MXPA98010049A - Method and apparatus for controlling esp flotation machines - Google Patents

Abstract

A computerized "smart" system (110) and methods to monitor, diagnose, operate and control various parameters and processes of flotation machines (40) are presented. The computer control system operates at least one of a plurality of control devices (48) based on the input of one or more monitoring sensors (42, 44) in a manner that provides continuous, real-time operational control. The response of the control system is based on the system's own process model, which in turn is based on the input of the sensor and one or more advanced analysis techniques, including, but not limited to, neural networks, algorithms genetic, confusing logic, expert systems, statistical analysis, signal processing, pattern recognition, categorical analysis and combinations thereof. Process and operating parameters of particular interest include speed and amount of chemical reagent addition, foam thickness, energy consumption and aeration rate. In a particularly preferred embodiment, the apparatus comprises a foam flotation machine with at least one video sensor (46) that provides an input which is analyzed by a process model generated by a combination of statistical methods and neural networks. As a result of the analysis, at least one output can be generated to activate a control device (48) that carries out changes in the operation variables as suggested by the process model. In another particularly preferred embodiment, the apparatus comprises a foam flotation machine with at least one laser spectrometer (114) that provides input with respect to the composition of the input (feed) and output (effluent) currents.

Description

METHOD AND APPARATUS FOR CONTROLLING ESOTHING FLOATING MACHINES BACKGROUND OF THE INVENTION i. Field of the Invention This invention relates generally to foam flotation machines for the separation of particles from a liquid suspension or pulp. More particularly, this invention relates to methods and apparatuses for automatically monitoring, operating and controlling continuous feed flotation machines using "intelligent" computer control systems and remote sensing devices, particularly detection devices of the laser spectroscopy type. 2. Brief Description of the Previous Technique Flotation machines are used in many industrial applications for separation of particulate materials from suspensions in a liquid, usually water. The particles to be removed from the suspension are treated with reagents that make them hydrophobic or water repellent, and a gas is supplied, usually REF. 29008 air, to the suspension in the form of small bubbles. The hydrophobic particles come into contact with the bubbles and adhere to them, rising with them to the surface of the liquid to form a foam. The foam containing the floating particles is then removed, such as the concentrate or product, while any hydrophilic particle is left behind in the liquid phase or passes out as waste. Flotation machines find particular utility in the metal recovery industry, providing superior recovery of metals or metallic minerals from a solid / liquid mixture known as "pulp", "suspension" or "gangue". The flotation process can also be applied to the removal of oil droplets or emulsified oil particles, as well as to fibrous or vegetable material such as paper fibers, bacterial cells and the like. In most applications, reagents known as collectors selectively hydrophobicize one or more of the suspended particle species, thereby assisting the process of coalition and collection by air bubbles. It is also common to find foaming agents to assist in the formation of a stable foam on the surface of the liquid. The process of adding various reagents to the system is known as conditioning.

Flotation machines have been developed in numerous different known configurations. In some conventional embodiments, the flotation machine includes a receptacle, a cell or tank with substantially vertical walls, and an internal rotation member known as a rotor-disperser. The rotor provides agitation to maintain the suspension of the pulps, and can also extract external air to the interior of the tank through a vertical tube. The spout decomposes the air into tiny bubbles and disperses it evenly through the pulp, and at the same time provides mechanical mixing of air and pulp. Such cells may also include a false bottom and a suction tube to provide a channeled flow path, ensuring maximum recirculation of the suspension and air / suspension mixing. In other conventional embodiments, the rotor operates only for agitation and aeration is provided by an external means, usually a fan or compressor. Alternatively, the air can be dissolved in a liquid, which is then injected into the pulp or suspension. The air used can be atmospheric air, or an inert gas such as nitrogen or argon. Other proposed flotation cells include a tank and a means for generating ultrasound, which acts to agitate the pulp and thus generates the separation of solids, as described in U.S. Patent No. 5,059,309 to Jordán. Alternatively, particle separation can be carried out by a combination of air, magnetic and / or electric fields as described in U.S. Patent No. 5,224,604 to Duczmal and Schneider. Another known configuration of a flotation machine is the column. In one column, the conditioned suspension is introduced into the upper part of the receptacle, a thin vertical column and air bubbles are formed in the bottom of the column by venting pressurized air through a diffuser. A foam layer is formed which has the particles floating above the liquid and flowing overhead from the top of the column. The position of the foam-liquid interface is maintained at a desired level by controlling, for example, the liquid flow from the bottom of the column. Optionally, wash water is introduced near the top of the foam layer to create a downward flow of liquid which tends to reduce the entrainment of unwanted gangue particles in the upper flow of foam. In these types of flotation columns, the liquid flows down while the bubbles rise vertically upwards. Since the ascension of the bubbles is strongly related to their size, the bubbles must be above a certain critical diameter to ascend through the liquid and the interior of the foam layer. Various other alternative embodiments of the column flotation machine have been described, for example, in U.S. Patent No. 4,938,865 to Jameson, which introduces an air / suspension mixture into the column, where the separation takes place. The efficient and effective operation of flotation machines requires the monitoring and control of a multitude of processes and operational parameters. By "process parameters" it is meant parameters such as suspension concentrations and bubble size, as described above. Other process parameters that are included, but not limited, are the density of the pulp in the flotation machine chamber, the concentration and distribution of bubbles, the removal rates of product and waste, the addition of reagent and the consumption rates, the air flow, the solids concentration, the foam mass and volume, the foam level, the pulp level, the feeding speed and the like. By "operational parameters" it is meant to include various operating parameters of the flotation machine such as rotor speed and position, position of the suction tube, position of the tuner, power consumption and the like. These classifications and examples are for convenience and only as examples.

Flotation machines present demanding problems with respect to the design and installation of sensors associated with flotation machines, the acquisition of various measurements, the ability to communicate data and energy inside and outside the flotation machine, as well as the ability to provide control devices within the machine and operating such control devices in response to an instruction from a central control computer. A special challenge has been to improve the efficiency control of the various parameters discussed above. Each of these parameters must be adjusted to optimize both the economic operation of the plant, as well as the operating conditions, that is, an efficient total yield and desired levels of purification. Flotation machines are usually controlled by simple feedback or after-feed control circuits. Various devices have been described which can be used to monitor important parameters in the operation of the flotation machine. The most common of these describes a flotation machine separation control system comprising a controller '(for example a microprocessor) which communicates with one or more sensors and in response to the information received from the sensors, drives a control apparatus (for example a valve) for adjusting one or more control parameters. For example, in U.S. Patent No. 4,343,654 to Lambert, a control system that solves the pulp level is described, wherein a computer communicates with a level sensor, and is based on these signals and preprogrammed instructions from the memory of the computer. computer, sends control signals to a ventilation element which regulates the ventilation of air and thus adjusts the degree of foam. U.S. Patent No. 5,011,595 to Meenan uses forward feed and feedback control methods to detect solids concentrations and adjust the rate of chemical addition to the feed streams. The control system includes optoelectric detectors that respond to different concentrations of solids and suspension parameters. The detectors send signals regarding the solids concentrations and suspension parameters to a process controller. In response, the process controller adjusts the rate of chemical addition to the feed stream of the foam machine to control the separation of solids from the impurities. The controller calculates the forward power output from the signals and the controller adjusts the output of the addition of different chemicals or additives to the processing machine. The controller also calculates a feedback output after receiving a signal from a third detector which monitors the extent of separation and recovery of solids from the processing machine. Related patents include U.S. Patent No. 4,795,550 to Nelson and Oblad, and U.S. Patent No. 4,797,559 to Oblad et al. , which describe a method and apparatus for determining the reflectivity of the waste of a coal flotation machine using a laser and a bifurcated fiber optic cell to supply signals. In U.S. Patent No. 5,062,964 to Ortner and Pfalzer another control system directed to control the amount of foam is described. A probe measures the amount of foam and transmits a signal to a controller or regulating device, which in turn controls the amount of air introduced into the system by means of a valve. The control of multiple parameters is obtained in U.S. Patent No. 3,551,897 to Cooper, which describes the measurement of various operating conditions, and then a calculation is made of a plurality of coefficients that, together with certain equations, describe the process in a point in the particular time, and then the use of the same equations to adjust certain parameters in order to optimize the operating conditions and maximize the performance.

For the most part, the prior art control systems resolve only one or two operational processes or parameters, for example, they control the level of liquid or foam. In U.S. Patent No. 5,073,253 to Bishop and Gray, a foam-supported float is provided which operates in battery with an ultrasonic level detector to provide a measurement of the foam level. U.S. Patent No. 4,938,865 to Jameson uses a controller to operate a valve that introduces air into the top of a column. U.S. Patent No. 4,552,651 to Sandbrook and Scandrol discloses devices for measuring pulp density and pulp level. Then the two signals are combined to a single signal which is used to control the level of liquid in the machine by adjusting the speed of extraction of the waste. U.S. Patent No. 5,192,423 to Duczmal and Schneider, utilizes a control device to maintain the desired level of liquid and to optimize foam collection. U.S. Patent No. 4,795,550 and the document entitled "Fuzzy Mdel Based Control for a Mineral Flotation Plant" by A, Cipriano 'and M. Ramos represent the prior art closest to the present invention. Other simple controllers have been used to measure and adjust the pulp feed density. For example, U.S. Patent No. 5,368,166 to Chu ak, et al. , describes a control device for measuring pulp density and for controlling the flow rate of water and foaming agent. In U.S. Patent No. 5,417,102 to Prevost a differential densitometer is described for continuously measuring undissolved total solids in a liquid. One of the most important process parameters to control is the rate of addition of chemical reagents for conditioning. This speed affects both the quality of the product (ie, the amount of extracted ore and the purity) as well as the cost of the total process. There have been numerous descriptions that solve this parameter, in addition to the US patent number 5, 011, 595 described above. U.S. Patent No. 4,810,371 to Fonesca describes a system for controlling the carbon content in coal waste which includes detecting the carbon content of the waste from a flotation cell and controlling the supply of additives to the machine to optimize the recovery of carbon in the suspension. In U.S. Patent No. 4,731,176 to Macdonald, a method and apparatus for detecting variations in solids content in at least one outlet stream and then adjusting the amount of flotation reagent is disclosed. In U.S. Patent No. 4,559,134 a particle size analyzer is used to compare an analysis of the size of solid particles in a separate stream with an analysis of the size of solid particles in a feed stream. The rate of addition of the collection reagent is adjusted in response by a controller. An important parameter of operation is the consumption of the energy of the flotation machine. Maximizing the efficiency of the machine by a suitable rotor, a disperser and the placement of the suction tube can represent important savings in the cost of operation. However, it is not considered that any previous technique has solved a control system specifically designed to minimize energy consumption and at the same time maximize the efficiency and purity of the product. Furthermore, none of the prior art documents mentioned above is considered to provide a computerized "intelligent" control system, comprehensive to operate, control and monitor various flotation machines. The ability to provide precise control and monitoring, the real time of such flotation machines constitutes a current critical industrial need.

BRIEF DESCRIPTION OF THE INVENTION The problems discussed above and others additional as well as deficiencies of the prior art are solved or diminished by the various methods and apparatus of the present invention to provide computerized "intelligent" systems to operate, control, monitor and diagnose various parameters and processes of flotation machines. By the term "intelligent" is meant the use of computerized control methods that include, but are not limited to, neural networks, genetic algorithms, confusing logic, expert systems, statistical analysis, signal processing, pattern recognition, analysis categorical or combinations thereof. Therefore, in preferred embodiments (but not necessarily in all embodiments), this invention comprises at least one of these control methods and other more advanced methods than conventional stabilization control. An intelligent flotation machine of the type described herein has the ability to detect information about itself, predict its own future state, adapt and change with respect to time as the process and operating conditions change, learn about its own operation and change its operation mode to improve the operation. Specifically, the control system of the present invention regularly receives instrument readings, digitized video images or other data indicating the state of the flotation machine; analyzes these readings in terms of one or more continuously updated internal models, generated by themselves; and makes changes in the operation variables as suggested by the internal models. In accordance with the present invention, a computer control system acts on at least one of a plurality of control devices based, in part, on input from one or more monitoring sensors in a manner that provides continuous operational control in real time . It will be appreciated that it is difficult to detect and communicate certain parameters in real time within the flotation machines. Thus, according to an important feature of the present invention, a variety of technologies can be used including ultrasonic absorption and reflection, laser-heated cavity spectroscopy, laser-induced burst spectroscopy (LIBS), laser-induced mass spectroscopy. (LIMS), X-ray fluorescence, neutron activation spectroscopy, pressure measurement, reflectance or absorption of microwave or millimeter wave radar and other optical and acoustic methods. In a preferred embodiment, the sensor or sensors comprise a means for determining the composition of the input stream and the particle size. Ideally, such a sensor will provide the read data to the input stream without the need to remove samples from the process stream in order to be analyzed in a separate position. Therefore, a preferred sensor includes sensors that use laser spectroscopy (i.e., laser-induced burst spectroscopy and laser-induced mass spectroscopy). Such sensors can oscillate in an arc-shaped path, can be moved linearly along the process flow or in the radius of the tank to provide a profile of the process stream without the need to remove individual samples of the process stream. Alternatively, multiple separate sensors can be used to obtain a complete profile of the process stream. A particularly preferred embodiment of the present invention utilizes an image forming system comprising video cameras that produce images which are completed in data usable by the process models of the present invention. This modality also includes an advanced control system that uses both pattern analysis and neural networks, as well as statistics and color vector analysis. The mapping of high dimensionality input vectors to low dimensionality maps is a way of preserving the topological order by these advanced control systems and can be used to monitor the operation of a floating process on a continuous basis, which is highly advantageous when monitoring flotation cell banks. The computer controller used in the system of the present invention is preferably a personal computer or work station, with an associated display device (CRT screen) and an input / output device (keyboard or touch screen). The controller can be located in the foam flotation machine or in a remote location such as a central control room in a plant. Importantly, the controller can control one or a plurality of flotation machines in a single location or in a plurality of sites. The computerized monitoring and control system described above for foam flotation equipment provides a comprehensive scheme for monitoring and controlling a variety of input and output parameters as well as a plurality of operational parameters resulting in increased efficiency, optimization of operation and increased safety . The features discussed above and other features and advantages of the present invention will be appreciated and understood by those familiar with the art from the following detailed description and drawings.

BRIEF DESCRIPTION OF THE DRAWINGS Referring now to the drawings, wherein like elements are similarly numbered in the various figures: Figures 1A-D are schematic sectional views of flotation cells and flotation columns with which the monitoring system is used and control of the present invention; Figure 2 is a schematic view of a monitoring and control system for a flotation machine according to the present invention; Figure 3 is a schematic view of a preferred monitoring and control system utilizing a LIBS or LIMS sensor system, in accordance with the present invention; Figure 4 is a schematic view of a monitoring and control system using a LIBS or LIMS sensor to monitor the composition and particle size of a dry or dehydrated process flow, in accordance with the present invention; Figure 5 is a schematic view of a monitoring and control system using a LIBS or LIMS sensor to monitor the composition and particle size of a dry or dehydrated process flow, in accordance with the present invention; and Figures 6A-B are schematic views of a monitoring and control system using a LIBS or LIMS sensor to monitor a wet or wet process according to the present invention.

DESCRIPTION PE THE PREFERRED MODALITY The invention relates to methods and apparatus for automatically controlling, operating and monitoring flotation machines using "intelligent" computer controlled systems and remote sensing devices. By the term "intelligent" is meant the use of computerized control methods that include but are not limited to neural networks, genetic algorithms, confused logic, expert systems, statistical analysis, signal processing, pattern recognition, categorical analysis or a combination of them to analyze inputs in terms of one or more internal models, continuously updated, generated by themselves, and to make changes in the operation variables as suggested by the models. It should be understood that the term flotation machine is used in its most general sense, including traditional flotation cells, or flotation columns, where flotation can be carried out by a variety of means including air, ultrasound, fields magnetic or electric or a combination thereof. Furthermore, it should be understood that the flotation machine in the context of the present invention can refer to a single cell or column, or to a bank or set of cells or columns. With reference to Figures 1A-D, simplified examples of flotation machines contemplated by the present invention are shown. In figure IA, a common float cell is shown with number 10. Flotation cell 10 includes an impeller 12 centrally mounted for rotation about an adjacent vertical axis, but spaced from the bottom of receptacle 14 having a pulp feed orifice 16 from which a feed tube 18 extends downward to a position just above a stabilizer 20. Conditioning agents are received through the bottom end of tube 22. The pulp is finally discharged through outlet 24. Figure IB shows a flotation cell where it is mounted an injection device 30 for ejecting a two phase gas / liquid mixture within the cell. Figure IC shows this cell mounted for operation in a bank of cells.

Figure ID shows a typical flotation column 32 contemplated for use with the present invention. The flotation columns 32 comprise a column 33 provided with an aeration source 34 and washing water 35. Aeration (bubble generation) can be obtained either directly through internal sprinklers or after external gas contact with water or with suspension. Wash water is usually added from an array of perforated tubes located just below the foam overflow flange. Feed 36 is introduced approximately one third down from the top of column 33, and descends against the ascending bubbles of the aeration source 34. The foam concentrate 37 is poured into the lip of the upper column, while the waste 38 leaves the bottom of the flotation column. According to the present invention, the flotation machines of the type discussed above and in the prior art are provided with one or more sensors for the detection of one or more parameters related to the process and operation of the flotation machine. In addition, a computerized control system can be located in the flotation machine, near the flotation machine or in a remote position of the flotation machine that is provided for interaction with the sensor or sensors in the flotation machine. This computer control system includes a control computer and one or more control devices which are actuated in response to an instruction signal from the control computer. Importantly, the response of the control system will preferably be based on both the sensor input and a series of expert rules, initially determined in advance and continually updated to the proper analysis of its operation of the control system. The control will continuously generate and update its own "process model" using data inputs described and one or all of the advanced analysis techniques, including neural networks, genetic algorithms, confusing logic, expert systems, statistical analysis or a combination of these. The control system will have the ability to independently select the best analysis technique for the current data set. The computer control system will operate one or a plurality of control devices based on the input of one or more monitoring sensors so as to provide continuous operational control in real time. In addition, the control system may include a monitoring system for data classification, preventive maintenance or failure and prediction of wear. Additionally, the control system may include diagnostics in relation to the condition of the equipment.

Referring now to Figure 2, there is shown a scheme that describes the examples of the monitoring sensors, control devices and components and features of the control system of this invention. Figure 2 shows more particularly a flotation machine 40 having associated thereto one or more process sensors 42 and / or one or more equipment sensors 44 which include optional video cameras 46 (or image generating devices). In addition, the flotation machine is associated with one or more operational control devices 48. The sensors 42, 44 communicate through an appropriate communication system, i.e., an analog and / or digital data acquisition interface 50 with the central control computer 52. One or more control devices 48 communicate through an appropriate communication system, ie, an analog and / or digital control output interface 54 with a central controller 52. Alternatively, sensors 42, 44 and control devices 48 communicate through a unique, appropriate control computer 52. As mentioned previously, the control computer 52 can be located on the flotation machine, near the flotation machine or at a remote location such as the control room. The computer 52 has associated therewith a screen 56 for displaying the data and other parameters, a keyboard 58 or another means for inputting control signals, data and the like, a memory or recorder 60 and a modem 62 for entering and transmitting data to the computer. the control computer 52 from at least one remote location. With reference still to Figure 2, the control computer 52 receives a variety of inputs which have been categorized generally in terms of: (1) information stored in the memory when the flotation machine is manufactured; (2) information programmed at the site where the flotation machine will be used; (3) process parameters detected by the process sensors 42; and (4) equipment (operational) parameters detected by the equipment sensors 44. The outputs from the control computer can generally be categorized as: (1) data stored in memory 60 associated with a control computer 52; (2) operational control of the flotation machine; and (3) real-time information provided to the operator on the monitor 56 associated with the control computer 52. The following table summarizes the various inputs and outputs.

SALI DAS TICKETS TABLE 1. INFORMATION ORIGINALLY STORED IN THE MEMORY 1. STORED MEMORY DATA OPERATIONS MAINTENANCE INFORMATION OPERATIONS DATA TRAINING INFORMATION PREVENTIVE MAINTENANCE INFORMATION PROCESS MODELS (OPTIONAL) PREDICTION OF FAULTS AND WEAR CONTROLS AND LINES OF THE PROCESS GUIDE (OPTIONAL) 2. PROGRAMMED INFORMATION ON THE SITE 2. CONTROL OF OPERATIONS INTERVAL OPERATION VOLUMES OR MASS FLOW SPEEDS DESIRED PARAMETERS OF OUTPUT AIR FLOW SPEEDS SITE SPECIFIC DATA (FOR EXAMPLE ENVIRONMENTAL) PULP LEVELS PROCESS MODELS (OPTIONAL) FOAM LEVELS CONTROLS AND LINES OF PROCESS GUIDE (OPTIONAL) PH SIZE, CONCENTRATION AND PARTICLE DISTRIBUTION, 3. PROCESS PARAMETERS DETECTED FLOTATION REAGENT ADDITION SPEED VOLUME AND MASS FLOW PRESSURES CM PULP LEVELS FLOW PATTERNS FOAM LEVELS AGITATION SPEED FOAM MOBILITY POSITION / ORIENTATION OF THE AGITATOR FOAM VISCOSITY POSITION / ORIENTATION OF THE SUPPLIER COLOR OF THE FOAM POSITION / ORIENTATION OF THE EXTRACTION PIPE PARTICLE SIZE DISTRIBUTION ENERGY EXTRACTION CONCENTRATION OF SOLIDS BUBBLE SIZE DISTRIBUTION 3. PRESENTATION IN THE MONITOR CHEMICAL COMPOSITION DIAGNOSIS OF THE EQUIPMENT CONDITION DISTRIBUTION OF BUBBLES IN PULP ORDER OF DIVERSE PARTS DENSITY MODEM / FAX FOR REQUESTING PARTS REGIONAL PRESSURES PRESENTATION OF OPERATING PARAMETERS SCADA OR DCS AIR FLOW SPEED LIQUID FLOW SPEED FLOW FLOW SPEED ADDITIONAL REAGENT SPEEDS VIBRATION DETECTED EQUIPMENT PARAMETERS POSITION OF THE AGITATION MECHANISM TUNER POSITION SUPPLIER POSITION ROTATIONAL SPEED OF THE AGITATION MECHANISM ELECTRIC POWER EXTRACTION OF THE AGITATOR EXTRACTION OF COMPRESSOR ELECTRICAL POWER CM Tnfnrmation Stored in memory Examples of information originally stored in the memory include information regarding the operation and maintenance of the flotation machine and operator training information, all of which may be readily available to an operator on the display screen 56 associated with the control computer 52.

Information Scheduled on the Site Examples of information programmed at the site where the flotation machine is to be used include operating ranges, equipment parameters and desired feed parameters, together with other data and site-specific environmental factors. The introduction into the control computer also includes various process models, process controls and guide lines. These models and objectives can be stored in the memory or can be programmed on the site, as appropriate.

Process and Equipment Parameters A further important feature of the present invention is the large number of process sensors 42, 44, which detect a variety of aspects in relation to the flotation machine, its operations and its feed, waste and flotation streams. The sensors are particularly important in relation to the speed of chemical addition, energy consumption, aeration rate and thicknesses of the foam layer. Other process parameters which may be detected include, but are not limited to, bubble loading, volume or mass flow rates in the feed, concentrate, foam or waste streams; the air flow velocities in the feed, concentrate, foam or waste streams; the density of the feed, concentrate, foam or waste streams; the chemical or mineralogical composition of the feed, concentrate, foam or waste streams; the pulp or foam levels; the particle size, concentration and distribution of solids in the feed, concentrate, foam or waste streams; the size, color and distribution of bubbles in the feed, concentrate, foam or waste streams; the pH of the feed, concentrate, foam or waste streams; the rate of addition of flotation reagents including foaming agents, collection agents, promoting agents, suppressive agents and the like; the regional pressure and flow patterns within the flotation machine, the acoustic emissions from the flotation machine; or digitized video images of the foam surface or other key parts of the process, analyzed to determine the key characteristics of the object from which the image is being formed. The equipment parameters which can be detected include, but are not limited to, the agitation speed, the induced or forced air flow velocity, the position and orientation of a foam assimilation device, the position and orientation of a tube. of extraction, the position and orientation of an agitator, the position and orientation of a jet, the extraction of power from a stirrer motor and the extraction of power from other devices such as a compressor. It will be appreciated that it is often difficult to detect and communicate certain parameters in real time within the flotation machines. Therefore, a variety of technologies including ultrasonic absorption and reflection, laser-heated cavity spectroscopy can be used in the present invention., laser-induced burst spectroscopy (LIBS), laser induced mass spectroscopy (LIMS), X-ray fluorescence spectroscopy, neutron activation spectroscopy, 'measurement of pressure, reflectance or absorption in microwave or millimeter wave radar, or other optical and acoustic methods. A microwave sensor suitable for detecting moisture and other constituents in solid and liquid phase in the inlet fluid streams and output fluid is described in U.S. Patent No. 5,455,516, all of the content of which is incorporated herein by reference . An example of an apparatus suitable for detection using LIBS is described in U.S. Patent No. 5,379,103, the entire contents of which is incorporated herein by reference. An example of a suitable apparatus for detecting LIMS is the LASMA laser mass analyzer available from Advanced Power Technologies, Inc. of Washington, D.C. A preferred embodiment uses a sensor based on laser spectroscopy and is described in detail in the following, with reference to Figures 3-6. In a suitable acoustic sensor, one or more microphones, single-axis accelerometers or multi-axis accelerometers are placed on or near the flotation machine. The acoustic emissions that arise from the machine, which include subsonic, sonic and ultrasonic waves, are detected either directly by the accelerometers or by microphones as they are transmitted through the air. The acoustic emissions are converted to electromagnetic signals and digitized for processing. The processing may include, but is not limited to Fourier transformation, fast Fourier transformation and waveform transformation. It is known that the signal characterizes changes in the process and takes place in the flotation machine. However, typically a stochastic model that relates the acoustic emission signal to the process and operation of the machine is too complex to be useful. Therefore, the transformed emissions signal is preferably used as an input to an advanced control system, as described in the following, where it can be used in a neural network or other heuristic model system to control the operation of the machine and the flotation process. Appropriate techniques for communication between sensors, control computer and other components include wired electrical systems, optical systems, RF systems (radiofrequency), acoustic systems, video systems and ultrasonic systems.

Data Stored in Memory With reference more particularly to the data stored in the memory, it will be appreciated that the computerized monitoring and control system of this invention can use the aforementioned sensors to monitor various parameters at the time and thus provide a detailed historical record of the operation. of the flotation machine. This record can be used with the control computer to elaborate a flotation machine operation model, adjust models for flotation machine operation or generally to learn how the flotation machine behaves in response to changes in various inputs. At any time, such operation data can be retrieved from the memory of a local computer to the flotation machine or remotely. The data can be displayed in real time while the flotation machine is operating using the monitor 56, or as a historical record of some previous operation sequence. This record can also be used to provide a classification of data, provide trends and preventive maintenance information, predict failures and predict wear and tear on the machine. The preformatted reports can present the retrieved data to show information such as hours of operation, generated alarms, start numbers, number of operations, electric power used, maximum and minimum values for measured variables, total processed power and the like. By using operation data, the manufacturer of flotation equipment can recommend measures to avoid wasted time and to optimize the operating time. In addition, maintenance procedures can be suggested based on the operation records of the elapsed operating time and unusual operating conditions. The recording of operation data in this manner helps eliminate problems of various operating conditions of the flotation equipment. This improves the ability of the flotation equipment manufacturer to solve the user's operational problems and to keep the equipment online. Optionally, these data 66, 68 can then be used to provide alarms or emergency notification 70 when certain critical levels are reached.

Operations Control The controller 52 preferably communicates through standard communication cards used with personal computers or work stations. As such, there are Ethernet, RS-232 and modem capabilities for operator use. Therefore, the present invention allows a given plant to collect flotation machine operation data by means of Ethernet distribution systems in a plant or other network. Additionally, the present invention can communicate with other process devices not supplied by the manufacturer. In this way, the operator uses the control and monitoring system of this invention to obtain information in a larger portion of the process. By using a connected plant network, the operator can monitor the real-time operation of the flotation machine and the historical records. The appropriate programming elements for this activity include operator screens for data display, and display of messages for operating assistance, and manual operation and maintenance can also be included online. The operator can also control and optimize the operation of the flotation machine through the plant network. The operating parameters as described below can also be part of a total Supervisory Control and a Data Acquisition System (SCADA) or a distributed control system (DCS). As is well known, in a SCADA or DCS system, the devices of the microprocessor convert the plant measurement and status inputs into computer data for recording and transmissions to higher level processors. The SCADA or DCS system therefore connects to many controllers and field devices to obtain information and make global decisions. The supervisory expert controls make strategic decisions for the operation of a process or plant unit and send established points to dedicated controllers which make the changes to actuators and finally to the process as a whole. Continuing with reference to figure 2, a further important feature of this invention is that, in response to one or more parameters detected by the sensors 42, 44, the operation of the flotation machine in this way can finally be adjusted efficiently, it can be changed and preferably used during one or more advanced computerized control methods. The control of the machine includes the control of the mechanical operation status and the control of the operating intervals to optimize a safe operation at the same time as efficient. Such advanced computerized control methods include, but are not limited to, neural networks, genetic algorithms, unclear logic, expert systems, statistical analysis, signal processing, pattern recognition, categorical analysis or combinations thereof. Therefore, in a preferred embodiment, this invention comprises at least one of these control methods and other more advanced methods than conventional stabilization control methods, e.g., simple feedback or forward feed control circuits. of the prior art. The response of the system is based on a series of expert rules, initially determined in advance and continually updated based on the analysis of the control system itself. The control system will continuously generate and update its own "process model" using the sensor inputs described and the analysis techniques mentioned above. The control system may have the ability to independently select the best analysis technique for the current data set.

Although the control 52 may operate using any of a plurality of advanced computerized control methods, it is also contemplated that these methods may be combined with one or more methods of the prior art, including forward feeding or feedback control circuits. Feed forward is when the process and measurements of the machine (or the calculated, inferred, modeled variables normally considered in advance with respect to the machine process) are used in the controller 52 to effectively control the operation of the machine. floatation. The forward feed schemes inherently recognize that the conditions and condition of the feed material of the flotation machine change with respect to time and that, by detecting or calculating these changes before they enter the flotation machine, the Control schemes can be more effective than they would otherwise be possible. The feedback is where the measurements and the calculated values indicating the machine's process operation and the machine's state are used by the controller 52 and the schematic of control contained in it to stabilize the • operation and optimize the operation as power conditions change as well as changes the operation of the machine with reference to the set points and the optimization objectives.

The process and machine models are embedded in the controller 52, since they are methods for evaluating the models to determine the optimum present and future operating conditions for the machine. Optimal conditions are specified by flexible objective functions that are introduced into the controller 52 by the operators or the plant control system with which they are working, with control and optimization of the entire plant. The models contained in it are adapted in their mathematical form or representation, as well as the parameters associated with any given model, and changes can be made as required. These models include, but are not limited to, first principles and phenomenological models as well as all kinds of empirical models that include neural network representations and other state space approaches. The optimization is carried out by combining the knowledge content of the processes and the machine through these models with approximately equal expert system rules. These rules constitute operational facts and heuristic knowledge about the flotation machine and the process streams that are processed. The rule system can be made up of crisp and confusing representations and combine all forward feeding, feedback and model representations of the machine and the process to stay stable, safe and also with optimal operation, which includes the machine and the process. The determination of the optimal operation stages include evaluating the representation of the model of the machine and the process. This is done by combining the expert system rules and models together with the objective functions. Genetic algorithms and other methods of operation are used to evaluate the models to determine the best possible operating conditions at any point in time. These methods are combined in such a way that the combined control approach changes and le with respect to time and is adapted to improve performance with respect to machines and process operation. A detailed description of a suitable system using an internal process model as described herein for use in connection with the present invention is described in the US application serial number 60 / 037,355, filed on February 21, 1997, assigned to the assignee of the present, all the content of which is incorporated herein by reference. As discussed in the above, the adaptive control system of this invention uses one or a combination of internal and / or external process and / or machine variables to characterize or control the operation of the flotation machine, in terms of the output of desired processes. Preferably, the control system continually updates its knowledge of the process so that the control operation improves with respect to time. One of the important calculated values included in this process is the economical operation of the flotation machine. The economic operation includes the base operating costs of the machine that include the use of power and the use of chemical additives, the treatment of normalized operating costs with total throughput speeds and the quality of the products that are manufactured, both in absolute terms as in standardized terms for the feeding conditions, and the economic value of the processed products. With reference still to Figure 2, in response to one or more parameters detected by the sensors 42 and 44, the advanced control system of the microprocessor can drive one or more processes and / or equipment control devices 48 for control operations. The operational outputs from the central controller 52 can be processed through a control output interconnect 54. In some cases, the control devices will be activated if certain detected parameters are out of the normal or the range of operation of the pre-selected float machine. This operating interval can be programmed in the control system either before or during the operation. Examples of operational parameters which can be adjusted include, but are not limited to, volume or mass flow rates within the feed, concentrate, foam or waste streams; the induced or forced air flow velocities in the feed, concentrate, foam or waste streams; the levels of pulp or foam; the particle size, concentration and distribution of solids in the feed, concentrate, foam or waste streams; bubble size, bubble volume and bubble distribution in feed, concentrate, foam or waste streams; the pH of the feed, concentrate, foam or waste streams; the rate of addition of flotation reagents including foaming agents, collection agents, promotion agents, suppressive agents and the like; regional pressures and flow patterns within the flotation machine; the agitation speed in the machine; the position and orientation of a foam-clogging device; the position and orientation of a collection tube; the position and orientation of an agitator; the position and orientation of a pump; the extraction of power from an agitator motor, and the extraction of power from other devices, such as a compressor. The operational controls. above and examples of actual control devices which will provide such operational control will be described in greater detail in the following.

Presentation in a Monitor With reference still to Figure 2, other outputs include the real-time status of various parameters in the flotation machine. Therefore, the operator can use the computerized control and the monitoring system in the present invention to diagnose the present condition of the equipment, the order of the scattered parts (a modem / fax 66 can be included to order scattered parts) or to obtain a reading as part of a SCADA or DCS system, as described above. A particularly preferred embodiment of the present invention utilizes an image forming system comprising video cameras or the like 46 that produce images which are converted to data usable by the process models of the present invention. Flotation plant operators currently use visual observation of the color and consistency of flotation foams to estimate the performance of a circuit. The automation of the visual analysis of the foam compositions would provide greatly improved process control. A description of a sensor system for use in mineral processing operations is described by J.M. Oestreich, et al .; Minerals Engineering, Vol. 8, Nos. 1-2, pp. 31-39, 1995, incorporated herein by reference. The color sensor system described therein comprises a color video camera, a light source, a video capture board, a computer and a computer program that compares the measured color vector angles with a calibration curve previously stored Multiple cameras can be connected to a single single color sensing computer or a single camera can simultaneously observe several positions using a fiber optic cable network. This preferred embodiment of the present invention may further comprise an advanced control system that utilizes both pattern analysis and neural networks, as well as statistical and color vector analysis. As described by Oestreich et al., Before, gray level dependency matrix methods are used to extract the statistical characteristics that form digitized images of the foams. These statistical characteristics constitute a compact set of essential data contained in the original image, which can be related to the metallurgical parameters of the flotation process through neural networks. Whether supervised neural networks, such as learning vector quantization systems, unsupervised networks, such as self-organized mappings, or self-organized neural networks which can map high dimensional input vectors to lower dimensional maps in a topological manner where the are the ones that are used. Topological maps have the advantage that they can be used to follow the operation of flotation processes on a continuous basis, as opposed to a discrete classification by other classification paradigms. For example, when a process system consisting of a bank of flotation cells is considered, the process can be monitored by means of a characteristic profile on a two-dimensional characteristic map, which would allow early detection of the deviation from optimal conditions by means of intelligent automation systems by comparing the current profile of the system with an ideal or optimum profile. In addition to the color, the viscosity and mobility of the foams can be recorded and analyzed by visual means. Therefore, in a further embodiment of this invention, a series of modules are used to monitor different characteristics with a high degree of accuracy. Therefore, a machine vision system based on the interpretation of visual characteristics of the structure of the foam that has a modular structure, in which a module will differentiate between foams based on differences in morphology, a next module will be based on the distinction of mobility of foam, another will extract the chromatic information, other the average bubble size and so on.

Referring now to Figure 3, a preferred embodiment of the present invention is shown wherein an intelligent control system generally shown with the number 110 includes one or more laser-induced burst spectroscopy sensors (LIBS sensors) and / or sensors. of laser-induced mass spectroscopy (LIMS sensors). The LIBS and LIMS sensors are particularly useful in the determination of elemental composition in situ, that is, without the need for removal of a sample for analysis in a separate position. This represents a significant advance over the prior art, for example compositional analysis by X-ray analyzers. In fact, X-ray analyzers have been used to determine the concentration of certain elements in flotation flow streams, but require the Removal of a sample and analysis in a separate position. Each analysis usually requires at least 15 to 20 minutes. In addition, such analyzes must necessarily be discrete measurements and therefore can not provide flow (ie continuous) determinations of composition in real time. In contrast, the control system 110 according to the present invention allows a discrete or continuous rapid real-time analysis. The general configuration of the intelligent control system according to the present invention 110 comprises the control computer 112 described in detail above, which receives data from a LIBS sensor 114. A LIBS type sensor suitable for use with the present invention is described in the aforementioned U.S. Patent No. 5,379,103 to Zigler. Such sensors are capable of measuring the concentration percent of one or more elements in a mixture. The controller 112 operates at least one control device 116 in response to the data received from the LIBS sensor 114 and an internal process model as described in detail above. The control device 16 affects the operational parameter of the processing system 118 which contains a mixture 120 of multiple components. The LIBS sensors are particularly suitable for determining the elemental composition essentially in dry or dehydrated solids or in foams. Therefore, although the particular embodiments described herein are directed to a foam flotation machine, other LIBS sensors utilizing processing systems, in association with a controller for monitoring the composition, are within the scope of the present invention. . Such processing systems are those which have sample streams which do not need to be dried or dehydrated and which include, but are not limited to, thickeners, filters, centrifuges, analysis of molten metal or mud streams from melting furnaces, chemical process and the like.

A particularly preferred embodiment using LIBS sensors together with the intelligent control system according to the present invention is generally shown with the number 210 in Figure 4. This embodiment exemplifies the analysis and control of samples which do not require dehydration. The crushed ore 212 for separation of the at least one foam flotation machine 214 is moved along a strip 216 to the grinding apparatus 218. After grinding, the ore is conditioned or stored in a conditioning tank or feed box 222. Reagents can be added to the crusher apparatus 218 and / or to the feed box 222 or conditioning tank by means of the reagent addition system 224. The conditioned and shredded material is then floated by foam in at least one flotation machine 214. The LIBS sensor 226 analyzes the composition of one or more constituents of the crushed ore 212 and communicates this data to the intelligent controller 228. Preferably, the controller uses this data as input to a computer program which uses the neural network and the pattern analysis to characterize the sample and estimate its composition in terms of contained chemical or mineral compounds. In response to this analysis and an internal process model, the controller can then send signals to the grinding apparatus 218, to the reagent addition system 224 to make adjustments with respect to the reagent addition rate, or it can operate at least one control device 230 that affects the operational parameters of the machine of foam flotation. Such operational parameters include, but are not limited to, the speed of the impeller, the rate of aeration, the laundering of the foam, the flow rate and the various levels of each phase, the feed rate and the like. With reference to Figure 5, a second preferred embodiment is shown using LIBS sensors together with the intelligent control system of the present invention, generally with the number 231. In this embodiment, the LIBS sensor performs an analysis of some key elements in dry or dehydrated samples, for example, the concentration of copper, molybdenum, iron, silicon and magnesium in copper flotation concentrates. Therefore, the LIBS sensor 232 is placed close to the foam overflow 234 or the foam flotation machine 218. Therefore, the LIBS sensor incorporates a rugged optical system to allow operation on or near the process streams, which provides tolerance for vibration, dust and moisture. The sensor 232 may also comprise one or more mechanisms for movement of the device by translation, rotation or random deviation, so that successive analyzes of different parts of the sample stream may be taken. The data from the sensor 232 is communicated to the control computer 228, which can operate one or more control devices as described above. The modalities described above are directed to analysis of essentially dry or dehydrated samples. Such modalities are particularly useful insofar as the analysis is rapid, and provides real time data with respect to a process flow. In a third embodiment of the present invention utilizing LIBS sensors, wet samples are dehydrated and analyzed to provide data for the intelligent control system. This modality still provides a quick analysis in real time. With reference to FIGS. 6A-B, the sensor 312 LIBS detects a sample stream 314 from a conditioning tank / feed box 316. The sensor 318 LIBS detects a waste sample stream 320 from the foam flotation machine 324. . The data from each sensor is communicated in the control computer 326, which in turn affects the operational parameters of both the foam flotation system by operating various control devices as described above. Because the sample streams 320, 322 contain moisture, each must be dehydrated before analysis by the LIBS sensor. Accordingly, each sample stream is first passed through system 340, as shown in Figure 6B. The system 340 comprises the sample feed 320, 322 (usually in the form of a suspension), a suspension head tank 342, and a continuous vacuum band press filter 344. Preferred vacuum band press filters are available from Ei co, Salt Lake City, Utah. Both the suspension head tank 342 and the vacuum band press filters 344 can be sized appropriately to provide the desired level of dehydration prior to activation for analysis. The suspension 320, 322 enters the head tank 342 and is regularly discharged on the filter band 346, where it is dehydrated before analysis and then discharged. Sensors 321, 318 LIBS analyze sample 348 dehydrated. This system is particularly advantageous in that it allows the analysis of materials of unknown moisture content, without requiring the samples to dry completely. The materials can be analyzed without the need of transport to a remote site. In another additional preferred embodiment, other dehydration devices may be used, as appropriate. For exa, the device 350 shown in Figure 6C functions by passing a sang means 352, for exa a moving band or a rotating disk, through a suspension 354 that is analyzed, to capture a thin layer by adhesion. of the solids in the suspension. The thin layer 356 can then be dried by a stream of air 358 in motion, before analysis by LIBS, and can be removed from the sang means 352 by water spray or a scraper 360 after analysis. Although the present invention has been described in conjunction with foam flotation machines, it will be appreciated that many of the detection, monitoring and control and instrumentation techniques can be used in connection with any processing system for a mixture of multiple components. Although the preferred embodiments have been shown and described, various modifications and substitutions may be made thereto without departing from the spirit and scope of the invention. Accordingly, it is to be understood that the present invention has been described by way of illustration and not as limitation. It is noted that in relation to this date, the best method known by the applicant to carry out the aforementioned invention, is the conventional one for the manufacture of the objects to which it relates. Having described the invention as above, property is claimed as contained in the following:

Claims (22)

1. A foam flotation machine, the flotation machine is characterized in that it comprises: at least one laser spectroscopy sensor for detecting the real time at least one parameter related to the elemental composition of at least one of the inflows and output associated with the flotation machine; a control computer associated with the flotation machine and communicating with the sensor; a control device for controlling the flotation machine, the control device communicates with the control computer, wherein the control computer drives the control device in response to the sensor input.

2. The foam flotation machine, according to claim 1, characterized in that the flotation machine is selected from the group consisting of flotation cells or cells and flotation columns.

3. The foam flotation machine, according to claim 1, characterized in that it includes one or more additional sensors that are selected from the group consisting of sensors for detecting pulp entry volume, pulp entry mass, pulp input, pulp level, foam level, foam mass, foam mobility, foam viscosity, foam color, waste output volume, waste output density, waste output mass, particle size, particle distribution, particle concentration, bubble size, bubble distribution, bubble concentration, chemical or mineralogical composition, regional pressures, air flow velocity, liquid flow velocity, foam flow velocity, rate of addition of reactive, bubble loading and acoustic emissions.

4. The foam flotation machine, according to claim 1, characterized in that the laser spectroscopy sensor is selected from the group consisting of laser-induced burst spectroscopy and laser-induced mass spectroscopy sensors.

5. The foam flotation machine, according to claim 1, characterized in that the control computer includes a process model which is at least partially self-generated and continuously updated and adapted in terms of position, stirring speed, extraction of electrical energy, reagent addition rate, aeration, foam wash, foam level, pulp level, feed rate, bubble size, bubble volume and bubble distribution.

6. The foam flotation machine, according to claim 5, characterized in that: the process model is continuously updated using at least one of the advanced analysis techniques that are selected from the group consisting of neural networks, genetic algorithms , confused logic, expert systems, statistical analysis, signal processing, pattern recognition and categorical analysis.

The foam flotation machine, according to claim 1, characterized in that it includes at least one additional sensor, wherein the additional sensor comprises at least one video camera.

8. The foam flotation machine, according to claim 1, characterized in that: at least one laser spectroscopy sensor is placed to analyze a sample of the material to be separated before such material is added to the flow of entry.

9. The foam flotation machine, according to claim 1, characterized in that: at least one laser spectroscopy sensor is placed to analyze a sample of the material to be separated subsequent to drying or dehydration.

10. The foam flotation machine, according to claim 1, characterized in that at least one laser spectroscopy sensor includes: at least one mechanism for moving the sensor in at least one translation, rotation or hydration.

11. The foam flotation machine, according to claim 1, characterized in that it includes: at least one drying device associated with the flotation machine for drying a sample of the metal to be separated before analysis by at least one a laser spectroscopy sensor.

12. The foam flotation machine, according to claim 1, characterized in that the control device controls at least one operation parameter that is selected from the group consisting of position of the agitation mechanism, shape of the holster, position of the sucker, disperser position, suction tube position, stirring speed, electric power extraction, reagent addition rate, aeration, foam wash, foam level, pulp level, feed rate, bubble size, volume of bubbles and distribution of bubbles.

13. A method for controlling a processing system for a mixture of multiple components, the method is characterized in that it comprises: detecting in real time at least one parameter related to the elemental composition of at least one associated input and output flow with the system using at least one laser spectroscopy sensor; control the processing system based, at least in part, on information from the sensor system.

The method according to claim 13, characterized in that it further comprises: analyzing at least one parameter by means of an internal process model which is, at least partially, self-generated and updated and continuously adapted.

The method according to claim 14, characterized in that the internal process model is continually updated by means of an advanced control technique that is selected from the group consisting of neural networks, genetic algorithms, unclear logic, expert systems, analysis statistical, signal processing, pattern recognition, categorical analysis or a combination thereof.

16. The method according to claim 15, characterized in that the internal process model is further generated and updated by means of at least one technique that is selected from the group consisting of forward feed and feedback loops.

17. The method according to claim 13, characterized in that it includes one or more additional sensors that are selected from the group consisting of sensors to detect the pulp inlet volume, the pulp inlet mass, the pulp inlet density, the pulp level, foam level, foam mass, foam mobility, foam viscosity, foam color, waste output volume, waste output density, waste output mass, size particle size, particle distribution, particle concentration, bubble size, bubble distribution, bubble concentration, chemical composition, reagent addition, regional pressures, air flow velocity, liquid flow velocity, foam flow velocity , speed of reagent addition, bubble loads and acoustic emissions.

The method according to claim 13, characterized in that the laser spectroscopy sensor is selected from the group consisting of laser-induced burst spectroscopy and laser-induced mass spectroscopy sensors.

The method according to claim 13, characterized in that: the control includes controlling of at least one operational parameter that is selected from the group consisting of the position of the agitation mechanism, the shape of the holster, the position of the holster, the position of the disperser, the position of the suction tube, the speed of agitation, the extraction of electrical power, the speed of addition of reagent, aeration, washing of foam, foam level, level of pulp, speed of feeding, the size of bubbles, the volume of bubbles and the distribution of bubbles.

20. An improved foam flotation machine, having at least one associated sensor, the improvement is characterized in that it comprises: a control system for analyzing the sensor inputs in terms of at least one continuously updated, self-generated internal model, based at least partially on advanced analysis techniques that are selected from the group consisting of neural networks, genetic algorithms, expert systems, signal processing, pattern recognition, categorical analysis or a combination thereof.

21. The foam flotation machine, according to claim 20, characterized in that: the control system is embedded at least partially in the foam flotation machine.

22. The foam flotation machine, according to claim 20, characterized in that it includes a sensor which comprises one or more acoustic sensors for detecting acoustic emissions emanating from the foam flotation machine and where the control system processes received signals of the sensor to characterize changes in the process that take place in the foam flotation machine. SUMMARY OF THE INVENTION A computerized "smart" system (110) and methods to monitor, diagnose, operate and control various parameters and processes of flotation machines (40) are presented. The computer control system operates at least one of a plurality of control devices (48) based on the input of one or more monitoring sensors (42, 44) in a manner that provides continuous, real-time operational control. The response of the control system is based on the system's own process model, which in turn is based on the input of the sensor and one or more advanced analysis techniques, including, but not limited to, neural networks, algorithms genetic, confusing logic, expert systems, statistical analysis, signal processing, pattern recognition, categorical analysis and combinations thereof. Process and operating parameters of particular interest include speed and amount of chemical reagent addition, foam thickness, energy consumption and aeration rate. In a particularly preferred embodiment, the apparatus comprises a foam flotation machine with at least one video sensor (46) that provides an input which is analyzed by a process model generated by a combination of statistical methods and neural networks. As a result of the analysis, at least one output can be generated to activate a control device (48) that carries out changes in the operation variables as suggested by the process model. In another particularly preferred embodiment, the apparatus comprises a foam flotation machine with at least one laser spectrometer (114) that provides input with respect to the composition of the inlet (feed) and outlet (effluent) streams.