Stepping test

Stepping motors STEP test Step test Steranes... 

A.STM.B764, Std. Methodfor Simultaneous Thickness and Electrochemical Potential determination of Individual Eayers in Multi-layer Mickel deposit (STEP test), American Society for Testing and Materials, Philadelphia, Pa., 1986. 

Fitting Dynamic Models to E erimental Data In developing empirical transfer functions, it is necessary to identify model parameters from experimental data. There are a number of approaches to process identification that have been pubhshed. The simplest approach involves introducing a step test into the process and recording the response of the process, as illustrated in Fig. 8-21. The i s in the figure represent the recorded data. For purposes of illustration, the process under study will be assumed to be first order with deadtime and have the transfer func tion ... 

The principal limitation to using these rules is that the true process parameters are often unknown. Steady-state gain K can be calculated from a process model or determined from the steady-state results of a step test as Ac/Au, as shown in Fig. 8-28. The test will not be viable, however, if the time constant of the process is longer than a few... 

The specimen is placed between heavy cylindrical brass electrodes, which carry electrical current during the test. There are two ways of running this test for dielectric strength. In the short-time test the voltage is increased from zero to breakdown at a uniform rate. The precise rate of voltage rise is specified in the governing material specifications. In the step-by-step test the initial... 

Figure 6.1. Block diagram illustration of an open-loop step test. 

To make use of empirical tuning relations, one approach is to obtain the so-called process reaction curve. We disable the controller and introduce a step change to the actuator. We then measure the open-loop step response. This practice can simply be called an open-loop step test. Although we disconnect the controller in the schematic diagram (Fig. 6.1), we usually only need to turn the controller to the manual mode in reality. As shown in the block diagram, what we measure is a lumped response, representing the dynamics of the blocks Ga,... 

Figure 6.2. Illustration of fitting Eq. (6-2, solid curve) to open-loop step test data representative of self-regulating and multi-capacity processes (dotted curve). The time constant estimation shown here is based on the initial slope and a visual estimation of dead time. The Ziegler-Nichols tuning relation (Table 6.1) also uses the slope through the inflection point of the data (not shown). Alternative estimation methods are provided on our Web Support.

One reason why this approximation works is that process unit operations are generally open-loop stable, and many are multi-capacity in nature. Reminder Underdamped response of the system is due to the controller, which is taken out in the open-loop step test. 

Even though this result is based on what we say is a process function, we could apply (E6-4) as if the derivation is for the first order with dead time function GPRC obtained from an open-loop step test. 

Say we model our process (read fitting the open-loop step test data) as a first order function with time delay, and expecting experimental errors or uncertainties, our measured or approximate model... 

Empirical tuning with open-loop step test Measure open-loop step response, the so-called process reaction curve. Fit data to first order with dead-time function. 

Example 10.6 A classic example of an MIMO problem is a distillation column.13 From open-loop step tests, the following transfer functions are obtained ... 

A critical factor in the successful application of any optimization technique is the availability of a suitable dynamic model. As mentioned previously, in typical MPC applications an empirical model is identified from data acquired during extensive plant tests. The experiments generally consist of a series of step tests, in which the manipulated variables are adjusted one at a time, and the tests require a period of 1-3 weeks. Details concerning the procedures used in the plant tests and subsequent model identification are usually considered to be proprietary information. The scaling and conditioning of plant data for use in model identification and control calculations can be key factors in the success of the application. 

Time-Domain Eyeball Fitting of Step Test Data... 

Since the operations to get frequency response from step-test data involve numerical differentiation of the data, the results are less reliable than pulse test data as frequency is increased. 

Write a digital computer program that will calculate G,i j from step test data. 

Endurance and time to exhaustion are also important components of athletic performance. Decreases in either measure were observed in several studies (19,21,38 12). Holland (38) noted a 10% reduction in work performed during all-out cycle ergometer exercise after 24 hr of sleep deprivation. Brodan and Kuhn (39) evaluated subjects (n = 7, sleep debt = 120 hr) with the Harvard step test (reflects cardiorespiratory endurance and recovery) and revealed adaptation during the test but impaired recovery. Martin (41) utilized treadmill testing at 80% V02 max and found decreased time to exhaustion, increased perceived exertion, and increased minute ventilation (n = 8, sleep debt = 36 hr). Martin and Chen (42) revealed a 20% reduction in time to exhaustion after 50 hr of sleep deprivation. Decreased time to exhaustion after 30 hr of sleep deprivation has been demonstrated even when subjects were allowed caffeine intake (21). 

From this point, we may use the 7-step test procedure ... 

One possible way to identify hazards and risks is to consider the problem as a sequence of steps. Testing and evaluating potentially mutagenic chemicals could proceed through the following steps ... 

For this data set, at a familywise error rate of 5%, one-step testing leads to the conclusion that 174 genes are differentially expressed. Closed and partition stepdown testing are guaranteed to infer at least those same 174 genes to be differentially expressed. In fact, these last two methods both infer three additional genes to be differentially expressed that is, a total of 177 genes. 

In this section we focus on hypothesis testing and discuss both individual and simultaneous tests for detecting nonzero effects. Of special interest are the step-down tests described in Section 5.2, as these offer improved power over single-step tests. 

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