls a programmable FPGA logic array, also contained within the data acquisition system.

[0095] The acquisition system allows the generation of analog excitation signals and the measurement of analog measurement signals from electrodes 100.

[0096] The acquisition system may integrate, for example, a cRIO-9039 controller from the manufacturer National Instruments which includes a programmable logic network, NL9262 modules from the manufacturer National Instruments for the generation of analog excitation signals and NI-9223 modules from the manufacturer National Instruments for the measurement of analog signals from electrodes 100.

[0097] The method of measuring and processing signals implemented by the system for detecting faults and preventing pump failures according to the invention will now be described.

[0098] It is specified that the electrical sensor 10 is first installed within the fluidic circuit with the electrodes 100 arranged as previously indicated. Electrode excitation

[0099] A first step consists of simultaneously exciting all the electrodes 100 by a potential having a well-chosen shape.

[0100] The electrodes 100 constitute a set of linearly independent electrodes. They are used to create electrical excitations on the surface of the body and to measure its electrical properties.

[0101] The excitation according to the variant of trigonometric patterns [Math 2] is as follows: for a number of ne electrodes, there exist (ne - 1) linearly independent excitation patterns. The Fourier basis functions are a natural choice for describing these linearly independent patterns, according to the equation:

[0102] [Math.l] __S__oinS

[0103] According to a first alternative, all the electrodes are excited simultaneously using trigonometric excitations.

[0104] This set of simultaneous excitations is decomposed into spatial oscillations according to the Fourier basis and into temporal oscillations.

[0105] Different frequencies are imposed in order to establish a distinction between the different trigonometric signals in frequency multiplexing.

[0106] For each trigonometric excitation pattern, each electrode En is associated with a static voltage Vnsta.

[0107] The set of static voltages Vnsta forms a set of sinu- functions soidal and cosinusoidal having different spatial frequencies m.

[0108] Fig. 4 represents the spatial cosine patterns for m varying from 1 to 5. Sinusoidal patterns are not shown.

[0109] The electrodes are arranged on the periphery dQ of the body, represented by the dashed lines in [Fig.4]. The solid lines represent the excitation potential imposed on the electrodes.

[0110] The static potential Vn>msta associated with each electrode En is defined by the following equation, for n between 1 and ne: [YES] [Math.2] (t) = .008 (2nfmt) [Ccos(mGn) + <sin (^)]

[0112] where A is a signal amplitude, mel,...,(n_e-l) represents the spatial frequency, the number of electrodes, 0n is the angular position of electrode n, fm = m * f0 is an oscillation frequency, f0 is a fundamental frequency chosen such that fm is less than the Nyquist frequency of the system for all m, O the set of odd natural numbers, £ the set of even natural numbers.

[0113] For a given set of ne electrodes, all independent excitation patterns are fully described with (ne - 1) different spatial frequencies. For the particular case where 0n = 2ir n / ne, the electrodes are distributed regularly around the periphery of the body.

[0114] Each spatial frequency m is associated with a temporal frequency fm and is imposed simultaneously on each of the electrodes.

[0115] Thus, each simultaneous excitation potential Vnexc comprises a superposition of (ne — 1) trigonometric functions, each function oscillating at a particular frequency fm.

[0116] The excitation signal of an electrode n is Vnexc, defined by the following equation:

[0117] [Math.3] C'A) = V Ht- ' = ÆJ^cos ( 2rrfmt ) [ Ccos( m0n ) + ^sin( ^ ) ].

[0118] Each potential Vnexc(t) thus defined is simultaneously applied to each electrode En. Care is taken to ensure that the sum of the excitation voltages of the ne electrodes is zero for all time t. This translates into the condition:

[0119] [Math.4] w = 0.

[0120] According to a second alternative of the invention, the excitation form is as follows:

[0121] [Math.5] "tituix vr(r) = -O

[0122] in which, by convention, a sum is identically zero if the value of the starting index is greater than that of the final index,

[0123] where:

[0124] [Math.6] (t) - A if n (Infî),

[0125] [Math.7] lT = ( / / -1)^-^ + 1,

[0126] And

[0127] [Math.8] ,max("+1")n l„ = n ne--—,

[0128] and with F y.( / )] denoting the (n-1)th element of the identity defining the voltage Vj(t), under the convention that the terms j are always arranged in ascending order of the indices i in such an identity. Excitation can be applied to all electrodes simultaneously or to a subset of electrodes sequentially. Measurement of electrical properties

[0129] The electrical properties of the fluid flowing in section 21 are then measured using electrodes 100.

[0130] Unit 12 controls the programmable logic network of the acquisition system so as to generate 16 excitation signals having the properties described. These 16 digital signals are converted into analog signals by the NL9262 modules and transmitted via coaxial cables to the electrodes 100.

[0131] The printed circuit board 12 includes an excitation circuit for each electrode 100, each of these circuits having a resistance R as illustrated in [Fig. 5]. As can be seen in this figure, the potential Vnexc is imposed on one side of the resistance R, the other side being connected to the electrode En.

[0132] The Neumann boundary condition at electrode En is the current In flowing through the excitation circuit. This current is obtained by measuring the voltage Vnmeas = R In across the resistor. As with Vnexc, this signal is a sum of trigonometric functions. Data processing

[0133] In a fourth step, the data measured in the second step are processed in order to either directly provide information to a processing algorithm or to obtain a signed data matrix representative of an image. Generation of Mn data points

[0134] In a first sub-step of the fourth step of the measurement process, the data points Mn are calculated for each electrode n.

[0135] The Fourier transform of the measured signal Vnmeas is calculated from a P-point current measurement sequence In(p), where p is the discrete time and satisfies 0 < p < P, i.e.:

[0136] [Math.9] = F[Z„(p)] = where i = and the normalization factor 8 -

[0137] The Fourier transform can be calculated at the frequency fi which corresponds to the frequency at which P Fourier coefficients are calculated.

[0138] The frequencies fm of the Vnexc voltages are chosen to be harmonics of fb. This allows the measured signals to be distinguished. Thus, each coefficient k is associated with a particular frequency fm.

[0139] The data are then generated at a frequency fi and the resolution in the Fourier space is Af = fm+i - fm = fb. It can be noted that the highest frequency is chosen to be less than the Nyquist frequency of the system fNyq = 1 / 2 Ap, where Ap is the sampling time.

[0140] The data points Mn(k) are the moduli of each Fourier coefficient k for each electrode n:

[0141] [Math. 10] M,Sk) =

[0142] where R is the value of the resistance used for the measurement of Vnmeas with Vnmeas = R In across the resistor, P is the number of points in a discrete sequence of measurement of the current In, p is the discrete time, k is a Fourier coefficient between 1 and (ne - 1) and [3P = (2irp / P),

[0143] Each data point defines the current of a given trigonometric pattern at a given electrode. The set of data points Mn(k) for all n and all k constitutes the measurement data.

[0144] The excitation frequencies are determined as follows. The sampling frequency fDAQ of the data acquisition system limits the maximum frequency fm of the voltages Vnexec, the Nyquist frequency fNyq = fDAQ / 2 constituting an upper limit.

[0145] For a data acquisition system such as fDAQ = 1 MS / s, the frequency of Nyquist is equal to 500 kHz.

[0146] To take advantage of the small errors in the residual voltage resulting from the energy stored in the electrode-electrolyte contact impedance, continuous signals must be provided. To generate continuous signals at different frequencies, the signals are chosen to be harmonics of the lowest generated frequency.

[0147] When the potential applied to an electrode is removed, some of the electrical energy is stored for a few tens of microseconds at the interface between the electrode and the surrounding medium. This contact impedance phenomenon introduces an error in the measurement and necessitates a dead time between two successive excitations to allow this energy to dissipate. Generating continuous signals has the advantage of never de-exciting the applied voltages, thus avoiding errors related to contact impedance and eliminating the need for dead times.

[0148] With 16 electrodes, a set of excitation signals is generated at 15 different frequencies (according to [Math 2]) and at 120 different frequencies (according to [Math 5]). Considering the sampling rate of the acquisition system, for example 1 MS / s, the frequencies can be chosen such that Σ = i * f0 where fo is the fundamental frequency and i is between 1 and 15 or 1 and 120, respectively.

[0149] Furthermore, in the case with 15 frequencies, the discrete Fourier transforms can be chosen to be performed at P = 32 points since only positive results are considered. This results in an image data acquisition rate of 1 * 10⁶ / 32 = 31,250 frames per second. This choice implies that the lowest sinusoidal signal frequency fi is equal to the computation frequency of the discrete Fourier transforms, and that the highest frequency f₁₅ = 15 * f₀ = 468.875 kHz is below the Nyquist limit of 500 kHz for the system under consideration.

[0150] The excitation amplitudes are determined in the following way.

[0151] The voltage generation and acquisition modules operate within a range of ±10 V. Considering the Vnexc voltages, the amplitude A of the sinusoids must be significantly lower than the sum of the generated sinusoids due to constructive interference. However, the signal amplitude A must be as large as possible to minimize the signal-over-noise ratio.

[0152] Another limitation to consider is the maximum permissible variation between two successively generated potentials. Real-time control in the acquisition system allows for the selection of a satisfactory value of A = 0.15 V, which gives resonance peaks at ± 2.25 V. The rapid transition between positive and negative signal values ​​prevents the occurrence of electrolytic effects. For example, electrolysis occurs in water when a DC voltage is applied. greater than 1.2 V. This phenomenon does not appear for alternating voltages greater than 1.2 V if these voltages vary sufficiently rapidly. Obtaining a data matrix D

[0153] In a second substep, a data matrix D is obtained from the data points Mn.

[0154] For the system considered, with 16 electrodes and using NI-9223 modules, a fixed-point data format with 20 bits allocated to the number, including 5 bits for precision digits, can be used. The electrode index n, from 1 to 16, and the Fourier coefficient k, from 1 to 15, can be described by 4-bit binary numbers.

[0155] For a 32-electrode system, each data point module Mn(k) is coded with the numbers n and k in the following form:

[0156] [Math. 11] Mn(k) (+,8,0) + (+,8,0) + (+,16,11), o □ □ kn M

[0157] where the fixed-point format<s, b, p> is used with s: signed / unsigned; b: number of bits allocated; p: number of bits for precision. The Mn(k) data is encoded in U32 format.

[0158] The n data points measured on the n electrodes for a given Fourier coefficient k, i.e. for a given frequency fm, give the following data vector:

[0159] [Math. 12] {M„(^)) = (M|(t) M^k) M } (k) ... M„,(k))

[0160] where the Mn(k) are integers encoded in U32 format.

[0161] The ne - 1 vectors can be concatenated into a data matrix D:

[0162] [Math. 13] Mid)) D= M(3)) 1) ) /

[0163] if the excitation form [Math 2] is implemented,

[0164] or

[0165] [Math. 14] i M(i)}

[0166] if the excitation form [Math 5] is implemented.

[0167] The size of the data is then S = ne (ne - 1).

[0168] Only the moduli of the Fourier transforms are part of the data.

[0169] For one image, the data size is S * 32 bits = 4 kB. In comparison, the process described in publications [2], [3], [4] results in 127 kB of data for one image, without additional information on the boundary conditions.

[0170] Thus, the measurement method implemented by the system according to the invention allows a higher image acquisition rate and also allows the data size to be reduced by a factor of ne / 2 compared to the method described in publications [2], [3], [4]. Obtaining a signed data matrix

[0171] In a third substep, a signed data matrix is ​​obtained, which is representative of an image.

[0172] The Fourier transforms give a magnitude and a phase. The sign of each data point is estimated from the phase.

[0173] Thus, considering an excitation signal applied to each electrode En at a frequency fm having the form:

[0174] [Math. 15] VZ (t) = Acos (2kf J) [S^cos (men) + Csin (~,

[0175] the phase of the signal is expressed as:

[0176] [Math. 16]

[0177] The phase of the current Iimeas(t) measured at electrode Ei at frequency fm is:

[0178] [Math. 17]

[0179] 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:

[0180] [Math. 18]

[0181] The phase shift depends on the design of the TIE sensors and the nature of the flow within the body. If the phase shift is significant, wrapping effects can make it impossible to reconstruct the sign of the data. This is because the phase is symmetric to a transformation of 2irN, where N is an integer. If the phase is greater than 2ir, it is wrapped around itself.

[0182] The following two cases have been identified:

[0183] [Math. 19] I &nJ ( k ) | < f et > 7112.

[0184] In the first case, the sign of the data points is calculated from the preceding equation. The element of the signed data matrix corresponding to the k-th Fourier coefficient and the n-th electrode is then:

[0185] [Math.20] n ~

[0186] In the second case, the wrapping effects prevent the estimation of the sign of Dnk. A sign matrix S is then introduced to allocate an arbitrary sign to the data.

[0187] The sign matrix S is estimated from the sign of the excitation signal at t = 0 for a given harmonic at a given electrode by introducing the sign function:

[0188] [Math.21] '1 If ¥“>0, - -0 if V" = 0, -1 If V„ < 0,

[0189] with Vnmeas as defined above.

[0190] The sign matrix S is more particularly defined such that its rows represent the signs of a cosine function alternating with those of a sine function, each row having an integer number of periods. The first two rows have a single period, and the number of periods increases by one for each subsequent pair of rows.

[0191] In other words, if the excitation form [Math 2] is implemented, the rows of the sign matrix S are defined such that the i-th element of the j-th row is the sign of cosine ([2ir / ([j+l] / 2)]*(il) / ne) for odd j and sine ([2jt / (j / 2)]*(il) / ne) for even j.

[0192] For example, the first element of the first row of the sign matrix is ​​the The sign of cosine(0) is +. For a number of electrodes ne equal to 16, the sign of the fifth element of the first row is the sign of cosine (2ir*[4 / 16]), which is 0.

[0193] Thus, the first row of the sign matrix represents the signs of one period of a cosine function, that is, the signs of cosine (2ir*(il) / ne) for the i-th element of the row. The second row represents the signs of one period of a sine function, that is, the signs of sine (2ir*(il) / ne). The third row represents the signs of two periods of a cosine function, that is, the signs of cosine ([2ir / 2]*(il) / ne). The fourth row represents the signs of two periods of a sine function, that is, the signs of sine ([2ir / 2]*(il) / ne). The fifth line represents the signs of three periods of a cosine function, i.e. the signs of cosine ([2jt / 3] *(i- l) / ne), and so on up to the (ne-l)th line.

[0194] For example, for a 16-electrode device, the sign matrix takes the form illustrated in [Fig. 9]. For a 32-electrode device, the sign matrix takes the form illustrated in [Fig. 10].

[0195] If the excitation form [Math 5] is implemented, the opposite sign is assigned to the nearest excitation electrode, in particular for a measuring electrode located equidistant between two excitation electrodes. The amplitude is experimentally measured to be on the order of 0(10⁻⁷) A, corresponding to a negligible contribution to the data.

[0196] The use of such a sign matrix makes it possible to optimize data processing to form an image. It allows the sign of each data point to be estimated and an image to be reconstructed.

[0197] For a large phase shift, i.e. greater than or equal to ji / 2, the arbitrarily signed amplitudes of the ne - 1 excitation patterns of the ne electrodes, in other words the elements of the signed data matrix corresponding to the k-th Fourier coefficient and the n-th electrode, are given by:

[0198] [Math.22] Algorithmic implementation

[0199] The HOTE part of the acquisition system continuously sends the frequency and amplitude parameters to the FPGA of the acquisition system.

[0200] Fig. 6 illustrates an algorithm for generating excitation signals for the 16 electrodes.

[0201] With the system considered, the FPGA receives the data points 16 by 16 in a loop clocked at 1 MS / s to create 16 analog signals.

[0202] In a first step, the system is initialized.

[0203] Initially, the FPGA is empty. The HOST loads the FPGA and then the NL9262 modules. are reset.

[0204] In a second step, an interrupt request is sent and received.

[0205] A hardware interrupt is used to notify the HOST when the FPGA is ready to begin data acquisition. The FPGA waits for confirmation from the HOST before starting acquisition.

[0206] In a third step, a sampling check is carried out.

[0207] A sample pulse generation function is called to begin generating data points. The frequency at which the function is called determines the sampling rate for generating the data points. In parallel, an I / O status write function is called at the same frequency to check the status of each generated sample.

[0208] In a fourth step, digital excitation signal functions are generated.

[0209] The HOST commands the FPGA to start generating the excitation signal functions.

[0210] In a fifth step, the analog excitation signals are generated. The sixteen excitation signals are sent to the electrodes.

[0211] In a sixth step, the HOST confirms the generation of signals and reports any errors at the HOST or FPGA level.

[0212] Steps 1 and 2 are performed once at the start of the algorithm. Steps 3 to 6 are iterated for each output point at the sampling frequency.

[0213] The sampling frequency may be between 10 kHz and 500 MHz, preferably between 500 kHz and 50 MHz.

[0214] Fig. 7 represents an algorithm for processing data received from electrodes 100.

[0215] Measuring the voltages across the resistors R allows the Neumann boundary conditions for implementing the image reconstruction algorithm to be deduced. The acquisition rate of 1 MS / s on 16 channels corresponds to a data transfer rate of 320 MB / s.

[0216] The use of fast Fourier transforms, considering only the Fourier coefficients associated with a generated signal, reduces data size without impacting data quality. This also acts as an effective bandpass filter. However, the real-time calculation of 16 fast Fourier transforms requires significant computing power. The FPGA, which allows real-time and parallel transformation of signals into their Fourier components over multiple channels, is a suitable tool for performing this task.

[0217] In a first step A, the system is initialized.

[0218] The FPGA resets the NI-9223 analog signal acquisition modules.

[0219] In a second step B, the memories are configured.

[0220] The HOST configures and starts direct access to the FPGA's memory. The FPGA configures and starts sixteen first-in, first-out queues to ensure communication between the sixteen measurement channels and their fast Fourier transform calculations.

[0221] In a third step C, an interrupt request is sent and received.

[0222] A hardware interrupt ensures that the queues and direct memory access are ready.

[0223] In a fourth step D, the sampling is checked.

[0224] A sample pulse generation function is called to control the sampling frequency and an I / O status read function is called at the same frequency to check the status of each sample and report any error to the HOST.

[0225] In a fifth step E, the analog measurement signals are acquired.

[0226] The I / O read function is configured to read a single sample from each channel of each NI-9223 module. This function is called at 1 MHz and regulated by the sample pulse generation function.

[0227] In a sixth step F, the fast Fourier transform of each channel is calculated in a 1 MHz loop. The computation time is determined by the number P of points considered for the Fourier transform. Once the P measured data points have been transferred for the Fourier transform calculations, the function returns the P Fourier coefficients one by one at each iteration of the Fourier transform loop. Subsequently, the amplitudes of the Fourier coefficients are calculated at a frequency of 1 MHz.

[0228] In a seventh step G, data addressing is performed.

[0229] The amplitude data points in U32 format form with the corresponding Fourier coefficient (in U16 format) and the corresponding channel (in U16 format) a data element in U64 format. At each iteration of the Fourier transform loop, 16 elements for the 16 channels are written into direct access memory to be transmitted to the HOST.

[0230] In an eighth step H, the data matrix is ​​constructed.

[0231] The HOST waits for the direct access memory to collect at least 240 elements, representing a complete data image. The address of the nth electrode and the Fourier coefficient associated with the amplitude are used to form the data matrix D.

[0232] In a ninth step I, the data matrices are recorded.

[0233] The data are used to perform real-time image reconstruction or to be recorded. The image is based on a reconstruction algorithm one-step iterative least squares, for example the algorithm described in publication [5].

[0234] Real-time image reconstruction can generate on the order of a hundred images per second.

[0235] In a tenth step J, the acquisition of the signals is confirmed and an error check is performed.

[0236] The synchronization of the analog signal generation and measurement modules is checked and any errors are reported.

[0237] Steps A to C are performed once at the start of the algorithm.

[0238] Steps D to G are iterated for each output point at the frequency sampling.

[0239] Once a complete data matrix containing ne*(ne - 1) data points is acquired, the algorithm proceeds to step H. Steps H to J are iterated at the image acquisition frequency.

[0240] The sampling frequency may be between 10 kHz and 500 MHz, preferably between 500 kHz and 50 MHz.

[0241] Figure 8 represents, on the graphs in the left-hand section, the excitation signals for six of the sixteen electrodes. Each signal consists of a sum of 15 sinusoidal functions.

[0242] The solid lines of the right-hand graphs of [Fig.8] represent, in the equivalent Fourier space, the amplitudes of the measured voltages Vmeas at the resistances R shown in [Fig.2], with R = 200 Q. The dashed lines represent the Fourier transforms of the voltages of the generated signals.

[0243] Figure 11 illustrates the experimental images and images obtained by neural network reconstruction from the aforementioned measurement matrices of a water flow containing air bubbles, according to the invention, and, for comparison, the experimental images according to the prior art. It is clear that the detection according to the invention is much more precise than according to the prior art and corresponds almost perfectly to the experimental situation.

[0244] Depending on the signals from the flowing fluid representing one or more cavitations, the electronic automatic control unit 14 modifies or does not modify the operating frequency of the pump 20 or even interrupts it, so as to avoid any overconsumption of electricity and where appropriate to prevent any breakage of the pump 20.

[0245] The invention is not limited to the examples just described; in particular, features of the illustrated examples can be combined in unillustrated variants.

[0246] Other variations and improvements may be envisaged without departing from the scope of the invention. In particular, the process implemented by the system according to The invention may use other acquisition systems than the one described.

[0247] If, in the illustrated example, the number of electrodes in the sensor is 16 or 32, a smaller number, such as 4 or 12 electrodes, or a number greater than 32, can be considered. List of references cited

[0248] [1] Teague, G. (2002). Massflow measurement of multi-phase mixtures by means of tomography techniques. University of Cape Town, Faculty of Engineering, Department of Electrical Engineering.

[0249] [2] Dupré, A., Mylvaganam, S. (2017). Simultaneous and Continuons Excitation Strategy for High Speed E1T: the ONE-SHOT method. In Proceedings of the 9th World Congress on Industrial Process Tomography, pages 667 - 674.

[0250] [3] Damajou, M., Dupre, A., Dang, C., Ricciardi, G., Bourennane, S., Bellis, C. (2019). On the implémentation of simultaneous multi-frequency excitations and mea-surements for electrical impédance tomography. Sensors, 19(17).

[0251] [4] Damajou, M., Dupre, A., Dang, C., Ricciardi, G., Bourennane, S., Bellis, C., Mylvaganam, S. (2020). High Speed EIT with Multifrequency Excitation using FPGA and Response Analysis using FDM. IEEE Sensors.

[0252] [5] https: / / www.math.colostate.edu / ~siamcsu / files / NOSER.pdf

Claims

Claims

1. System (1) for optimizing the electrical consumption or electrical production of fluidic equipment with 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 a body of the fluidic equipment, with their end flush with the internal surface of the body and facing the rotating component; - an electronic circuit (12) for controlling the electrodes and for tomographic measurement by electrical impedance, the circuit being adapted to respectively excite the electrodes simultaneously, and to measure electrical impedance matrices of the flowing fluid including, where appropriate, cavitation bubbles in the body; - a signal processing unit (13), adapted to reconstruct images of the flowing fluid in the body from the impedance matrix measurements of the electronic circuit;- an electronic unit (14) for automatically controlling the control member of the fluidic equipment, adapted to modify the operating frequency of the equipment so as to adjust its operating electrical power and thus adjust its flow / power ratio.;

2. Optimization system according to claim 1, the fluidic equipment being a pump or a turbine, the end of the electrodes facing the free end of the blades of the pump or the turbine or being integrated therein, the control member being a frequency converter.

3. Optimization system according to claim 1 or 2, the operation of the electronic unit for automatic control of the fluidic equipment being controlled by that of the signal processing unit.

4. Optimization system according to one of the preceding claims, comprising a casing fixed around the body of the fluidic equipment, housing the electrical sensor with the electrodes housed and fixed individually in a sealed manner in a through hole of the body.

5. Optimization system according to claim 4, the housing housing a port for supplying electricity to the electrodes.

6. Optimization system according to one of the preceding claims, the signal processing unit being adapted to implement a neural network for image reconstruction.

7. Optimization system according to one of the preceding claims, the control circuit being adapted to implement the following steps: a / excitation of the electrodes, each electrode being excited by a potential Vnexc having either the form: [Math.2] V„ c ( t ) = Æ^cos ( 2jrf m t ) [ Çcos ( m0 n ) + Ô^sin ( ) where A is a signal amplitude, me 1, ..., ( ne -1) represents the spatial frequency, n( the number of electrodes, 0n is the angular position of electrode n, fm = m * f0 is an oscillation frequency, f0 is a fundamental frequency chosen such that fm is less than the Nyquist frequency of the system for all m, 0 the set of odd natural numbers, E the set of even natural numbers, i.e. the form: [Math.5] in which, by convention, a sum is identically zero if the value of the starting index is greater than that of the final index, where: [Math.6] = A sin 2 / rf .t ), [Math.7] / """ = + l And [Math. 8] and with [ V (f ) 1 denoting the (n- 1) th element of the identity defining the voltage Vj(t), under the convention that the terms i are always arranged in the increasing order of the indices i in such an identity, the excitation being carried out either simultaneously on all the electrodes according to [Math 5], or sequentially on a or more subsets of electrodes; b / measurement of the electrical properties Vnmeas of the fluid flow with the electrodes, c / processing of data from step b / of measurement, comprising the following sub-steps: cl / for each electrode En, calculation of the defined Mn data points by : [Math. 10] M„(k) = where R is the value of the resistance used for the measurement of Vnmeas with Vnmeas = R In at the terminals of the resistance, P is the number of points of a discrete sequence of measurements of the current In, p is the discrete time, k is a Fourier coefficient between 1 and (ne - 1) and [3P = (2irp / P), c2 / constitution of a data matrix D from the data points Mn(k) for all n and for all k, according to the equation: [Math. 13] if the excitation form [Math 2] is implemented, or [Math. 14] / W0) i M(2)} MO)) if the excitation form [Math 5] is implemented, c3 / constitution of a signed data matrix whose elements are defined by the following equation when the phase shift d>nj(k) between the excitation potential at electrode 1 and the current measured at electrode n is less than ir / 2: [Math.20] ~m _ sin(0„ XA<) ) m and whose elements are defined by the following equation when the phase shift <hn>i(k) between the excitation potential at electrode 1 and the current measured at electrode n is greater than or equal to ir / 2: [Math.22] _ ^Tf1 where S is a sign matrix defined such that: - if the excitation form [Math 2] is implemented, the i-th element of the j-th row of S is the sign of cosine([2ir / ([j+l] / 2)]*(il) / ne) for j odd and the sign of sine([2ir / (j / 2)]*(il) / ne) for j even, - if the excitation form [Math 5] is implemented, the opposite sign is assigned to the nearest excitation electrode, in particular for a measurement electrode located at an equal distance between two excitation electrodes, the amplitude is experimentally measured to be of the order of 0(10-7) A, corresponding to a negligible contribution to the data.

8. Optimization system according to claim 7, the control circuit being adapted to implement step a / with the set of potentials Vnexc verifying the condition: [Math.4] Tî =o.

9. Optimization system according to one of the preceding claims, the electrodes of the electrical sensor being angularly distributed in a regular manner around the body of the fluidic equipment.

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

11. Industrial installation, comprising at least one fluid circuit and an optimization system according to one of claims 1 to 9.< / hn>

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