Method or device for monitoring or evaluating belt conveyor using data model

Abstract

In a method for analysing a belt conveyor (1), a data model (3) is used, the data model (3) relating to a digital replica of the belt conveyor (1), a first function value (45) of the belt conveyor (1) is determined, the first function value (45) and a second function value (46) are used for analysing the belt conveyor, and the first function value (45) and the second function value (46) are used for analysing the digital replica of the belt conveyor (1). The second function value (46) is related to the belt conveyor (1) or to a further belt conveyor (2), the function value (45, 46) being determined at a time interval, or the function value (45, 46) being related to a different belt conveyor (1, 2). By means of the described standardization, a reference for performance evaluation of belt conveyors, as well as a reference for performance evaluation of belt conveyors with similar transport tasks, can be created.

Description

Technical Field

[0001] The present invention relates to a method or a device for monitoring or evaluating a belt conveyor and / or multiple belt conveyors using a data model. Thereby, the monitoring and evaluation of a belt conveyor or multiple belt conveyors are related to analysis. The present invention also relates to a computer program product for executing the method. The present invention particularly relates to a method for performance evaluation (i.e. evaluation of performance) of a belt conveyor or multiple belt conveyors using a digital twin in the mining industry (i.e. in mining). A digital twin is an example of a data model or an example of the use of a data model. Background Art

[0002] The method or device for monitoring or evaluating at least one belt conveyor using a data model particularly relates to condition monitoring and / or condition prediction of at least one belt conveyor. Condition monitoring, also known as Condition Monitoring (CM), is particularly used for the purpose of observing the "health status" of components, machines, assets, facility components and / or facilities, and making statements about changes in this status by analyzing CM-based data. For this purpose, for example, an Industrial Internet of Things platform, referred to as an IIoT platform, is used in order to record data transmitted by devices, store them in a decentralized manner, visualize raw data, analyze data and / or visualize results of analysis. Local solutions are also feasible.

[0003] Continuous condition monitoring and analysis of belt conveyor parameters helps to predict, for example, possible damage so that ideally damage is not allowed to occur in the first place. This is particularly relevant for important parameters such as vibration or power consumption). In the case of belt conveyors, sensors can record measured values ​​at different locations in the facility (e.g. cooling temperature, vibration, voltage and current and / or torque of power converters and / or motors) and forward the measured values ​​to an evaluation unit, for example, a corresponding condition monitoring system (CMS) and / or a controller. The CMS can also be integrated into the controller. The evaluation unit can process at least part of the measured data. This can include, for example, monitoring functions such as trend indicators, predictions and recording of raw data.

[0004] A data model can also be called a "digital twin". In particular, a digital twin is a representation of a real system in a digital environment (IT system), for example with the possibility of "setting up" time (i.e. observing the system quickly or slowly from the past to the present and into the future). A data model can relate to a single system, a part of a system, or a whole system.

[0005] Belt conveyors are used in particular as transport means in the field of basic material industry, in ports, in power plants, in mines, etc. Belt conveyors can be said to be the most commonly used transport means in the basic material industry (mining + cement) to efficiently transport bulk goods (such as ore, coal, gravel, cement) from one location to another. Cost pressure, the demand for improved performance and the need for optimized operation are basic drivers or requirements for the operation or users of belt conveyors or other industrial facilities.

[0006] Solutions exist for recording and evaluating technical aspects of belt conveyors, for example, to identify wear on workpieces or determine the probability of failure, for example, recording component temperatures and determining trends. In conjunction with data from the operating process, such as conveyor volume and operating time, key performance indicators (KPI: Key Performance Index) can be determined, which can also be used to draw statements about the performance of the facility.

[0007] Requirements related to industrial installations, such as those used or present in particular in the mining and cement fields, can be divided into two groups, for example. These two groups can also be referred to as types of main groupings.

[0008] For example, one group includes at least one of the following mechanical engineering aspects: increasing the service life of a component, preventing breakage, reducing wear, etc.

[0009] The second group includes, for example, at least one of the following process engineering aspects: prevention of downtime, reduction of facility operating time without material transport (no empty runs), fast start-up, etc.

[0010] For the first group, different solutions can be used to monitor and / or evaluate the condition of individual components, such as recording of temperatures or oscillations, in particular of different components such as bearings of conveyor rollers, bearings of motors, electric motors, etc. For example, in order to prevent direct damage, or in order to determine trends by corresponding analysis of these measured data, thus carrying out direct limit value monitoring, for example, to obtain statements about wear or findings about the probability of failure of individual components.

[0011] For example, data from the operating process of the industrial facility, such as feed rate, energy consumption, operating time, can be used for the second group to obtain KPIs for evaluating the performance of the facility. For example, the KPIs can be defined by the manufacturer, operator or user of the industrial facility at their own discretion. However, as a result, it may be more difficult to compare different facilities belonging to, for example, different operators.

[0012] Comparing belt conveyors can be difficult, for example, for the following reasons. Belt conveyors can differ by one or more of the following aspects: topology (particularly based on the topology of the installation site), transport capacity, components, etc. There are many other influencing factors and complex relationships that can flow into the monitoring or evaluation of the system. Summary of the invention

[0013] The object of the present invention is to analyze a belt conveyor more efficiently.

[0014] The object is achieved by a method according to claim 1 or a belt conveyor according to claim 14 or a computer program product according to claim 16. In particular, embodiments according to claims 2 to 13 and 15 are provided.

[0015] The data model is used in or with the method for analyzing a belt conveyor. The data model is a digital replica of a belt conveyor or is related to a belt conveyor. Using a digital replica (also called a digital twin), a belt conveyor can be fully or partially digitally replicated. Therefore, it is a replica of an actual belt conveyor, wherein the belt conveyor is, for example, in a commissioning phase, an operating phase, an idling phase, a maintenance phase (etc.) or in failure or dismantling, but has been running in the past. Under this method, a first function value of the belt conveyor is determined. In particular, the first function value is determined with the aid of a data model. A standardized first function value is thereby generated. Therefore, with the aid of a data model, a standardized function value can be formed. The data model is particularly specifically implemented for a determined belt conveyor. A standardized function value can be formed using this particular data model. Therefore, different belt conveyors can be compared by standardization. The first function value and the second function value are used to analyze the belt conveyor. The function value used for analysis is particularly a standardized function value. Therefore, the function value is standardized with the aid of a data model. Therefore, for example, there is a standardized first function value and a standardized second function value. In addition, two standardized function values ​​can still be named as the first function value in the second function value. Therefore, there are non-standardized function values ​​and standardized function values. The first standardized function value is determined, for example, by means of a first data model for the first belt conveyor. The second standardized function value is determined, for example, by means of a second data model for the second belt conveyor. In particular, the second function value is determined by means of a data model or by means of another data model for another belt conveyor. Thus, a standardized second function value is generated. Function values ​​can be analyzed by standardization, especially compared with each other. Therefore, the first standardized function value is particularly compared with the second standardized function value. The second function value is, for example, related to a belt conveyor (the belt conveyor can also be referred to as the first belt conveyor hereinafter) or related to another belt conveyor (that is, the second belt conveyor and / or the third belt conveyor, etc.). If the first function value and the second function value are related to the first belt conveyor, the first function value is determined, for example, before reconfiguring the first belt conveyor, and the second function value is determined after reconfiguring the first belt conveyor. Reconfiguration, for example, is about a new path. Thus, the data of the belt conveyor can be compared with each other in a standardized manner before and after the transformation. In a further example, the load of the belt conveyor changes, in particular the weight of the load changes. Therefore, if the energy demand (as an example of a function value) is also independent of the topology and can be standardized with respect to the load, the load together with the topology has a great influence on the energy demand of the belt conveyor. Thus, for example, it is feasible to standardize and, for example, compare the function values ​​of the belt conveyor under different loads. Since the function values ​​are standardized, a first function value under a first load condition can be compared with a second function value under a second load condition.In another example, there can be a first belt conveyor and another second belt conveyor, which can be compared with each other. Comparison is analysis. Therefore, the first belt conveyor and / or the second belt conveyor can be analyzed. The other (second) belt conveyor (it is also possible to analyze multiple belt conveyors) is, for example, in a different position from the first belt conveyor. A first function value is determined for the first belt conveyor, which will be standardized or has been standardized. A second function value is determined for the second belt conveyor, which will be standardized or has been standardized. It is made feasible by standardization, that is, multiple first function values ​​or one first function value of the first belt conveyor are compared with multiple second function values ​​or one second function value of the second belt conveyor. Standardization is achieved with the help of a data model. The first data model is used as a digital replica for the first belt conveyor. The second data model is used as a digital replica for the second belt conveyor. The formation of the digital replica is the task of the data model. With the help of the corresponding digital replica, the corresponding belt conveyor can be analyzed by standardization. Without standardization, belt conveyors cannot be compared, especially due to their topological dependence.

[0016] At least a first function value is normalized with the aid of a data model for the analysis of at least one belt conveyor, wherein in particular the topological dependency of the function value is at least reduced with the aid of the normalization. The normalization can also eliminate topological dependencies from one function value or from a plurality of function values. By means of the normalization with the aid of a data model or with the aid of a plurality of data models for different belt conveyors, for example, two belt conveyors can be compared with one another or two belt conveyors can be analyzed, which belt conveyors overcome different height profiles and / or which convey different loads.

[0017] For analyzing the first belt conveyor and the second belt conveyor, i.e., in particular for comparing the first belt conveyor with the second belt conveyor, for example, a first function value of the first belt conveyor is standardized by means of a first data model for the first belt conveyor, in particular, at least a topological dependency of the function value is reduced by means of the standardization, and a second function value of the second belt conveyor is standardized by means of a second data model for the second belt conveyor, in particular, at least a topological dependency of the function value is reduced by means of the standardization. Thus, the first function value is associated with the first belt conveyor and the second function value is associated with the second belt conveyor, wherein the function values ​​can be compared by the standardization. Thus, for example, the belt conveyors can be distinguished from each other by the height profile to be overcome, and since the height profile has been standardized, the belt conveyors can be compared with each other with respect to the energy consumption of the belt conveyors and / or the efficiency of the belt conveyors.

[0018] In addition, for example, another belt conveyor can be operated in parallel with the first belt conveyor in time (also operated as in the past), wherein the other belt conveyor can, for example, be closed or dismantled. The belt conveyor that has been transformed and represents the first belt conveyor as a transformed belt conveyor can also be called another belt conveyor. A belt conveyor that transports different materials and / or different quantities of materials can also be called another belt conveyor. This situation is particularly about the same belt conveyor being used for different items at different times, that is, for example, transporting different materials. The function value is particularly determined in time intervals and / or the function value is related to different belt conveyors. Therefore, different belt conveyors are, for example, belt conveyors that run at different locations or in different time periods. Therefore, for example, the belt conveyor after the belt conveyor is transformed is different from the first state, so that the first belt conveyor can be compared with the second belt conveyor. An example of a time interval when determining a function value:

[0019] - Every minute,

[0020] - hourly (especially for process information),

[0021] - Every month (especially for long-term evaluation of measures taken, such as replacing parts, using better bearings, using more powerful motors, using different conveyor belts, etc.)

[0022] - annually (particularly for reasons as in the case of the sub-item "monthly" and / or determined in particular according to the season, temperature, snowfall, rainfall, etc.)

[0023] In order to determine a curve over time with which a trend development becomes apparent, the function value can also be related to a value or values ​​which are determined / measured, for example, every hour.

[0024] In an embodiment of the method, a first function value is determined, which establishes a relationship between the required energy and the given transport task and allows the belt conveyor to be evaluated (reference value). The required energy is particularly related to the drive energy of all drives of the belt conveyor used to transport the transported items or a selected part. Because, in general, belt conveyors are very different due to different topologies, different wheelbases, and different lifting heights, in this way only the observed belt conveyor can be evaluated, and the change in the behavior of the belt conveyor can be inferred from the change in the function value in the medium term and in the long term. In addition, the second belt conveyor should be similar or identical to the first belt conveyor in terms of topology, wheelbase, lifting height, etc. In the case of the first belt conveyor, it can be established over time if necessary, and the behavior change can be caused by wear, temperature influence, functional deterioration of each component and / or similar situations.

[0025] Therefore, the analysis of belt conveyors is particularly related to benchmarking, i.e., for example, for a benchmarking process of a belt conveyor (GF), using measured values ​​of the relevant belt conveyor or using measured values ​​of the relevant belt conveyor from a continuously operating facility with belt conveyors or a facility in which the belt conveyor is used. Therefore, due to the dedicated measuring facility or measuring operation, an analysis, such as a comparison, is possible without affecting the operation of multiple belt conveyors or one belt conveyor.

[0026] As mentioned above, belt conveyors can be very different, wherein comparability (especially only by means of the above-mentioned first function value) is not possible or is possible only in individual cases. Nevertheless, in order to achieve the benchmark process, in particular certain conditions must be met, such as at least:

[0027] 1. For the belt conveyor to be analyzed or compared, a digital replica is required in which the electrical and mechanical behavior of the belt conveyor is reproduced with the aid of mathematical algorithms; the mathematical algorithms used are in particular in this case based on standards such as DIN and / or CEMA;

[0028] 2. Standardizing one or more belt conveyors with the aid of digital copies; thereby in particular inconsistencies are excluded and comparable results are provided. For this purpose, the above-mentioned function values ​​are used and the standardized function values ​​are determined in particular by

[0029] - Excludes lifting capacity and,

[0030] - only energy used mechanically and / or

[0031] - Eliminate dynamic operation processes;

[0032] Eliminating the lifting capacity allows to remove the differences in belt conveyor topology; in particular, considering only the mechanical energy allows to remove the influence of different drive configurations and efficiency; dynamic operating processes (e.g., starting and stopping) are eliminated due to the influence of different operating behaviors of belt conveyors. Dynamic operating processes are especially processes in which the speed of the goods to be or being transported changes due to acceleration.

[0033] Thus, standardization can be achieved in one, two or three ways. Standardization allows the same or similar states of different belt conveyors to be compared or evaluated. The analysis (such as, for example, a benchmark process) does not need to be a snapshot, but can also be achieved over a longer period of time (a day, a week...). It can thereby be ensured that sufficient measurement data are collected to determine the first function value or the second function value, which is standardized; as already described in the final version, in this case it is also possible to take into account the load category and / or the loading category.

[0034] 3. The belt conveyors to be compared advantageously have the same or similar design, wherein, in particular, the ratio of the total resistance, which is the sum of the specific resistance and the secondary resistance, is similarly large. The same design means, in particular, that the belt conveyors are designed in accordance with the known rules of DIN or CEMA. A similarly large ratio of the specific resistance to the secondary resistance in comparison with the total resistance can be divided into the following groups:

[0035] Group 1 → Proprietary resistance and minor resistance < 5% of total resistance

[0036] Group 2 → Proprietary resistance and minor resistance < 10% of total resistance

[0037] Group 3 → Proprietary resistance and minor resistance < 15% of total resistance

[0038] This division is representative. It can be adapted to the belt conveyor used for the analysis. According to the rules known from the standards (e.g. DIN or CEMA), the specific resistance and the secondary resistance are determined in each digital copy of the belt conveyor. For example, in DIN there is a diagram for illustrating the importance of the infeed roller resistance for the dimensioning of a safe system with the lowest possible investment and operating costs, which shows the dimensioning of the resistance ratios for a long belt conveyor, with a difference between a horizontally running conveyor and a conveyor with a slope of about 5%. In this case, it is pointed out that, for example, with the increasing use of energy-optimized conveyor belts, the proportion of the infeed roller resistance to the total movement resistance will decrease accordingly in the future. When comparing the resistance ratios of two long belt conveyors of the same design but with different inclinations, the following resistances are distinguished: slope resistance, specific resistance, secondary resistance, oscillation bending resistance, conveyor belt slip resistance, load roller running resistance and infeed roller resistance.

[0039] In an embodiment of the method, two and / or all three of the above conditions are fully or partially met.

[0040] Belt conveyors that meet these conditions, ie are located in the same group (such as described in the third point) can be compared with each other.

[0041] Determine the allowed values ​​of the function for the two descriptions:

[0042] - using a first, also non-standardized function value, to evaluate a single belt conveyor with respect to its running behavior, wherein the running behavior can include electrical and mechanical properties as well as running quality; running quality can mean:

[0043] oHow does a belt conveyor work continuously?

[0044] oAre there many phases of operation where no material is transported? and / or

[0045] oAre starting and stopping processes frequent?

[0046] - in the same belt conveyor, the use of first, also non-standardized function values, to identify medium-term or long-term changes in order to determine the causes individually and take countermeasures if necessary;

[0047] - using the second function value to compare different belt conveyors with one another based on the functionality described by the first function value, wherein the first function value and the second function value are standardized;

[0048] It is thus possible, for example, to compare the performance of belt conveyors in different plants, such as cement plants, mining etc., with one another and to carry out corresponding benchmarking processes;

[0049] When evaluating the benchmark process, positive experiences in plant A can be transferred to the operating conditions in plant B; the benchmark process can provide the basis for optimizing the operating behavior of the belt conveyor at different locations.

[0050] In an embodiment of the method, standardization is performed for the analysis. In this case, standardization is particularly about one function value or a plurality of function values. Comparability of belt conveyors can be achieved by standardization. Therefore, even if a first belt conveyor is different from a second belt conveyor, the first belt conveyor can be compared with the second belt conveyor by means of standardization. For example, differences are obtained by different lifting heights and / or different lengths of the conveyor belts of the belt conveyors and / or different conveying materials and / or maintenance, etc. By the described standardization, a benchmark for evaluating the performance of a belt conveyor and for evaluating the performance of belt conveyors with similar transport tasks can be created.

[0051] Installations in mining are dimensioned in particular according to technical, physical or mathematical rules, wherein these rules are defined in belt conveyors, for example, in DIN or CEMA. This enables standardization of belt conveyors in particular. Digital twins can be developed for different belt conveyors, which are based on the above-mentioned rules and can be verified, for example, using measurement data, so that the digital twin behaves exactly like its physical twin. This can be achieved based on dimensional data or using first measurements during or shortly after commissioning. In this way, for example, the original state of a belt conveyor can be stored in the digital twin.

[0052] In an embodiment of the method, the operating state of the belt conveyor is standardized. An example of an operating state is the speed at which the belt conveyor is operated.

[0053] In an embodiment of the method, characteristic values ​​of the material are standardized, wherein the characteristic values ​​relate in particular to the weight and / or quantity of the material or represent its value. The material is a transported material, i.e., conveyed using a belt conveyor. The standardization of the material or of the characteristic values ​​of the material is related, for example, to the loading of the material and / or the specific density of the material. Different loadings of the belt conveyor with material result in loading categories. The loading categories can also be referred to as load categories. For example, the loading categories can differ from one another as follows or contain the following parameters:

[0054] -Quantity difference at the same speed

[0055] - Mass per unit length = conveying capacity (e.g., in tons / hour) / speed (e.g., in meters / second)

[0056] Standardization by load category enables standardization of identical belt conveyors, allowing variations in the function value to be identified. A function value can be determined for each load category, allowed to vary over time, and conclusions can then be drawn about the performance and / or condition of the belt conveyor.

[0057] In the embodiment of the method, the lifting height is standardized. The lifting height is the height to be overcome or overcome by means of a belt conveyor. The lifting height can have a positive value or a negative value or can be zero. Different height profiles of the terrain can be overcome by means of a belt conveyor, so that different individual lifting heights are obtained, in particular due to the ups and downs on the terrain, a total lifting height is obtained. By standardizing the lifting height, it is possible to compare different belt conveyors with each other. The function value is particularly determined for the corresponding speed and the corresponding loading situation and the lifting height is standardized. Therefore, a comparison of different belt conveyors is possible. In particular, it is possible to simultaneously consider the conveying capacity, because the conveying capacity is indirectly included in the loading category.

[0058] In an embodiment of the method, the first function value of the relevant belt conveyor (ie, in particular the first belt conveyor) and the second function value of the further belt conveyor are standardized. Thus, the method can be applied to a variety of belt conveyors, wherein the standardization makes it possible to compare different belt conveyors.

[0059] In an embodiment of the method, the belt conveyors differ in their length and / or conveying capacity by no more than 50%, in particular by 25%, wherein the belt conveyors in particular have similar transport tasks. Similar transport tasks are, for example, when transporting the same type of goods, such as iron ore, coal, sand, etc. By specifying the maximum difference, comparability is made easier and / or the standardization effort is reduced. The belt conveyors to be compared are therefore intended in particular for similar transport tasks. In the case of the following belt conveyors, similar transport tasks are obtained, which differ in the length of the paths they travel:

[0060] - Long distance conveyors (in kilometers) (conveying functions from A to B over a distance of one kilometer or more)

[0061] - Storage area conveyors located in storage areas, especially in units of 100 meters (conveying function from A to B)

[0062] -Bin unloading conveyor (function of unloading material from bin or silo).

[0063] In an embodiment of the method, the function value is an energy performance index. The energy performance characteristic index can also be referred to as an energy performance indicator (EnPI). The energy performance index is a KPI (key performance indicator) that can describe the performance of using a belt conveyor. However, because belt conveyors vary greatly and there are multiple influencing variables and complex relationships that have an impact on this characteristic number, i.e., EnPI, the comparability of different belt conveyors is almost impossible without performing standardization. The comparability of belt conveyors is obtained by standardization. This means, for example, that the operator of the belt conveyor can determine the EnPI and then also estimate whether the determined value is good or bad because a benchmark is available. Therefore, it is feasible to determine the energy performance characteristic number of the belt conveyor, and in the case of a belt conveyor, in particular, by using a digital twin in combination with the actual measurement data of the belt conveyor to determine a benchmark, which in particular allows the operator to immediately evaluate the performance of the operator's belt conveyor.

[0064] For example, if the digital twin can be run using measured data of the actual system operation of the belt conveyor (e.g. conveying volume, speed, operating time), KPIs such as EnPI can be determined in particular. These performance characteristic numbers then describe the theoretical performance of the belt conveyor without taking into account changes in the original state (i.e., for example, the state shortly after the first startup). The influence of wear, temperature, summer or winter operation, the alignment state of the belt conveyor (for transferable belt conveyors) or other changes is not taken into account. The actual EnPI can be determined in particular based on the measured values ​​and compared with the theoretical EnPI. The comparison then allows the performance of the considered facility (i.e., the belt conveyor) to be immediately judged.

[0065] In one embodiment of the method, a technical deviation and / or a technical fault is detected.

[0066] Examples of technical bias are:

[0067] -Changes in drive performance requirements

[0068] - Increased rolling resistance of the conveyor belt

[0069] -wait.

[0070] Examples of technical failures are:

[0071] - Unplanned downtime and / or interruption due to component damage

[0072] - Unplanned stoppages and / or interruptions due to material spillage, misalignment of conveyor belts, etc.

[0073] -wait.

[0074] In an embodiment of the method, program deviations and / or faults are identified. If such a situation is identified, countermeasures can be suggested or automatically executed.

[0075] Examples of procedural deviations are:

[0076] - Fluctuations in material supply

[0077] - Material supply is interrupted, especially frequently

[0078] -The conveyor belt is only running partially loaded

[0079] - Poor energy performance, as higher drive power is consumed for less material

[0080] - changes in the running behavior due to temperature changes (e.g. due to low temperatures; this causes the lubricant to become more viscous and thus leads to increased running resistance of the bearing)

[0081] Examples of process failures are:

[0082] - Frequent interruptions impair the performance of the belt conveyor,

[0083] - Frequent slowdown of transport also impairs the performance of belt conveyors.

[0084] The cause of dispersion and / or deviations can also lie in the facility control. For example, incorrectly set boundaries lead to frequent malfunctions and thus outages.

[0085] The determined function values ​​and the trends derived therefrom give an indicator for the performance of the belt conveyor and thus the condition of the belt conveyor. By determining the function value by means of standardizing the speed and by means of assigning to the described load category, an information item for a single belt conveyor is obtained. This standardization allows the function values ​​to be compared under the same operating conditions. Further standardization of the lifting height also allows "similar" belt conveyors to be compared with each other (similar belt conveyors refer to, for example, those designed according to the same standards, transporting the same goods, etc.). Therefore, performance comparison (benchmarking) in belt conveyors is feasible. As described above, the function value provides an indicator of the condition of the belt conveyor, and then, further investigation is needed in particular to determine the specific cause (technical or process).

[0086] In an embodiment of the method, an intervention is performed in the operation of the belt conveyor. This refers in particular to the actual, i.e. physically existing, belt conveyor. The intervention can have a positive influence on the performance, i.e. the performance of the belt conveyor. The intervention concerns, for example, changes in the mechanics of the belt conveyor and / or the electrical aspects of the belt conveyor and / or the loading of the belt conveyor.

[0087] In an embodiment of the method, the effectiveness of the intervention is analyzed. This analysis makes it possible to gradually improve the performance of the belt conveyor. In order to analyze the effectiveness of the intervention, for example, a second function value and / or further function values ​​are used. These function values ​​are determined or standardized according to the described method.

[0088] In an embodiment of the method, the operator of a system in the mining industry, i.e., in particular, the operator of a belt conveyor, can evaluate the performance of the facility under consideration or the development of the belt conveyor with respect to the original state. It is thereby possible to quickly evaluate changes in the facility and the impact of the changes (e.g., new conveyor belts, replacement of support rollers, change of start and stop times, replacement of gearboxes). The effects of the measures taken (e.g., new parts in the facility, new operating modes) quickly become visible. This method can assist operators in improving the performance of their facilities or consciously tracking the development of belt conveyors. For example, the size of a belt conveyor, for example, should take into account continuous use under rated load, and, if necessary, extreme cases. The use of digital twins can allow the current operating conditions (e.g., loading conditions, conveyor belt speed) to be included in the evaluation. The consideration of "what if..." is thus more realistic. That is, how does the original-sized belt conveyor perform under current load conditions and speed conditions. If necessary, with a digital twin of appropriate quality, the influence of wear behavior or temperature effects can be considered. For example, providing technical data to maintenance personnel of the facility is another aspect of using digital replicas (i.e., in particular digital twins). By combining technical and economic data, the benefits of this support can be further enhanced.Such digital solutions represent improvements in the operation of the facility combined with the automation of the facility in bulk material handling.

[0089] The belt conveyor has in particular a sensor for determining sensor data, wherein at least one item of sensor data can be used to determine a function value, wherein one of the described methods can be performed to analyze the function value. For example, a programmable logic controller, a control system or a monitoring system can be used for the analysis.

[0090] In an embodiment of the belt conveyor, the belt conveyor has a monitoring system. For example, the monitoring system also provides the feasibility of trend analysis. The determination and / or analysis of the function value particularly requires data that can be provided by the monitoring system or corresponding sensors. The method for determining and / or analyzing the function value can be a component of the monitoring system or can be installed separately.

[0091] A computer program product is provided for installation on a computing unit, wherein the computer program product is designed to carry out one of the methods described. BRIEF DESCRIPTION OF THE DRAWINGS

[0092] The present invention is described and explained in more detail below using the accompanying drawings in an exemplary manner. Those skilled in the art can combine the various features of the embodiments shown in the accompanying drawings to form new implementations without departing from the scope of the present invention. The same reference numerals represent similar elements. The accompanying drawings show:

[0093] Figure 1 shows a method for analyzing a belt conveyor,

[0094] Figure 2 An alternative method for analyzing a belt conveyor is shown,

[0095] Figure 3 Another approach to analyzing a belt conveyor taking into account a monitoring system is shown.

[0096] Figure 4 shows a method for comparing two belt conveyors using a database,

[0097] Figure 5 A method for comparing two belt conveyors using two databases is shown.

[0098] Figure 6 A first diagram showing an energy performance indicator curve,

[0099] Figure 7 A further diagram showing an energy performance indicator curve is shown,

[0100] Figure 8 A first diagram shows an intervention in the operation of a belt conveyor,

[0101] Fig. 9 A further illustration shows an intervention in the operation of a belt conveyor.

[0102] Fig.10 shows a sequence of processing steps under predetermined conditions,

[0103] Fig.11 shows the functional blocks in the simulation software,

[0104] Fig.12 shows the time evolution of the drive power and the load on the conveyor belt,

[0105] Fig.13 shows the distribution of load categories,

[0106] Fig.14 shows the evolution of energy performance indicators over time,

[0107] Fig.15 shows a detailed view of an example functional block,

[0108] Fig.16 shows a simplified diagram for determining the function value, and

[0109] Fig.17 Normalized and unnormalized first and second function values ​​are shown. DETAILED DESCRIPTION

[0110] according to Figure 1The diagram shows a method for analyzing a belt conveyor 1. The belt conveyor 1 is a real belt conveyor. A standardized digital replica of the actual belt conveyor is obtained through a data model 3 or through the model. The digital replica can also be called a digital twin. In the data model 3, measurement data, i.e., actual values ​​13 of the real belt conveyor 1, such as the speed and / or load of the belt conveyor, i.e., the load of the belt conveyor, are used. In the standardized model 5, the actual value 14 is standardized according to the speed of the belt conveyor 1 and the loading category of the belt conveyor 1. Therefore, the actual value or actual measured value 13 is particularly used for the speed and load of the data model 3. The actual value or actual measured value 14 used for the standardized module 5 is particularly the measured power and load. The result value 43 is determined using the data model 3. The result value 44 is determined using the standardized module 5. The result value 43 and the result value 44 can already be function values. The result value 43 and the result value 44 are stored in the database 6. With the result value 43 and the result value 44, it is also possible to first determine the function value or even another function value. The determination is performed, for example, in the database 6 or in another determination device (not shown). The function values ​​stored in the database can be visualized and / or compared in the visual image 10. The database 6 provides visualization data 47. Therefore, the image provides the feasibility of visualization, analysis and / or comparison, in particular the comparison of actual values ​​with simulated values. The function value is, for example, an energy performance indicator. From this, in particular, a comparison is obtained between the development of the actually measured energy performance indicator and the energy performance indicator determined by simulation using the data model 3 with the aid of the actual measured values ​​13, 14. The actual values ​​of speed and load are inputs, i.e., input variables, for the digital replica, i.e., the data model 3. The required power (Power) is calculated and normalized. By using the load, load categories can be distinguished. According to this normalization, the theoretical energy performance indicator of each load category is determined according to the load category and speed (Speed). The determined function values ​​can be plotted against time to visualize the development or trend. The digital replica, i.e., the data model, describes, for example, an ideal state or original state of a belt conveyor. In particular, normalization must also be performed in order to compare with an actual belt conveyor.

[0111] The consumed energy (in particular measured values, or calculated from measured values) is standardized, in particular according to speed and load category, and an actual energy performance indicator for the respective load category is determined. The difference in the result between the theoretical energy performance indicator and the actual energy performance indicator describes the state of the facility. The visualization of the analysis or comparison between at least one actual function value and the simulated function value is performed, in particular using a visualization device (e.g. a screen) by means of a visual image 10.

[0112] according to Figure 2A further method for analyzing a belt conveyor 1 is shown, wherein a first function value 45 is calculated from the result values ​​43 and 44 in the processing module 9. Figure 2 , the data model 3, the standardization module 5 and the database 6 are implemented in the cloud 8. The cloud 8 is an Internet-based system. Cloud computing and cloud data storage can be performed centrally or decentralized. The visualization 10 of the analysis can take place, for example, at a facility, that is, in particular, at a facility where the belt conveyor 1 is located.

[0113] Figure 3 A further method for analyzing an actual belt conveyor 1 is shown, wherein actual values ​​(measured values) 13 and 14 are taken from a monitoring system 15. The monitoring system 15 monitors the belt conveyor 1. In the standardization module 5, the actual values ​​are standardized according to speed and load category. In the data model 3, a digital replica of the real belt conveyor is implemented, which is standardized. Standardization here means standardization according to speed and load category. The database 6 is implemented in the cloud 8. Comparison can be made using a visual representation 10. For example, the development of energy performance indicators can be actually measured and compared in a simulated manner, using the actual values ​​as input for the simulation.

[0114] according to Figure 4 The diagram of FIG. 6 shows a method for comparing two belt conveyors (a first belt conveyor 1 and a second belt conveyor 2) using a common database 6. Figure 4 , and according to Figure 1 Compared to the example of , the data model 3′ is also standardized according to the increase in order to be able to compare different belt conveyors with each other. The data model 3′ is also standardized according to the increase in and the standardization module 5 is assigned to the belt conveyor 1. The data model 4′ is also standardized according to the increase in and the further standardization module 5 is assigned to the belt conveyor 2. The belt conveyor 2 generates actual measured values ​​13′ and 14′. The data models 3′ and 4′ are compared with the data models according to Figures 1 to 3 The data models differ in that an additional normalization is performed according to the travel of the respective belt conveyor 1 or 2. In the notation of data models 3, 3', the belt conveyor is therefore also drawn straight due to the normalization. The lift is a measure of the gradient (positive and negative) that the belt conveyor has to overcome. According to Figure 4 , also standardized according to the lift, in order to be able to compare different belt conveyors with one another, in particular different height profiles have to be overcome. Therefore, the standardization is carried out according to speed, load category and lift. A monitoring system can also be used here, but is not shown. The data models 3' and 4' produce result values ​​43 and 43'. The corresponding standardization module 5 generates result values ​​44 and 44'. Using the data in the database 6, different belt conveyors in a plant, open pit or mine can be compared.

[0115] and Figure 4 compared to, Figure 5 A method for comparing two belt conveyors 1 and 2 using two databases 6 and 7 is shown. Database 6 is assigned to belt conveyor 1. Database 7 is assigned to belt conveyor 2. A first function value 45 of database 6 can be compared with a second function value 46 of database 7. Normalization is performed according to speed, load (load category) and lift. The representation 10 can also be realized, for example, by a monitoring system not shown.

[0116] according to Figure 4 and Figure 5 , different belt conveyors can be compared in an industrial plant, an open pit or a mine or in different plants, different open pits or different mines. For this purpose, the number of databases 6.7 can be adjusted accordingly.

[0117] according to Figure 6 The diagram shows a comparison of energy indicators (EnPI: Energy Performance Index) 12 as an example of function values. The following energy indicator is shown for a constant speed (e.g. 50% or 80% of the rated speed) and for three different load categories I, II and III. The values ​​(data) 21 of the following energy indicator are plotted over time 20 (date), wherein the values ​​have the following properties: actual value, theoretical value (predicted value) and dimension (dim (stands for nominal dimension, i.e. considered as the original design of the belt conveyor)):

[0118] 22EnPi dim (load category I) kWh / (t*km)

[0119] 23EnPi dim (load category III) kWh / (t*km)

[0120] 24EnPi theo(Load Category II)kWh / (t*km)

[0121] 25EnPi actual (load category I) kWh / (t*km)

[0122] 26EnPi actual (load category III) kWh / (t*km)

[0123] 27EnPi dim (load category II) kWh / (t*km)

[0124] 28EnPi theo(Load Category I)kWh / (t*km)

[0125] 29EnPi theo(Load Category III)kWh / (t*km)

[0126] 30EnPi actual (load category II) kWh / (t*km)

[0127] This is an example of a result showing the theoretical and actual energy performance indicators over time for three load categories. According to the standardization, these energy performance indicators are normalized according to speed (many belt conveyors operate at a constant speed (fixed speed), fewer operate at variable speed) and load category. It is also possible to calculate EnPi dim for different load categories. The value is a theoretical value calculated based on the indicated dimensions. If the belt conveyor operates at variable speed, it is possible to normalize according to different speeds, load categories and, if necessary, lifts, wherein such a display of the results can be performed, for example, in three dimensions or by means of a matrix, Figure 6 Not shown in .

[0128] Figure 7 The diagram in shows a further comparison of the energy performance indicators according to load class. The energy performance indicator (e.g. in kWh / t*km) is shown over time (e.g. in minutes (min), hours (h), days (d) or months). The figure distinguishes between load class I 31, load class II 32 and load class III 33. Energy performance indicators 34, 37 and 40 are based on the original design, i.e. calculated based on the dimensions of the belt conveyor. Energy performance indicators 35, 38 and 41 are theoretical and energy performance indicators 36, 39 and 42 are actual. Theoretically means, it is determined in the data model (i.e. the digital twin).

[0129] according to Figure 8 The diagram of FIG. 4 shows an evaluation of the effect of an intervention 19 in a real system, i.e. a belt conveyor 1. The intervention 19 takes place based on an analysis in an analysis device 49. In the analysis device 49, the function values ​​are analyzed based on the processing module 9 and the database 6 and the intervention 19 is generated in the belt conveyor. The system data 16 are also processed in the analysis device 49. For example, the sensor data 11 generates the measured values ​​13 and 14.

[0130] according to Fig. 9 The diagram shows how an intervention 19 can be analyzed. The described procedure can be used to evaluate an intervention that has been carried out. An intervention is a change to the actual belt conveyor 1. The effectiveness of an intervention can be evaluated by determining a function value. For example, an intervention is a lower load or an increased load of the belt conveyor or a replacement of the conveyor belt.

[0131] according to Fig.10 A diagram shows a series of processing steps for a given condition. The following elements are shown:

[0132] 50: Condition A constant speed (constant speed)

[0133] 51: Condition BI with 2000t> conveyor load 1800t

[0134] 52: Condition B II with 2000t> conveyor load 1800t

[0135] 53: Condition B III with 2000t> conveyor load 1800t

[0136] 54: Condition B IV with 2000t> conveyor load 1800t

[0137] 56: If A and BI are true then

[0138] 57: If A and B II are true then

[0139] 58: If A and B III are true then

[0140] 59: If A and B IV are true then

[0141] 60, 61, 62, 63: Integrate current drive power and conveying elements

[0142] 64: Calculate the energy performance index of load category I (function value)

[0143] 65: Calculate the energy performance index for load category II (function value)

[0144] 66: Calculate the energy performance index for load category III (function value)

[0145] 67: Calculate the energy performance index for load category IV (function value)

[0146] By integration, the drive power [kW] gives the energy [kWh] and the transport capacity [t / h] gives the transport volume [t]. The energy performance index is calculated by dividing the energy by (transport volume * transport route) [kWh / (t*km)].

[0147] according to Fig.11 The diagram shows functional blocks 70, 71, 72 and 73 in the simulation software for determining the energy performance indicators for four load categories:

[0148] ·I 31,

[0149] II 32

[0150] III 33

[0151] ●IV 74.

[0152] according to Fig.12The diagram shows the values ​​77 of the drive performance 75 for a belt conveyor and the values ​​of the load 76 on the conveyor belt over time 78, divided into load categories I, II, III and IV. The boundary condition here is a constant speed. For example, 40%, 100% or 110% of the rated speed.

[0153] according to Fig.13 The illustration in shows the allocation of load categories. For example, consider load category III, i.e. the time in which a load 76 is in this category. This results in knowledge of the drive power 75 consumed during the same time. The relevant delivery capacity is allocated to class III, so that the energy performance indicator can then be determined. The observation area in class III is stored in gray.

[0154] according to Fig.14 The diagram shows approximately parallel curves for the values ​​of 79 energy performance indicators for different levels 1 to IV:

[0155] 81 En PI_I

[0156] 82 En PI_II

[0157] 83 En PI_III

[0158] 84 En PI_IV

[0159] Over time 78. This shows the user that no significant changes have occurred on the belt conveyor during this period.

[0160] according to Fig.15 The diagram of FIG. 8 shows a detailed view of an example function block 80. A function block is provided for each load class. Normalization according to lifting is considered, ie, in particular, subtracting lifting work. In addition to Fig.11 In addition to the representation of the functional blocks in , further standardization according to promotion is also shown here.

[0161] according to Fig.16 , showing a schematic diagram for determining the function value for a load category, more specifically, once in the form of a total value and once in the form of a subtracted lifting performance, ie normalized lifting height (lift=0 m).

[0162] The following elements are displayed:

[0163] 50: Condition A with constant speed (constant velocity)

[0164] 51: Condition BI with 2000t> conveyor load 1800t

[0165] 56: If A and BI are true then

[0166] 85: Determine the transport capacity of the transport

[0167] 86: Calculate the total power required

[0168] 87: Calculate the required lifting capacity

[0169] 88: Integrate the current delivery volume

[0170] 89: Integrate the current total power

[0171] 90: Integrate the current total performance minus the improved performance

[0172] 91: Calculate the energy performance index for load category I (function value)

[0173] 92: Calculate the simplified energy performance indicator (function value) for load category I.

[0174] By integration, the drive power [kW] is converted into energy [kWh] and the transport capacity [t / h] is converted into flow [t]. The energy performance index is calculated by dividing the energy by (transportation volume*transportation route) [kWh / (t*km)].

[0175] according to Fig.17 , showing standardized and non-standardized first and second function values. A first belt conveyor 1 and a second belt conveyor 1′ are symbolically represented. The actual first measured value 14 of the first belt conveyor 1 is provided to a first standardization module 5, wherein the first standardization module 5 has a first data model 95 for simulating the first belt conveyor 1. A first result value 43 is determined using the first standardization module 5. The first result value 43 can simultaneously be a first function value, wherein the first function value is standardized by the first standardization module 5. The actual second measured value 14′ of the second belt conveyor 1′ is provided to a second standardization module 5′, wherein the second standardization module 5′ has a second data model 95′ for simulating the second belt conveyor 1′. Using the second standardization module 5′, a second result value 43′ is determined. The second result value 43′ can simultaneously be a second function value, wherein the second function value is standardized by the second standardization module 5′. The standardized function values ​​43, 43′ can be compared with each other. The comparison by normalization is valid because the belt conveyors 1 , 1 ′ are comparable, which is indicated by the symbol ≈96.

Claims

1. A method for analyzing a belt conveyor (1), wherein: using a data model (3), wherein the data model (3) is related to a digital replica of the belt conveyor (1), wherein a first function value (45) of the belt conveyor (1) is determined, wherein the first function value (45) and a second function value (46) are used to analyze the belt conveyor, wherein the second function value (46) is related to the belt conveyor (1) or another belt conveyor (2), In this case, at least the first function value (45, 46) is normalized for the analysis by means of the data model (3), wherein in particular at least the topological dependency of the function value is reduced by means of the normalization.

2. The method according to claim 1, wherein: The function values ​​(45, 46) are associated with one or more belt conveyors (2) of identical or similar design.

3. The method according to claim 1 or 2, wherein: The function values ​​(45, 46) are determined at time intervals or the function values ​​(45, 46) are related to different belt conveyors (1, 2).

4. The method according to any one of claims 1 to 3, wherein: Standardize operating status.

5. The method according to any one of claims 1 to 4, wherein: Characteristic values ​​of the material are normalized, wherein the characteristic value is in particular related to the weight and / or the quantity of the material.

6. The method according to any one of claims 1 to 5, wherein: Standardize lifting height.

7. The method according to any one of claims 1 to 6, wherein: The normalization is based on a first functional value (45) of the belt conveyor (1) and a second functional value (46) of the further belt conveyor (2).

8. The method according to any one of claims 1 to 7, wherein: The belt conveyors (1, 2) differ by no more than 50% in their length and / or conveying capacity, wherein the belt conveyors (1, 2) in particular have similar transport tasks.

9. The method according to any one of claims 1 to 8, wherein: The function value is an energy performance index.

10. The method according to any one of claims 1 to 9, wherein: Identify technical deviations and / or technical failures.

11. The method according to any one of claims 1 to 10, wherein: Identify procedural deviations and / or failures.

12. The method according to any one of claims 1 to 11, wherein: An intervention is performed on the operation of the belt conveyor (1, 2).

13. The method according to any one of claims 1 to 12, wherein: Analyze the effectiveness of the intervention.

14. A belt conveyor (1) having a sensor for determining sensor data (9), wherein: At least one item of sensor data can be used to determine a function value (45), wherein a method according to any one of claims 1 to 13 can be carried out to evaluate the function value (45).

15. The belt conveyor (1) according to claim 14, wherein: The belt conveyor has a monitoring system (15).

16. A computer program product for installation on a computing unit, wherein: The computer program product is implemented for performing the method according to any one of claims 1 to 13.

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